diff --git a/_freeze/CH1_getting_started/execute-results/html.json b/_freeze/CH1_getting_started/execute-results/html.json
index fa425fa..5ff8906 100644
--- a/_freeze/CH1_getting_started/execute-results/html.json
+++ b/_freeze/CH1_getting_started/execute-results/html.json
@@ -1,8 +1,11 @@
{
- "hash": "a0c3fbfa2b712ae66111138f0b6b8152",
+ "hash": "2ef97ab80f5ab82604f96f23f11721ae",
"result": {
- "markdown": "---\ntitle: \"Chapter 1 - Getting Started with R\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n- Be familiar with R Studio.\n- Explore the RStudio environment, layout, and customization.\n- Understand the Key Benefits of using R.\n- How to run code in R.\n- Know where to get help.\n- Discover R's data types.\n- Be able to create Variables.\n\n# What is R?\n\nAn open source programming language and environment for statistical computing and graphics.\n\nIt was initially written by **Ross Ihaka and Robert Gentleman** at the Department of Statistics of the University of Auckland in New Zealand.\n\nIt provides a wide variety of statistical techniques out of the box, leading to popularity among Analysts, Statisticians and Data Scientists.\n\nSince it was created by statisticians (instead of computer scientists), R has some quirky aspects to it that take some time to get used to.\n\n## What are the benefits of using R?\n\nR is the 6th most popular programming language in the [Popularity of Programming Languages Index (PYPL)](https://pypl.github.io/PYPL.html) as of January 2024.\n\nThere are several reasons for this trend:\n\n- Free and open source, people can modify and share because its design is publicly accessible.\n\n- Cross Platform, it can be used across a range of operating systems i.e Windows, Linux, OS.\n\n- Great support from a diverse and welcoming community. e.g. #rstats twitter community, numerous [R Meet Ups](https://www.meetup.com/topics/r-programming-language). They have written outstanding open access material that you can use to learn R.\n\n- There are lots of [packages available](https://cran.r-project.org/web/packages/available_packages_by_name.html) which contain implementations of processes and ready-made code not available out of the box.\n\n- Powerful tool for communicating results, including:\n\n - [RMarkdown](https://rmarkdown.rstudio.com/) makes it easy to turn your files into PDF'S, Power point presentations\n - [Shiny](https://shiny.rstudio.com/) allows you to make beautiful interactive apps and dashboards.\n\n# R Studio\n\nR is a programming language that runs computations, while R Studio is an integrated development environment (IDE) that provides an interface by adding many convenient features and tools.\n\nYou do not have to use R Studio to code in R, however it was built specifically to get the best out of the language and is highly recommended. If you cannot get access to R Studio desktop edition, you could consider using Posit Cloud (the new name for R Studio Cloud). Instructions for this are in a separate html guide.\n\nOther IDEs that work with R include:\n\n- [Jupyter notebook](https://jupyter.org/)\n- [VisualStudio](https://visualstudio.microsoft.com/services/visual-studio-online/)\n\n## Opening R Studio\n\nR Studio is broken down into four panels.\n\nWhen you open R Studio for the first time, you see this:\n\n{fig-alt=\"R Studio interface with the Code Editor, Environment, Console and Files panes.\"}\n\nIf you don't see the Code Editor pane, go to the tool bar and click **View -\\> Panes -\\> Show All Panes**.\n\nYou can also make panes bigger or smaller by hovering between two panes and then clicking and dragging.\n\n## Global Settings Changes\n\nUpon first opening R Studio, you have the most basic form of the tool that has some of the most useful workflow features off by default. Let's adjust these settings.\n\nFirstly, navigate to \"Tools\" and \"Global Options\", which is where this tweaking takes place.\n\n{fig-alt=\"Global options menu with general, code, appearance and more as options.\"}\n\nYou see that R Studio can be heavily customised. You will only scratch the surface here.\n\n- First, remain on the \"General\" menu and:\n - Under **Workspace**, untick \"Restore .RData into workspace at startup\" and change the drop down below it to \"Never\".\n - Under **History**, untick \"Always save history (even when not saving .Rdata)\".\n\nThe reason you don't want to use these is that they are legacy ways of saving R code, and are not as effective or useful as more modern ways of saving your work, controlling coding logs with Git and so on.\n\n- Secondly, navigate to the \"Code\" menu and \"Editing\" sub-menu:\n - Provided you have R Version 4.1+, tick \"Use native pipe operator \\|\\>\".\n - Tick \"Soft-wrap R source files\", which prevents code continuation past the width of the editor pane.\n- Thirdly, change to the \"Display\" sub-menu, still within the \"Code\" menu:\n - Tick \"Allow scroll past end of document\" if you would like to be able to scroll past the final lines of your script.\n - Tick \"Highlight R function calls\", as this is incredibly useful for distinguishing different R objects.\n - Tick \"Use rainbow parentheses\" as this allows you to distinguish between different layers of brackets, which helps with syntax errors.\n- Finally, navigate to the \"Appearance\" menu:\n - Change the font size to whatever is most comfortable for you, 14 works well.\n - Change the help font size to whatever is most comfortable for you, 12 is a good default.\n - Choose a theme that suits your preferences, many people prefer dark mode themes such as \"Vibrant Ink\" due to the code highlighting functionality.\n\nNow that you have R Studio set up, you will create an R Project to make management of your code simpler.\n\n## R Projects\n\nCreating an R Project enables your work to be bundled in a folder that is:\n\n- Self-contained\n- Portable\n\nAll the scripts, data files, figures, outputs and history can be stored in sub-folders.\n\nThe root folder of the R Project (which you choose when you create it) contains the **.Rproj** file and is the **working directory** each time you open it.\n\n### Creating an R Project\n\nTo create an R Project, select **File --\\> New Project** and you will be given some examples of where to store the .Rproj file, a.k.a where the working directory will be.\n\n{fig-alt=\"A project can be created in a new directory, existing directory or from GitHub.\"}\n\nYou can:\n\n- Create a **New Directory** - Create a new folder/directory for the R Project to be placed in, all subfolders created within will be part of the project.\n\n- Create a project in an **Existing Directory** - Creating an R Project in an existing folder/directory\n\n- Import an existing project from a repository created on a Version Control platform, such as GitHub or Gitlab. This is beyond the scope of this course.\n\n### **Exercise** {.unnumbered}\n\nCreate an R project in an **existing directory**, selecting the **course_content** folder provided.\n\nIn your own work, saving it one level higher in the root folder is a better approach. For this course, you must save it where you will save your scripts so the filepaths function correctly.\n\n{fig-alt=\"The root folder showing the .Rproj file alongside the othr folders.\"}\n\nAfter creating the R Project, it will open and set your working directory.\n\nWere you to share your folder with others, they can open the project file and everything will be set for them. This is a big step towards ensuring reproducibility.\n\n### Re-opening the project\n\nDue to the changes you made earlier to the global settings, R Studio will be fresh each time you open it.\n\nSo how do you get back to your project?\n\nThankfully, you have the project menu in the top right, which allows you to:\n\n- Create a new project\n- Open existing project(s)\n- Close projects\n- See recently open projects and jump straight to them\n\n{fig-alt=\"The top right menu that allows you to interact with projects.\"}\n\nFrom here, assume you create and save your scripts in this project in order for filepaths in Chapter 3 onwards to function.\n\n> Let's return now to R Studio, and discuss each of its 4 panes in detail.\n\n## The Console Pane\n\nThe bottom left pane is the console, where you can type and execute code. This also contains a **terminal** or **command line** that can be used to interact with your computer.\n\nR output will appear in the console regardless of where you execute it from.\n\nTo run code in the Console, type next to the command prompt and hit \"Enter\".\n\n### Exercise\n\n::: panel-tabset\nLet's practice some mathematics in the console.\n\n### **Exercise** {.unnumbered}\n\n1. Type the expressions below and run them in the console one at a time.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n2 + 4\n\n23 - 6; 36 + 5\n\n1 + 3 +\n```\n:::\n\n\n### **Show Answer** {.unnumbered}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n2 + 4\n```\n:::\n\n\nNotice the \\[1\\]. This is how R tells you the position you're at in execution.\n\nAs a rule of thumb, write and execute separate commands on separate lines. Although it is messy and often unhelpful, you can put multiple commands on the same line by separating them by a semicolon.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n23 - 6; 36 + 5\n```\n:::\n\n\nNote that if a **\"+\"** appears instead of the command prompt **\"\\>\"**, this means that the statement you submitted was incomplete. The console is expecting further input.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n1 + 3 +\n```\n:::\n\n\nYou can either complete the expression or press the **escape** key to reset.\n:::\n\nThe R Studio Console automatically maintains a history so you can retrieve previous commands.\n\nOn a blank line in the Console, press the up arrow key and see what happens.\n\nThe issue with coding in the console is that you can't save it and it is not easy to edit, which brings you to the code editor.\n\n## The Code Editor Pane\n\nThis is the top left pane, where you will do the majority of your coding. Often this is in the form of R scripts. A **script** is usually a text file which you write your code in, generally code that is longer than a few lines. It is recommended that you create a few of these as you proceed through the course.\n\n### **Creating a new script**\n\n**Click on File -\\> New file -\\> R Script**\n\n::: {.callout-note}\nAlternatively you can press the short cut keys Ctrl+Shift+N.\n:::\n\nScripts execute sequentially from top to bottom, and give you the advantages of:\n\n- Syntax highlighting, to identify code elements by colour\n- Auto completion of code\n\nYou will see the benefits of these as you type your code throughout the course.\n\n### **Saving a new script**\n\nIn practice, you would save your scripts in a specific folder. Each sub-folder of the root project would containing one type of file (R scripts, images, notebooks etc).\n\nThis is known as a **tree** structure, where there is a root of the tree, and the sub-folders themselves are the **branches**.\n\nFor this course, save your scripts in the root directory (where the .Rproj files are), this will ensure all filepaths for later chapters function as expected.\n\nTo save the script click on \"File\", select \"Save as\" and choose a location.\n\n::: {.callout-note}\nAlternatively you can press the short cut keys Ctrl + S.\n:::\n\n### **Running code in an R Script**\n\nAfter typing some code in your R script, there are several ways to run it:\n\n- Click the cursor to the end of the line of code and press **CTRL + ENTER**.\n\n- To run every line of code in your file you can press **CTRL + SHIFT + ENTER**.\n\nYou can use keyboard shortcuts to diversify and speed up your workflow if appropriate.\n\n### **Example**\n\nType the following in your script and run the code:\n\n(i) Run line by line with Ctrl + Enter.\n\n(ii) Run every line with Ctrl + Shift + Enter.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n\"I am learning R\"\n\n2 + 4\n\n23 - 6; 36 + 5\n```\n:::\n\n\n### Commenting Code\n\nCommenting your code to describe functionality is an important skill to learn. It allows others to use your code in the future and can help you pick up code you haven't worked on for a while. As with most skills, start small and build up your experience with practice.\n\nYou can add comments using the hash key \"#\".\n\nThe **hash (#)** tells R not to run any of the text on that line to the right of the symbol. Keep your comments concise and to the point. Excessive comments can make code look cluttered and confusing.\n\n### **Example** {.unnumbered}\n\nLets write a comment in your script.\n\nType the hash \"#\" and write yourself a note at the top of your script.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# This is my first R script\n```\n:::\n\n\nComments will be used throughout these course materials to highlight new concepts.\n\nAdd your own if helpful, or edit/remove any that don't help.\n\n::: {.callout-tip}\nComments can also be used to prevent R from running code that you don't want to delete by typing a hash at the beginning of the line of code.\n:::\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Comment out a line of code\n\n# 2 + 2 \n```\n:::\n\n\n::: {.callout-note}\nAlternatively you highlight line(s) of code and press CTRL + SHIFT + C to comment them out.\n:::\n\n### **Multi-line Commentary** {.unnumbered}\n\nTo write more than one line of code, use a hash sign followed by a single quotation mark **#'**.\n\nThis creates a multi-line comment that inputs the symbol again each time you start a new line.\n\nYou can delete the **#'** on a new line where you want to write code for R to run.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n#' This is a multi-line comment\n#' you hope you like the look of R Studio so far!\n```\n:::\n\n\n## The Environment Pane\n\nThe top right pane is very useful as it shows you what you have saved in your workspace (environment), such as:\n\n- Variables\n- Functions\n- Datasets\n\nAlso in the Environment is the **History** tab, which keeps a record of all previous commands.\n\nIn newer versions of R Studio there is the **Tutorial** tab, which provides links to install the built in tutorial for this tool.\n\n## Files and Packages Pane\n\nThe bottom right pane has a number of different tabs:\n\n- The **Files** tab has a navigable file manager, just like the file explorer or finder app on your operating system.\n\n- The **Plots** tab is where graphics you create will appear.\n\n- The **Packages** tab shows you the packages that are installed and those that can be installed, more on this in Chapter 3.\n\n- The **Help** tab allows you to search the R documentation for help and is where the help appears when you ask for it from the Console.\n\n- You may also see a **Viewer** tab, which comes with installed packages that allow you to export scripts to different formats such as HTML and PDF. It will show you the finished product.\n\n## Cheat Sheets\n\nFor more information about R Studio, you can find the R Studio Cheat Sheet under the **Help -\\> Cheat sheet**.\n\nThere are cheat sheets for almost every popular package and tool within this framework, make sure to bookmark them as you go!\n\n# Data Types\n\nTo get the best out of R, you need to understand the basic data types and how to operate on them.\n\nDifferent data types have different properties; if you try to run:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n1 + \"two\"\n```\n:::\n\n\nyou will get an error due to a mismatch of types, since you are adding a number to a word.\n\n## Numeric Data\n\nLet's start by working with numbers.\n\n### Numeric Data Types\n\nNot all numeric data is categorised the same. There are two key datatypes for them:\n\n- Double (dbl)\n\n- Integers (int)\n\n- A **Double** is the general numeric datatype and by default R will treat all numbers you use as double unless you give it an explicit reason to think otherwise.\n\n - So any number with or without a decimal place will be treated as double. This is quite different from other languages such as Python.\n\n- An **Integer** is a positive or negative whole number with no decimal place, such as -2, -1, 0, 1, 2.\n\n - In R these aren't as widely used, but should it be required, you specify them using a capital \"L\" at the end of the number for R to recognize them as such.\n\n### Numeric Operators\n\nYou will likely perform mathematical operations with numbers. Here is a list of some common operators:\n\n| Operator | Description |\n|:---------------------------:|:-----------------------------------------:|\n| \\+ | Addition |\n| \\- | Subtraction |\n| \\* | Multiplication |\n| / | Division |\n| \\^ | Exponents/Powers |\n| %% | [Modulo Division](https://en.wikipedia.org/wiki/Modulo_operation) |\n| %/% | [Floor Division](https://en.wikipedia.org/wiki/Floor_and_ceiling_functions) |\n\nLet's have a play. What do you think the code below does?\n\n### **Example**\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Numeric operations\n\n9 + 27.73\n\n(59 + 73 + 2) / 3\n```\n:::\n\n\nR will follow BODMAS/BIDMAS for the order of mathematical operations.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# R follows Order of Operations. \n\n10 + 11 * 12 / 3 - 5^2\n```\n:::\n\n\n5\\^2 means 5 raised to the power of 2 (squared) or 5 \\* 5.\n\n## Textual Data\n\nIn R, you refer to text as **character** (chr) strings. They are sequences of character data, usually used to store qualitative data.\n\nStrings are contained within either 'single' or \"double\" quotation marks.\n\nAll characters between the opening and the closing quote are part of the string.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Example of a character string\n\n\"Hello World\"\n```\n:::\n\n\nThe choice between single and double quotes is up to the user, as long as you start and end with the same symbol.\n\n### **A note on quotes** {.unnumbered}\n\nWhat you must be careful of however, is utilising apostrophes or quotes within a sentence.\n\nIf you must do this, you use one quotation mark to open and close the string and the **other** to type the quote.\n\nThe following code is incorrect:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Incorrect character string\n\n\"You should be proud of when you typed \"Hello World\" and ran that code!\"\n```\n:::\n\n\nNotice that the syntax highlighting has told you that something is wrong, as the \"Hello World\" is outside of the string, since you used too many double quotes.\n\nHowever, if you switch to single quotes, this will work fine.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Correct character string\n\n\"You should be proud of when you typed 'Hello World' and ran that code!\"\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Correct character string\n\n'You should be proud of when you typed \"Hello World\" and ran that code!'\n```\n:::\n\n\nNotice that the outputs here are slightly different. This is because when inside a string, R needs to be sure that the character (such as a quote mark) is being used as raw text, as opposed to it's other function as a way to create strings.\n\nThis manifests itself as a **backslash \\\\** which is known as an escape character. It basically tells R to interpret the character that directly follows it as raw text.\n\n::: {.callout-tip}\nIf you forget to put quotes around something, you can highlight and press the quote key and it will add quotes to both sides.\n:::\n\n## Logical Data\n\nIn R these are written as \"TRUE\" or \"FALSE\" and cannot take any other form.\n\n::: {.callout-note}\nThey are special R data types - not characters!\n:::\n\n### Comparisons to produce logicals\n\nThese seem arbitrary at first, but are **essential** for comparison purposes, and are created under the hood many times when performing data manipulations such as filtering.\n\nThe logical operators that can output them as an answer to a question are as follows:\n\n| Logical Operator | Description |\n|:----------------:|:------------------------:|\n| \\< | Less Than |\n| \\<= | Less Than or Equal To |\n| \\> | Greater Than |\n| \\>= | Greater Than or Equal To |\n| == | Equal To |\n| != | Not Equal To |\n| %in% | Membership |\n| \\| | Or |\n| & | And |\n\n### **Examples** {.unnumbered}\n\nIs 4 greater than 5?\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Greater than comparison\n\n4 > 5\n```\n:::\n\n\nIs 25 equivalent to 5 squared?\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check equivalence comparison\n\n25 == 5^2\n```\n:::\n\n\nIs 1 not equivalent to 2?\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check non-equivalence comparison\n\n1 != 2\n```\n:::\n\n\n### Numeric representation of logicals\n\nSince logicals are binary operators (they are one or the other, nothing else), they also have binary numeric values behind them:\n\n- TRUE is represented as 1\n- FALSE is represented as 0.\n\nTherefore, you can convert them to numbers and even perform arithmetic operations on them!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Prove that TRUE has a numeric representation\n\nTRUE + TRUE\n```\n:::\n\n\nAnd use any other operator too!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Prove that FALSE has a numeric representation\nFALSE * 2.5\n```\n:::\n\n\nThese are quite a complex datatype and there is much more beyond the scope of the course in this topic.\n\n### **Checking Datatypes** {.unnumbered}\n\nyou can see the respective type of any data by using the **typeof()** function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Output datatypes of specific numeric inputs\n\ntypeof(10)\n\ntypeof(10L)\n```\n:::\n\n\n## Functions\n\nR has a range of built-in functions for common operations.\n\n:::{.callout-note}\nFunctions are commands that take an input, do something to it, and produce an output. These are essential to R programming and will be covered in detail later.\n:::\n\nFunctions in R are written as:\n\n- A word (the name given to the function by its creator), which is **fixed**.\n- Brackets, inside which you type the inputs (data types or structures you wish to pass into the function).\n\nFor example:\n\n- The square root function is written as **sqrt(inputs)**\n- The rounding function is written as **round(inputs)**\n\nLet's see these in action.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the square root of 9 using functions.\n\nsqrt(9)\n\n\n# Rounding a value using functions. \n\nround(3.6357)\n```\n:::\n\n\nThe inputs you give to the function are called **values** and have labels/names, known as the **argument**, which are fixed by the creator of the function.\n\nIn general this is written as:\n\n> **function(argument = value,..)**\n\n### **Arguments**\n\nNotice that above you didn't give the argument, you just gave the value. This is acceptable in this case as sqrt() and round() are quite simple functions.\n\nHowever, functions such as round() can take more than one argument, many are optional and some have a default value that can be turned off and tweaked.\n\n> A common example is when rounding, you would likely want to specify the number of decimal places to round to. This can be controlled with the optional **digits** argument.\n\nyou separate arguments within functions using commas, as follows:\n\n> **func(argument_1 = value_1, argument_2 = value_2,...)**\n\nLet's see an example of using multiple arguments with the round() function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round to 2 decimal places\n\nround(3.6357, digits = 2) \n```\n:::\n\n\nYou **must** make sure that the argument name is correct (as defined by the function itself), otherwise you will get an error.\n\n:::{.callout-note}\nNotice that even without the digits argument, the round() function works. This is because digits (like many arguments) is optional, and has a value of 0 by default, rounding to the nearest whole number.\n:::\n\n### **Function documentation**\n\nYou can investigate what specific functions do by navigating to the \"Help\" tab in the bottom right and searching it by name.\n\n{fig-alt=\"The document string of the rounding functions in R.\"}\n\nyou see:\n\n- The description of the function of family of functions (group of functions that perform similar actions).\n\n- Examples of its use under \"Usage\".\n\n- Descriptions of its arguments and what they expect as their values under \"Arguments\".\n\nand some other niche notes for more advanced R users.\n\n## Exercise\n\n::: panel-tabset\n### **Exercise**\n\nWhat is the data type of the following?\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Guess the datatypes\n\n\"10\"\n\n10L\n\n10\n\nTRUE\n\n\"ten\"\n\n\"TRUE\"\n\nFALSE\n\n\"FALSE\"\n```\n:::\n\n\n### **Show Answer**\n\nThe \"typeof()\" output denotes the (R internal) type or storage mode of any object.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find out the datatypes\n\ntypeof(\"10\")\n\ntypeof(10L)\n\ntypeof(10)\n\ntypeof(TRUE)\n\ntypeof(\"ten\")\n\ntypeof(\"TRUE\")\n\ntypeof(FALSE)\n\ntypeof(\"FALSE\")\n```\n:::\n\n\nWere there any that surprised you?\n:::\n\n## Data Type Conversion\n\nNow that you know some of the data types you will look at how to convert between them.\n\nR doesn't require you to set the data type when you create it, instead it figures out what the best data type is for the object you are creating - numeric, character, logical, etc.\n\nGiven that R is a dynamically typed language, sometimes the inference it makes about data types are not correct and must be altered.\n\n### The as.type() family\n\nIn order to convert the data, you need to use the **as.type()** family of functions, some examples being:\n\n- **as.numeric()** to convert to Double.\n\n- **as.character()** to convert to Characters.\n\n- **as.logical()** to convert to Logical.\n\nLet's see some in action. What do you notice in the output?\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Examples of type conversion\n\nas.integer(4.996453)\n\nas.numeric(\"2\")\n\nas.character(245)\n```\n:::\n\n\nA summary:\n\n- as.integer() did no rounding, it just removed everything after the decimal place and left the integer component.\n\n- as.numeric() converted the string \"2\" to a double.\n\n- as.charater() placed quotation marks around 245 to make it a character string.\n\nYou can check the types of these conversions by wrapping them up in a typeof() function. Nesting functions like this is commonplace in R and many other programming languages.\n\nBrackets can get unruly when doing this, the rainbow colours you setup earlier will help distinguish which bracket belongs to which function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check the type of converted data\n\ntypeof(as.integer(4.996453)) \n```\n:::\n\n\n# Variable Assignment\n\nVariables are an integral part of any programming language.\n\nThey allow you to store and label data under a specific name, acting as a place holder. Think of it as a container, the main purpose is to label and store the data in memory.\n\n## Creating and Returning a Variable\n\nYou can assign a value to a variable using the **\\<-** operator.\n\n:::{.callout-tip}\nThe keyboard shortcut for this is ALT - (alt + dash/minus).\n:::\n\nAn example is below:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To assign a variable\n\nweight_kg <- 60\n```\n:::\n\n\nThe variable name goes on the left, followed by the assignment operator, then lastly the value that name is assigned to.\n\nOnce an object has been created it will appear in your Environment pane which helps you keep track of what objects you have in your current workspace - the top right pane.\n\nLiterally typing the name of the variable and running the code returns the value assigned to it.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To display the variable\n\nweight_kg\n```\n:::\n\n\n### **Concatenation**\n\nIf you wanted to display the weight a bit better, you could use the \"cat()\" function (concatenate).\n\nThis can take data, raw character strings and variables as inputs, grouping them together in a sentence/sequence of outputs.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the cat() function to display your result\n\ncat('my weight is: ', weight_kg)\n```\n:::\n\n\nYou could continue this with other variables created as well. Let's add your age.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating an age variable and improving the sentence\n\nage_yrs <- 27\n\ncat(\"My weight is\", weight_kg, \"kg, and I am\", age_yrs, \"years old.\")\n```\n:::\n\n\n### **Mathematical Operations on Variables**\n\nYou can apply addition, subtraction and other operations to your variables. It is the value assigned to the variable that determines the datatype.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Prove that the value is what determines the datatype\n\ntypeof(weight_kg)\n```\n:::\n\n\nNow let's do some maths.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add 4 to your weight\n\nweight_kg + 4\n```\n:::\n\n\n### **Creating new variables from existing**\n\nYou can modify the value of a variable in some way and then assign that to a new variable.\n\nFor example, let's convert weight from kg to lbs, where 1kg = 2.2lbs\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a new variable, converting the existing one\n\nweight_lb <- weight_kg * 2.2\n\n# To display the variable\n\nweight_lb\n```\n:::\n\n\n### **Overwrite and reassign an existing variable**\n\nIf you want to reassign a variable you could use the assignment operator again.\n\nLet's assign your height as 5.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create height variable\n\nheight <- 5\n\n\n# Display height\n\nheight\n```\n:::\n\n\nUsing the same variable name will overwrite the previously assigned variable, even if you assign it to the same value.\n\nLet's overwrite height to a different value.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Assign and overwrite height\n\nheight <- 7\n\n# Display new height\n\nheight\n```\n:::\n\n\nYou can also assign variables using the **=** operator, but this is considered bad practice in R as it is used to give function arguments a value.\n\n## Removing Variables\n\nTo remove a variable, use the **remove()** function of R or the alias **rm()**.\n\nFor example:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Removing assigned variables using the remove function\n\nremove(height)\n\n# rm(height) will also work\n```\n:::\n\n\nBe careful with this, R will not warn you that you are about to permanently remove a variable, it will perform the action you asked it to.\n\nShould you do this by mistake, you need to re-run the line where the variable was created.\n\n## Variable Names\n\nNaming variables is another skill important to programming. Some points to consider:\n\n- R is case sensitive, so whatever you name your variables has be typed **exactly** to display them.\n- Names must start with a letter.\n- Names cannot contain spaces, this is an error in syntax.\n- Names cannot use reserved words such as \"TRUE\" or \"FALSE\" or the name of a function like \"sqrt()\", which already mean something in R.\n- Names should be descriptive, so that when someone else is reading your code they don't have to guess what data is held within a variable.\n\nNotice above where you wrote \"weight_kg\", it is a weight value in kg.\n\n### **Cases**\n\nThere are several conventions for construction variable and function names:\n\n**snake_case**\n\n- Names are entirely lower case.\n- Names separate words with underscores \\*\\*\\_\\*\\*.\n\n**camel case**\n\n- Names start with a capital letter and each word is separated by them, such as **WeightKg**\n\n**period case**\n\n- Names are separated with full stops, such as **weight.kg**.\n\nSnake case is used often and leads to clear, informative variable names without too much complexity.\n\nThere is more detailed information on good variables names in your other course: [Best Practice in Programming](https://learninghub.ons.gov.uk/course/view.php?id=497)\n\n## Exercise\n\n::: panel-tabset\n### **Exercise**\n\n1. Why does this code not work?\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Assign my_variable\n\nmy_variable <- 10\n\n\n# Not working\n\nmy_varIable\n```\n:::\n\n\n2. Create two variables:\n\n- Time at a value of 30 seconds.\n- Distance at a value of 10 metres.\n\nThen:\n\n- Double the time variable and overwrite it.\n- Add 5 to the distance variable and overwrite it.\n\n3. Using the variables you created above, compute the speed using the formula:\n\n- **speed = distance / time**\n\n4. Use the remove() and rm() functions to remove the time and distance variables.\n\n### **Show Answer**\n\n1. You would have got the error below:\n\n:::{.callout-important}\nError: object 'my_varIable' not found\n:::\n\nVariables are case sensitive, so when you called the variable with a capital \"I\", it tried to recall a name that didn't exist.\n\nError messages of the form \"object '...' not found\" tell you that R cannot find an object, in this case variable, with that name.\n\n2. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create time\n\ntime_secs <- 30\n\n# Create distance\n\ndistance_metres <- 10\n\n# Overwrite time\n\ntime_secs <- 30 * 2\n\n# Overwrite distance\n\ndistance_metres <- distance_metres + 5\n```\n:::\n\n\n3. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create speed using the formula\n\nspeed <- distance_metres / time_secs\n\n# Display speed\n\nspeed\n```\n:::\n\n\n4. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Remove time\n\nremove(time_secs)\n\nrm(distance_metres)\n```\n:::\n\n:::\n\n# Help\n\nThere is a wealth of resource to help you progress in your R journey. Some of these are explored below.\n\n## Cheat Sheets\n\nYou can access these by clicking on **Help** tab in R Studio and then **RStudio Cheat Sheets**. They provide an excellent reference point for many common tasks.\n\n{fig-alt=\"The dplyr cheat sheet for data manipulation.\"}\n\n## R Documentation\n\n::: panel-tabset\n### **Example** {.unnumbered}\n\nWhen you use a function for a first time or come back to it at a later date , it can be helpful to look through its documentation.\n\nYou can use code to access help documentation:\n\n- Precede the function name with a question mark **?**.\n\n- You can use the **help()** function built into R and the name of the function inside it.\n\nLet's see an example with the mean() function, that computes the mean of a collection of values.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To access the R help documentation\n\n?mean \n\n#or \n\nhelp(mean) # Note that you didn't need to use () on the function name\n```\n:::\n\n\nYou could also use Google to search for the same documentation online, with the accessibility benefits offered by html.\n\nBecoming adept at searching for answers to your queries and using coding elements is a skill that many programmers build up over time. You don't need to memorise every piece of syntax.\n\n### **Help Pages** {.unnumbered}\n\nEach help page is divided into sections.\n\nWhich sections appear can vary from help page to help page, but you can usually expect to find these useful headings:\n\n**Description** - A short summary of what the function does.\n\n**Usage** - An example of how you would type the function. Each argument of the function will appear in the order R expects you to supply it (if you don't use argument names).\n\n**Arguments** - A list of each argument the function takes and what to supply to it as a value. You will spend most of your time here, investigating what options are available.\n\n**Details** - A more in-depth description of the function and how it operates.\n\n**Value** - A description of what the function returns when you run it.\n\n**See Also** - A short list of related R functions.\n\n**Examples** - Example code that uses the function and is guaranteed to work. This helps give you an idea of what the function is capable of.\n:::\n\n## Stack Overflow\n\n[Stack Overflow](https://stackoverflow.com/questions/tagged/r) is a great site to check if anyone has experienced an error before.\n\nYou can search the R-tagged questions on the Stack Overflow site, of which there are over 501,000 as of January 2024.\n\nNote that to make the most use of the forum, you should provide:\n\n- What you were attempting with the code you wrote\n- The code you wrote\n- Steps you took to try and solve it (your interpretation of what happened)\n\nThis allows other users to replicate your problem, so they can explain what to do or why the method causes issues.\n\n## The Data Science Campus Faculty Team\n\nIf you have any issues with this course; or notice any errors, please contact the training team on the email:\n\n> **Data.Science.Campus.Faculty\\@ons.gov.uk**\n\nPlease be aware that due to training commitments there may be a small wait before you respond to your query.\n\n# Summary\n\nYou have covered a lot material in R and yet there is still so much more to cover in terms of functionality, as R has so much to offer.\n\nBy no means are you expected to remember all the above, what is better is that you understand the problems you want to solve and then use the references or material provided to go about solving it.\n\nNext up you will look at data structures in R.\n",
- "supporting": [],
+ "engine": "knitr",
+ "markdown": "---\ntitle: \"Chapter 1 - Getting Started with R\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n- Be familiar with R Studio.\n- Explore the RStudio environment, layout, and customization.\n- Understand the Key Benefits of using R.\n- How to run code in R.\n- Know where to get help.\n- Discover R's data types.\n- Be able to create Variables.\n\n# What is R?\n\nAn open source programming language and environment for statistical computing and graphics.\n\nIt was initially written by **Ross Ihaka and Robert Gentleman** at the Department of Statistics of the University of Auckland in New Zealand.\n\nIt provides a wide variety of statistical techniques out of the box, leading to popularity among Analysts, Statisticians and Data Scientists.\n\nSince it was created by statisticians (instead of computer scientists), R has some quirky aspects to it that take some time to get used to.\n\n## What are the benefits of using R?\n\nR is the 6th most popular programming language in the [Popularity of Programming Languages Index (PYPL)](https://pypl.github.io/PYPL.html) as of January 2024.\n\nThere are several reasons for this trend:\n\n- Free and open source, people can modify and share because its design is publicly accessible.\n\n- Cross Platform, it can be used across a range of operating systems i.e Windows, Linux, OS.\n\n- Great support from a diverse and welcoming community. e.g. #rstats twitter community, numerous [R Meet Ups](https://www.meetup.com/topics/r-programming-language). They have written outstanding open access material that you can use to learn R.\n\n- There are lots of [packages available](https://cran.r-project.org/web/packages/available_packages_by_name.html) which contain implementations of processes and ready-made code not available out of the box.\n\n- Powerful tool for communicating results, including:\n\n - [RMarkdown](https://rmarkdown.rstudio.com/) makes it easy to turn your files into PDF'S, Power point presentations\n - [Shiny](https://shiny.rstudio.com/) allows you to make beautiful interactive apps and dashboards.\n\n# R Studio\n\nR is a programming language that runs computations, while R Studio is an integrated development environment (IDE) that provides an interface by adding many convenient features and tools.\n\nYou do not have to use R Studio to code in R, however it was built specifically to get the best out of the language and is highly recommended. If you cannot get access to R Studio desktop edition, you could consider using Posit Cloud (the new name for R Studio Cloud). Instructions for this are in a separate html guide.\n\nOther IDEs that work with R include:\n\n- [Jupyter notebook](https://jupyter.org/)\n- [VisualStudio](https://visualstudio.microsoft.com/services/visual-studio-online/)\n\n## Opening R Studio\n\nR Studio is broken down into four panels.\n\nWhen you open R Studio for the first time, you see this:\n\n{fig-alt=\"R Studio interface with the Code Editor, Environment, Console and Files panes.\"}\n\nIf you don't see the Code Editor pane, go to the tool bar and click **View -\\> Panes -\\> Show All Panes**.\n\nYou can also make panes bigger or smaller by hovering between two panes and then clicking and dragging.\n\n## Global Settings Changes\n\nUpon first opening R Studio, you have the most basic form of the tool that has some of the most useful workflow features off by default. Let's adjust these settings.\n\nFirstly, navigate to \"Tools\" and \"Global Options\", which is where this tweaking takes place.\n\n{fig-alt=\"Global options menu with general, code, appearance and more as options.\"}\n\nYou see that R Studio can be heavily customised. You will only scratch the surface here.\n\n- First, remain on the \"General\" menu and:\n - Under **Workspace**, untick \"Restore .RData into workspace at startup\" and change the drop down below it to \"Never\".\n - Under **History**, untick \"Always save history (even when not saving .Rdata)\".\n\nThe reason you don't want to use these is that they are legacy ways of saving R code, and are not as effective or useful as more modern ways of saving your work, controlling coding logs with Git and so on.\n\n- Secondly, navigate to the \"Code\" menu and \"Editing\" sub-menu:\n - Provided you have R Version 4.1+, tick \"Use native pipe operator \\|\\>\".\n - Tick \"Soft-wrap R source files\", which prevents code continuation past the width of the editor pane.\n- Thirdly, change to the \"Display\" sub-menu, still within the \"Code\" menu:\n - Tick \"Allow scroll past end of document\" if you would like to be able to scroll past the final lines of your script.\n - Tick \"Highlight R function calls\", as this is incredibly useful for distinguishing different R objects.\n - Tick \"Use rainbow parentheses\" as this allows you to distinguish between different layers of brackets, which helps with syntax errors.\n- Finally, navigate to the \"Appearance\" menu:\n - Change the font size to whatever is most comfortable for you, 14 works well.\n - Change the help font size to whatever is most comfortable for you, 12 is a good default.\n - Choose a theme that suits your preferences, many people prefer dark mode themes such as \"Vibrant Ink\" due to the code highlighting functionality.\n\nNow that you have R Studio set up, you will create an R Project to make management of your code simpler.\n\n## R Projects\n\nCreating an R Project enables your work to be bundled in a folder that is:\n\n- Self-contained\n- Portable\n\nAll the scripts, data files, figures, outputs and history can be stored in sub-folders.\n\nThe root folder of the R Project (which you choose when you create it) contains the **.Rproj** file and is the **working directory** each time you open it.\n\n### Creating an R Project\n\nTo create an R Project, select **File --\\> New Project** and you will be given some examples of where to store the .Rproj file, a.k.a where the working directory will be.\n\n{fig-alt=\"A project can be created in a new directory, existing directory or from GitHub.\"}\n\nYou can:\n\n- Create a **New Directory** - Create a new folder/directory for the R Project to be placed in, all subfolders created within will be part of the project.\n\n- Create a project in an **Existing Directory** - Creating an R Project in an existing folder/directory\n\n- Import an existing project from a repository created on a Version Control platform, such as GitHub or Gitlab. This is beyond the scope of this course.\n\n### **Exercise** {.unnumbered}\n\nCreate an R project in an **existing directory**, selecting the **course_content** folder provided.\n\nIn your own work, saving it one level higher in the root folder is a better approach. For this course, you must save it where you will save your scripts so the filepaths function correctly.\n\n{fig-alt=\"The root folder showing the .Rproj file alongside the othr folders.\"}\n\nAfter creating the R Project, it will open and set your working directory.\n\nWere you to share your folder with others, they can open the project file and everything will be set for them. This is a big step towards ensuring reproducibility.\n\n### Re-opening the project\n\nDue to the changes you made earlier to the global settings, R Studio will be fresh each time you open it.\n\nSo how do you get back to your project?\n\nThankfully, you have the project menu in the top right, which allows you to:\n\n- Create a new project\n- Open existing project(s)\n- Close projects\n- See recently open projects and jump straight to them\n\n{fig-alt=\"The top right menu that allows you to interact with projects.\"}\n\nFrom here, assume you create and save your scripts in this project in order for filepaths in Chapter 3 onwards to function.\n\n> Let's return now to R Studio, and discuss each of its 4 panes in detail.\n\n## The Console Pane\n\nThe bottom left pane is the console, where you can type and execute code. This also contains a **terminal** or **command line** that can be used to interact with your computer.\n\nR output will appear in the console regardless of where you execute it from.\n\nTo run code in the Console, type next to the command prompt and hit \"Enter\".\n\n### Exercise\n\n::: panel-tabset\nLet's practice some mathematics in the console.\n\n### **Exercise** {.unnumbered}\n\n1. Type the expressions below and run them in the console one at a time.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n2 + 4\n\n23 - 6; 36 + 5\n\n1 + 3 +\n```\n:::\n\n\n\n\n### **Show Answer** {.unnumbered}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n2 + 4\n```\n:::\n\n\n\n\nNotice the \\[1\\]. This is how R tells you the position you're at in execution.\n\nAs a rule of thumb, write and execute separate commands on separate lines. Although it is messy and often unhelpful, you can put multiple commands on the same line by separating them by a semicolon.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n23 - 6; 36 + 5\n```\n:::\n\n\n\n\nNote that if a **\"+\"** appears instead of the command prompt **\"\\>\"**, this means that the statement you submitted was incomplete. The console is expecting further input.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n1 + 3 +\n```\n:::\n\n\n\n\nYou can either complete the expression or press the **escape** key to reset.\n:::\n\nThe R Studio Console automatically maintains a history so you can retrieve previous commands.\n\nOn a blank line in the Console, press the up arrow key and see what happens.\n\nThe issue with coding in the console is that you can't save it and it is not easy to edit, which brings you to the code editor.\n\n## The Code Editor Pane\n\nThis is the top left pane, where you will do the majority of your coding. Often this is in the form of R scripts. A **script** is usually a text file which you write your code in, generally code that is longer than a few lines. It is recommended that you create a few of these as you proceed through the course.\n\n### **Creating a new script**\n\n**Click on File -\\> New file -\\> R Script**\n\n::: {.callout-note}\nAlternatively you can press the short cut keys Ctrl+Shift+N.\n:::\n\nScripts execute sequentially from top to bottom, and give you the advantages of:\n\n- Syntax highlighting, to identify code elements by colour\n- Auto completion of code\n\nYou will see the benefits of these as you type your code throughout the course.\n\n### **Saving a new script**\n\nIn practice, you would save your scripts in a specific folder. Each sub-folder of the root project would containing one type of file (R scripts, images, notebooks etc).\n\nThis is known as a **tree** structure, where there is a root of the tree, and the sub-folders themselves are the **branches**.\n\nFor this course, save your scripts in the root directory (where the .Rproj files are), this will ensure all filepaths for later chapters function as expected.\n\nTo save the script click on \"File\", select \"Save as\" and choose a location.\n\n::: {.callout-note}\nAlternatively you can press the short cut keys Ctrl + S.\n:::\n\n### **Running code in an R Script**\n\nAfter typing some code in your R script, there are several ways to run it:\n\n- Click the cursor to the end of the line of code and press **CTRL + ENTER**.\n\n- To run every line of code in your file you can press **CTRL + SHIFT + ENTER**.\n\nYou can use keyboard shortcuts to diversify and speed up your workflow if appropriate.\n\n### **Example**\n\nType the following in your script and run the code:\n\n(i) Run line by line with Ctrl + Enter.\n\n(ii) Run every line with Ctrl + Shift + Enter.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n\"I am learning R\"\n\n2 + 4\n\n23 - 6; 36 + 5\n```\n:::\n\n\n\n\n### Commenting Code\n\nCommenting your code to describe functionality is an important skill to learn. It allows others to use your code in the future and can help you pick up code you haven't worked on for a while. As with most skills, start small and build up your experience with practice.\n\nYou can add comments using the hash key \"#\".\n\nThe **hash (#)** tells R not to run any of the text on that line to the right of the symbol. Keep your comments concise and to the point. Excessive comments can make code look cluttered and confusing.\n\n### **Example** {.unnumbered}\n\nLets write a comment in your script.\n\nType the hash \"#\" and write yourself a note at the top of your script.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# This is my first R script\n```\n:::\n\n\n\n\nComments will be used throughout these course materials to highlight new concepts.\n\nAdd your own if helpful, or edit/remove any that don't help.\n\n::: {.callout-tip}\nComments can also be used to prevent R from running code that you don't want to delete by typing a hash at the beginning of the line of code.\n:::\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Comment out a line of code\n\n# 2 + 2 \n```\n:::\n\n\n\n\n::: {.callout-note}\nAlternatively you highlight line(s) of code and press CTRL + SHIFT + C to comment them out.\n:::\n\n### **Multi-line Commentary** {.unnumbered}\n\nTo write more than one line of code, use a hash sign followed by a single quotation mark **#'**.\n\nThis creates a multi-line comment that inputs the symbol again each time you start a new line.\n\nYou can delete the **#'** on a new line where you want to write code for R to run.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n#' This is a multi-line comment\n#' you hope you like the look of R Studio so far!\n```\n:::\n\n\n\n\n## The Environment Pane\n\nThe top right pane is very useful as it shows you what you have saved in your workspace (environment), such as:\n\n- Variables\n- Functions\n- Datasets\n\nAlso in the Environment is the **History** tab, which keeps a record of all previous commands.\n\nIn newer versions of R Studio there is the **Tutorial** tab, which provides links to install the built in tutorial for this tool.\n\n## Files and Packages Pane\n\nThe bottom right pane has a number of different tabs:\n\n- The **Files** tab has a navigable file manager, just like the file explorer or finder app on your operating system.\n\n- The **Plots** tab is where graphics you create will appear.\n\n- The **Packages** tab shows you the packages that are installed and those that can be installed, more on this in Chapter 3.\n\n- The **Help** tab allows you to search the R documentation for help and is where the help appears when you ask for it from the Console.\n\n- You may also see a **Viewer** tab, which comes with installed packages that allow you to export scripts to different formats such as HTML and PDF. It will show you the finished product.\n\n## Cheat Sheets\n\nFor more information about R Studio, you can find the R Studio Cheat Sheet under the **Help -\\> Cheat sheet**.\n\nThere are cheat sheets for almost every popular package and tool within this framework, make sure to bookmark them as you go!\n\n# Data Types\n\nTo get the best out of R, you need to understand the basic data types and how to operate on them.\n\nDifferent data types have different properties; if you try to run:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n1 + \"two\"\n```\n:::\n\n\n\n\nyou will get an error due to a mismatch of types, since you are adding a number to a word.\n\n## Numeric Data\n\nLet's start by working with numbers.\n\n### Numeric Data Types\n\nNot all numeric data is categorised the same. There are two key datatypes for them:\n\n- Double (dbl)\n\n- Integers (int)\n\n- A **Double** is the general numeric datatype and by default R will treat all numbers you use as double unless you give it an explicit reason to think otherwise.\n\n - So any number with or without a decimal place will be treated as double. This is quite different from other languages such as Python.\n\n- An **Integer** is a positive or negative whole number with no decimal place, such as -2, -1, 0, 1, 2.\n\n - In R these aren't as widely used, but should it be required, you specify them using a capital \"L\" at the end of the number for R to recognize them as such.\n\n### Numeric Operators\n\nYou will likely perform mathematical operations with numbers. Here is a list of some common operators:\n\n| Operator | Description |\n|:---------------------------:|:-----------------------------------------:|\n| \\+ | Addition |\n| \\- | Subtraction |\n| \\* | Multiplication |\n| / | Division |\n| \\^ | Exponents/Powers |\n| %% | [Modulo Division](https://en.wikipedia.org/wiki/Modulo_operation) |\n| %/% | [Floor Division](https://en.wikipedia.org/wiki/Floor_and_ceiling_functions) |\n\nLet's have a play. What do you think the code below does?\n\n### **Example**\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Numeric operations\n\n9 + 27.73\n\n(59 + 73 + 2) / 3\n```\n:::\n\n\n\n\nR will follow BODMAS/BIDMAS for the order of mathematical operations.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# R follows Order of Operations. \n\n10 + 11 * 12 / 3 - 5^2\n```\n:::\n\n\n\n\n5\\^2 means 5 raised to the power of 2 (squared) or 5 \\* 5.\n\n## Textual Data\n\nIn R, you refer to text as **character** (chr) strings. They are sequences of character data, usually used to store qualitative data.\n\nStrings are contained within either 'single' or \"double\" quotation marks.\n\nAll characters between the opening and the closing quote are part of the string.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Example of a character string\n\n\"Hello World\"\n```\n:::\n\n\n\n\nThe choice between single and double quotes is up to the user, as long as you start and end with the same symbol.\n\n### **A note on quotes** {.unnumbered}\n\nWhat you must be careful of however, is utilising apostrophes or quotes within a sentence.\n\nIf you must do this, you use one quotation mark to open and close the string and the **other** to type the quote.\n\nThe following code is incorrect:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Incorrect character string\n\n\"You should be proud of when you typed \"Hello World\" and ran that code!\"\n```\n:::\n\n\n\n\nNotice that the syntax highlighting has told you that something is wrong, as the \"Hello World\" is outside of the string, since you used too many double quotes.\n\nHowever, if you switch to single quotes, this will work fine.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Correct character string\n\n\"You should be proud of when you typed 'Hello World' and ran that code!\"\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Correct character string\n\n'You should be proud of when you typed \"Hello World\" and ran that code!'\n```\n:::\n\n\n\n\nNotice that the outputs here are slightly different. This is because when inside a string, R needs to be sure that the character (such as a quote mark) is being used as raw text, as opposed to it's other function as a way to create strings.\n\nThis manifests itself as a **backslash \\\\** which is known as an escape character. It basically tells R to interpret the character that directly follows it as raw text.\n\n::: {.callout-tip}\nIf you forget to put quotes around something, you can highlight and press the quote key and it will add quotes to both sides.\n:::\n\n## Logical Data\n\nIn R these are written as \"TRUE\" or \"FALSE\" and cannot take any other form.\n\n::: {.callout-note}\nThey are special R data types - not characters!\n:::\n\n### Comparisons to produce logicals\n\nThese seem arbitrary at first, but are **essential** for comparison purposes, and are created under the hood many times when performing data manipulations such as filtering.\n\nThe logical operators that can output them as an answer to a question are as follows:\n\n| Logical Operator | Description |\n|:----------------:|:------------------------:|\n| \\< | Less Than |\n| \\<= | Less Than or Equal To |\n| \\> | Greater Than |\n| \\>= | Greater Than or Equal To |\n| == | Equal To |\n| != | Not Equal To |\n| %in% | Membership |\n| \\| | Or |\n| & | And |\n\n### **Examples** {.unnumbered}\n\nIs 4 greater than 5?\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Greater than comparison\n\n4 > 5\n```\n:::\n\n\n\n\nIs 25 equivalent to 5 squared?\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check equivalence comparison\n\n25 == 5^2\n```\n:::\n\n\n\n\nIs 1 not equivalent to 2?\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check non-equivalence comparison\n\n1 != 2\n```\n:::\n\n\n\n\n### Numeric representation of logicals\n\nSince logicals are binary operators (they are one or the other, nothing else), they also have binary numeric values behind them:\n\n- TRUE is represented as 1\n- FALSE is represented as 0.\n\nTherefore, you can convert them to numbers and even perform arithmetic operations on them!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Prove that TRUE has a numeric representation\n\nTRUE + TRUE\n```\n:::\n\n\n\n\nAnd use any other operator too!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Prove that FALSE has a numeric representation\nFALSE * 2.5\n```\n:::\n\n\n\n\nThese are quite a complex datatype and there is much more beyond the scope of the course in this topic.\n\n### **Checking Datatypes** {.unnumbered}\n\nyou can see the respective type of any data by using the **typeof()** function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Output datatypes of specific numeric inputs\n\ntypeof(10)\n\ntypeof(10L)\n```\n:::\n\n\n\n\n## Functions\n\nR has a range of built-in functions for common operations.\n\n:::{.callout-note}\nFunctions are commands that take an input, do something to it, and produce an output. These are essential to R programming and will be covered in detail later.\n:::\n\nFunctions in R are written as:\n\n- A word (the name given to the function by its creator), which is **fixed**.\n- Brackets, inside which you type the inputs (data types or structures you wish to pass into the function).\n\nFor example:\n\n- The square root function is written as **sqrt(inputs)**\n- The rounding function is written as **round(inputs)**\n\nLet's see these in action.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the square root of 9 using functions.\n\nsqrt(9)\n\n\n# Rounding a value using functions. \n\nround(3.6357)\n```\n:::\n\n\n\n\nThe inputs you give to the function are called **values** and have labels/names, known as the **argument**, which are fixed by the creator of the function.\n\nIn general this is written as:\n\n> **function(argument = value,..)**\n\n### **Arguments**\n\nNotice that above you didn't give the argument, you just gave the value. This is acceptable in this case as sqrt() and round() are quite simple functions.\n\nHowever, functions such as round() can take more than one argument, many are optional and some have a default value that can be turned off and tweaked.\n\n> A common example is when rounding, you would likely want to specify the number of decimal places to round to. This can be controlled with the optional **digits** argument.\n\nyou separate arguments within functions using commas, as follows:\n\n> **func(argument_1 = value_1, argument_2 = value_2,...)**\n\nLet's see an example of using multiple arguments with the round() function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round to 2 decimal places\n\nround(3.6357, digits = 2) \n```\n:::\n\n\n\n\nYou **must** make sure that the argument name is correct (as defined by the function itself), otherwise you will get an error.\n\n:::{.callout-note}\nNotice that even without the digits argument, the round() function works. This is because digits (like many arguments) is optional, and has a value of 0 by default, rounding to the nearest whole number.\n:::\n\n### **Function documentation**\n\nYou can investigate what specific functions do by navigating to the \"Help\" tab in the bottom right and searching it by name.\n\n{fig-alt=\"The document string of the rounding functions in R.\"}\n\nyou see:\n\n- The description of the function of family of functions (group of functions that perform similar actions).\n\n- Examples of its use under \"Usage\".\n\n- Descriptions of its arguments and what they expect as their values under \"Arguments\".\n\nand some other niche notes for more advanced R users.\n\n## Exercise\n\n::: panel-tabset\n### **Exercise**\n\nWhat is the data type of the following?\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Guess the datatypes\n\n\"10\"\n\n10L\n\n10\n\nTRUE\n\n\"ten\"\n\n\"TRUE\"\n\nFALSE\n\n\"FALSE\"\n```\n:::\n\n\n\n\n### **Show Answer**\n\nThe \"typeof()\" output denotes the (R internal) type or storage mode of any object.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find out the datatypes\n\ntypeof(\"10\")\n\ntypeof(10L)\n\ntypeof(10)\n\ntypeof(TRUE)\n\ntypeof(\"ten\")\n\ntypeof(\"TRUE\")\n\ntypeof(FALSE)\n\ntypeof(\"FALSE\")\n```\n:::\n\n\n\n\nWere there any that surprised you?\n:::\n\n## Data Type Conversion\n\nNow that you know some of the data types you will look at how to convert between them.\n\nR doesn't require you to set the data type when you create it, instead it figures out what the best data type is for the object you are creating - numeric, character, logical, etc.\n\nGiven that R is a dynamically typed language, sometimes the inference it makes about data types are not correct and must be altered.\n\n### The as.type() family\n\nIn order to convert the data, you need to use the **as.type()** family of functions, some examples being:\n\n- **as.numeric()** to convert to Double.\n\n- **as.character()** to convert to Characters.\n\n- **as.logical()** to convert to Logical.\n\nLet's see some in action. What do you notice in the output?\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Examples of type conversion\n\nas.integer(4.996453)\n\nas.numeric(\"2\")\n\nas.character(245)\n```\n:::\n\n\n\n\nA summary:\n\n- as.integer() did no rounding, it just removed everything after the decimal place and left the integer component.\n\n- as.numeric() converted the string \"2\" to a double.\n\n- as.charater() placed quotation marks around 245 to make it a character string.\n\nYou can check the types of these conversions by wrapping them up in a typeof() function. Nesting functions like this is commonplace in R and many other programming languages.\n\nBrackets can get unruly when doing this, the rainbow colours you setup earlier will help distinguish which bracket belongs to which function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check the type of converted data\n\ntypeof(as.integer(4.996453)) \n```\n:::\n\n\n\n\n# Variable Assignment\n\nVariables are an integral part of any programming language.\n\nThey allow you to store and label data under a specific name, acting as a place holder. Think of it as a container, the main purpose is to label and store the data in memory.\n\n## Creating and Returning a Variable\n\nYou can assign a value to a variable using the **\\<-** operator.\n\n:::{.callout-tip}\nThe keyboard shortcut for this is ALT - (alt + dash/minus).\n:::\n\nAn example is below:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To assign a variable\n\nweight_kg <- 60\n```\n:::\n\n\n\n\nThe variable name goes on the left, followed by the assignment operator, then lastly the value that name is assigned to.\n\nOnce an object has been created it will appear in your Environment pane which helps you keep track of what objects you have in your current workspace - the top right pane.\n\nLiterally typing the name of the variable and running the code returns the value assigned to it.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To display the variable\n\nweight_kg\n```\n:::\n\n\n\n\n### **Concatenation**\n\nIf you wanted to display the weight a bit better, you could use the \"cat()\" function (concatenate).\n\nThis can take data, raw character strings and variables as inputs, grouping them together in a sentence/sequence of outputs.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the cat() function to display your result\n\ncat('my weight is: ', weight_kg)\n```\n:::\n\n\n\n\nYou could continue this with other variables created as well. Let's add your age.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating an age variable and improving the sentence\n\nage_yrs <- 27\n\ncat(\"My weight is\", weight_kg, \"kg, and I am\", age_yrs, \"years old.\")\n```\n:::\n\n\n\n\n### **Mathematical Operations on Variables**\n\nYou can apply addition, subtraction and other operations to your variables. It is the value assigned to the variable that determines the datatype.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Prove that the value is what determines the datatype\n\ntypeof(weight_kg)\n```\n:::\n\n\n\n\nNow let's do some maths.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add 4 to your weight\n\nweight_kg + 4\n```\n:::\n\n\n\n\n### **Creating new variables from existing**\n\nYou can modify the value of a variable in some way and then assign that to a new variable.\n\nFor example, let's convert weight from kg to lbs, where 1kg = 2.2lbs\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a new variable, converting the existing one\n\nweight_lb <- weight_kg * 2.2\n\n# To display the variable\n\nweight_lb\n```\n:::\n\n\n\n\n### **Overwrite and reassign an existing variable**\n\nIf you want to reassign a variable you could use the assignment operator again.\n\nLet's assign your height as 5.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create height variable\n\nheight <- 5\n\n\n# Display height\n\nheight\n```\n:::\n\n\n\n\nUsing the same variable name will overwrite the previously assigned variable, even if you assign it to the same value.\n\nLet's overwrite height to a different value.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Assign and overwrite height\n\nheight <- 7\n\n# Display new height\n\nheight\n```\n:::\n\n\n\n\nYou can also assign variables using the **=** operator, but this is considered bad practice in R as it is used to give function arguments a value.\n\n## Removing Variables\n\nTo remove a variable, use the **remove()** function of R or the alias **rm()**.\n\nFor example:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Removing assigned variables using the remove function\n\nremove(height)\n\n# rm(height) will also work\n```\n:::\n\n\n\n\nBe careful with this, R will not warn you that you are about to permanently remove a variable, it will perform the action you asked it to.\n\nShould you do this by mistake, you need to re-run the line where the variable was created.\n\n## Variable Names\n\nNaming variables is another skill important to programming. Some points to consider:\n\n- R is case sensitive, so whatever you name your variables has be typed **exactly** to display them.\n- Names must start with a letter.\n- Names cannot contain spaces, this is an error in syntax.\n- Names cannot use reserved words such as \"TRUE\" or \"FALSE\" or the name of a function like \"sqrt()\", which already mean something in R.\n- Names should be descriptive, so that when someone else is reading your code they don't have to guess what data is held within a variable.\n\nNotice above where you wrote \"weight_kg\", it is a weight value in kg.\n\n### **Cases**\n\nThere are several conventions for construction variable and function names:\n\n**snake_case**\n\n- Names are entirely lower case.\n- Names separate words with underscores \\*\\*\\_\\*\\*.\n\n**camel case**\n\n- Names start with a capital letter and each word is separated by them, such as **WeightKg**\n\n**period case**\n\n- Names are separated with full stops, such as **weight.kg**.\n\nSnake case is used often and leads to clear, informative variable names without too much complexity.\n\nThere is more detailed information on good variables names in your other course: [Best Practice in Programming](https://learninghub.ons.gov.uk/course/view.php?id=497)\n\n## Exercise\n\n::: panel-tabset\n### **Exercise**\n\n1. Why does this code not work?\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Assign my_variable\n\nmy_variable <- 10\n\n\n# Not working\n\nmy_varIable\n```\n:::\n\n\n\n\n2. Create two variables:\n\n- Time at a value of 30 seconds.\n- Distance at a value of 10 metres.\n\nThen:\n\n- Double the time variable and overwrite it.\n- Add 5 to the distance variable and overwrite it.\n\n3. Using the variables you created above, compute the speed using the formula:\n\n- **speed = distance / time**\n\n4. Use the remove() and rm() functions to remove the time and distance variables.\n\n### **Show Answer**\n\n1. You would have got the error below:\n\n:::{.callout-important}\nError: object 'my_varIable' not found\n:::\n\nVariables are case sensitive, so when you called the variable with a capital \"I\", it tried to recall a name that didn't exist.\n\nError messages of the form \"object '...' not found\" tell you that R cannot find an object, in this case variable, with that name.\n\n2. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create time\n\ntime_secs <- 30\n\n# Create distance\n\ndistance_metres <- 10\n\n# Overwrite time\n\ntime_secs <- 30 * 2\n\n# Overwrite distance\n\ndistance_metres <- distance_metres + 5\n```\n:::\n\n\n\n\n3. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create speed using the formula\n\nspeed <- distance_metres / time_secs\n\n# Display speed\n\nspeed\n```\n:::\n\n\n\n\n4. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Remove time\n\nremove(time_secs)\n\nrm(distance_metres)\n```\n:::\n\n\n\n:::\n\n# Help\n\nThere is a wealth of resource to help you progress in your R journey. Some of these are explored below.\n\n## Cheat Sheets\n\nYou can access these by clicking on **Help** tab in R Studio and then **RStudio Cheat Sheets**. They provide an excellent reference point for many common tasks.\n\n{fig-alt=\"The dplyr cheat sheet for data manipulation.\"}\n\n## R Documentation\n\n::: panel-tabset\n### **Example** {.unnumbered}\n\nWhen you use a function for a first time or come back to it at a later date , it can be helpful to look through its documentation.\n\nYou can use code to access help documentation:\n\n- Precede the function name with a question mark **?**.\n\n- You can use the **help()** function built into R and the name of the function inside it.\n\nLet's see an example with the mean() function, that computes the mean of a collection of values.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To access the R help documentation\n\n?mean \n\n#or \n\nhelp(mean) # Note that you didn't need to use () on the function name\n```\n:::\n\n\n\n\nYou could also use Google to search for the same documentation online, with the accessibility benefits offered by html.\n\nBecoming adept at searching for answers to your queries and using coding elements is a skill that many programmers build up over time. You don't need to memorise every piece of syntax.\n\n### **Help Pages** {.unnumbered}\n\nEach help page is divided into sections.\n\nWhich sections appear can vary from help page to help page, but you can usually expect to find these useful headings:\n\n**Description** - A short summary of what the function does.\n\n**Usage** - An example of how you would type the function. Each argument of the function will appear in the order R expects you to supply it (if you don't use argument names).\n\n**Arguments** - A list of each argument the function takes and what to supply to it as a value. You will spend most of your time here, investigating what options are available.\n\n**Details** - A more in-depth description of the function and how it operates.\n\n**Value** - A description of what the function returns when you run it.\n\n**See Also** - A short list of related R functions.\n\n**Examples** - Example code that uses the function and is guaranteed to work. This helps give you an idea of what the function is capable of.\n:::\n\n## Stack Overflow\n\n[Stack Overflow](https://stackoverflow.com/questions/tagged/r) is a great site to check if anyone has experienced an error before.\n\nYou can search the R-tagged questions on the Stack Overflow site, of which there are over 501,000 as of January 2024.\n\nNote that to make the most use of the forum, you should provide:\n\n- What you were attempting with the code you wrote\n- The code you wrote\n- Steps you took to try and solve it (your interpretation of what happened)\n\nThis allows other users to replicate your problem, so they can explain what to do or why the method causes issues.\n\n## The Data Science Campus Faculty Team\n\nIf you have any issues with this course; or notice any errors, please contact the training team on the email:\n\n> **Data.Science.Campus.Faculty\\@ons.gov.uk**\n\nPlease be aware that due to training commitments there may be a small wait before you respond to your query.\n\n# Summary\n\nYou have covered a lot material in R and yet there is still so much more to cover in terms of functionality, as R has so much to offer.\n\nBy no means are you expected to remember all the above, what is better is that you understand the problems you want to solve and then use the references or material provided to go about solving it.\n\nNext up you will look at data structures in R.\n",
+ "supporting": [
+ "CH1_getting_started_files"
+ ],
"filters": [
"rmarkdown/pagebreak.lua"
],
diff --git a/_freeze/CH2_data_structures/execute-results/html.json b/_freeze/CH2_data_structures/execute-results/html.json
index 29c78b9..7afa54c 100644
--- a/_freeze/CH2_data_structures/execute-results/html.json
+++ b/_freeze/CH2_data_structures/execute-results/html.json
@@ -1,8 +1,11 @@
{
- "hash": "34ef06cf103c325c7e0821bee1747ae4",
+ "hash": "b1ce5c50aa850e7934a0d4fed9380a75",
"result": {
- "markdown": "---\ntitle: \"Chapter 2 - Data Structures in R\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: true\n freeze: auto # re-render only when source changes\n---\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Be familiar with data structures in R.\n* Understand how vectors operate.\n* Be familiar with lists.\n* Be familiar with data frames and tibbles.\n\n\n# Data Structures\n\nWe rarely work with single data values, we often work with a combination or collection of data.\n\nR organises these in certain structures, and stores this data so that we can manipulate and work with it.\n\n# Vectors\n\nIn the previous chapter we looked at variables, where we said we could assign a name to a value. \n\nCrucially, each of these values (and by extension the variable itself) has an associated datatype.\n\nIn the below example, we create a variable with the **character** data type.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To assign a variable\n\nmy_friends <- \"ian\"\n```\n:::\n\n\nSuppose you wanted to store more than one value in \"my_friends\", e.g \"hannah\", \"mike\", \"almas\".\n\nThe following seem like possible solutions to this problem, but unfortunately are not the correct way to store multiple data points.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# This code will throw an error\n\nmy_friends <- \"ian\", \"hannah\", \"mike\", \"almas\"\n\nmy_friends <- (\"ian\", \"hannah\", \"mike\", \"almas\")\n```\n:::\n\n\nYou will get the error below,\n\n>**Error: unexpected ',' in \"my_friends <- \"ian\",\"**\n\nas the comma should not be used in this way.\n\nThis brings us to the **c()** function.\n\n\n## The c() Function\n\nThe \"c()\" function is used for creating a vector in R, which is it's most simple data structure. The c stands for **combine**.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n#To access the R help documentation\n\n?c()\n\n# or\n\nhelp(c)\n```\n:::\n\n\nWe can use this function to store multiple elements (data points) in a single variable, with each element **separated by a comma**.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector\n\nmy_friends <- c(\"ian\", \"hannah\", \"mike\", \"almas\")\n\n# To display the data\n\nmy_friends\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"ian\" \"hannah\" \"mike\" \"almas\" \n```\n:::\n:::\n\n\nLet's check the datatype of our new vector.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check datatype of my_friends\n\ntypeof(my_friends)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"character\"\n```\n:::\n:::\n\n\nWe see that this is a character vector, a.k.a, a vector containing character data. This is because each element contained within the vector are character type. \n\n\n## Vector Definition\n\nA vector is a collection of values that are **all of the same type** (doubles, characters, etc.).\n\nSince R insists all elements in a vector have to be of the same type we then can have types of vectors. These are:\n\n* Logical vector - contains only logical values.\n* Numerical vector - contains only numerical values.\n* Character vector - contains only character values. \n\nThere are more types of vectors, but for the purpose of our learning these are sufficient.\n\nVisually:\n\n{fig-alt=\"Diagram of a vector as a column (collection) of the same red rectangle.\"}\n\n## Creating Vectors \n\nThere are several different ways of creating a vector. You can create a vector by using:\n\n- The combine function **c()** that we saw previously.\n\n- The sequence function **seq()** to create any sequence of numbers.\n\n- The **colon** operator to create a vector of consecutive numbers.\n\n\n### The c() function (combine)\n\nLet's create a numeric vector with c() this time!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector using the combine function\n\nsample_vector <- c(1, 2, 3, 4, 5)\n\n# To display the created vector\n\nsample_vector \n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 1 2 3 4 5\n```\n:::\n:::\n\n\n### The seq() function (sequence)\n\nA sequence of values has:\n\n* A starting point\n* An ending point\n* A \"step\", a.k.a the value we jump by from number to number.\n\n> For example, if we start at 2, end at 10 and step by 2 we will have (2, 4, 6, 8, 10) as our final sequence. \n\nThe seq() function takes the arguments:\n\n* from - the start point\n* to - the end point\n* by - the step value\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector using the sequence function,\n\nsequence_vector <- seq(from = 2, to = 6, by = 2)\n\n# To display the created vector\n\nsequence_vector\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 2 4 6\n```\n:::\n:::\n\n\nEarlier we saw in the console the number [1] next to our output. This represents the position of the element to the right of this number in the vector. \n\nThus, 2 is element 1 of our vector, 4 is element 2 and so on. This is essential information for later.\n\n\n### The Colon Operator\n\nA range of values (i.e., consecutive values) could be generated as a vector using a colon **:** in R.\n\nSince this is consecutive, we can't have broken sequences like seq() allows.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector using a colon\n\ncolon_vector <- 6:10\n\n# To display the created vector\n\ncolon_vector\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 6 7 8 9 10\n```\n:::\n:::\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise** {-}\n\n1. Create two vectors, one with numeric data and one with character data and name them appropriately. For example favourite_movies, lucky_numbers.\n\n2. Use the c() function to create a new vector with your vectors as inputs. This combines the smaller vectors into a larger vector, further showcasing their versatility.\n\n3. Find the type of your new vector. Why do you think this is the case?\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a character vector\n\nfavourite_movies <- c(\"Frozen\", \"The Lion King\", \"Moana\", \"The Dark Knight\") \n\n# To display the data\n\nfavourite_movies\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n:::\n\n```{.r .cell-code}\n# Creating a numeric vector \n \nlucky_numbers <- c(7, 12, 15, 1) \n\n# To display the data\n\nlucky_numbers\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 7 12 15 1\n```\n:::\n:::\n\n\n2. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector of vectors\n\nmovies_and_numbers <- c(favourite_movies, lucky_numbers)\n\nmovies_and_numbers\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n[5] \"7\" \"12\" \"15\" \"1\" \n```\n:::\n:::\n\n\n3. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Checking the type of vector\n\ntypeof(movies_and_numbers)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"character\"\n```\n:::\n:::\n\n\n:::\n\nWe end up with a character vector as opposed to an error for incompatible types (numeric and character). \n\nAs vectors are supposed to be of the same data type, R will convert values so that they are all the same datatype. This is called **coercion**, which works on a complex heirarchy:\n\n* Any datatype can be converted to a character by wrapping it in quotation marks **\" \"**. \n* Any integer can be converted to a double by adding in the decimal place, i.e. 1L --> 1.0\n* Any logical can be converted to an integer or double as they have numeric representation as 1 and 0 (or 1.0, 0.0) in the background.\n\nHowever, a character such as \"hello\" cannot be converted to any other type.\n\nAs such, we have:\n\n>**Logical < Integer < Double < Character** and we see that character is the most all encompassing, with logicals being converted from but not to. \n\n\n## Vectorised Language\n\nVectors aren't just containers for homogeneous data (data of the same type). \n\n> **As R is a vectorised language, this means operations are applied to each element of the vector automatically, without the need to loop through the vector.** \n\nThis is not a common behaviour among programming languages and is a key advantage of R's nature as a vectorised language.\n\nThis also means that every variable we have created so far have also been vectors with one element, and the operators (such as adding 5 to them) have been vectorised operations. \n\nLet's see this in practice!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add sample and colon vector\n\nvector_addition <- sample_vector + colon_vector\n\n\nvector_addition\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 7 9 11 13 15\n```\n:::\n:::\n\n\nWe see that each first element is added, each second element is added and so on, this is an element wise operation (element by element).\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Multiplying vectors (element wise)\n\nvector_multiplication <- sample_vector * colon_vector\n\n\nvector_multiplication\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 6 14 24 36 50\n```\n:::\n:::\n\n\nWe see that each first element is multiplied, each second element is multiplied and so on.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Multiply vector by a value\n\nsample_vector <- sample_vector * 3\n\n\nsample_vector\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 3 6 9 12 15\n```\n:::\n:::\n\n\nWe see that each element is multiplied by 3, like expanding a bracket!\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Try and add \"sample_vector\" and \"sequence_vector\".\n\n2. Can you figure out what has happened?\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Adding two vectors of different lengths\n\nvector_after_addition <- sample_vector + sequence_vector\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning in sample_vector + sequence_vector: longer object length is not a\nmultiple of shorter object length\n```\n:::\n\n```{.r .cell-code}\nvector_after_addition \n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 5 10 15 14 19\n```\n:::\n:::\n\n\n2. Here we have one vector with 3 elements and one with 5 elements. The number of elements in a vector is referred to as the **length** of the vector, so sample vector has length 5.\n\nWhen we try to add vectors of different lengths R gives a warning message as the **longer object length is not a multiple of the shorter object length**.\n\nAs we can see R has recycled the elements in the shorter vector, wrapped them around to reach the length of the longer one, before adding them together.\n\nWhen applying arithmetic to two vectors their lengths should either be equal, or the length of the longer one a multiple of the length of the shorter one, i.e. adding a vector of length 3 to a length 6. \n\n:::\n\n\n## Indexing a Vector \n\nOften, we want to select specific elements or ranges of them to work with going forward. \n\nElements in a vector can be selected using square brackets **[ ]**. \n\n> **We are going to use indexes, which are the position of each element within the vector.** \n\nNote that R indexes start at 1 (not 0 like other languages).\n\n## **Example - Indexing a single element**{-}\n\nTake the favourite_movies vector from the earlier exercise.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To display the vector\n\nfavourite_movies\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n:::\n:::\n\n\nIf we want to select \"The Lion King\" from this vector, which is at position 2, we need to use the number 2 in square brackets. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting the second element in the vector\n\nfavourite_movies[2] \n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"The Lion King\"\n```\n:::\n:::\n\n\nReading this left to right we are:\n\n* From the favourite_movies vector\n* Select [ ]\n* The element at position 2\n\n## **Example - Index Sequentially**{-}\n\nWe can also index multiple elements using the colon operator. Remember that this creates a sequence of consecutive numbers, so allows us to index sequentially.\n\nFor example, if we wanted to select from \"The Lion King\" to \"The Dark Knight\", we select from index 2 to index 4, i.e. **2:4**.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting sequentially\n\nfavourite_movies[2:4] \n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n:::\n:::\n\n\n## **Example - Index out of sequence**{-}\n\nWe can even index **out of sequence**, such as obtaining the elements at indexes 1, 3 and 4. \n\nThis is interesting as most other programming languages require external packages to be able to do this, whereas R does it out of the box.\n\nTo do this, we need to create a vector of values inside the square brackets, using the c() function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting first, third and fourth items\n\nfavourite_movies[c(1,3,4)] \n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Frozen\" \"Moana\" \"The Dark Knight\"\n```\n:::\n:::\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nUse the vector below containing days of the week (Monday - Sunday), for the exercises.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Days of the week vector\n\ndays_of_the_week <- c(\"Monday\",\n \"Tuesday\",\n \"Wednesday\",\n \"Thursday\",\n \"Friday\",\n \"Saturday\",\n \"Sunday\")\n```\n:::\n\n\n\n1. Select Wednesday only.\n\n2. Select the week days.\n\n3. Select Tuesday and Thursday.\n\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting Wednesday\n\ndays_of_the_week[3]\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Wednesday\"\n```\n:::\n:::\n\n\n2. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting the week days\n\ndays_of_the_week[1:5]\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Monday\" \"Tuesday\" \"Wednesday\" \"Thursday\" \"Friday\" \n```\n:::\n:::\n\n\n3. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting Tuesday and Thursday\n\ndays_of_the_week[c(2,4)] \n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Tuesday\" \"Thursday\"\n```\n:::\n:::\n\n\n\n### **Extension Exercise**{-}\n\nRun the following lines of code one at a time and try to determine what is happening.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find out what the code below does\n\ndays_of_the_week[3] <- \"Wensday\"\n\n\n# Find out what the code below does\n\ndays_of_the_week[c(-6,-7)]\n\n# Find out what the code below does\n\ndays_of_the_week[8]\n```\n:::\n\n\n### **Extension Answer**{-}\n\n* The first line of code modifies the element at index position 3 and overwrites it (notice the assignment operator) to something else.\n\n* Using the minus sign when selecting elements reverses the process, i.e. tells R **not** to select that value. So here we are saying select all except index positions 6 and 7.\n\n* Giving an index position outside of the range of vector elements returns **NA (Not Available)** as there is no 8th value in the vector.\n\n:::\n\n\n# Lists \n\nLists are similar data structure to vectors in that they are an ordered collection of elements. \n\nThey differ to vectors because their elements can be of any type, including vectors and lists themselves! \n\nUnlike with vectors, where combining multiple vectors creates one vector, in lists, each element can also be a collection of elements, and no coercion or combination takes place in its creation.\n\n>**So why do you need lists?** \n\nLists enables you to gather a variety of objects with different contents and lengths under one name in an ordered way.\n\n{fig-alt=\"Visual of a list, with each element being a collection of boxes with different colours.\"}\n\nTo create a list we will use the **list()** function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a list\n\nmovies_numbers_friends <- list(favourite_movies, lucky_numbers, my_friends)\n\n# To display the list\n\nmovies_numbers_friends\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[[1]]\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n\n[[2]]\n[1] 7 12 15 1\n\n[[3]]\n[1] \"ian\" \"hannah\" \"mike\" \"almas\" \n```\n:::\n:::\n\n\nEach of the contents will appear on a new line:\n\n* Starting with double-square brackets [[1]], this denotes the first element of the list, since it is a **container of containers** there are 2 levels to select from.\n* Next is the singular square bracket [1] denoting the first element of the numeric vector inside the list. \n\nThis is interesting as indexing from a list is a little more complicated.\n\n\n## Indexing from a list\n\nWe can select at two levels from lists, and this differs by what we actually **return** as a result. \n\nPreviously when we indexed from vectors:\n\n* If we selected one value, we return the value itself as a single data point.\n* If we selected a few values, we return a **vector** of those chosen values, as it is still a collection after all. \n\nWith lists:\n\n* If we select with double square brackets, **[[ ]]**, we return the collection at position 1 in this list, this could be a vector, another list, whatever the value is.\n* If we select with single square brackets, **[ ]**, we return a smaller list just containing the element we asked for. \n\n>**Let's see this in practice**\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Index to return the collection at position 1\n\nmovies_numbers_friends[[1]]\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Index to return a smaller/sub-list with element 1 only\n\nmovies_numbers_friends[1]\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[[1]]\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n:::\n:::\n\n\nWe can even **double-select** to select the collection with double brackets, and then a specific element or collection of elements from there.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Access \"The Dark Knight\" from the list\n\nmovies_numbers_friends[[2]][4]\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 1\n```\n:::\n:::\n\n\nSo we access the second element of the list, which is a character vector, then the 4th element of the vector. \n\n\n# Data Frames\n\nData frames are like the tables we are used to from Excel and other programs, with columns and rows that form a 2 dimensional object.\n\nThey are collections of vectors, where:\n\n* Each vector contains the same data type\n* Subsequent vectors contain different data types (i.e. column 1 could be numeric, column 2 could be character)\n\nAs a whole, DataFrames have the following features:\n\n* Columns are variables.\n* Rows are observations (i.e. an entry for each variable forms an observation/row).\n* They can hold variables of different types.\n\n{fig-alt=\"Visual of a dataframe where each column has a name.\"}\n\nTo create one, we can use the **data.frame()** function on vectors you would like to be your columns, they must be the same length.\n\n>**Using data.frame()**\n\nWithin this function, the argument we assign the vectors to becomes the column name, providing us a handy shortcut to doing these tasks separately. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create a dataframe with favourite movies and numbers\n\nabout_me_df <- data.frame(numbers = lucky_numbers,\n movies = favourite_movies)\n\nabout_me_df\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n numbers movies\n1 7 Frozen\n2 12 The Lion King\n3 15 Moana\n4 1 The Dark Knight\n```\n:::\n:::\n\n\nYou see that this just prints the column names and content in the console. We would need to investigate the data further to obtain other information about it.\n\nWhen it comes to working with data, these are outdated, and the **tidyverse**, which we will be introduced to in the next chapter, provide us an excellent upgrade to the data frame, known as the **tibble**.\n\nWe will see this in the next chapter.\n\n\n# Summary\n\nWe have covered a lot material in R and yet there is still so much more to cover in terms of functionality, as R has so much to offer. \n\nBy no means are you expected to remember all the above, what is better is that you understand the problems you want to solve and can then use the references or material provided (or you find yourself) to go about solving it. \n\nNext up, we will introduces packages, importing and exporting data. \n",
- "supporting": [],
+ "engine": "knitr",
+ "markdown": "---\ntitle: \"Chapter 2 - Data Structures in R\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: true\n freeze: auto # re-render only when source changes\n---\n\n\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Be familiar with data structures in R.\n* Understand how vectors operate.\n* Be familiar with lists.\n* Be familiar with data frames and tibbles.\n\n\n# Data Structures\n\nWe rarely work with single data values, we often work with a combination or collection of data.\n\nR organises these in certain structures, and stores this data so that we can manipulate and work with it.\n\n# Vectors\n\nIn the previous chapter we looked at variables, where we said we could assign a name to a value. \n\nCrucially, each of these values (and by extension the variable itself) has an associated datatype.\n\nIn the below example, we create a variable with the **character** data type.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To assign a variable\n\nmy_friends <- \"ian\"\n```\n:::\n\n\n\n\nSuppose you wanted to store more than one value in \"my_friends\", e.g \"hannah\", \"mike\", \"almas\".\n\nThe following seem like possible solutions to this problem, but unfortunately are not the correct way to store multiple data points.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# This code will throw an error\n\nmy_friends <- \"ian\", \"hannah\", \"mike\", \"almas\"\n\nmy_friends <- (\"ian\", \"hannah\", \"mike\", \"almas\")\n```\n:::\n\n\n\n\nYou will get the error below,\n\n>**Error: unexpected ',' in \"my_friends <- \"ian\",\"**\n\nas the comma should not be used in this way.\n\nThis brings us to the **c()** function.\n\n\n## The c() Function\n\nThe \"c()\" function is used for creating a vector in R, which is it's most simple data structure. The c stands for **combine**.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n#To access the R help documentation\n\n?c()\n\n# or\n\nhelp(c)\n```\n:::\n\n\n\n\nWe can use this function to store multiple elements (data points) in a single variable, with each element **separated by a comma**.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector\n\nmy_friends <- c(\"ian\", \"hannah\", \"mike\", \"almas\")\n\n# To display the data\n\nmy_friends\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"ian\" \"hannah\" \"mike\" \"almas\" \n```\n\n\n:::\n:::\n\n\n\n\nLet's check the datatype of our new vector.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check datatype of my_friends\n\ntypeof(my_friends)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"character\"\n```\n\n\n:::\n:::\n\n\n\n\nWe see that this is a character vector, a.k.a, a vector containing character data. This is because each element contained within the vector are character type. \n\n\n## Vector Definition\n\nA vector is a collection of values that are **all of the same type** (doubles, characters, etc.).\n\nSince R insists all elements in a vector have to be of the same type we then can have types of vectors. These are:\n\n* Logical vector - contains only logical values.\n* Numerical vector - contains only numerical values.\n* Character vector - contains only character values. \n\nThere are more types of vectors, but for the purpose of our learning these are sufficient.\n\nVisually:\n\n{fig-alt=\"Diagram of a vector as a column (collection) of the same red rectangle.\"}\n\n## Creating Vectors \n\nThere are several different ways of creating a vector. You can create a vector by using:\n\n- The combine function **c()** that we saw previously.\n\n- The sequence function **seq()** to create any sequence of numbers.\n\n- The **colon** operator to create a vector of consecutive numbers.\n\n\n### The c() function (combine)\n\nLet's create a numeric vector with c() this time!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector using the combine function\n\nsample_vector <- c(1, 2, 3, 4, 5)\n\n# To display the created vector\n\nsample_vector \n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 1 2 3 4 5\n```\n\n\n:::\n:::\n\n\n\n\n### The seq() function (sequence)\n\nA sequence of values has:\n\n* A starting point\n* An ending point\n* A \"step\", a.k.a the value we jump by from number to number.\n\n> For example, if we start at 2, end at 10 and step by 2 we will have (2, 4, 6, 8, 10) as our final sequence. \n\nThe seq() function takes the arguments:\n\n* from - the start point\n* to - the end point\n* by - the step value\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector using the sequence function,\n\nsequence_vector <- seq(from = 2, to = 6, by = 2)\n\n# To display the created vector\n\nsequence_vector\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 2 4 6\n```\n\n\n:::\n:::\n\n\n\n\nEarlier we saw in the console the number [1] next to our output. This represents the position of the element to the right of this number in the vector. \n\nThus, 2 is element 1 of our vector, 4 is element 2 and so on. This is essential information for later.\n\n\n### The Colon Operator\n\nA range of values (i.e., consecutive values) could be generated as a vector using a colon **:** in R.\n\nSince this is consecutive, we can't have broken sequences like seq() allows.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector using a colon\n\ncolon_vector <- 6:10\n\n# To display the created vector\n\ncolon_vector\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 6 7 8 9 10\n```\n\n\n:::\n:::\n\n\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise** {-}\n\n1. Create two vectors, one with numeric data and one with character data and name them appropriately. For example favourite_movies, lucky_numbers.\n\n2. Use the c() function to create a new vector with your vectors as inputs. This combines the smaller vectors into a larger vector, further showcasing their versatility.\n\n3. Find the type of your new vector. Why do you think this is the case?\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a character vector\n\nfavourite_movies <- c(\"Frozen\", \"The Lion King\", \"Moana\", \"The Dark Knight\") \n\n# To display the data\n\nfavourite_movies\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n\n\n:::\n\n```{.r .cell-code}\n# Creating a numeric vector \n \nlucky_numbers <- c(7, 12, 15, 1) \n\n# To display the data\n\nlucky_numbers\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 7 12 15 1\n```\n\n\n:::\n:::\n\n\n\n\n2. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector of vectors\n\nmovies_and_numbers <- c(favourite_movies, lucky_numbers)\n\nmovies_and_numbers\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n[5] \"7\" \"12\" \"15\" \"1\" \n```\n\n\n:::\n:::\n\n\n\n\n3. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Checking the type of vector\n\ntypeof(movies_and_numbers)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"character\"\n```\n\n\n:::\n:::\n\n\n\n\n:::\n\nWe end up with a character vector as opposed to an error for incompatible types (numeric and character). \n\nAs vectors are supposed to be of the same data type, R will convert values so that they are all the same datatype. This is called **coercion**, which works on a complex heirarchy:\n\n* Any datatype can be converted to a character by wrapping it in quotation marks **\" \"**. \n* Any integer can be converted to a double by adding in the decimal place, i.e. 1L --> 1.0\n* Any logical can be converted to an integer or double as they have numeric representation as 1 and 0 (or 1.0, 0.0) in the background.\n\nHowever, a character such as \"hello\" cannot be converted to any other type.\n\nAs such, we have:\n\n>**Logical < Integer < Double < Character** and we see that character is the most all encompassing, with logicals being converted from but not to. \n\n\n## Vectorised Language\n\nVectors aren't just containers for homogeneous data (data of the same type). \n\n> **As R is a vectorised language, this means operations are applied to each element of the vector automatically, without the need to loop through the vector.** \n\nThis is not a common behaviour among programming languages and is a key advantage of R's nature as a vectorised language.\n\nThis also means that every variable we have created so far have also been vectors with one element, and the operators (such as adding 5 to them) have been vectorised operations. \n\nLet's see this in practice!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add sample and colon vector\n\nvector_addition <- sample_vector + colon_vector\n\n\nvector_addition\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 7 9 11 13 15\n```\n\n\n:::\n:::\n\n\n\n\nWe see that each first element is added, each second element is added and so on, this is an element wise operation (element by element).\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Multiplying vectors (element wise)\n\nvector_multiplication <- sample_vector * colon_vector\n\n\nvector_multiplication\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 6 14 24 36 50\n```\n\n\n:::\n:::\n\n\n\n\nWe see that each first element is multiplied, each second element is multiplied and so on.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Multiply vector by a value\n\nsample_vector <- sample_vector * 3\n\n\nsample_vector\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 3 6 9 12 15\n```\n\n\n:::\n:::\n\n\n\n\nWe see that each element is multiplied by 3, like expanding a bracket!\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Try and add \"sample_vector\" and \"sequence_vector\".\n\n2. Can you figure out what has happened?\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Adding two vectors of different lengths\n\nvector_after_addition <- sample_vector + sequence_vector\n```\n\n::: {.cell-output .cell-output-stderr}\n\n```\nWarning in sample_vector + sequence_vector: longer object length is not a\nmultiple of shorter object length\n```\n\n\n:::\n\n```{.r .cell-code}\nvector_after_addition \n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 5 10 15 14 19\n```\n\n\n:::\n:::\n\n\n\n\n2. Here we have one vector with 3 elements and one with 5 elements. The number of elements in a vector is referred to as the **length** of the vector, so sample vector has length 5.\n\nWhen we try to add vectors of different lengths R gives a warning message as the **longer object length is not a multiple of the shorter object length**.\n\nAs we can see R has recycled the elements in the shorter vector, wrapped them around to reach the length of the longer one, before adding them together.\n\nWhen applying arithmetic to two vectors their lengths should either be equal, or the length of the longer one a multiple of the length of the shorter one, i.e. adding a vector of length 3 to a length 6. \n\n:::\n\n\n## Indexing a Vector \n\nOften, we want to select specific elements or ranges of them to work with going forward. \n\nElements in a vector can be selected using square brackets **[ ]**. \n\n> **We are going to use indexes, which are the position of each element within the vector.** \n\nNote that R indexes start at 1 (not 0 like other languages).\n\n## **Example - Indexing a single element**{-}\n\nTake the favourite_movies vector from the earlier exercise.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To display the vector\n\nfavourite_movies\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n\n\n:::\n:::\n\n\n\n\nIf we want to select \"The Lion King\" from this vector, which is at position 2, we need to use the number 2 in square brackets. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting the second element in the vector\n\nfavourite_movies[2] \n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"The Lion King\"\n```\n\n\n:::\n:::\n\n\n\n\nReading this left to right we are:\n\n* From the favourite_movies vector\n* Select [ ]\n* The element at position 2\n\n## **Example - Index Sequentially**{-}\n\nWe can also index multiple elements using the colon operator. Remember that this creates a sequence of consecutive numbers, so allows us to index sequentially.\n\nFor example, if we wanted to select from \"The Lion King\" to \"The Dark Knight\", we select from index 2 to index 4, i.e. **2:4**.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting sequentially\n\nfavourite_movies[2:4] \n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n\n\n:::\n:::\n\n\n\n\n## **Example - Index out of sequence**{-}\n\nWe can even index **out of sequence**, such as obtaining the elements at indexes 1, 3 and 4. \n\nThis is interesting as most other programming languages require external packages to be able to do this, whereas R does it out of the box.\n\nTo do this, we need to create a vector of values inside the square brackets, using the c() function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting first, third and fourth items\n\nfavourite_movies[c(1,3,4)] \n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Frozen\" \"Moana\" \"The Dark Knight\"\n```\n\n\n:::\n:::\n\n\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nUse the vector below containing days of the week (Monday - Sunday), for the exercises.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Days of the week vector\n\ndays_of_the_week <- c(\"Monday\",\n \"Tuesday\",\n \"Wednesday\",\n \"Thursday\",\n \"Friday\",\n \"Saturday\",\n \"Sunday\")\n```\n:::\n\n\n\n\n\n1. Select Wednesday only.\n\n2. Select the week days.\n\n3. Select Tuesday and Thursday.\n\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting Wednesday\n\ndays_of_the_week[3]\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Wednesday\"\n```\n\n\n:::\n:::\n\n\n\n\n2. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting the week days\n\ndays_of_the_week[1:5]\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Monday\" \"Tuesday\" \"Wednesday\" \"Thursday\" \"Friday\" \n```\n\n\n:::\n:::\n\n\n\n\n3. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting Tuesday and Thursday\n\ndays_of_the_week[c(2,4)] \n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Tuesday\" \"Thursday\"\n```\n\n\n:::\n:::\n\n\n\n\n\n### **Extension Exercise**{-}\n\nRun the following lines of code one at a time and try to determine what is happening.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find out what the code below does\n\ndays_of_the_week[3] <- \"Wensday\"\n\n\n# Find out what the code below does\n\ndays_of_the_week[c(-6,-7)]\n\n# Find out what the code below does\n\ndays_of_the_week[8]\n```\n:::\n\n\n\n\n### **Extension Answer**{-}\n\n* The first line of code modifies the element at index position 3 and overwrites it (notice the assignment operator) to something else.\n\n* Using the minus sign when selecting elements reverses the process, i.e. tells R **not** to select that value. So here we are saying select all except index positions 6 and 7.\n\n* Giving an index position outside of the range of vector elements returns **NA (Not Available)** as there is no 8th value in the vector.\n\n:::\n\n\n# Lists \n\nLists are similar data structure to vectors in that they are an ordered collection of elements. \n\nThey differ to vectors because their elements can be of any type, including vectors and lists themselves! \n\nUnlike with vectors, where combining multiple vectors creates one vector, in lists, each element can also be a collection of elements, and no coercion or combination takes place in its creation.\n\n>**So why do you need lists?** \n\nLists enables you to gather a variety of objects with different contents and lengths under one name in an ordered way.\n\n{fig-alt=\"Visual of a list, with each element being a collection of boxes with different colours.\"}\n\nTo create a list we will use the **list()** function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a list\n\nmovies_numbers_friends <- list(favourite_movies, lucky_numbers, my_friends)\n\n# To display the list\n\nmovies_numbers_friends\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[[1]]\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n\n[[2]]\n[1] 7 12 15 1\n\n[[3]]\n[1] \"ian\" \"hannah\" \"mike\" \"almas\" \n```\n\n\n:::\n:::\n\n\n\n\nEach of the contents will appear on a new line:\n\n* Starting with double-square brackets [[1]], this denotes the first element of the list, since it is a **container of containers** there are 2 levels to select from.\n* Next is the singular square bracket [1] denoting the first element of the numeric vector inside the list. \n\nThis is interesting as indexing from a list is a little more complicated.\n\n\n## Indexing from a list\n\nWe can select at two levels from lists, and this differs by what we actually **return** as a result. \n\nPreviously when we indexed from vectors:\n\n* If we selected one value, we return the value itself as a single data point.\n* If we selected a few values, we return a **vector** of those chosen values, as it is still a collection after all. \n\nWith lists:\n\n* If we select with double square brackets, **[[ ]]**, we return the collection at position 1 in this list, this could be a vector, another list, whatever the value is.\n* If we select with single square brackets, **[ ]**, we return a smaller list just containing the element we asked for. \n\n>**Let's see this in practice**\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Index to return the collection at position 1\n\nmovies_numbers_friends[[1]]\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n\n\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Index to return a smaller/sub-list with element 1 only\n\nmovies_numbers_friends[1]\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[[1]]\n[1] \"Frozen\" \"The Lion King\" \"Moana\" \"The Dark Knight\"\n```\n\n\n:::\n:::\n\n\n\n\nWe can even **double-select** to select the collection with double brackets, and then a specific element or collection of elements from there.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Access \"The Dark Knight\" from the list\n\nmovies_numbers_friends[[2]][4]\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 1\n```\n\n\n:::\n:::\n\n\n\n\nSo we access the second element of the list, which is a character vector, then the 4th element of the vector. \n\n\n# Data Frames\n\nData frames are like the tables we are used to from Excel and other programs, with columns and rows that form a 2 dimensional object.\n\nThey are collections of vectors, where:\n\n* Each vector contains the same data type\n* Subsequent vectors contain different data types (i.e. column 1 could be numeric, column 2 could be character)\n\nAs a whole, DataFrames have the following features:\n\n* Columns are variables.\n* Rows are observations (i.e. an entry for each variable forms an observation/row).\n* They can hold variables of different types.\n\n{fig-alt=\"Visual of a dataframe where each column has a name.\"}\n\nTo create one, we can use the **data.frame()** function on vectors you would like to be your columns, they must be the same length.\n\n>**Using data.frame()**\n\nWithin this function, the argument we assign the vectors to becomes the column name, providing us a handy shortcut to doing these tasks separately. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create a dataframe with favourite movies and numbers\n\nabout_me_df <- data.frame(numbers = lucky_numbers,\n movies = favourite_movies)\n\nabout_me_df\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n numbers movies\n1 7 Frozen\n2 12 The Lion King\n3 15 Moana\n4 1 The Dark Knight\n```\n\n\n:::\n:::\n\n\n\n\nYou see that this just prints the column names and content in the console. We would need to investigate the data further to obtain other information about it.\n\nWhen it comes to working with data, these are outdated, and the **tidyverse**, which we will be introduced to in the next chapter, provide us an excellent upgrade to the data frame, known as the **tibble**.\n\nWe will see this in the next chapter.\n\n\n# Summary\n\nWe have covered a lot material in R and yet there is still so much more to cover in terms of functionality, as R has so much to offer. \n\nBy no means are you expected to remember all the above, what is better is that you understand the problems you want to solve and can then use the references or material provided (or you find yourself) to go about solving it. \n\nNext up, we will introduces packages, importing and exporting data. \n",
+ "supporting": [
+ "CH2_data_structures_files"
+ ],
"filters": [
"rmarkdown/pagebreak.lua"
],
diff --git a/_freeze/CH3_import_export/execute-results/html.json b/_freeze/CH3_import_export/execute-results/html.json
index a2ffba1..10ac47c 100644
--- a/_freeze/CH3_import_export/execute-results/html.json
+++ b/_freeze/CH3_import_export/execute-results/html.json
@@ -1,8 +1,11 @@
{
- "hash": "d7a341db396328f8e41ec2dc7d16cda6",
+ "hash": "4d1ddee9c805f42ab0bb86e0b6d227a6",
"result": {
- "markdown": "---\ntitle: \"Chapter 3 - Importing and Exporting Data\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Understand the importance of argument order in functions.\n* Have an understanding of what packages are.\n* Be able to load and install a package.\n* Be able to check package versions and R version.\n* Be able to import data from multiple formats.\n* Be able to inspect loaded data.\n* Be able to export data.\n* Be able to explore data.\n\n\n# Returning to Functions\n\nSo far we have seen many functions, such as:\n\n* sqrt()\n* round()\n* c()\n* list()\n\nYou should make it a habit to explore the help files when you are using a function for the first time so you know:\n\n* What required arguments there are.\n* What optional arguments there are.\n* What default arguments there are (some arguments have a value by default so we can exclude them without error). \n\nRecall that they follow the form:\n\n> **functionName(argument1 = value1, argument2 = value2, and so on)**\n\n\n## How functions work\n\nThe seq() function from chapter 2 is the perfect example to reinforce how functions work, as well as common pitfalls.\n\nLet's take a closer look at the help file for seq().\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Help doc for seq()\n\n?seq\n\n# or\n\nhelp(seq)\n```\n:::\n\n\n\n{fig-alt=\"Seq() function help file.\"}\n\n\n### Function help files\n\nEvery help file will have a series of sections describing what the function does. It is worth focusing on the description, the usage and especially the arguments first. \n\n**Description**\n\nFor example, in the help file for seq() under **Description**, it tells us it is a function to \"Generate regular sequences\". \n\n**Usage**\n\nWe can see that seq() takes the required arguments:\n\n* from (which is 1 by default)\n* to (which is 1 by default)\n* by (which is calculated by default)\n\nand the optional arguments:\n\n* length.out \n* along.with\n\n\n**Arguments**\n\nHere, we can find out what these arguments are:\n\n - from, to: the starting and maximal end values of the sequence.\n - by number: increment of the sequence.\n\n\n### Execution of function arguments\n\nWe used this function when creating vectors, here's a reminder.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a sequence of numbers\n\nseq(from = 2, to = 6, by = 2)\n```\n:::\n\n\nLet's consider what happens instead when we **don't** specify the arguments, just their values.\n\n### **Example**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a sequence of numbers - not specifying arguments\n\nseq(1,10)\n```\n:::\n\n\nThis has generated a sequence of numbers from 1 to 10. In this case we did not supply a value for by, so it took the default value, which in this case is 1.\n\nWhat if we flip 10 and 1 instead?\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a sequence of numbers\n\nseq(10,1)\n```\n:::\n\n\nSo it is clear that where we place the value is important, because arguments are resolved **by position**, in the order specified in the help documnentation.\n\nSo above:\n\n* In the first example, it is assumed that we want a sequence from 1 that goes to 10. \n* Then if we swap the numbers it is assumed we want to sequence from 10 that goes to 1. \n\nHowever, if we name the arguments **explicitly** using argument = value, the order we specify them does not matter. \n\nLet's see this in action:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Reversing arguments but using argument name\n\nseq(to = 10, from = 1)\n```\n:::\n\n\nYou can sometimes run into errors with more complicated functions by taking the arguments for granted. \n\nOften there are many optional arguments that are resolved (position wise) before the required ones.\n\n>**We would encourage you to specify the arguments and parameters as it makes your code easier to understand.**\n\n\n# Packages\n\nOur default R installation, often referred to as **base R** gives us a lot of functionality out of the box.\n\nIf we want to implore the newest methodologies, adopted by the wider R community, then we need to install packages to achieve this.\n\n>**Packages are a collection of functions, compiled code and sometimes data sets which are stored in a library of code within R.**\n\nIn order to use a package, we first need to install it:\n\n* R installs packages from [CRAN](https://cran.r-project.org/) **The Comprehensive R Archive Network.** that contains over 20,000 packages.\n\n* You can install packages from outside of CRAN (such as from [GitHub](https://github.com/)) with specific functions. Please be aware of the source and quality in these cases.\n\nYour department may have a slightly different way of installing packages, so clearing this up is a good port of call.\n\n\n## Installing Packages\n\nTo install a package, we use the code below for **each** new package. \n\n>**install.packages(\"package_name\", dependencies = TRUE)** where dependencies allows the install to also take into account other packages your chosen one needs to function correctly. \n\nDependent on your Operating System, another parameter is also recommended:\n\n* For windows, use **type = win.binary**.\n* For mac, use **type = mac.binary** (this may differ for Apple Silicon).\n\n>**Important**: You will only need to install packages once, you should either do this in the console, or comment out the line in your script where this is done. \n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Install the packages below using the **R console** one at a time.\n\n* tidyverse\n\n* janitor\n\nNote that tidyverse is a collection of R packages that follow the same programming paradigm, so will take quite some time to install. \n\n### **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Installing packages\n\ninstall.packages(\"tidyverse\", dependencies = TRUE, type = \"win.binary\")\n\ninstall.packages(\"janitor\", dependencies = TRUE, type = \"win.binary\")\n```\n:::\n\n\n:::\n\nSuccessful installation should finish with messages as below, sometimes interspersed with some warnings. \n\n```\n## package 'janitor' successfully unpacked and MD5 sums checked\n## \n## The downloaded binary packages are in\n## C:\\Users\\bandai1\\AppData\\Local\\Temp\\Rtmpm0ZY69\\downloaded_packages\n```\n\n## Loading Packages\n\nThink of packages as owning a book; you purchase (install) the book once, and after that when you need to reference it you can pick it up off your bookshelf. \n\nIn R we call this **loading**, and you should always load packages at the very top of your script.\n\nTo load a package, use the code:\n\n>**library(package_name)** where the package name is not a string this time. \n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nLoad the packages you installed in the prior exercise:\n\n* tidyverse\n\n* janitor\n\n### **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# loading packages\n\nlibrary(tidyverse)\n\nlibrary(janitor)\n```\n:::\n\n\n:::\n\nThere is almost always some output we get when loading packages. Some options are:\n\n* **package \"X\" was built under R Version \"Y\"** - this states that your R version may be lower than the one the package was written using. This is not always an issue, but you should endeavour to remain updated with your software. \n\n* **The following objects are masked from \"package::package_name\":** - this arises when functions from your newly loaded package have identical names to either a function in base R, or from another outside package.\n * As such, the package you loaded takes precedence, and it's function under that name will be used. \n * You can get around this by using the syntax **package_name::function_name** as R will attempt to autofill the functions from that package, and there is no way to misconstrue what package the function comes from. \n\n\n## Checking Versions\n::: {.panel-tabset}\n\nReturning to the versions issue, we may have an older version of R than the one the package was built for.\n\n### **Check R Version** {-}\n\nWe can check R version by running this command.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To check the version of R\n\nversion\n```\n:::\n\n\nYou can see that we are running 4.1.3\n\nIf your version is a little older, this is fine, but we **thoroughly** recommend versions 4.1 and above and discourage versions beginning with a 3.\n\nOlder versions, such as 3.6.3 (which is popular) are no longer supported by the creators, and will conflict with almost all training you will engage with whilst learning. \n\n\n### **Check Package Version**{-}\n\nUse the packageVersion() function with the package supplied as a string.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Checking the package version\n\npackageVersion(\"tidyverse\")\n```\n:::\n\n\nYou see that we have the up to date 2.0.0, this is backwards compatible with some older versions, but beware of argument name changes to functions.\n\nIf you are working collaboratively you should always check that you are all using the same versions of packages. \n\n\n### **Masked Objects**{-}\n\nOne of the masks at play with tidyverse is the **filter()** functions:\n\n* Base R has a filter() function to apply on time series.\n* Whereas dplyr (a tidyverse package for data manipulation) has a filter() function to select rows based on columns.\n\nThese both take very different parameters, so it is important to know what we have masked. After loading the tidyverse, it will assume we want to use the dplyr version of filter going forward. \n\nTo use the alternative we would need to type \n\n>**stats::filter()**\n\n:::\n\n\n# Tidyverse\n\nHere we will introduce the tidyverse, a collection of R packages that changed the way many work with R forever. \n\nThe packages in tidyverse share a common philosophy for data manipulation and exploration so they work well together. \n\nThis philosophy is that of Tidy Data, described first in the [seminal paper](https://vita.had.co.nz/papers/tidy-data.pdf) by Hadley Wickham, the tidyverse's creator. \n\n## Advantages of the Tidyverse\n\nThe tidyverse is:\n\n* Well documented. Each sub-library has its own website containing a 'cheat-sheet' and vignettes. We thoroughly recommend bookmarking these.\n\n* Well established in the R data science community, meaning common issues and queries are already answered on platforms such as [Stack Overflow](https://stackoverflow.com/questions/tagged/r).\n\n* Designed such that all sub packages follow a core 'philosophy' which encourages best practice. \n\n* Open-source software and free to use. As are the books written by the tidyverse creator Hadley Wickham. The highest recommendation we can make is [R for Data Science](https://r4ds.hadley.nz/). \n\n\n## Disadvantages of the Tidyverse\n\n* Like R, tidyverse can have a steep learning curve, and its reliance on functional programming can confuse beginners. \n\n* It is incredibly flexible, which makes it hard to determine which solutions to problems are the best.\n\n* Quite verbose (wordy), which can lead to long scripts. \n\n\n## Tidyverse Breakdown\n\nBelow is a list of the core packages in tidyverse to provide some awareness into what they make possible:\n\n* [readr](http://readr.tidyverse.org) - Data import\n* [tibble](https://tibble.tidyverse.org/) - Tibbles, a modern re-imagining of data frames\n* [tidyr](https://tidyr.tidyverse.org/) - Data Tidying\n* [dplyr](https://dplyr.tidyverse.org/) - General data anipulation\n* [stringr](https://stringr.tidyverse.org/) - String anipulation\n* [forcats](https://forcats.tidyverse.org/) - Factor variables \n* [ggplot2](https://ggplot2.tidyverse.org/) - Data Visualisation\n* [purrr](https://purrr.tidyverse.org/) - Functional Programming\n* [lubridate](https://lubridate.tidyverse.org/) - For dealing with dates and times - included in tidyverse 2.0.0 onwards. \n\n\n{fig-alt=\"Tidyverse workflow of import, tidy, transform/model/visualise and communicate.\"}\n\nThe first of the core packages we will delve into is **readr**, which deals with reading in data, and by extension **tibbles**, the excellent update to dataframes that the tidyverse provides. \n\nHowever, we need an understanding of the working directory beforehand.\n\n\n# Working Directory\n\nR has a powerful notion of the working directory. This is where R looks for files that you ask it to load, and where it will put any files that you ask it to save. \n\nWe often refer to this as the \"starting point\" when R looks for a file you specified the path for.\n\nThankfully, we are using an **R project**, which makes filepaths and directories reproducible, by ensuring everyone who opens the project has this set by default.\n\n>**If you are not using a project (we recommend you do) you will need to set your own working directory with the [setwd() function](https://www.geeksforgeeks.org/how-to-use-setwd-and-getwd-in-r/) that requires a full path to the directory to change it manually.**\n\n\n## Checking Working Directory\n\nThe getwd() function (get working directory) is ideal.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Getting the working directory\n\ngetwd()\n```\n:::\n\n\nIf you are inside the project created within these materials, you should have the same final step in the \"path\", that of the \"Course_content\" folder.\n\n> **In Windows file paths are specified using back slashes, but in R a backslash already has a meaning, so we use a forward slash or two back slashes instead.**\n\n\n# Reading in Data\n\nThere are a variety of ways of reading data into R, in this chapter we will look at reading data using the packages:\n\n* readr - loaded with tidyverse\n* readxl - installed with tidyverse, but loaded separately. \n\n\n## Readr\n\nThe package provides a fast and friendly way to read data from:\n\n* Comma Separated Value (csv) files\n* Tab Separated Value (tsv) files\n\nconverting them to **tibbles**, which are the required data structure in the tidyverse. \n\nLet's formally introduce them now.\n\n### Tibbles\n\nTibbles are data frames, but they tweak some older behaviours to make life a little easier, R is over 20 years old after all:\n\n* Tibbles complain more when variables do not exist - leads to easier error checking.\n* Tibbles don't change variable names.\n* Tibbles don't tweak variable types from the source data. \n\n**The key benefits of tibbles are:**\n\n* In addition to its name, each column reports its type.\n\n* The dimensions of the tibble are shown at the top.\n\n* Tibbles have a refined print method that shows only the first 10 rows, and all the columns that fit on screen. This makes it much easier to work with large data.\n\n\n### How readr works\n\nThis package reads in datasets we supply by using a **family of functions**, ones that have the same prefix.\n\n> **read_filetype()**\n\nThe most common, and one we will use throughout the course is **read_csv()**.\n\n### Considerations to make\n\n> Before importing your data you need to know:\n\n* Where it is stored?\n\n* What kind of file is it?\n\n* Are there missing values in the data?\n * Missing values in R are denoted by **NA**.\n\nThe code will take the following form:\n\n>**data_name <- read_csv(file_path)**\n\nand readr will:\n\n* Assume the first row of your data is the headings of the columns.\n\n* Attempt to guess the datatype of columns, given their content. If a numeric column contains 99 doubles and one character, then the same coercion that happened with vectors will happen again (since columns are vectors) and we get a character column.\n * One of the first data checks you should do is that the types of the columns match what you expect. \n\n\n### Example - Our first filepaths\n\nLet's load in the titanic dataset in the \"Data\" folder. \n\nWe need to figure out where this is and how to get there from our current working directory, so that we can tell R. \n\n::: {.panel-tabset}\n\n### **Absolute Filepaths**{-}\n\nAn **absolute** or full filepath is constructed as:\n\n>\"starting_drive/step_1/step_2/step_3/..../destination\"\n\nthis details the full path taken to reach the file.\n\nTo reach \"titanic.csv\" the absolute filepath for us is \n\n>\"C:/Users/marshj1/af_introduction_to_r/data/titanic.csv\"\n\nNote that your usernames and drives will differ to ours. \n\n### **Relative Filepaths**{-}\n\nA relative filepath is the path to reach the file **relative** to the current working directory. \n\nThus we are already part of the way there, and just need to tell R where to go from here:\n\n>\"working_directory/step_1/step_2/.../destination\"\n\nHowever, in our case, our working directory is one level deeper than we'd like to be, in the **course_content** folder.\n\n>To reach the dataset, we must exit this folder to get back to the root, then enter the data folder, and select **titanic.csv**\n\nTo do so, we need to know how to go back one folder level, or exit the current directory, this is written as **../** where the two full stops denote going back. \n\nAs such, the relative filepath we need to reach the dataset is\n\n>\"Data/titanic.csv\"\n\nVisually, to understand the tree-like folder structure, we have something like the following going on:\n\n{fig-alt=\"Top level is introduction to R, folders are at level 2, items in the folders are level 3.\"}\n\n### **Loading in the data**{-}\n\nLet's read in titanic using a relative filepath. \n\nWe simply need to go into the **data** folder, then select the **titanic.csv** file to load in.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Read in titanic with read_csv()\n\ntitanic_data <- read_csv(\"Data/titanic.csv\")\n```\n:::\n\n\nYou will get some information on:\n\n* rows and columns\n* Counts of each column datatype\n\n### **Inspect Data**{-}\n\nLet's call the name of the variable we have created to see the output of our first tibble.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Display the titanic data\n\ntitanic_data\n```\n:::\n\n\nNotice the refined print we get from this, that provides so much more information than the data frame output did in chapter 2. \n\nIt may take more time to read and understand, but prevents you from having to use many additional functions to find out things such as dimensions (rows and cols).\n\nAnother example of inspection is with View(), which opens a separate tab in the code editor pane with the dataset in spreadsheet form.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Viewing the data - Note the capital V\n\nView(titanic_data)\n```\n:::\n\n\n:::\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Having read in the titanic data above, have a look at the column Age of passenger.\n\n2. What type of data would you expect this column to be?\n\n3. Use the \"str()\" function to see the data type R has set it to be.\n\n\n### **Show Answer**{-}\n\n1. Have a look at the column Age of passenger.\n\n2. The column looks numeric.\n\n3. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the str() function\n\nstr(titanic_data)\n```\n:::\n\n\nWe can see that R has classed the column as character because of the **.** and asterisk within it.\n\nNotice how much of the information this provides is also represented in the tibble output, very impressive!\n\n:::\n\n### Dealing with Missing Values at Read-in\n\nWhilst we cannot observe all missing values at this stage, examples that cause columns to be cast to unexpected data types are often spotted quickly.\n\nWe can easily correct this by adding the **na** paramter to the read_csv() function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Specifying missing values as a vector to read_csv()\n\ntitanic_data <- read_csv(\"Data/titanic.csv\", \n na = c(\"*\", \".\", \"\", \"NULL\"))\n```\n:::\n\n\nThis is read as:\n\n> **Where there is the a full stop, asterisk, NULL (entirely empty) value or a blank space, class is it as a missing value.**\n\nWe can now see that the . and * in the age column have been replaced with NA's and the age column is now numeric.\n\nYou may see all sorts of missing values in practice, deriving from data entry:\n\n* negative numbers where it makes no sense\n* abnormally large values such as 999999\n\n>**There are many other useful arguments you can use when reading in data, check the help documentation for read_csv() for details.**\n\n\n## Readxl\n\nWe use readxl to read excel data into R, it supports both .xls and .xlsx formats.\n\nEven though it is installed alongside the tidyverse, it must be loaded separately.\n\nThe code for read in is very similar to the read_csv() example, just using the read_excel() function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Load in readxl\n\nlibrary(readxl)\n```\n:::\n\n\nExcel workbooks are more complex than flat files as they are **workbooks**, featuring multiple sheets. \n\nWe can output their names using the excel_sheets() function, which will become important shortly.\n\n\n### Example \n\nLet's read in the police dataset.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Reading in excel data using the readxl package\n\npolice_data <- read_excel(\"Data/police_data.xlsx\")\n\nView(police_data)\n```\n:::\n\n\nWe see that this is the **first sheet** in our workbook which is just the \"Notes\". This is the default behaviour of read_excel() unless we specify otherwise.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Observe sheet names in police data\n\nexcel_sheets(\"Data/police_data.xlsx\")\n```\n:::\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nUse an additional argument in \"read_excel()\" to read in the second sheet of the police dataset.\n\nYou will need to look at the help documentation for read_excel() to help you with this. \n\n\n### **Show Answer**{-}\n\nYou can use the name of the sheet or the number/index. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the sheet parameter in 2 ways\n\npolice_data <- read_excel(\"Data/police_data.xlsx\",\n sheet = 2)\n\n# Alternatively\n\npolice_data <- read_excel(\"Data/police_data.xlsx\",\n sheet = \"Table P1\")\n\npolice_data\n```\n:::\n\n\nThis is better but still not ideal:\n\n* The top columns are mostly blank with no real significant data.\n\n * We can get around this by specifying the **range** parameter in read_excel, to denote the range of cells to capture.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the range parameter to avoid empty rows\n\n\npolice_data <- read_excel(\"Data/police_data.xlsx\",\n sheet = 2,\n range = \"A5:AA48\")\n\npolice_data\n```\n:::\n\n\n:::\n\n# Exporting the Data\n\nWhen you read a file into R, the data is loaded into memory. This means that any changes you make won't be reflected in the original file you loaded. \n\nIf you want to preserve the changes you make to the dataset you have to export the data object to its own file. \n\nWe have a family of functions for this, just like reading in, the **write_filetype()** functions.\n\n## Example\n\nAs an example, let's write out the police data which now has the correct sheet and range as a csv (flat) file instead.\n\nWe must supply two arguments to **write_csv()**:\n\n* dataset itself\n* file, which must be the filepath of **where to save your file**. \n\nThe path is constructed similarly as before\n\n>**\"../folder/my_file.csv\" as we must back out of the course_content folder first**\n\nIf you specify a folder that doesn't exist, the function will create it for you. In this case, let's create a separate folder called \"outputs\". \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Exporting data using write_csv()\n\nwrite_csv(police_data, file = \"../outputs/police.csv\")\n```\n:::\n\n\nThis stores our police_data in the outputs folder under the name \"police.csv\". \n\n\n# Inspecting the Data\n\nAfter importing our data, the first thing we may want to do is have a quick look at it:\n\n* We can check it looks similar to the source file.\n* We can check if there are the same number of rows and columns we expect.\n* We can check if the columns loaded in as the datatype we expect.\n* We can check if there are obvious missing values at the tail ends. \n\nWe can do these checks in a variety of ways, be that from base R, or in the tidyverse.\n\n## Inspecting Data Functions\n::: {.panel-tabset}\n\n### **Tail Ends**{-}\n\nWe can output the first or last 6 rows of the dataset by using the **head()** and **tail()** functions.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Head of titanic\n\nhead(titanic_data)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Tail of titanic\n\ntail(titanic_data)\n```\n:::\n\n\n### **Dimensions**{-}\n\nWe can output the number of rows and columns or each separately with the following functions.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of rows in titanic\n\nnrow(titanic_data)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of columns in titanic\n\nncol(titanic_data)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Dimensions - Vector of nrow and ncol\n\ndim(titanic_data)\n```\n:::\n\n\n### **Column names**{-}\n\nWe can output the column names of a dataset as a vector using the **names()** function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Column names in titanic\n\nnames(titanic_data)\n```\n:::\n\n\n### **Glimpse (dplyr)**{-}\n\nUp to here, the functions prior were from base R, which the tibble deals with for us with its refined print method.\n\nThe tidyverse library has dplyr, a data manipulation package, that provides arguably the best inspection function, known as glimpse().\n\nThis refines the print even more, to just a snapshot of the content of the columns themselves. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Have a glimpse at titanic\n\nglimpse(titanic_data)\n```\n:::\n\n\nWe still retain much of the information from before:\n\n* The number of rows and columns\n* Column names\n* Column data types\n* The first 5-10 observations\n\nWe recommend using this function after each manipulation you make to the data, as a **sense check**.\n\n:::\n\n# Summary\n\nWell done for working your way through this solid introduction to the readr package in the tidyverse,\n\nBy no means are you expected to remember all the above, what is better is that you understand the problems you want to solve and can then use references or provided material to go about solving it.\n\nIn the next chapter we will look at data manipulation with the dplyr package from the tidyverse. \n",
- "supporting": [],
+ "engine": "knitr",
+ "markdown": "---\ntitle: \"Chapter 3 - Importing and Exporting Data\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Understand the importance of argument order in functions.\n* Have an understanding of what packages are.\n* Be able to load and install a package.\n* Be able to check package versions and R version.\n* Be able to import data from multiple formats.\n* Be able to inspect loaded data.\n* Be able to export data.\n* Be able to explore data.\n\n\n# Returning to Functions\n\nSo far we have seen many functions, such as:\n\n* sqrt()\n* round()\n* c()\n* list()\n\nYou should make it a habit to explore the help files when you are using a function for the first time so you know:\n\n* What required arguments there are.\n* What optional arguments there are.\n* What default arguments there are (some arguments have a value by default so we can exclude them without error). \n\nRecall that they follow the form:\n\n> **functionName(argument1 = value1, argument2 = value2, and so on)**\n\n\n## How functions work\n\nThe seq() function from chapter 2 is the perfect example to reinforce how functions work, as well as common pitfalls.\n\nLet's take a closer look at the help file for seq().\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Help doc for seq()\n\n?seq\n\n# or\n\nhelp(seq)\n```\n:::\n\n\n\n\n\n{fig-alt=\"Seq() function help file.\"}\n\n\n### Function help files\n\nEvery help file will have a series of sections describing what the function does. It is worth focusing on the description, the usage and especially the arguments first. \n\n**Description**\n\nFor example, in the help file for seq() under **Description**, it tells us it is a function to \"Generate regular sequences\". \n\n**Usage**\n\nWe can see that seq() takes the required arguments:\n\n* from (which is 1 by default)\n* to (which is 1 by default)\n* by (which is calculated by default)\n\nand the optional arguments:\n\n* length.out \n* along.with\n\n\n**Arguments**\n\nHere, we can find out what these arguments are:\n\n - from, to: the starting and maximal end values of the sequence.\n - by number: increment of the sequence.\n\n\n### Execution of function arguments\n\nWe used this function when creating vectors, here's a reminder.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a sequence of numbers\n\nseq(from = 2, to = 6, by = 2)\n```\n:::\n\n\n\n\nLet's consider what happens instead when we **don't** specify the arguments, just their values.\n\n### **Example**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a sequence of numbers - not specifying arguments\n\nseq(1,10)\n```\n:::\n\n\n\n\nThis has generated a sequence of numbers from 1 to 10. In this case we did not supply a value for by, so it took the default value, which in this case is 1.\n\nWhat if we flip 10 and 1 instead?\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a sequence of numbers\n\nseq(10,1)\n```\n:::\n\n\n\n\nSo it is clear that where we place the value is important, because arguments are resolved **by position**, in the order specified in the help documnentation.\n\nSo above:\n\n* In the first example, it is assumed that we want a sequence from 1 that goes to 10. \n* Then if we swap the numbers it is assumed we want to sequence from 10 that goes to 1. \n\nHowever, if we name the arguments **explicitly** using argument = value, the order we specify them does not matter. \n\nLet's see this in action:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Reversing arguments but using argument name\n\nseq(to = 10, from = 1)\n```\n:::\n\n\n\n\nYou can sometimes run into errors with more complicated functions by taking the arguments for granted. \n\nOften there are many optional arguments that are resolved (position wise) before the required ones.\n\n>**We would encourage you to specify the arguments and parameters as it makes your code easier to understand.**\n\n\n# Packages\n\nOur default R installation, often referred to as **base R** gives us a lot of functionality out of the box.\n\nIf we want to implore the newest methodologies, adopted by the wider R community, then we need to install packages to achieve this.\n\n>**Packages are a collection of functions, compiled code and sometimes data sets which are stored in a library of code within R.**\n\nIn order to use a package, we first need to install it:\n\n* R installs packages from [CRAN](https://cran.r-project.org/) **The Comprehensive R Archive Network.** that contains over 20,000 packages.\n\n* You can install packages from outside of CRAN (such as from [GitHub](https://github.com/)) with specific functions. Please be aware of the source and quality in these cases.\n\nYour department may have a slightly different way of installing packages, so clearing this up is a good port of call.\n\n\n## Installing Packages\n\nTo install a package, we use the code below for **each** new package. \n\n>**install.packages(\"package_name\", dependencies = TRUE)** where dependencies allows the install to also take into account other packages your chosen one needs to function correctly. \n\nDependent on your Operating System, another parameter is also recommended:\n\n* For windows, use **type = win.binary**.\n* For mac, use **type = mac.binary** (this may differ for Apple Silicon).\n\n>**Important**: You will only need to install packages once, you should either do this in the console, or comment out the line in your script where this is done. \n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Install the packages below using the **R console** one at a time.\n\n* tidyverse\n\n* janitor\n\nNote that tidyverse is a collection of R packages that follow the same programming paradigm, so will take quite some time to install. \n\n### **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Installing packages\n\ninstall.packages(\"tidyverse\", dependencies = TRUE, type = \"win.binary\")\n\ninstall.packages(\"janitor\", dependencies = TRUE, type = \"win.binary\")\n```\n:::\n\n\n\n\n:::\n\nSuccessful installation should finish with messages as below, sometimes interspersed with some warnings. \n\n```\n## package 'janitor' successfully unpacked and MD5 sums checked\n## \n## The downloaded binary packages are in\n## C:\\Users\\bandai1\\AppData\\Local\\Temp\\Rtmpm0ZY69\\downloaded_packages\n```\n\n## Loading Packages\n\nThink of packages as owning a book; you purchase (install) the book once, and after that when you need to reference it you can pick it up off your bookshelf. \n\nIn R we call this **loading**, and you should always load packages at the very top of your script.\n\nTo load a package, use the code:\n\n>**library(package_name)** where the package name is not a string this time. \n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nLoad the packages you installed in the prior exercise:\n\n* tidyverse\n\n* janitor\n\n### **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# loading packages\n\nlibrary(tidyverse)\n\nlibrary(janitor)\n```\n:::\n\n\n\n\n:::\n\nThere is almost always some output we get when loading packages. Some options are:\n\n* **package \"X\" was built under R Version \"Y\"** - this states that your R version may be lower than the one the package was written using. This is not always an issue, but you should endeavour to remain updated with your software. \n\n* **The following objects are masked from \"package::package_name\":** - this arises when functions from your newly loaded package have identical names to either a function in base R, or from another outside package.\n * As such, the package you loaded takes precedence, and it's function under that name will be used. \n * You can get around this by using the syntax **package_name::function_name** as R will attempt to autofill the functions from that package, and there is no way to misconstrue what package the function comes from. \n\n\n## Checking Versions\n::: {.panel-tabset}\n\nReturning to the versions issue, we may have an older version of R than the one the package was built for.\n\n### **Check R Version** {-}\n\nWe can check R version by running this command.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# To check the version of R\n\nversion\n```\n:::\n\n\n\n\nYou can see that we are running 4.1.3\n\nIf your version is a little older, this is fine, but we **thoroughly** recommend versions 4.1 and above and discourage versions beginning with a 3.\n\nOlder versions, such as 3.6.3 (which is popular) are no longer supported by the creators, and will conflict with almost all training you will engage with whilst learning. \n\n\n### **Check Package Version**{-}\n\nUse the packageVersion() function with the package supplied as a string.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Checking the package version\n\npackageVersion(\"tidyverse\")\n```\n:::\n\n\n\n\nYou see that we have the up to date 2.0.0, this is backwards compatible with some older versions, but beware of argument name changes to functions.\n\nIf you are working collaboratively you should always check that you are all using the same versions of packages. \n\n\n### **Masked Objects**{-}\n\nOne of the masks at play with tidyverse is the **filter()** functions:\n\n* Base R has a filter() function to apply on time series.\n* Whereas dplyr (a tidyverse package for data manipulation) has a filter() function to select rows based on columns.\n\nThese both take very different parameters, so it is important to know what we have masked. After loading the tidyverse, it will assume we want to use the dplyr version of filter going forward. \n\nTo use the alternative we would need to type \n\n>**stats::filter()**\n\n:::\n\n\n# Tidyverse\n\nHere we will introduce the tidyverse, a collection of R packages that changed the way many work with R forever. \n\nThe packages in tidyverse share a common philosophy for data manipulation and exploration so they work well together. \n\nThis philosophy is that of Tidy Data, described first in the [seminal paper](https://vita.had.co.nz/papers/tidy-data.pdf) by Hadley Wickham, the tidyverse's creator. \n\n## Advantages of the Tidyverse\n\nThe tidyverse is:\n\n* Well documented. Each sub-library has its own website containing a 'cheat-sheet' and vignettes. We thoroughly recommend bookmarking these.\n\n* Well established in the R data science community, meaning common issues and queries are already answered on platforms such as [Stack Overflow](https://stackoverflow.com/questions/tagged/r).\n\n* Designed such that all sub packages follow a core 'philosophy' which encourages best practice. \n\n* Open-source software and free to use. As are the books written by the tidyverse creator Hadley Wickham. The highest recommendation we can make is [R for Data Science](https://r4ds.hadley.nz/). \n\n\n## Disadvantages of the Tidyverse\n\n* Like R, tidyverse can have a steep learning curve, and its reliance on functional programming can confuse beginners. \n\n* It is incredibly flexible, which makes it hard to determine which solutions to problems are the best.\n\n* Quite verbose (wordy), which can lead to long scripts. \n\n\n## Tidyverse Breakdown\n\nBelow is a list of the core packages in tidyverse to provide some awareness into what they make possible:\n\n* [readr](http://readr.tidyverse.org) - Data import\n* [tibble](https://tibble.tidyverse.org/) - Tibbles, a modern re-imagining of data frames\n* [tidyr](https://tidyr.tidyverse.org/) - Data Tidying\n* [dplyr](https://dplyr.tidyverse.org/) - General data anipulation\n* [stringr](https://stringr.tidyverse.org/) - String anipulation\n* [forcats](https://forcats.tidyverse.org/) - Factor variables \n* [ggplot2](https://ggplot2.tidyverse.org/) - Data Visualisation\n* [purrr](https://purrr.tidyverse.org/) - Functional Programming\n* [lubridate](https://lubridate.tidyverse.org/) - For dealing with dates and times - included in tidyverse 2.0.0 onwards. \n\n\n{fig-alt=\"Tidyverse workflow of import, tidy, transform/model/visualise and communicate.\"}\n\nThe first of the core packages we will delve into is **readr**, which deals with reading in data, and by extension **tibbles**, the excellent update to dataframes that the tidyverse provides. \n\nHowever, we need an understanding of the working directory beforehand.\n\n\n# Working Directory\n\nR has a powerful notion of the working directory. This is where R looks for files that you ask it to load, and where it will put any files that you ask it to save. \n\nWe often refer to this as the \"starting point\" when R looks for a file you specified the path for.\n\nThankfully, we are using an **R project**, which makes filepaths and directories reproducible, by ensuring everyone who opens the project has this set by default.\n\n>**If you are not using a project (we recommend you do) you will need to set your own working directory with the [setwd() function](https://www.geeksforgeeks.org/how-to-use-setwd-and-getwd-in-r/) that requires a full path to the directory to change it manually.**\n\n\n## Checking Working Directory\n\nThe getwd() function (get working directory) is ideal.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Getting the working directory\n\ngetwd()\n```\n:::\n\n\n\n\nIf you are inside the project created within these materials, you should have the same final step in the \"path\", that of the \"Course_content\" folder.\n\n> **In Windows file paths are specified using back slashes, but in R a backslash already has a meaning, so we use a forward slash or two back slashes instead.**\n\n\n# Reading in Data\n\nThere are a variety of ways of reading data into R, in this chapter we will look at reading data using the packages:\n\n* readr - loaded with tidyverse\n* readxl - installed with tidyverse, but loaded separately. \n\n\n## Readr\n\nThe package provides a fast and friendly way to read data from:\n\n* Comma Separated Value (csv) files\n* Tab Separated Value (tsv) files\n\nconverting them to **tibbles**, which are the required data structure in the tidyverse. \n\nLet's formally introduce them now.\n\n### Tibbles\n\nTibbles are data frames, but they tweak some older behaviours to make life a little easier, R is over 20 years old after all:\n\n* Tibbles complain more when variables do not exist - leads to easier error checking.\n* Tibbles don't change variable names.\n* Tibbles don't tweak variable types from the source data. \n\n**The key benefits of tibbles are:**\n\n* In addition to its name, each column reports its type.\n\n* The dimensions of the tibble are shown at the top.\n\n* Tibbles have a refined print method that shows only the first 10 rows, and all the columns that fit on screen. This makes it much easier to work with large data.\n\n\n### How readr works\n\nThis package reads in datasets we supply by using a **family of functions**, ones that have the same prefix.\n\n> **read_filetype()**\n\nThe most common, and one we will use throughout the course is **read_csv()**.\n\n### Considerations to make\n\n> Before importing your data you need to know:\n\n* Where it is stored?\n\n* What kind of file is it?\n\n* Are there missing values in the data?\n * Missing values in R are denoted by **NA**.\n\nThe code will take the following form:\n\n>**data_name <- read_csv(file_path)**\n\nand readr will:\n\n* Assume the first row of your data is the headings of the columns.\n\n* Attempt to guess the datatype of columns, given their content. If a numeric column contains 99 doubles and one character, then the same coercion that happened with vectors will happen again (since columns are vectors) and we get a character column.\n * One of the first data checks you should do is that the types of the columns match what you expect. \n\n\n### Example - Our first filepaths\n\nLet's load in the titanic dataset in the \"Data\" folder. \n\nWe need to figure out where this is and how to get there from our current working directory, so that we can tell R. \n\n::: {.panel-tabset}\n\n### **Absolute Filepaths**{-}\n\nAn **absolute** or full filepath is constructed as:\n\n>\"starting_drive/step_1/step_2/step_3/..../destination\"\n\nthis details the full path taken to reach the file.\n\nTo reach \"titanic.csv\" the absolute filepath for us is \n\n>\"C:/Users/marshj1/af_introduction_to_r/data/titanic.csv\"\n\nNote that your usernames and drives will differ to ours. \n\n### **Relative Filepaths**{-}\n\nA relative filepath is the path to reach the file **relative** to the current working directory. \n\nThus we are already part of the way there, and just need to tell R where to go from here:\n\n>\"working_directory/step_1/step_2/.../destination\"\n\nHowever, in our case, our working directory is one level deeper than we'd like to be, in the **course_content** folder.\n\n>To reach the dataset, we must exit this folder to get back to the root, then enter the data folder, and select **titanic.csv**\n\nTo do so, we need to know how to go back one folder level, or exit the current directory, this is written as **../** where the two full stops denote going back. \n\nAs such, the relative filepath we need to reach the dataset is\n\n>\"Data/titanic.csv\"\n\nVisually, to understand the tree-like folder structure, we have something like the following going on:\n\n{fig-alt=\"Top level is introduction to R, folders are at level 2, items in the folders are level 3.\"}\n\n### **Loading in the data**{-}\n\nLet's read in titanic using a relative filepath. \n\nWe simply need to go into the **data** folder, then select the **titanic.csv** file to load in.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Read in titanic with read_csv()\n\ntitanic_data <- read_csv(\"Data/titanic.csv\")\n```\n:::\n\n\n\n\nYou will get some information on:\n\n* rows and columns\n* Counts of each column datatype\n\n### **Inspect Data**{-}\n\nLet's call the name of the variable we have created to see the output of our first tibble.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Display the titanic data\n\ntitanic_data\n```\n:::\n\n\n\n\nNotice the refined print we get from this, that provides so much more information than the data frame output did in chapter 2. \n\nIt may take more time to read and understand, but prevents you from having to use many additional functions to find out things such as dimensions (rows and cols).\n\nAnother example of inspection is with View(), which opens a separate tab in the code editor pane with the dataset in spreadsheet form.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Viewing the data - Note the capital V\n\nView(titanic_data)\n```\n:::\n\n\n\n\n:::\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Having read in the titanic data above, have a look at the column Age of passenger.\n\n2. What type of data would you expect this column to be?\n\n3. Use the \"str()\" function to see the data type R has set it to be.\n\n\n### **Show Answer**{-}\n\n1. Have a look at the column Age of passenger.\n\n2. The column looks numeric.\n\n3. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the str() function\n\nstr(titanic_data)\n```\n:::\n\n\n\n\nWe can see that R has classed the column as character because of the **.** and asterisk within it.\n\nNotice how much of the information this provides is also represented in the tibble output, very impressive!\n\n:::\n\n### Dealing with Missing Values at Read-in\n\nWhilst we cannot observe all missing values at this stage, examples that cause columns to be cast to unexpected data types are often spotted quickly.\n\nWe can easily correct this by adding the **na** paramter to the read_csv() function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Specifying missing values as a vector to read_csv()\n\ntitanic_data <- read_csv(\"Data/titanic.csv\", \n na = c(\"*\", \".\", \"\", \"NULL\"))\n```\n:::\n\n\n\n\nThis is read as:\n\n> **Where there is the a full stop, asterisk, NULL (entirely empty) value or a blank space, class is it as a missing value.**\n\nWe can now see that the . and * in the age column have been replaced with NA's and the age column is now numeric.\n\nYou may see all sorts of missing values in practice, deriving from data entry:\n\n* negative numbers where it makes no sense\n* abnormally large values such as 999999\n\n>**There are many other useful arguments you can use when reading in data, check the help documentation for read_csv() for details.**\n\n\n## Readxl\n\nWe use readxl to read excel data into R, it supports both .xls and .xlsx formats.\n\nEven though it is installed alongside the tidyverse, it must be loaded separately.\n\nThe code for read in is very similar to the read_csv() example, just using the read_excel() function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Load in readxl\n\nlibrary(readxl)\n```\n:::\n\n\n\n\nExcel workbooks are more complex than flat files as they are **workbooks**, featuring multiple sheets. \n\nWe can output their names using the excel_sheets() function, which will become important shortly.\n\n\n### Example \n\nLet's read in the police dataset.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Reading in excel data using the readxl package\n\npolice_data <- read_excel(\"Data/police_data.xlsx\")\n\nView(police_data)\n```\n:::\n\n\n\n\nWe see that this is the **first sheet** in our workbook which is just the \"Notes\". This is the default behaviour of read_excel() unless we specify otherwise.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Observe sheet names in police data\n\nexcel_sheets(\"Data/police_data.xlsx\")\n```\n:::\n\n\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nUse an additional argument in \"read_excel()\" to read in the second sheet of the police dataset.\n\nYou will need to look at the help documentation for read_excel() to help you with this. \n\n\n### **Show Answer**{-}\n\nYou can use the name of the sheet or the number/index. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the sheet parameter in 2 ways\n\npolice_data <- read_excel(\"Data/police_data.xlsx\",\n sheet = 2)\n\n# Alternatively\n\npolice_data <- read_excel(\"Data/police_data.xlsx\",\n sheet = \"Table P1\")\n\npolice_data\n```\n:::\n\n\n\n\nThis is better but still not ideal:\n\n* The top columns are mostly blank with no real significant data.\n\n * We can get around this by specifying the **range** parameter in read_excel, to denote the range of cells to capture.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using the range parameter to avoid empty rows\n\n\npolice_data <- read_excel(\"Data/police_data.xlsx\",\n sheet = 2,\n range = \"A5:AA48\")\n\npolice_data\n```\n:::\n\n\n\n\n:::\n\n# Exporting the Data\n\nWhen you read a file into R, the data is loaded into memory. This means that any changes you make won't be reflected in the original file you loaded. \n\nIf you want to preserve the changes you make to the dataset you have to export the data object to its own file. \n\nWe have a family of functions for this, just like reading in, the **write_filetype()** functions.\n\n## Example\n\nAs an example, let's write out the police data which now has the correct sheet and range as a csv (flat) file instead.\n\nWe must supply two arguments to **write_csv()**:\n\n* dataset itself\n* file, which must be the filepath of **where to save your file**. \n\nThe path is constructed similarly as before\n\n>**\"../folder/my_file.csv\" as we must back out of the course_content folder first**\n\nIf you specify a folder that doesn't exist, the function will create it for you. In this case, let's create a separate folder called \"outputs\". \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Exporting data using write_csv()\n\nwrite_csv(police_data, file = \"../outputs/police.csv\")\n```\n:::\n\n\n\n\nThis stores our police_data in the outputs folder under the name \"police.csv\". \n\n\n# Inspecting the Data\n\nAfter importing our data, the first thing we may want to do is have a quick look at it:\n\n* We can check it looks similar to the source file.\n* We can check if there are the same number of rows and columns we expect.\n* We can check if the columns loaded in as the datatype we expect.\n* We can check if there are obvious missing values at the tail ends. \n\nWe can do these checks in a variety of ways, be that from base R, or in the tidyverse.\n\n## Inspecting Data Functions\n::: {.panel-tabset}\n\n### **Tail Ends**{-}\n\nWe can output the first or last 6 rows of the dataset by using the **head()** and **tail()** functions.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Head of titanic\n\nhead(titanic_data)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Tail of titanic\n\ntail(titanic_data)\n```\n:::\n\n\n\n\n### **Dimensions**{-}\n\nWe can output the number of rows and columns or each separately with the following functions.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of rows in titanic\n\nnrow(titanic_data)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of columns in titanic\n\nncol(titanic_data)\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Dimensions - Vector of nrow and ncol\n\ndim(titanic_data)\n```\n:::\n\n\n\n\n### **Column names**{-}\n\nWe can output the column names of a dataset as a vector using the **names()** function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Column names in titanic\n\nnames(titanic_data)\n```\n:::\n\n\n\n\n### **Glimpse (dplyr)**{-}\n\nUp to here, the functions prior were from base R, which the tibble deals with for us with its refined print method.\n\nThe tidyverse library has dplyr, a data manipulation package, that provides arguably the best inspection function, known as glimpse().\n\nThis refines the print even more, to just a snapshot of the content of the columns themselves. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Have a glimpse at titanic\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\nWe still retain much of the information from before:\n\n* The number of rows and columns\n* Column names\n* Column data types\n* The first 5-10 observations\n\nWe recommend using this function after each manipulation you make to the data, as a **sense check**.\n\n:::\n\n# Summary\n\nWell done for working your way through this solid introduction to the readr package in the tidyverse,\n\nBy no means are you expected to remember all the above, what is better is that you understand the problems you want to solve and can then use references or provided material to go about solving it.\n\nIn the next chapter we will look at data manipulation with the dplyr package from the tidyverse. \n",
+ "supporting": [
+ "CH3_import_export_files"
+ ],
"filters": [
"rmarkdown/pagebreak.lua"
],
diff --git a/_freeze/CH4_tibbles_dplyr/execute-results/html.json b/_freeze/CH4_tibbles_dplyr/execute-results/html.json
index 0d39a1e..65e7bc8 100644
--- a/_freeze/CH4_tibbles_dplyr/execute-results/html.json
+++ b/_freeze/CH4_tibbles_dplyr/execute-results/html.json
@@ -1,8 +1,11 @@
{
- "hash": "5fd5986894156aee6970504680b26a33",
+ "hash": "fb4daea818449793d3e03bd845b8d345",
"result": {
- "markdown": "---\ntitle: \"Chapter 4 - Tibbles and dplyr\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Understand the importance of clean variable names.\n* Be able to clean column names using the janitor package.\n* Understand the use of the pipe operator.\n* Be able to sort data with dplyr's **arrange** verb.\n* Be able to select data with dplyr's **select** verb.\n* Be able to filter data with dplyr's **filter** verb. \n* Be able to transform data with dplyr's **mutate** verb.\n* Be able to join datasets together.\n\n\n# Packages and Data\n\nRemember, the first steps when starting a new script are:\n\n* Load in the packages required for the work.\n* Read in datasets required and assign them to a variable in memory.\n\n## Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Load the following packages:\n\n* Tidyverse\n* janitor\n\n2. Read in the **titanic.csv** file and assign it to the name \"titanic_data\". Remember to assign null values properly (as in Chapter 3) using the \"na\" parameter. \n\n* Remember that you are in your R project, which sets the working directory to be inside the **Course_content** folder. \n\n3. Have a glimpse of your dataset. \n\n\n### **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Load packages\n\nlibrary(tidyverse)\nlibrary(janitor)\n\n\n# Read in titanic.csv and set null values to be specific symbols\n\ntitanic_data <- read_csv(\"Data/titanic.csv\", \n na = c(\"*\", \".\", \"\", \"NULL\"))\n\n# Have a peak\n\nglimpse(titanic_data)\n```\n:::\n\n\n:::\n\n\nAs a reminder, in the titanic dataset our columns are:\n\n* **Pclass**: Passenger’s class, 1 = 1st (Upper), 2 = 2nd(Middle), 3 = 3rd(Lower)\n* **Survived**: Survived (1) or died (0)\n* **Name**: Passenger’s name\n* **Sex**: Passenger’s sex\n* **Age of Passenger**: Passenger’s age\n* **SibSp**: Number of siblings/spouses aboard (excluding the person)\n* **Parch**: Number of parents/children aboard (excluding the person)\n* **Ticket**: Ticket number\n* **Fare**: Fare\n* **Cabin**: Cabin number\n* **Embarked**: Port of embarkation, C = Cherbourg, Q = Queenstown, S = Southampton\n\n\nWe can see more details on the [Data Dictionary](https://www.kaggle.com/c/titanic/data)\n\n\n# Column Names\n\nIn the previous session we stated that every column in a tibble is a variable and it is good practice to not have spaces within variable names, as spaces makes it harder for us to call on the variables when we need to use them.\n\nWhen you enter data in Excel, you most often don’t think too much about what you call each column. After all, you just label them once and as long as they are documented, this isn't given too much thought.\n\nWhen you are working with variables in R though, you need to type the name of each variable, every time you want to work with it. So, it makes sense to make your column names as simple, but meaningful as possible.\n\n## Retuning columns by name\n\nIn base R, to call a column by name and return its contents as a single vector (remember, each column in a tibble is a vector) we use the dollar sign **$** operator.\n\nYou will notice the list of column names will pop up and you can move through them with arrow keys and select the one you want. \n\n### Example\n\nLet's return the column \"Pclass\".\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return Pclass with base R\n\ntitanic_data$Pclass\n```\n:::\n\n\nThis returns the entire vector (usually up to 1000 entries) so it would be useful to use **glimpse()** or other inspection functions for a sense check.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return Pclass and glimpse\n\nglimpse(titanic_data$Pclass)\n```\n:::\n\n\nThis could already prove frustrating due to needing to remember the capital letters, particularly if the autocomplete is slowing down.\n\nHowever, it can get worse if spaces are included in the column name.\n\n### Example - Returning column with spaces\n\nLet's take the \"name of Passenger\" column and try to return it without the auto-complete.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntitanic$name Of Passenger\n```\n:::\n\n\nThis will throw an error as spaces in syntax are not allowed, R cannot process code in this way as a space should usually denote the end of a line of code. \n\nTo get around this we enclose column names with spaces in backticks **\\` \\`** and you will notice that the autocomplete does the same. \n\nThis allows the entire column name to be read as one entity.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting a column with spaces in the names\n\nglimpse(titanic_data$`name Of Passenger`)\n```\n:::\n\n\nWhilst this works, it is bad practice to use capitalisation and spaces, as it complicates things for us as well as others we collaborate with.\n\n### A word of warning\n\nWhilst this is completely fine in Base R, there are unexpected consequences of using this technique, particularly when making changes to a column using assignment. \n\n* With the tidyverse, when we use its myriad of functions, we can check manipulations on the data without overwriting the underlying variable unless we **explicitly** ask it to do so with **<-**.\n\n* However, with the **$** method, we can overwrite a column for example and this will **implicitly** and permanently change the underlying variable, which we must be careful of.\n\nShould you make a mistake following this choice, you would have to revert back to the original data and read it back in to start from scratch, as recreating data is a nightmare.\n\n### Accessing column names\n\nWe can see the column names by using the \"names()\" function to print a character vector of the column names.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Getting the column names using the names function\n\nnames(titanic_data)\n```\n:::\n\n\nWe will need to do some work on these to remove the use of capitalisation and spaces. \n\n\n## Cleaning Column Names\n\n### The Janitor Package\n\nThe **janitor** package offers many functions used to manipulate data, such as finding duplicates. In this chapter we will use it to clean column names. \n\nThe function to use is called \"clean_names()\" and automatically formats the column names as **snake_case**, but this can be altered with an additional parameter.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Clean the column names and overwrite the variable\n\ntitanic_data <- clean_names(titanic_data)\n\n# Getting the column names of the dataset\n\nnames(titanic_data)\n```\n:::\n\n\n\n# The Data Manipulation Package dplyr \n\nThis is one of the most powerful packages in the **tidyverse**, which makes data manipulation simple and code easy to read.\n\nWe will look at how to perform the following actions:\n\n1. arrange/sort\n2. select\n3. filter\n4. mutate\n5. joining data\n\nwith the aim of the package to provide a function for each basic **verb** of data manipulation. This has led to them being referred to as such in the documentation. \n\nEach of the verbs have the same structure:\n\n> **verb(.data, info,....)**, note the full stop which is syntax to allow us to reference variables from the dataset (enables auto-completion too!)\n\nand the [cheat sheet](https://nyu-cdsc.github.io/learningr/assets/data-transformation.pdf) is incredibly useful for a reference piece. \n\nBefore we jump into the verbs, let's see dplyr's version of renaming columns!\n\n\n## Rename\n\nWe may wish to remain within the tidyverse when cleaning column names (say, Janitor is not available to you), which invites the use of **rename()**.\n\nThis allows you to change column names one at a time using the following syntax:\n\n> **rename(.data, new_name = old_name)**\n\nAs an example, let's rename the age_of_passenger column to simply \"age\". \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Rename the age_of_passenger column to age\n\nrename(.data = titanic_data,\n age = age_of_passenger)\n```\n:::\n\n\nIf we glimpse the data again:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Take a peak at titanic data\n\nglimpse(titanic_data)\n```\n:::\n\n\nWe see that age has not carried through to the underlying dataset.\n\nThis is an excellent feature of the tidyverse, in that if we do not:\n\n* Directly overwrite the variable \n* Or create a new one using assignment **<-**\n\nthen it just shows us what that process will do, so we can then make the decision on whether it's what we want. \n\n\n### Renaming multiple columns\n\nOne of the best things about dplyr's functions is that the .data argument clues the function in to the columns themselves, which means we can just continually list them, or make changes to them, without wrapping them in a vector **c()**, like many other libraries. \n\nAs an example, let's create a new variable and rename the \"of_passenger\" columns.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Rename of_passenger columns and create a new variable\n\ntitanic_renamed <- rename(.data = titanic_data,\n name = name_of_passenger,\n sex = sex_of_passenger,\n age = age_of_passenger) # Notice autocompletion\n\nglimpse(titanic_renamed)\n```\n:::\n\n\nWe also didn't need to give them in the order specified either, the function automatically knows what columns we are referring to in the underlying dataset.\n\nThere is much more we can say about the structure of these functions, but we will see this as we proceed through the verbs themselves. \n\n\n## Arrange\n\nOur data is displayed in the same order as the source data.\n\nWe may want to sort our data based on specific columns. \n\nTo do so, we use the verb **arrange()**. \n\n### Example - Single column sort\n\nFrom here, we will only create a new variable or overwrite the existing one when a change we wish to permanently keep is performed. \n\nWe highly encourage you to do the same, as creating multiple new variables you will never use again will clutter up your environment. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort titanic by fare\n\narrange(.data = titanic_data,\n fare)\n```\n:::\n\n\nWe get a larger output here that does not show us all columns at a glance, so checking that the outcome is what we expect is more difficult.\n\nWe should instead use **glimpse()** to check the output, which needs to be written first in the code. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort by fare and then glimpse\n\nglimpse(arrange(.data = titanic_data,\n fare))\n```\n:::\n\n\nNotice that by default, arrange() sorted the fare column in **ascending** order.\n\n### **Small Aside - Functions**{-}\n\nNotice that glimpse() is **written first** but **executed last**, since R evaluates functions from the inside out.\n\nAfter all, if glimpse() has no input, we can't see anything at all! \n\nKeep this in mind as it will become very important later.\n\n\n### Example - Desending Order Sort\n\nTo sort a column in descending order, we use the **desc()** function and the column name as its input. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort titanic in descending order \n\nglimpse(arrange(.data = titanic_data,\n desc(fare))) \n```\n:::\n\n\n### Example - Multi-Column Sort\n\nWe can also sort by multiple columns, but this creates a chain of **dependence**, in that the first column sort is maintained before the second sort is performed. \n\nThis means that the second sort won't change the order from the first sort.\n\n* When this becomes useful is if there are numerous examples of the same value, such as the 0.0000 values in the fare column.\n * Whilst the position of 0.0000 will not change, the values in the adjacent column will be sorted. Some of those paying £0 fare may have been younger than others, after all. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Multi-column sort\n\nglimpse(arrange(.data = titanic_data,\n fare,\n age_of_passenger))\n```\n:::\n\n\nNotice that we were able to just continually reference columns from the data as if they were arguments to the function, and the verb understands that immediately, just like with rename().\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nSort the titanic data set by age in **descending** order, then fare in **ascending** order. \n\nGlimpse the result.\n\n### **Show Answer**{-}\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort by age desc, fare asc\n\nglimpse(arrange(.data = titanic_data,\n desc(age_of_passenger),\n fare))\n```\n:::\n\n:::\n\n\n## Select\n\nSometimes we will want to work with smaller tibbles that contain just a subset of available columns.\n\nThe **select()** verb is perfect for this, and it takes the arguments:\n\n* The first is our dataset, made even simpler with \".data\"\n* From here we list as many columns by name as we would like to be retained in our selecting process.\n * The order in which we specify them is the order they will be in the smaller tibble.\n\n### Example - Single Column\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting data\n\nglimpse(select(.data = titanic_data, \n name_of_passenger))\n```\n:::\n\n\nNotice that this has returned a tibble with one column, not the underlying vector itself that **$** would have.\n\n### Example - Multiple Columns\n\nIf we want to select multiple columns, we can continue to list them, separating with commas, as we did with **arrange()**.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting data\n\nglimpse(select(.data = titanic_data,\n name_of_passenger, \n age_of_passenger,\n pclass))\n```\n:::\n\n\n\n### Example - Columns in a range\n\nWe can select consecutive columns (next to one another) with the syntax we used for indexing in chapter 2, the colon **:** operator.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting from passenger class to the age of passenger in order\n\nglimpse(select(.data = titanic_data,\n pclass:age_of_passenger))\n```\n:::\n\n\nNotice that we return the columns from pclass to age_of_passenger in the order of the source data. \n\n\n### Selecting with exclusion\n\nUp to this point we have selected with **inclusion**, a.k.a we specify the columns we want to include in our smaller tibble.\n\nThe real power of select comes from it's flexibility, in that we can reduce the amount of code to write by using **exclusion** instead, a.k.a specify the columns we don't want to include.\n\nSay we want to keep 7 of 9 columns, instead of typing out the names of all 7, we can just exclude the 2 we don't want instead. \n\n### **Example**{-}\n\nTo exclude, we use the minus sign operator **-** which signifies \"do not select this\" or \"select, not this\".\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting by excluding columns we don't want\n\nglimpse(select(.data = titanic_data, \n -name_of_passenger, \n -age_of_passenger, \n -pclass))\n```\n:::\n\n\nThere is an even more streamlined way to do this, by wrapping the columns in a vector with the **c()** function and using one minus sign outside it.\n\nYou can think of this as expanding brackets in mathematics:\n\n> \\-c(col1, col2) = c(\\-col1, \\-col2) = \\-col1, \\-col2\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using a vector for exclusion\n\nglimpse(select(.data = titanic_data, \n -c(name_of_passenger, \n age_of_passenger, \n pclass)))\n```\n:::\n\n\n\n### Selecting with Index Position\n\nWe can also select the columns using their index position, starting from 1, just like we did with data structures in chapter 2.\n\nLet's select columns 1 to 4, and also column 7.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting sequential and out of sequence columns with index position\n\nglimpse(select(.data = titanic_data, \n 1:4, \n 7))\n```\n:::\n\n\nExclusion works similarly here with the minus sign.\n\nNote that whilst this may be required in some cases, it is usually better to be **explicit** with the exact column names, if possible. \n\n\n### Select Helper Functions\n\nAs if **select()** wasn't already helpful enough, it even has helper functions that allow us to select on specific patterns, such as a prefix or suffix in a column name. \n\nThey are as follows:\n\n* starts_with(match): Starts with a prefix.\n* ends_with(match): Ends with a suffix.\n* contains(match): Contains a literal string.\n* matches(match): Matches a [regular expression](https://www.regular-expressions.info/quickstart.html).\n* everything(): Selects all variables.\n* last_col(): Selects the last column.\n\n\nThese can be passed instead of column names **and** alongside selected column names as well. \n\n### **Examples**{-}\n\nLet's return columns that start with an \"s\".\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting columns\n\nglimpse(select(.data = titanic_data, \n starts_with(\"s\")))\n```\n:::\n\n\nAs a second example, let's return everything.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting everything\n\nglimpse(select(.data = titanic_data,\n everything()))\n```\n:::\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n\n1. Select the second, third and fourth columns from titanic_data, without typing all three.\n\n\n2. Select all columns except \"fare\", \"cabin\" and \"embarked\" from titanic_data. Note that these are consecutive.\n\n\n3. Select just the last column from titanic_data using a helper function.\n\n\n4. Select the columns that end in the suffix \"passenger\" using a helper function.\n\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Select second, third and fourth column\n\nglimpse(select(.data = titanic_data, \n survived:sex_of_passenger))\n```\n:::\n\n\n2. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Using exclusion on a range\n\nglimpse(select(.data = titanic_data, \n -fare:-embarked))\n\n# OR\n\n# glimpse(select(.data = titanic_data,\n# -c(fare, cabin, embarked)))\n\n# OR\n\n# glimpse(select(.data = titanic_data,\n# -fare,\n# -cabin,\n# -embarked))\n```\n:::\n\n\n3. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting last column only\n\nglimpse(select(.data = titanic_data,\n last_col())) \n```\n:::\n\n\n\n4.\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting on a suffix\n\nglimpse(select(.data = titanic_data,\n ends_with(\"passenger\"))) \n```\n:::\n\n:::\n\n\n## The Pipe Operator \n\nUp until now, we have run verbs one at a time on our dataset, be it to sort or select columns. \n\nThe real power of the tidyverse comes from the ability to chain these functions together in a sequence for more complex data manipulation tasks. \n\nHowever, out of the box, this becomes laborious quickly due to the nature of functions. \n\n### Returning to Functions - Composition\n\nAs we saw earlier with glimpse(), to apply many functions to a single output, known as **composition** of functions, we must nest them, with the function applied last being written first, and evaluated from the inside to the outside.\n\n### **Example**{-}\n\nFor example, let's take the **sqrt()** and **round()** mathematical functions and apply them together, so that we obtain the square root of a number and hence round it to a specified number of decimal places.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compose mathematical functions\n\nround(sqrt(2))\n```\n:::\n\n\nNotice that the functions are evaluated in reverse order (from the inside, out) just as you would with writing this mathematically. You would perform the square root operation first, **then** round the result. \n\nShould we wish to use an extra parameter, we need to start thinking about the brackets, as they are the opening and closing doors of a function itself.\n\nThus, the **digits** parameter needs to go inside the round() brackets, not the sqrt() ones.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compose mathematical functions with extra parameters\n\nround(sqrt(2), digits = 2)\n```\n:::\n\n\nNotice that the input to the function round() was the output from the sqrt() function. \n\n\n### Composition of functions in the tidyverse\n\nThis becomes tricky to comprehend when working with the tidyverse functions, as we are effectively performing actions in sequence, such as selecting the columns we want and **then** sorting the result. \n\nAs such, the output of one function is the input to another:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select passenger columns and fare then arrange by fare\n\nglimpse(arrange(.data = select(.data = titanic_data,\n ends_with(\"passenger\"),\n fare),\n desc(fare)))\n```\n:::\n\n\nNotice that the input to arrange was the result of a select operation, so we had to keep track of our brackets and ensure that the desc(fare) was placed within arrange(), **not** select().\n\nGoing forward, we will see more verbs that can be applied on top of this, and it becomes difficult to manage. \n\nThis is where the pipe operator comes in.\n\n\n### Introducing the Pipe\n\nThe Pipe Operator makes it possible to chain a sequence of functions starting with the base data as an input to the sequence.\n\nThis removes the need to type the **.data** argument each time. \n\n* Prior to R 4.1, the pipe operator came from a package known as **magrittr**, which would be loaded alongside the tidyverse, and it took the form **%>%**.\n\n* From R 4.1 onwards, the operator comes as standard with base R, as it has become the universal standard for data analysis. It now takes the form **|>**, and this option must be turned on in the Tools --> Global Options tab. \n\n{fig-alt=\"The Code, Editing pane with the native pipe operator tick box.\"}\n\nThe shortcut for this operator is **CTRL + SHIFT + M** and is one you will use alot from here on. \n\n### **Example - Single Value**{-}\n\nLet's return to our square root and rounding functions. Let's apply one, and then both in sequence using our new operator.\n\n* First, we write the value or dataset we wish to apply functions to, it is at the entrance to the \"pipe\" if you will. \n* Then, we write the function we wish to use and any additional parameters we may need. \n* The pipe operator **passes** the input to the function, so we do not need to write it within the brackets.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Our first pipe - with a single value\n\n2 |> sqrt()\n```\n:::\n\n\nYou can read the pipe operator as **AND THEN**. \n\nIt takes the output of one function AND THEN uses that as the input of the next function, and so on. \n\nThis means that to chain a sequence of functions, we will use the pipe operator again to pipe our output to our next function as its input. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Our first sequence of pipes\n\n2 |> sqrt() |> \n round(digits = 2)\n```\n:::\n\n\nThis is quite the shift from what we have done so far, but is more readable in plain english: \n\n>**To the value 2, apply the square root function, and then, round that output to 2 decimal places.**\n\nNotice, that following the second pipe, we insert a new line, which automatically moves us in a few spaces. This is optional but is easier to read as a sequence.\n\n\n### Using the Pipe Operator with the tidyverse\n\nWhat was done above was an oversimplification of why the pipe was created, in reality it was created to pipe datasets into functions, as opposed to a single value. \n\nEven in the case of datasets, we do not need to pipe if we are only applying a single function such as glimpse().\n\nIt is when we are performing a chain of steps that the pipe completely simplifies our code, enhacing readability.\n\n\n### **Example**{-}\n\nLet's return to our previous example, where we selected passenger demographics and sorted by fare. \n\n* First, we write the dataset we want to apply this sequence of steps to.\n* AND THEN pipe that into the **select()** function, specifying what columns we wish to retain.\n* AND THEN pipe that output to the **arrange()** function, so that it can be sorted by whatever column(s) we wish.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Repeat earlier operation with pipes\n\ntitanic_data |> \n select(ends_with(\"passenger\"),\n fare) |> \n arrange(desc(fare))\n```\n:::\n\n\nThis way, the code is written in the order that it executes, as opposed to the reverse order without the pipe operator. \n\n>**To the titanic dataset, we select columns that end with \"passenger\" as well as the fare column, and then, sort that in descending order of fare paid.**\n\nWe could also pipe the output to a glimpse() for easier sense checking.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Pipeline with glimpse\n\ntitanic_data |> \n select(ends_with(\"passenger\"),\n fare) |> \n arrange(desc(fare)) |> \n glimpse()\n```\n:::\n\n\n\n### **Variables with tidyverse chains**{-}\n\nNotice that we didn't create a variable in the prior conversion.\n\nThis is because it can cause confusion between the assignment operator **<-** and the pipe operator **|>** if not covered separately. \n\nIn front of the previous sequence, known as a **pipeline**, we would write our variable name and assignment operator, which saves the final output in memory.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Save pipeline as a variable \n\ntitanic_demographics_sort <- titanic_data |> \n select(ends_with(\"passenger\"),\n fare) |> \n arrange(desc(fare))\n\n\ntitanic_demographics_sort |> \n glimpse()\n```\n:::\n\n\nBe careful not to confuse the meaning of the two operators, this will take some practice to get used to. \n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nSpeaking of pratice, let's try out our new tool!\n\nCreate a pipeline that:\n\n* Selects the first five columns of the data\n* Arranges them in ascending order of age.\n\nAssign this output to a new variable and glimpse it.\n\n\n### **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting and ordering by age with pipes\n\ntitanic_age_sort <- titanic_data |> \n select(pclass:age_of_passenger) |> \n arrange(age_of_passenger)\n\ntitanic_age_sort |> \n glimpse()\n```\n:::\n\n\n:::\n\n\n## Filter\n\nOften, we are only interested in groups of rows that adhere to a specific condition, such as:\n\n* Passengers that paid over or under a certain fare.\n* Passengers who are in a particular age threshold.\n* Passengers who embarked from a particular port.\n\nand of course, combinations of the above.\n\nThe next verb, **filter()** allows us to subset our rows in this way. To understand this section, we first need to consider conditions.\n\n\n### Conditional Statements\n\nA conditional statement is one that returns **TRUE** or **FALSE** dependent on the outcome. \n\nWe saw examples of these back in Chapter 1, when we were producing logicals with comparisons. For example:\n\n* 4 < 5 is a condition statement that evaluates to TRUE\n* 4 != 4 is a conditional statement that evaluates to FALSE\n\nLogical Operator| Description\n:--------------:|:------------:\n < | Less Than\n <= | Less Than or Equal To\n \\> | Greater Than\n >= | Greater Than or Equal To\n == | Equal To\n != | Not Equal To\n \\| | Or\n & | And\n ! | Not\n any() | Checks if any value in a logical vector are TRUE\n all() | Checks if all values in a logical vector are TRUE\n is.na() | Is the value missing (NA)?\n between() | Is between 2 numbers\n\n\n>**Note: The \"!\" allows us to flip or invert an expression. Basically, if an expression returns c(TRUE, TRUE, FALSE), the inverted expression (place ! in front of it) will return c(FALSE, FALSE, TRUE).**\n\nThese statements can of course be much more complex than comparing two single numbers, we can apply them across columns with dplyr's **filter()** verb! \n\n\n### Single Conditional Filtering\n\nWe will first look at filtering by a single condition, which are constructed as follows:\n\n* We begin with the column to compare with.\n* Next is the logical operator of choice, such as **<**, **>**.\n* Last up is the value to compare each entry in the column to, which generates the set of TRUEs and FALSEs.\n\nThis is generated in the background, and **filter()** will keep only the rows that return **TRUE** from this comparison. \n\n> **For example, to subset down to only second class passengers, we would write: \"pclass == 2\".** \n\n### **Example - Categorical**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to retain only second class passengers\n\nsecond_class <- titanic_data |> \n filter(pclass == 2) |> \n glimpse()\n```\n:::\n\n\nA quick way to check that the filter has worked is to use base R's **unique()** function on the column. \n\nWe need to use our **$** here to reference columns by name as this is not a tidyverse method.\n\nLet's check the original data first.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return unique values from the original data\n\nunique(titanic_data$pclass)\n```\n:::\n\n\nWe see that the pclass column has 3 unique levels of 1, 2 and 3.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return unique values from the filtered data\n\nunique(second_class$pclass)\n```\n:::\n\n\nWe see that in the filtered data, we have just second class passengers, as expected. \n\n### **Example - Numeric**{-}\n\nLet's filter to passengers who paid above £200.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select passengers who paid more than 200\n\ntitanic_data |> \n filter(fare > 200) |> \n glimpse()\n```\n:::\n\n\nNotice that we didn't save this as a variable, as this was just an example, one we will not carry forward in our analysis. \n\nHowever, if you are being asked to answer specific questions, then saving the outputs of your manipulation pipelines as variables is very useful, to prevent overwriting the base data.\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Use filter to return the row for the passenger named: 'Birkeland, Mr. Hans Martin Monsen'\n\n2. Filter for passengers that are male and save it as a variable. Can you count how many there were?\n\n3. Filter for passengers that are under 18 years of age and save it as a variable. Can you count how many there were?\n\n4. **Extension - Harder**: What percentage of passengers in the dataset survived? Remember, to compute a percentage, we must multiply the proportion by 100. \n\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Filtering to a specific passenger\n\ntitanic_data |> \n filter(name_of_passenger == \n 'Birkeland, Mr. Hans Martin Monsen') |> \n glimpse()\n```\n:::\n\n\n2. \nTo display the number of males in the filtered data, we simply need the number of rows, the length of the data!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Males only\n\ntitanic_male <- titanic_data |> \n filter(sex_of_passenger == 'male')\n\n# Counting the number of males\n\nnrow(titanic_male)\n```\n:::\n\n\n3. \nTo display the number of passengers below 18 years of age in the filtered data, we simply need the number of rows, the length of the data!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Underage passengers \n\ntitanic_underage <- titanic_data |> \n filter(age_of_passenger < 18)\n\n\n# Counting the number of underage passengers\n\nnrow(titanic_underage)\n```\n:::\n\n\n4. \nFirstly, we need to filter the dataset to those who survived, and the percentage would be calculated as:\n\n> Number of those who survived/Number of passengers as a whole * 100\n\nRemember, we can compute the number who survived and the number of passengers, we just need the number of rows in each subsequent tibble.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Passengers who survived\n\ntitanic_survived <- titanic_data |> \n filter(survived == 1)\n\n# Survival percentage\n\n(nrow(titanic_survived) / nrow(titanic_data)) * 100\n```\n:::\n\nSo we see that, tragically, only 38% of the passengers aboard the titanic survived.\n\n:::\n\n\n### Multiple Conditional Filtering \n\nWe have thus far filtered on conditions for a single column, but there is no reason we can't use multiple conditions to filter by several conditions and/or columns at once. \n\nFor example:\n\n* We want **male** passengers who **survived**.\n* We want **over 18** passengers who embarked from **Southampton**.\n\nHowever, we do need to think about how the conditions relate to each other.\n\n\n### **Relationships between conditions**{-}\n\nThere are two ways we can combine conditions together:\n\n* **AND** relationships are given by the **&** symbol. \n * This implies both/all conditions must be met for a row to evaluate to TRUE before the filter is applied.\n \n* **OR** relationships are given by the **|** symbol. \n * This implies that if any of the conditions can be met (one or more) a given row evaluates to TRUE before the filter is applied.\n\n> This does mean that combinations of TRUE and FALSE conditions can lead to different outputs with AND/OR relationships. This is summarised in the table below.\n\n| Condition 1 | Condition 2 | AND Equates to | OR Equates to |\n|:-----------:|:------------:|:------------------:|:------------------:|\n| True | True | True | True |\n| True | False | False | True |\n| False | True | False | True |\n| False | False | False | False | \n\n\n### Examples\n\nFor our first example, let's filter to first class, female passengers. \n\nThis is an AND relationship, as they must be first class and female. Thus, any row that does not satisfy both of these conditions will be filtered out in the process. \n\nRemember that AND combinations are very strict, so ensure that the loss of a possibly large amount of data is appropriate for your analysis.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to first class female passengers\n\ntitanic_data |> \n filter(pclass == 1 & sex_of_passenger == \"female\") |> \n glimpse()\n```\n:::\n\n\nFor our next example, let's select passengers who were male **OR** adults (over 18). \n\nThis means that males under 18 will be kept and adult females will also be kept, as only one of the conditions needs to be true to be retained by filter!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to males or adults\n\ntitanic_data |> \n filter(sex_of_passenger == \"male\" | age_of_passenger > 18) |> \n glimpse()\n```\n:::\n\n\n\n### Special Cases of AND/OR\n\nWhilst the above conventions are easy to read from left to right, when constructing much more complex chains of conditions, it becomes laborious quickly. \n\nTo alleviate this, dplyr has some special functions that allow us to streamline cases of numerous conditions on the **same** column.\n\n\n### **The between() function**{-}\n\nFirst is the **between()** function, which is similarly to an and relationship for conditions on numeric columns.\n\nIt allows us to specify:\n\n* An upper bound for the value in the column, a.k.a the value for which it should not be larger than or equal to.\n* A lower bound for the value in the column, a.k.a the value for which it should not be smaller than or equal to.\n\n> For example, between(3.5 and 7.5) will retain values greater than or equal to 3.5 and less than or equal to 7.5.\n\nLet's filter to those that paid between £250 and £500 for their tickets.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to those that paid between two values\n\ntitanic_data |> \n filter(between(fare, left = 250, right = 500)) |> \n glimpse()\n```\n:::\n\n\nWhich is equivalent to saying:\n\n> filter(fare >= 250 & fare <= 500)\n\nOf course, we can combine this with other conditions across columns as well. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter tho those that paid between ?250 and ?500 who were female\n\ntitanic_data |> \n filter(between(fare, left = 250, right = 500) & \n sex_of_passenger == \"female\") |> \n glimpse()\n```\n:::\n\n\n\n### **The %in% function**{-}\n\nSecondly is the **%in%** function, which checks for membership of the column value in a vector of options we provide. \n\nThis is similar to an OR relationship, as it allows us to bring through multiple values from a column.\n\nLet's filter to capture those that embarked from Southampton or Cherbourg.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to those that embarked from S or C\n\ntitanic_data |> \n filter(embarked %in% c(\"S\", \"C\")) |> \n glimpse()\n```\n:::\n\n\nWe can check with **distinct()** whether this accomplished what we were looking for.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to those that embarked from S or C and check\n\ntitanic_data |> \n filter(embarked %in% c(\"S\", \"C\")) |> \n distinct(embarked)\n```\n:::\n\n\nThis process would be equivalent to performing:\n\n> filter(embarked == \"S\" | embarked == \"C\") \n\nand is incredibly useful for larger categorical variables we wish to trim. \n\nAs with between(), we can also combine this with other conditions.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select passengers embarking from S or C that were male\n\ntitanic_data |> \n filter(embarked %in% c(\"S\", \"C\") &\n sex_of_passenger == \"male\") |> \n glimpse()\n```\n:::\n\n\n### Negating Conditions\n\nWe can also use the negation operator **!** to reverse the outcome of the condition. \n\nThis is useful for cases where exclusion is quicker than typing out conditions for inclusion. \n\nSay for example you have a categorical variable with 9 unique categories.\n\nYou are interested in filtering so that only 8 of the categories remain. Instead of chaining **OR** conditions together, you can instead write the condition that would return **just** that one, and negate it to remove it instead.\n\n### **Example**{-}\n\nLet's see this in action by negating the statement to select passengers who embarked from Southampton, \n\nThis is the opposite of writing out filters to retain Cherbourg and Queenstown. \nThis is a great time saving measure for larger datasets.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use negation to filter down to passengers embarking from Cherbourg or Queenstown\n\ntitanic_data |> \n filter(!embarked == \"S\") |> \n distinct(embarked)\n```\n:::\n\n\nThis is, of course equivalent to using the not equal **!=** comparison in such a simple case:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter for passengers who did not embark from Southampton\n\ntitanic_data |> \n filter(embarked != \"S\") |> \n distinct(embarked)\n```\n:::\n\n\n### **Example - AND/OR Negation**{-}\n\nOf course, if you negate and **and**/**or** relationships:\n\n* Not only is each individual condition negated\n* The and/or is reversed to or/and respectively\n\nThis comes from logical statements in mathematics, specifically, De Morgan's laws.\n\n{fig-alt=\"Negating a combined statement negates each individual statement, as well as the logical operator combining them.\"}\n\nLet's take an example we we required those that embarked from Southampton or paid above £100 in fare.\n\nMathematically speaking, if we negate this condition, we get:\n\n> **!(southampton OR > 100 fare) = (!southampton AND !>100 fare)**\n\nIt is recommended to wrap your OR/AND condition in brackets, to ensure the negation is carried throughout. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Harder example\n\ntitanic_data |> \n filter(!(embarked == \"S\" | fare > 100)) |> \n distinct(embarked)\n```\n:::\n\n\nWe see that we have indeed negated the selection of Southampton, as expected.\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Filter so that only second or third class passengers are included in the data. \n\n2. Filter so that only passengers who travelled alone are included in the data. How many were there?\n\n\n3. **Extension Exercise** - What percentage of passengers who embarked from Cherbourg or Queenstown and paid a fare between £100 and £350 survived? \n\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter for second or third class passengers\n\ntitanic_data |> \n filter(pclass %in% c(2, 3)) |> \n glimpse()\n```\n:::\n\n\n\n2. \nFor those travelling alone, their sibsp and parch values should be 0.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filtering for passengers travelling alone\n\nlone_passengers <- titanic_data |> \n filter(sibsp == 0 & parch == 0) |> \n glimpse()\n\n# How many there are\n\nnrow(lone_passengers)\n```\n:::\n\n\n3. \nThis is a multi-stage problem, so we must filter for the required conditions (saving it to a variable), then compute the percentage.\n\nSince we need all of these conditions to be TRUE, we must use **&** to combine them.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter for those that embarked from C or Q, paid certain fare and survived\n\ncherb_queens_survivors <- titanic_data |> \n filter(embarked %in% c(\"C\", \"Q\") &\n between(fare, left = 100, right = 350) &\n survived == 1)\n\n# Compute final percentage\n\nround((nrow(cherb_queens_survivors) / nrow(titanic_data)) * 100, digits = 2)\n```\n:::\n\n:::\n\n\n## Mutate\n\nWhen cleaning and transforming data, we often want to apply changes at the column level, such as:\n\n* Converting to lower case/any character work\n* Rounding to a specified number of dp\n* Converting the datatype\n* Combine columns into ratios/proportions - known as **calculated columns **\n\nTo accomplish all of the above, we need our next verb, **mutate()**. To create a new column, we use the following syntax:\n\n> **mutate(new_column_name = contents_of_column)**\n\n\n### Constant Value Variables\n\nThe simplest example would be adding a constant column, which contains the same value all the way down. \n\nWhilst the applications of this are minimal, it is the best first example for understanding mutate.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add a constant character column\n\ntitanic_data |> \n mutate(character_col = \"two\") |> # Column filled with the string \"two\"\n glimpse() \n```\n:::\n\n\nAs another example, let's add a numeric constant column.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add a constant numeric column\n\ntitanic_data |> \n mutate(numeric_col = 3.14) |> # Column of pi\n glimpse()\n```\n:::\n\n\n### Modifying existing variables\n\nThe mutate function is incredibly smart, as it allows us to apply functions to an entire column, with each cell transformed in turn.\n\nFor example, should we wish to make the name of passenger column lower case, we can use the **str_to_lower()** function from **stringr**. \n\nTo apply a function to an existing column:\n\n> **mutate(existing_column = function(existing_column,..))**\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Convert names column to lower case\n\ntitanic_data |> \n mutate(name_of_passenger = str_to_lower(name_of_passenger)) |> \n glimpse()\n```\n:::\n\n \nAnother example might be to round the age column to the nearest whole number, which could allow for conversion to an integer.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round the age column to the nearest whole number\n\ntitanic_data |> \n mutate(age_of_passenger = round(age_of_passenger)) |> \n glimpse()\n```\n:::\n\n\nThis has the unexpected consequence of rounding the passenger with an age of 0.1667 (around 2 months) to 0, which makes no sense given the context. As such, it may be better to round to 2 decimal places.\n\nLet's do the same thing to the fare column as well, since money in GBP (£) is presented as two decimal places.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round the fare column to 2 decimal places\n\ntitanic_data |> \n mutate(fare = round(fare, digits = 2)) |> \n glimpse()\n```\n:::\n\n\nNotice that we have forgotten something, as age still has 4 decimal places.\n\n### **Exercise**{-}\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nIdentify the mistake we have made when converting existing columns and fix this mistake so that we permanently update them.\n\n### **Solution**{-}\n\nWe did not overwrite and reassign the titanic_data variable, we just observed the changes without permanently making them. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round the fare and age columns to 2 decimal places\n\ntitanic_data <- titanic_data |> \n mutate(age_of_passenger = round(age_of_passenger, digits = 2),\n fare = round(fare, digits = 2))\n\nglimpse(titanic_data)\n```\n:::\n\n\n:::\n\nOf course, this does not mean we should be overwriting titanic_data everytime, as often we are just overviewing a transformation and sense checking it.\n\n\n### Calculated Columns\n\nLet's see an example of creating a bespoke column by combining existing ones.\n\nHere we will create the family size of each person. To compute this we need:\n\n* The number of siblings or spouses on board (sibsp)\n* The numbr of parents or children on board (parch)\n* The person themselves, as they aren't factored in to sibsp or parch\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Determining family size per passenger\n\ntitanic_data <- titanic_data |> \n mutate(family_size = sibsp + parch + 1) # Add 1 for the person themselves\n\nglimpse(titanic_data)\n```\n:::\n\n\n### Conditional Columns\n\nWe can also use conditions like when we filtered, to create a logical column of TRUEs and FALSEs. \n\nThese are very common and are often known as **binary flags**, as they denote whether a certain condition is attained or not.\n\nThis is structured as follows:\n\n> **mutate(new_col = (condition))** where the condition is \"column operator value\", such as \"fare < 200\". \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a conditional column on whether passenger is female\n\ntitanic_data <- titanic_data |> \n mutate(is_female = (sex_of_passenger == \"female\"))\n\nglimpse(titanic_data)\n```\n:::\n\n\nUsually we want binary flags in numeric form, as most models we supply our data to require numeric variables. \n\nThis means we need to convert TRUE and FALSE to their numeric representations of 0 and 1.\n\nWe can use complex functions for matching and converting to perform this step. In particular, the **case_match()** function, which takes the following form:\n\n> **case_match(column, value_to_change ~ new_value, value_to_change ~ new_value)**\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Recode is_female to numeric\n\ntitanic_data <- titanic_data |> \n mutate(is_female = case_match(is_female,\n TRUE ~ 1, # Convert instances of TRUE to 1\n FALSE ~ 0)) # Convert instances of FALSE to 0\n\nglimpse(titanic_data)\n```\n:::\n\n\nYou may not have seen this notation before with the tilde **~**, this is known as a **formula** in R, where the right hand side is equivalent to the left hand side.\n\nThis is common convention in R, seen most with linear modelling to define the equation. See this [technical article on the tilde](https://medium.com/anu-perumalsamy/what-does-mean-in-r-18cecd1b223f#:~:text='~(tilde)'%20is%20an%20operator%20that%20splits%20the%20left,the%20set%20of%20feature%20variables.&text=In%20the%20above%20example%2C%20df,the%20columns%20wages%20and%20yearsEd.) for more information.\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nCreate a new column called \"fare_dollars\", which converts the fare from GBP (£) to USD (\\$). The current exchange rate as of January 2024 is:\n\n> **£1 = $1.27**\n\nEnsure that the column is rounded to 2 decimal places.\n\n### **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create fare dollars and rounding the output\n\ntitanic_data <- titanic_data |> \n mutate(fare_dollars = round(fare * 1.39, digits = 2))\n\nglimpse(titanic_data)\n```\n:::\n\n:::\n\n\n## Joining Data\n\nMuch of the information we need to answer questions of interest is featured across multiple smaller datasets, so we can **join** or **merge** them together for one cohesive dataset.\n\nWe do require something essential for this to be possible, however, a **column in common** such as a unique identifier or reference, such as:\n\n* NHS number, allowing for data linkage across the NHS.\n* Any account number allows for data linkage aross financial institutions.\n* Email, phone numbers, social media hangles allow for data linkage across social media and online shopping.\n* Addresses allow for spatial data linkage, for geospatial applications\n\n\n### **Naming Conventions for Join**{-}\n\nThe dplyr package has a family of functions for joins.\n\nThey take the form **type_join** where the prefix \"type\" denotes the type of join itself. \n\nA naming convention we must establish here is that of the tibbles themselves, namely:\n\n* The larger dataset, the one we just to join data to, is the **left tibble**.\n* The smaller dataset, the one we want to join to another, is the **right tibble**.\n\n### Types of Join\n\n* **inner_join** - A stricter join where only data common to both tibbles is retained.\n\n* **full_join** - All data from both tibbles is retained, matched up where possible.\n\n* **left_join** - All data from the left tibble is retained, and only matching rows are merged from the right tibble.\n\n* **right_join** - All data from the right tibble is retained, and only matching rows are merged from the left tibble. This is the inverse process of the left join.\n\nGraphically:\n\n{fig-alt=\"Venn diagrams for each of the prior examples, with the included data shaded.\"}\n\nThere are also Semi Joins and Anti Joins for filtering, which you can read about in Hadley Wickhams [R for Data Science Chapter 19](https://r4ds.hadley.nz/joins.html)\n\n\n### Examples\n\nJoins are best explored using examples of each type.\n\nWe will use 2 very small datasets that come with **dplyr** to build this up.\n\nThe first is band_members, which we must assign to a variable to save in the global environment.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nmembers_data <- band_members\n\nmembers_data\n```\n:::\n\n\nThe second is band instruments, which seems to have some connection to the prior dataset.\n\n\n::: {.cell}\n\n```{.r .cell-code}\ninstruments_data <- band_instruments\n\ninstruments_data\n```\n:::\n\n\nThese data sets have one common column which is **name**, so we can join them to have both band and plays in the same dataset. \n\nLet's assume that members_data is the left dataset and instruments_data is the right.\n\nPre-empting what will happen based on the above venn diagrams:\n\n* John and Paul appear in both datasets, so will be retained for most common joins.\n* Mick only appears in the members_data, so may disappear with stricter joins.\n* Keith only appears in the instruments_data, so may disappear with stricter joins.\n\n\n### **Join Syntax**{-}\n\nThe join functions take numerous arguments, with the following being required:\n\n* x - the left tibble\n* y - the right tibble\n* by - the column to join on\n\nand take the form:\n\n> **type_join(x = left_tibble, y = right_tibble, by = join_col)** where we can pipe in the left_tibble.\n\n\n### **Inner Join**{-}\n\nStarting with the inner join, this will only retain rows common to both datasets, which would see Mick and Keith removed. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Perform an inner join on band members and instruments data.\n\nmembers_data |> \n inner_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\nAs expected, we kept John and Paul, and now have another column of information about them!\n\n### **Full Join**{-}\n \nA full join retains all rows across both datasets, but this raises the question of what happens to the entry in the column that they aren't featured? i.e.\n\n* Mick has no plays entry\n* Keith has no band entry\n\nSimply, they are filled with **NA**, as they are missing.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Perform a full join on instruments and band data\n\nmembers_data |> \n full_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\nWe see that, indeed, Mick has no entry for plays and Keith has no entry in band.\n\n### **Left Join**{-}\n\nA left join retains all rows in the left tibble, and just the matching data in the right. This means Mick will come along with an **NA** in the plays column, but Keith will be lost entirely.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Perform left join on band and instruments data\n\nmembers_data |> \n left_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\n### **Right Join**{-}\n\nA right join is the opposite of a left join, so we will retain all values in the right tibble, including Keith, but only matching data in the left tibble, which means we will lose Mick.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Right join on band and instruments data\n\nmembers_data |> \n right_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\n\n### Matching columns with different names\n\nA very common problem that occurs when joining is matching columns being named differently.\n\nThis can sometimes be easily rectified with a **rename()**, but there will be cases where modifying the data in this way is not allowed. \n\nThis is where the **join_by()** function from dplyr comes in, providing us a way to specify that two differently named columns are indeed the same. \n\n### **Example**{-} \n\nHere we introduce the band_instruments2 data, which is similar to the former but with one key difference.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Instruments data\n\ninstruments2_data <- band_instruments2\n\ninstruments2_data\n```\n:::\n\n\nThe name variable is called \"artist\" here.\n\nWithin join_by(), we must set the column names of note equal to each other, using:\n\n> **join_by(left_col_name == right_col_name)**\n\nLet's join together band_instruments2 with the members data, using the join_by() function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Join columns with names that don't match\n\nmembers_data |> \n full_join(y = band_instruments2,\n by = join_by(name == artist))\n```\n:::\n\n\n\n### Binding Datasets\n\nAnother common way in which datasets are combined is by binding them, where one dataset is appended on top of the other either **row by row** or **column by column**.\n\nWith row binding: \n\n* Columns are matched by name automatically, so the positioning of them does not matter. \n* Missing columns will be filled with NA, so we must be careful of this.\n\nWith column binding:\n\n* Rows are matched by position, so the tibbles we bind absolutely **must** have the same number of rows, otherwise we will get an error.\n\n\n### **Binding Rows**{-}\n\nWe use the **bind_rows()** function from dplyr, which will widen the dataset by adding more entries.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Row bind the instruments tibbles\n\ninstruments_data |> \n bind_rows(instruments2_data)\n```\n:::\n\n\nSince instruments2 has the name variable and instruments has the artist variable, these are seen as independent, and hence filled with NAs since they don't match.\n\n\n### **Binding Columns**{-}\n\nWe use the **bind_cols()** function from dplyr, which will lengthen the dataset by adding more variables. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Column bind instruments 1 and 2\n\ninstruments_data |> \n bind_cols(instruments2_data)\n```\n:::\n\n\nNotice that despite plays being a repeating column, it is binded as we asked, and differentiated by its position, with the second column being \"plays...2\" and the fourth being \"plays...4\".\n\n\n### **Why we bind**{-}\n\nWhen data is collected consistently, it is often in the same form, be that monthly, weekly, annually and so on. \n\nTo create a historic time series, data must be sequentially appended unless separate storage is required. \n\nThis is often part of an automated process where data is ingested and then appended onto the existing, larger, collected dataset. \n\n\n### Union()\n\nAnother very useful function is **union()** which will stack the data vertically, but keep only the distinct (unique) rows. \n\nThis means that any duplicated rows that exist in the current tibble are not brought over in the process.\n\nHowever, this does **NOT** remove duplicated **values**, only entire duplicated rows in the combined data, an important distinction to make. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Band members and instruments\n\ninstruments_data |> \n union(instruments2_data)\n```\n:::\n\n\nYou will see that this causes an error, because Union is very strict about it's combination, in that all columns must match. \n\nLet's create a small tibble with matching columns to test this out.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create new entries for instruments data\n\nartist <- c(\"Mick\", \"Bono\", \"Ringo\", \"John\")\n\nplays <- c(\"guitar\", \"guitar\", \"piano\", \"guitar\")\n\ninstruments3_data <- tibble(artist = artist, plays = plays)\n\ninstruments3_data\n```\n:::\n\n\nNow let's union this instruments2, who's columns match exactly:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Union the instruments datasets\n\ninstruments2_data |> \n union(instruments3_data)\n```\n:::\n\nNotice that John, who would have been duplicated in the combination, was removed as intended by union().\n\n\n# Summary \n\nWe covered alot of content around dplyr here, but the possibilities are nearly endless with this incredible data manipulation library.\n\nBy no means are you meant to remember and recall the above. Instead, what is most important is that you understand the problem you are trying to solve, and can use the resources here (or your own) to then solve it.\n\nNext up, we will look at aggregating data and obtaining summary statistics.\n\n",
- "supporting": [],
+ "engine": "knitr",
+ "markdown": "---\ntitle: \"Chapter 4 - Tibbles and dplyr\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Understand the importance of clean variable names.\n* Be able to clean column names using the janitor package.\n* Understand the use of the pipe operator.\n* Be able to sort data with dplyr's **arrange** verb.\n* Be able to select data with dplyr's **select** verb.\n* Be able to filter data with dplyr's **filter** verb. \n* Be able to transform data with dplyr's **mutate** verb.\n* Be able to join datasets together.\n\n\n# Packages and Data\n\nRemember, the first steps when starting a new script are:\n\n* Load in the packages required for the work.\n* Read in datasets required and assign them to a variable in memory.\n\n## Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Load the following packages:\n\n* Tidyverse\n* janitor\n\n2. Read in the **titanic.csv** file and assign it to the name \"titanic_data\". Remember to assign null values properly (as in Chapter 3) using the \"na\" parameter. \n\n* Remember that you are in your R project, which sets the working directory to be inside the **Course_content** folder. \n\n3. Have a glimpse of your dataset. \n\n\n### **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Load packages\n\nlibrary(tidyverse)\nlibrary(janitor)\n\n\n# Read in titanic.csv and set null values to be specific symbols\n\ntitanic_data <- read_csv(\"Data/titanic.csv\", \n na = c(\"*\", \".\", \"\", \"NULL\"))\n\n# Have a peak\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\n:::\n\n\nAs a reminder, in the titanic dataset our columns are:\n\n* **Pclass**: Passenger’s class, 1 = 1st (Upper), 2 = 2nd(Middle), 3 = 3rd(Lower)\n* **Survived**: Survived (1) or died (0)\n* **Name**: Passenger’s name\n* **Sex**: Passenger’s sex\n* **Age of Passenger**: Passenger’s age\n* **SibSp**: Number of siblings/spouses aboard (excluding the person)\n* **Parch**: Number of parents/children aboard (excluding the person)\n* **Ticket**: Ticket number\n* **Fare**: Fare\n* **Cabin**: Cabin number\n* **Embarked**: Port of embarkation, C = Cherbourg, Q = Queenstown, S = Southampton\n\n\nWe can see more details on the [Data Dictionary](https://www.kaggle.com/c/titanic/data)\n\n\n# Column Names\n\nIn the previous session we stated that every column in a tibble is a variable and it is good practice to not have spaces within variable names, as spaces makes it harder for us to call on the variables when we need to use them.\n\nWhen you enter data in Excel, you most often don’t think too much about what you call each column. After all, you just label them once and as long as they are documented, this isn't given too much thought.\n\nWhen you are working with variables in R though, you need to type the name of each variable, every time you want to work with it. So, it makes sense to make your column names as simple, but meaningful as possible.\n\n## Retuning columns by name\n\nIn base R, to call a column by name and return its contents as a single vector (remember, each column in a tibble is a vector) we use the dollar sign **$** operator.\n\nYou will notice the list of column names will pop up and you can move through them with arrow keys and select the one you want. \n\n### Example\n\nLet's return the column \"Pclass\".\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return Pclass with base R\n\ntitanic_data$Pclass\n```\n:::\n\n\n\n\nThis returns the entire vector (usually up to 1000 entries) so it would be useful to use **glimpse()** or other inspection functions for a sense check.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return Pclass and glimpse\n\nglimpse(titanic_data$Pclass)\n```\n:::\n\n\n\n\nThis could already prove frustrating due to needing to remember the capital letters, particularly if the autocomplete is slowing down.\n\nHowever, it can get worse if spaces are included in the column name.\n\n### Example - Returning column with spaces\n\nLet's take the \"name of Passenger\" column and try to return it without the auto-complete.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntitanic$name Of Passenger\n```\n:::\n\n\n\n\nThis will throw an error as spaces in syntax are not allowed, R cannot process code in this way as a space should usually denote the end of a line of code. \n\nTo get around this we enclose column names with spaces in backticks **\\` \\`** and you will notice that the autocomplete does the same. \n\nThis allows the entire column name to be read as one entity.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting a column with spaces in the names\n\nglimpse(titanic_data$`name Of Passenger`)\n```\n:::\n\n\n\n\nWhilst this works, it is bad practice to use capitalisation and spaces, as it complicates things for us as well as others we collaborate with.\n\n### A word of warning\n\nWhilst this is completely fine in Base R, there are unexpected consequences of using this technique, particularly when making changes to a column using assignment. \n\n* With the tidyverse, when we use its myriad of functions, we can check manipulations on the data without overwriting the underlying variable unless we **explicitly** ask it to do so with **<-**.\n\n* However, with the **$** method, we can overwrite a column for example and this will **implicitly** and permanently change the underlying variable, which we must be careful of.\n\nShould you make a mistake following this choice, you would have to revert back to the original data and read it back in to start from scratch, as recreating data is a nightmare.\n\n### Accessing column names\n\nWe can see the column names by using the \"names()\" function to print a character vector of the column names.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Getting the column names using the names function\n\nnames(titanic_data)\n```\n:::\n\n\n\n\nWe will need to do some work on these to remove the use of capitalisation and spaces. \n\n\n## Cleaning Column Names\n\n### The Janitor Package\n\nThe **janitor** package offers many functions used to manipulate data, such as finding duplicates. In this chapter we will use it to clean column names. \n\nThe function to use is called \"clean_names()\" and automatically formats the column names as **snake_case**, but this can be altered with an additional parameter.\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Clean the column names and overwrite the variable\n\ntitanic_data <- clean_names(titanic_data)\n\n# Getting the column names of the dataset\n\nnames(titanic_data)\n```\n:::\n\n\n\n\n\n# The Data Manipulation Package dplyr \n\nThis is one of the most powerful packages in the **tidyverse**, which makes data manipulation simple and code easy to read.\n\nWe will look at how to perform the following actions:\n\n1. arrange/sort\n2. select\n3. filter\n4. mutate\n5. joining data\n\nwith the aim of the package to provide a function for each basic **verb** of data manipulation. This has led to them being referred to as such in the documentation. \n\nEach of the verbs have the same structure:\n\n> **verb(.data, info,....)**, note the full stop which is syntax to allow us to reference variables from the dataset (enables auto-completion too!)\n\nand the [cheat sheet](https://nyu-cdsc.github.io/learningr/assets/data-transformation.pdf) is incredibly useful for a reference piece. \n\nBefore we jump into the verbs, let's see dplyr's version of renaming columns!\n\n\n## Rename\n\nWe may wish to remain within the tidyverse when cleaning column names (say, Janitor is not available to you), which invites the use of **rename()**.\n\nThis allows you to change column names one at a time using the following syntax:\n\n> **rename(.data, new_name = old_name)**\n\nAs an example, let's rename the age_of_passenger column to simply \"age\". \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Rename the age_of_passenger column to age\n\nrename(.data = titanic_data,\n age = age_of_passenger)\n```\n:::\n\n\n\n\nIf we glimpse the data again:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Take a peak at titanic data\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\nWe see that age has not carried through to the underlying dataset.\n\nThis is an excellent feature of the tidyverse, in that if we do not:\n\n* Directly overwrite the variable \n* Or create a new one using assignment **<-**\n\nthen it just shows us what that process will do, so we can then make the decision on whether it's what we want. \n\n\n### Renaming multiple columns\n\nOne of the best things about dplyr's functions is that the .data argument clues the function in to the columns themselves, which means we can just continually list them, or make changes to them, without wrapping them in a vector **c()**, like many other libraries. \n\nAs an example, let's create a new variable and rename the \"of_passenger\" columns.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Rename of_passenger columns and create a new variable\n\ntitanic_renamed <- rename(.data = titanic_data,\n name = name_of_passenger,\n sex = sex_of_passenger,\n age = age_of_passenger) # Notice autocompletion\n\nglimpse(titanic_renamed)\n```\n:::\n\n\n\n\nWe also didn't need to give them in the order specified either, the function automatically knows what columns we are referring to in the underlying dataset.\n\nThere is much more we can say about the structure of these functions, but we will see this as we proceed through the verbs themselves. \n\n\n## Arrange\n\nOur data is displayed in the same order as the source data.\n\nWe may want to sort our data based on specific columns. \n\nTo do so, we use the verb **arrange()**. \n\n### Example - Single column sort\n\nFrom here, we will only create a new variable or overwrite the existing one when a change we wish to permanently keep is performed. \n\nWe highly encourage you to do the same, as creating multiple new variables you will never use again will clutter up your environment. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort titanic by fare\n\narrange(.data = titanic_data,\n fare)\n```\n:::\n\n\n\n\nWe get a larger output here that does not show us all columns at a glance, so checking that the outcome is what we expect is more difficult.\n\nWe should instead use **glimpse()** to check the output, which needs to be written first in the code. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort by fare and then glimpse\n\nglimpse(arrange(.data = titanic_data,\n fare))\n```\n:::\n\n\n\n\nNotice that by default, arrange() sorted the fare column in **ascending** order.\n\n### **Small Aside - Functions**{-}\n\nNotice that glimpse() is **written first** but **executed last**, since R evaluates functions from the inside out.\n\nAfter all, if glimpse() has no input, we can't see anything at all! \n\nKeep this in mind as it will become very important later.\n\n\n### Example - Desending Order Sort\n\nTo sort a column in descending order, we use the **desc()** function and the column name as its input. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort titanic in descending order \n\nglimpse(arrange(.data = titanic_data,\n desc(fare))) \n```\n:::\n\n\n\n\n### Example - Multi-Column Sort\n\nWe can also sort by multiple columns, but this creates a chain of **dependence**, in that the first column sort is maintained before the second sort is performed. \n\nThis means that the second sort won't change the order from the first sort.\n\n* When this becomes useful is if there are numerous examples of the same value, such as the 0.0000 values in the fare column.\n * Whilst the position of 0.0000 will not change, the values in the adjacent column will be sorted. Some of those paying £0 fare may have been younger than others, after all. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Multi-column sort\n\nglimpse(arrange(.data = titanic_data,\n fare,\n age_of_passenger))\n```\n:::\n\n\n\n\nNotice that we were able to just continually reference columns from the data as if they were arguments to the function, and the verb understands that immediately, just like with rename().\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nSort the titanic data set by age in **descending** order, then fare in **ascending** order. \n\nGlimpse the result.\n\n### **Show Answer**{-}\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Sort by age desc, fare asc\n\nglimpse(arrange(.data = titanic_data,\n desc(age_of_passenger),\n fare))\n```\n:::\n\n\n\n:::\n\n\n## Select\n\nSometimes we will want to work with smaller tibbles that contain just a subset of available columns.\n\nThe **select()** verb is perfect for this, and it takes the arguments:\n\n* The first is our dataset, made even simpler with \".data\"\n* From here we list as many columns by name as we would like to be retained in our selecting process.\n * The order in which we specify them is the order they will be in the smaller tibble.\n\n### Example - Single Column\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting data\n\nglimpse(select(.data = titanic_data, \n name_of_passenger))\n```\n:::\n\n\n\n\nNotice that this has returned a tibble with one column, not the underlying vector itself that **$** would have.\n\n### Example - Multiple Columns\n\nIf we want to select multiple columns, we can continue to list them, separating with commas, as we did with **arrange()**.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting data\n\nglimpse(select(.data = titanic_data,\n name_of_passenger, \n age_of_passenger,\n pclass))\n```\n:::\n\n\n\n\n\n### Example - Columns in a range\n\nWe can select consecutive columns (next to one another) with the syntax we used for indexing in chapter 2, the colon **:** operator.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting from passenger class to the age of passenger in order\n\nglimpse(select(.data = titanic_data,\n pclass:age_of_passenger))\n```\n:::\n\n\n\n\nNotice that we return the columns from pclass to age_of_passenger in the order of the source data. \n\n\n### Selecting with exclusion\n\nUp to this point we have selected with **inclusion**, a.k.a we specify the columns we want to include in our smaller tibble.\n\nThe real power of select comes from it's flexibility, in that we can reduce the amount of code to write by using **exclusion** instead, a.k.a specify the columns we don't want to include.\n\nSay we want to keep 7 of 9 columns, instead of typing out the names of all 7, we can just exclude the 2 we don't want instead. \n\n### **Example**{-}\n\nTo exclude, we use the minus sign operator **-** which signifies \"do not select this\" or \"select, not this\".\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting by excluding columns we don't want\n\nglimpse(select(.data = titanic_data, \n -name_of_passenger, \n -age_of_passenger, \n -pclass))\n```\n:::\n\n\n\n\nThere is an even more streamlined way to do this, by wrapping the columns in a vector with the **c()** function and using one minus sign outside it.\n\nYou can think of this as expanding brackets in mathematics:\n\n> \\-c(col1, col2) = c(\\-col1, \\-col2) = \\-col1, \\-col2\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using a vector for exclusion\n\nglimpse(select(.data = titanic_data, \n -c(name_of_passenger, \n age_of_passenger, \n pclass)))\n```\n:::\n\n\n\n\n\n### Selecting with Index Position\n\nWe can also select the columns using their index position, starting from 1, just like we did with data structures in chapter 2.\n\nLet's select columns 1 to 4, and also column 7.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting sequential and out of sequence columns with index position\n\nglimpse(select(.data = titanic_data, \n 1:4, \n 7))\n```\n:::\n\n\n\n\nExclusion works similarly here with the minus sign.\n\nNote that whilst this may be required in some cases, it is usually better to be **explicit** with the exact column names, if possible. \n\n\n### Select Helper Functions\n\nAs if **select()** wasn't already helpful enough, it even has helper functions that allow us to select on specific patterns, such as a prefix or suffix in a column name. \n\nThey are as follows:\n\n* starts_with(match): Starts with a prefix.\n* ends_with(match): Ends with a suffix.\n* contains(match): Contains a literal string.\n* matches(match): Matches a [regular expression](https://www.regular-expressions.info/quickstart.html).\n* everything(): Selects all variables.\n* last_col(): Selects the last column.\n\n\nThese can be passed instead of column names **and** alongside selected column names as well. \n\n### **Examples**{-}\n\nLet's return columns that start with an \"s\".\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting columns\n\nglimpse(select(.data = titanic_data, \n starts_with(\"s\")))\n```\n:::\n\n\n\n\nAs a second example, let's return everything.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting everything\n\nglimpse(select(.data = titanic_data,\n everything()))\n```\n:::\n\n\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n\n1. Select the second, third and fourth columns from titanic_data, without typing all three.\n\n\n2. Select all columns except \"fare\", \"cabin\" and \"embarked\" from titanic_data. Note that these are consecutive.\n\n\n3. Select just the last column from titanic_data using a helper function.\n\n\n4. Select the columns that end in the suffix \"passenger\" using a helper function.\n\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select second, third and fourth column\n\nglimpse(select(.data = titanic_data, \n survived:sex_of_passenger))\n```\n:::\n\n\n\n\n2. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Using exclusion on a range\n\nglimpse(select(.data = titanic_data, \n -fare:-embarked))\n\n# OR\n\n# glimpse(select(.data = titanic_data,\n# -c(fare, cabin, embarked)))\n\n# OR\n\n# glimpse(select(.data = titanic_data,\n# -fare,\n# -cabin,\n# -embarked))\n```\n:::\n\n\n\n\n3. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting last column only\n\nglimpse(select(.data = titanic_data,\n last_col())) \n```\n:::\n\n\n\n\n\n4.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting on a suffix\n\nglimpse(select(.data = titanic_data,\n ends_with(\"passenger\"))) \n```\n:::\n\n\n\n:::\n\n\n## The Pipe Operator \n\nUp until now, we have run verbs one at a time on our dataset, be it to sort or select columns. \n\nThe real power of the tidyverse comes from the ability to chain these functions together in a sequence for more complex data manipulation tasks. \n\nHowever, out of the box, this becomes laborious quickly due to the nature of functions. \n\n### Returning to Functions - Composition\n\nAs we saw earlier with glimpse(), to apply many functions to a single output, known as **composition** of functions, we must nest them, with the function applied last being written first, and evaluated from the inside to the outside.\n\n### **Example**{-}\n\nFor example, let's take the **sqrt()** and **round()** mathematical functions and apply them together, so that we obtain the square root of a number and hence round it to a specified number of decimal places.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compose mathematical functions\n\nround(sqrt(2))\n```\n:::\n\n\n\n\nNotice that the functions are evaluated in reverse order (from the inside, out) just as you would with writing this mathematically. You would perform the square root operation first, **then** round the result. \n\nShould we wish to use an extra parameter, we need to start thinking about the brackets, as they are the opening and closing doors of a function itself.\n\nThus, the **digits** parameter needs to go inside the round() brackets, not the sqrt() ones.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compose mathematical functions with extra parameters\n\nround(sqrt(2), digits = 2)\n```\n:::\n\n\n\n\nNotice that the input to the function round() was the output from the sqrt() function. \n\n\n### Composition of functions in the tidyverse\n\nThis becomes tricky to comprehend when working with the tidyverse functions, as we are effectively performing actions in sequence, such as selecting the columns we want and **then** sorting the result. \n\nAs such, the output of one function is the input to another:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select passenger columns and fare then arrange by fare\n\nglimpse(arrange(.data = select(.data = titanic_data,\n ends_with(\"passenger\"),\n fare),\n desc(fare)))\n```\n:::\n\n\n\n\nNotice that the input to arrange was the result of a select operation, so we had to keep track of our brackets and ensure that the desc(fare) was placed within arrange(), **not** select().\n\nGoing forward, we will see more verbs that can be applied on top of this, and it becomes difficult to manage. \n\nThis is where the pipe operator comes in.\n\n\n### Introducing the Pipe\n\nThe Pipe Operator makes it possible to chain a sequence of functions starting with the base data as an input to the sequence.\n\nThis removes the need to type the **.data** argument each time. \n\n* Prior to R 4.1, the pipe operator came from a package known as **magrittr**, which would be loaded alongside the tidyverse, and it took the form **%>%**.\n\n* From R 4.1 onwards, the operator comes as standard with base R, as it has become the universal standard for data analysis. It now takes the form **|>**, and this option must be turned on in the Tools --> Global Options tab. \n\n{fig-alt=\"The Code, Editing pane with the native pipe operator tick box.\"}\n\nThe shortcut for this operator is **CTRL + SHIFT + M** and is one you will use alot from here on. \n\n### **Example - Single Value**{-}\n\nLet's return to our square root and rounding functions. Let's apply one, and then both in sequence using our new operator.\n\n* First, we write the value or dataset we wish to apply functions to, it is at the entrance to the \"pipe\" if you will. \n* Then, we write the function we wish to use and any additional parameters we may need. \n* The pipe operator **passes** the input to the function, so we do not need to write it within the brackets.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Our first pipe - with a single value\n\n2 |> sqrt()\n```\n:::\n\n\n\n\nYou can read the pipe operator as **AND THEN**. \n\nIt takes the output of one function AND THEN uses that as the input of the next function, and so on. \n\nThis means that to chain a sequence of functions, we will use the pipe operator again to pipe our output to our next function as its input. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Our first sequence of pipes\n\n2 |> sqrt() |> \n round(digits = 2)\n```\n:::\n\n\n\n\nThis is quite the shift from what we have done so far, but is more readable in plain english: \n\n>**To the value 2, apply the square root function, and then, round that output to 2 decimal places.**\n\nNotice, that following the second pipe, we insert a new line, which automatically moves us in a few spaces. This is optional but is easier to read as a sequence.\n\n\n### Using the Pipe Operator with the tidyverse\n\nWhat was done above was an oversimplification of why the pipe was created, in reality it was created to pipe datasets into functions, as opposed to a single value. \n\nEven in the case of datasets, we do not need to pipe if we are only applying a single function such as glimpse().\n\nIt is when we are performing a chain of steps that the pipe completely simplifies our code, enhacing readability.\n\n\n### **Example**{-}\n\nLet's return to our previous example, where we selected passenger demographics and sorted by fare. \n\n* First, we write the dataset we want to apply this sequence of steps to.\n* AND THEN pipe that into the **select()** function, specifying what columns we wish to retain.\n* AND THEN pipe that output to the **arrange()** function, so that it can be sorted by whatever column(s) we wish.\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Repeat earlier operation with pipes\n\ntitanic_data |> \n select(ends_with(\"passenger\"),\n fare) |> \n arrange(desc(fare))\n```\n:::\n\n\n\n\nThis way, the code is written in the order that it executes, as opposed to the reverse order without the pipe operator. \n\n>**To the titanic dataset, we select columns that end with \"passenger\" as well as the fare column, and then, sort that in descending order of fare paid.**\n\nWe could also pipe the output to a glimpse() for easier sense checking.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Pipeline with glimpse\n\ntitanic_data |> \n select(ends_with(\"passenger\"),\n fare) |> \n arrange(desc(fare)) |> \n glimpse()\n```\n:::\n\n\n\n\n\n### **Variables with tidyverse chains**{-}\n\nNotice that we didn't create a variable in the prior conversion.\n\nThis is because it can cause confusion between the assignment operator **<-** and the pipe operator **|>** if not covered separately. \n\nIn front of the previous sequence, known as a **pipeline**, we would write our variable name and assignment operator, which saves the final output in memory.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Save pipeline as a variable \n\ntitanic_demographics_sort <- titanic_data |> \n select(ends_with(\"passenger\"),\n fare) |> \n arrange(desc(fare))\n\n\ntitanic_demographics_sort |> \n glimpse()\n```\n:::\n\n\n\n\nBe careful not to confuse the meaning of the two operators, this will take some practice to get used to. \n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nSpeaking of pratice, let's try out our new tool!\n\nCreate a pipeline that:\n\n* Selects the first five columns of the data\n* Arranges them in ascending order of age.\n\nAssign this output to a new variable and glimpse it.\n\n\n### **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Selecting and ordering by age with pipes\n\ntitanic_age_sort <- titanic_data |> \n select(pclass:age_of_passenger) |> \n arrange(age_of_passenger)\n\ntitanic_age_sort |> \n glimpse()\n```\n:::\n\n\n\n\n:::\n\n\n## Filter\n\nOften, we are only interested in groups of rows that adhere to a specific condition, such as:\n\n* Passengers that paid over or under a certain fare.\n* Passengers who are in a particular age threshold.\n* Passengers who embarked from a particular port.\n\nand of course, combinations of the above.\n\nThe next verb, **filter()** allows us to subset our rows in this way. To understand this section, we first need to consider conditions.\n\n\n### Conditional Statements\n\nA conditional statement is one that returns **TRUE** or **FALSE** dependent on the outcome. \n\nWe saw examples of these back in Chapter 1, when we were producing logicals with comparisons. For example:\n\n* 4 < 5 is a condition statement that evaluates to TRUE\n* 4 != 4 is a conditional statement that evaluates to FALSE\n\nLogical Operator| Description\n:--------------:|:------------:\n < | Less Than\n <= | Less Than or Equal To\n \\> | Greater Than\n >= | Greater Than or Equal To\n == | Equal To\n != | Not Equal To\n \\| | Or\n & | And\n ! | Not\n any() | Checks if any value in a logical vector are TRUE\n all() | Checks if all values in a logical vector are TRUE\n is.na() | Is the value missing (NA)?\n between() | Is between 2 numbers\n\n\n>**Note: The \"!\" allows us to flip or invert an expression. Basically, if an expression returns c(TRUE, TRUE, FALSE), the inverted expression (place ! in front of it) will return c(FALSE, FALSE, TRUE).**\n\nThese statements can of course be much more complex than comparing two single numbers, we can apply them across columns with dplyr's **filter()** verb! \n\n\n### Single Conditional Filtering\n\nWe will first look at filtering by a single condition, which are constructed as follows:\n\n* We begin with the column to compare with.\n* Next is the logical operator of choice, such as **<**, **>**.\n* Last up is the value to compare each entry in the column to, which generates the set of TRUEs and FALSEs.\n\nThis is generated in the background, and **filter()** will keep only the rows that return **TRUE** from this comparison. \n\n> **For example, to subset down to only second class passengers, we would write: \"pclass == 2\".** \n\n### **Example - Categorical**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to retain only second class passengers\n\nsecond_class <- titanic_data |> \n filter(pclass == 2) |> \n glimpse()\n```\n:::\n\n\n\n\nA quick way to check that the filter has worked is to use base R's **unique()** function on the column. \n\nWe need to use our **$** here to reference columns by name as this is not a tidyverse method.\n\nLet's check the original data first.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return unique values from the original data\n\nunique(titanic_data$pclass)\n```\n:::\n\n\n\n\nWe see that the pclass column has 3 unique levels of 1, 2 and 3.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Return unique values from the filtered data\n\nunique(second_class$pclass)\n```\n:::\n\n\n\n\nWe see that in the filtered data, we have just second class passengers, as expected. \n\n### **Example - Numeric**{-}\n\nLet's filter to passengers who paid above £200.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select passengers who paid more than 200\n\ntitanic_data |> \n filter(fare > 200) |> \n glimpse()\n```\n:::\n\n\n\n\nNotice that we didn't save this as a variable, as this was just an example, one we will not carry forward in our analysis. \n\nHowever, if you are being asked to answer specific questions, then saving the outputs of your manipulation pipelines as variables is very useful, to prevent overwriting the base data.\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Use filter to return the row for the passenger named: 'Birkeland, Mr. Hans Martin Monsen'\n\n2. Filter for passengers that are male and save it as a variable. Can you count how many there were?\n\n3. Filter for passengers that are under 18 years of age and save it as a variable. Can you count how many there were?\n\n4. **Extension - Harder**: What percentage of passengers in the dataset survived? Remember, to compute a percentage, we must multiply the proportion by 100. \n\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filtering to a specific passenger\n\ntitanic_data |> \n filter(name_of_passenger == \n 'Birkeland, Mr. Hans Martin Monsen') |> \n glimpse()\n```\n:::\n\n\n\n\n2. \nTo display the number of males in the filtered data, we simply need the number of rows, the length of the data!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Males only\n\ntitanic_male <- titanic_data |> \n filter(sex_of_passenger == 'male')\n\n# Counting the number of males\n\nnrow(titanic_male)\n```\n:::\n\n\n\n\n3. \nTo display the number of passengers below 18 years of age in the filtered data, we simply need the number of rows, the length of the data!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Underage passengers \n\ntitanic_underage <- titanic_data |> \n filter(age_of_passenger < 18)\n\n\n# Counting the number of underage passengers\n\nnrow(titanic_underage)\n```\n:::\n\n\n\n\n4. \nFirstly, we need to filter the dataset to those who survived, and the percentage would be calculated as:\n\n> Number of those who survived/Number of passengers as a whole * 100\n\nRemember, we can compute the number who survived and the number of passengers, we just need the number of rows in each subsequent tibble.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Passengers who survived\n\ntitanic_survived <- titanic_data |> \n filter(survived == 1)\n\n# Survival percentage\n\n(nrow(titanic_survived) / nrow(titanic_data)) * 100\n```\n:::\n\n\n\nSo we see that, tragically, only 38% of the passengers aboard the titanic survived.\n\n:::\n\n\n### Multiple Conditional Filtering \n\nWe have thus far filtered on conditions for a single column, but there is no reason we can't use multiple conditions to filter by several conditions and/or columns at once. \n\nFor example:\n\n* We want **male** passengers who **survived**.\n* We want **over 18** passengers who embarked from **Southampton**.\n\nHowever, we do need to think about how the conditions relate to each other.\n\n\n### **Relationships between conditions**{-}\n\nThere are two ways we can combine conditions together:\n\n* **AND** relationships are given by the **&** symbol. \n * This implies both/all conditions must be met for a row to evaluate to TRUE before the filter is applied.\n \n* **OR** relationships are given by the **|** symbol. \n * This implies that if any of the conditions can be met (one or more) a given row evaluates to TRUE before the filter is applied.\n\n> This does mean that combinations of TRUE and FALSE conditions can lead to different outputs with AND/OR relationships. This is summarised in the table below.\n\n| Condition 1 | Condition 2 | AND Equates to | OR Equates to |\n|:-----------:|:------------:|:------------------:|:------------------:|\n| True | True | True | True |\n| True | False | False | True |\n| False | True | False | True |\n| False | False | False | False | \n\n\n### Examples\n\nFor our first example, let's filter to first class, female passengers. \n\nThis is an AND relationship, as they must be first class and female. Thus, any row that does not satisfy both of these conditions will be filtered out in the process. \n\nRemember that AND combinations are very strict, so ensure that the loss of a possibly large amount of data is appropriate for your analysis.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to first class female passengers\n\ntitanic_data |> \n filter(pclass == 1 & sex_of_passenger == \"female\") |> \n glimpse()\n```\n:::\n\n\n\n\nFor our next example, let's select passengers who were male **OR** adults (over 18). \n\nThis means that males under 18 will be kept and adult females will also be kept, as only one of the conditions needs to be true to be retained by filter!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to males or adults\n\ntitanic_data |> \n filter(sex_of_passenger == \"male\" | age_of_passenger > 18) |> \n glimpse()\n```\n:::\n\n\n\n\n\n### Special Cases of AND/OR\n\nWhilst the above conventions are easy to read from left to right, when constructing much more complex chains of conditions, it becomes laborious quickly. \n\nTo alleviate this, dplyr has some special functions that allow us to streamline cases of numerous conditions on the **same** column.\n\n\n### **The between() function**{-}\n\nFirst is the **between()** function, which is similarly to an and relationship for conditions on numeric columns.\n\nIt allows us to specify:\n\n* An upper bound for the value in the column, a.k.a the value for which it should not be larger than or equal to.\n* A lower bound for the value in the column, a.k.a the value for which it should not be smaller than or equal to.\n\n> For example, between(3.5 and 7.5) will retain values greater than or equal to 3.5 and less than or equal to 7.5.\n\nLet's filter to those that paid between £250 and £500 for their tickets.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to those that paid between two values\n\ntitanic_data |> \n filter(between(fare, left = 250, right = 500)) |> \n glimpse()\n```\n:::\n\n\n\n\nWhich is equivalent to saying:\n\n> filter(fare >= 250 & fare <= 500)\n\nOf course, we can combine this with other conditions across columns as well. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter tho those that paid between ?250 and ?500 who were female\n\ntitanic_data |> \n filter(between(fare, left = 250, right = 500) & \n sex_of_passenger == \"female\") |> \n glimpse()\n```\n:::\n\n\n\n\n\n### **The %in% function**{-}\n\nSecondly is the **%in%** function, which checks for membership of the column value in a vector of options we provide. \n\nThis is similar to an OR relationship, as it allows us to bring through multiple values from a column.\n\nLet's filter to capture those that embarked from Southampton or Cherbourg.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to those that embarked from S or C\n\ntitanic_data |> \n filter(embarked %in% c(\"S\", \"C\")) |> \n glimpse()\n```\n:::\n\n\n\n\nWe can check with **distinct()** whether this accomplished what we were looking for.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter to those that embarked from S or C and check\n\ntitanic_data |> \n filter(embarked %in% c(\"S\", \"C\")) |> \n distinct(embarked)\n```\n:::\n\n\n\n\nThis process would be equivalent to performing:\n\n> filter(embarked == \"S\" | embarked == \"C\") \n\nand is incredibly useful for larger categorical variables we wish to trim. \n\nAs with between(), we can also combine this with other conditions.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select passengers embarking from S or C that were male\n\ntitanic_data |> \n filter(embarked %in% c(\"S\", \"C\") &\n sex_of_passenger == \"male\") |> \n glimpse()\n```\n:::\n\n\n\n\n### Negating Conditions\n\nWe can also use the negation operator **!** to reverse the outcome of the condition. \n\nThis is useful for cases where exclusion is quicker than typing out conditions for inclusion. \n\nSay for example you have a categorical variable with 9 unique categories.\n\nYou are interested in filtering so that only 8 of the categories remain. Instead of chaining **OR** conditions together, you can instead write the condition that would return **just** that one, and negate it to remove it instead.\n\n### **Example**{-}\n\nLet's see this in action by negating the statement to select passengers who embarked from Southampton, \n\nThis is the opposite of writing out filters to retain Cherbourg and Queenstown. \nThis is a great time saving measure for larger datasets.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use negation to filter down to passengers embarking from Cherbourg or Queenstown\n\ntitanic_data |> \n filter(!embarked == \"S\") |> \n distinct(embarked)\n```\n:::\n\n\n\n\nThis is, of course equivalent to using the not equal **!=** comparison in such a simple case:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter for passengers who did not embark from Southampton\n\ntitanic_data |> \n filter(embarked != \"S\") |> \n distinct(embarked)\n```\n:::\n\n\n\n\n### **Example - AND/OR Negation**{-}\n\nOf course, if you negate and **and**/**or** relationships:\n\n* Not only is each individual condition negated\n* The and/or is reversed to or/and respectively\n\nThis comes from logical statements in mathematics, specifically, De Morgan's laws.\n\n{fig-alt=\"Negating a combined statement negates each individual statement, as well as the logical operator combining them.\"}\n\nLet's take an example we we required those that embarked from Southampton or paid above £100 in fare.\n\nMathematically speaking, if we negate this condition, we get:\n\n> **!(southampton OR > 100 fare) = (!southampton AND !>100 fare)**\n\nIt is recommended to wrap your OR/AND condition in brackets, to ensure the negation is carried throughout. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Harder example\n\ntitanic_data |> \n filter(!(embarked == \"S\" | fare > 100)) |> \n distinct(embarked)\n```\n:::\n\n\n\n\nWe see that we have indeed negated the selection of Southampton, as expected.\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Filter so that only second or third class passengers are included in the data. \n\n2. Filter so that only passengers who travelled alone are included in the data. How many were there?\n\n\n3. **Extension Exercise** - What percentage of passengers who embarked from Cherbourg or Queenstown and paid a fare between £100 and £350 survived? \n\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter for second or third class passengers\n\ntitanic_data |> \n filter(pclass %in% c(2, 3)) |> \n glimpse()\n```\n:::\n\n\n\n\n\n2. \nFor those travelling alone, their sibsp and parch values should be 0.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filtering for passengers travelling alone\n\nlone_passengers <- titanic_data |> \n filter(sibsp == 0 & parch == 0) |> \n glimpse()\n\n# How many there are\n\nnrow(lone_passengers)\n```\n:::\n\n\n\n\n3. \nThis is a multi-stage problem, so we must filter for the required conditions (saving it to a variable), then compute the percentage.\n\nSince we need all of these conditions to be TRUE, we must use **&** to combine them.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Filter for those that embarked from C or Q, paid certain fare and survived\n\ncherb_queens_survivors <- titanic_data |> \n filter(embarked %in% c(\"C\", \"Q\") &\n between(fare, left = 100, right = 350) &\n survived == 1)\n\n# Compute final percentage\n\nround((nrow(cherb_queens_survivors) / nrow(titanic_data)) * 100, digits = 2)\n```\n:::\n\n\n\n:::\n\n\n## Mutate\n\nWhen cleaning and transforming data, we often want to apply changes at the column level, such as:\n\n* Converting to lower case/any character work\n* Rounding to a specified number of dp\n* Converting the datatype\n* Combine columns into ratios/proportions - known as **calculated columns **\n\nTo accomplish all of the above, we need our next verb, **mutate()**. To create a new column, we use the following syntax:\n\n> **mutate(new_column_name = contents_of_column)**\n\n\n### Constant Value Variables\n\nThe simplest example would be adding a constant column, which contains the same value all the way down. \n\nWhilst the applications of this are minimal, it is the best first example for understanding mutate.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add a constant character column\n\ntitanic_data |> \n mutate(character_col = \"two\") |> # Column filled with the string \"two\"\n glimpse() \n```\n:::\n\n\n\n\nAs another example, let's add a numeric constant column.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Add a constant numeric column\n\ntitanic_data |> \n mutate(numeric_col = 3.14) |> # Column of pi\n glimpse()\n```\n:::\n\n\n\n\n### Modifying existing variables\n\nThe mutate function is incredibly smart, as it allows us to apply functions to an entire column, with each cell transformed in turn.\n\nFor example, should we wish to make the name of passenger column lower case, we can use the **str_to_lower()** function from **stringr**. \n\nTo apply a function to an existing column:\n\n> **mutate(existing_column = function(existing_column,..))**\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Convert names column to lower case\n\ntitanic_data |> \n mutate(name_of_passenger = str_to_lower(name_of_passenger)) |> \n glimpse()\n```\n:::\n\n\n\n \nAnother example might be to round the age column to the nearest whole number, which could allow for conversion to an integer.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round the age column to the nearest whole number\n\ntitanic_data |> \n mutate(age_of_passenger = round(age_of_passenger)) |> \n glimpse()\n```\n:::\n\n\n\n\nThis has the unexpected consequence of rounding the passenger with an age of 0.1667 (around 2 months) to 0, which makes no sense given the context. As such, it may be better to round to 2 decimal places.\n\nLet's do the same thing to the fare column as well, since money in GBP (£) is presented as two decimal places.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round the fare column to 2 decimal places\n\ntitanic_data |> \n mutate(fare = round(fare, digits = 2)) |> \n glimpse()\n```\n:::\n\n\n\n\nNotice that we have forgotten something, as age still has 4 decimal places.\n\n### **Exercise**{-}\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nIdentify the mistake we have made when converting existing columns and fix this mistake so that we permanently update them.\n\n### **Solution**{-}\n\nWe did not overwrite and reassign the titanic_data variable, we just observed the changes without permanently making them. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Round the fare and age columns to 2 decimal places\n\ntitanic_data <- titanic_data |> \n mutate(age_of_passenger = round(age_of_passenger, digits = 2),\n fare = round(fare, digits = 2))\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\n:::\n\nOf course, this does not mean we should be overwriting titanic_data everytime, as often we are just overviewing a transformation and sense checking it.\n\n\n### Calculated Columns\n\nLet's see an example of creating a bespoke column by combining existing ones.\n\nHere we will create the family size of each person. To compute this we need:\n\n* The number of siblings or spouses on board (sibsp)\n* The numbr of parents or children on board (parch)\n* The person themselves, as they aren't factored in to sibsp or parch\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Determining family size per passenger\n\ntitanic_data <- titanic_data |> \n mutate(family_size = sibsp + parch + 1) # Add 1 for the person themselves\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\n### Conditional Columns\n\nWe can also use conditions like when we filtered, to create a logical column of TRUEs and FALSEs. \n\nThese are very common and are often known as **binary flags**, as they denote whether a certain condition is attained or not.\n\nThis is structured as follows:\n\n> **mutate(new_col = (condition))** where the condition is \"column operator value\", such as \"fare < 200\". \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a conditional column on whether passenger is female\n\ntitanic_data <- titanic_data |> \n mutate(is_female = (sex_of_passenger == \"female\"))\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\nUsually we want binary flags in numeric form, as most models we supply our data to require numeric variables. \n\nThis means we need to convert TRUE and FALSE to their numeric representations of 0 and 1.\n\nWe can use complex functions for matching and converting to perform this step. In particular, the **case_match()** function, which takes the following form:\n\n> **case_match(column, value_to_change ~ new_value, value_to_change ~ new_value)**\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Recode is_female to numeric\n\ntitanic_data <- titanic_data |> \n mutate(is_female = case_match(is_female,\n TRUE ~ 1, # Convert instances of TRUE to 1\n FALSE ~ 0)) # Convert instances of FALSE to 0\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\nYou may not have seen this notation before with the tilde **~**, this is known as a **formula** in R, where the right hand side is equivalent to the left hand side.\n\nThis is common convention in R, seen most with linear modelling to define the equation. See this [technical article on the tilde](https://medium.com/anu-perumalsamy/what-does-mean-in-r-18cecd1b223f#:~:text='~(tilde)'%20is%20an%20operator%20that%20splits%20the%20left,the%20set%20of%20feature%20variables.&text=In%20the%20above%20example%2C%20df,the%20columns%20wages%20and%20yearsEd.) for more information.\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\nCreate a new column called \"fare_dollars\", which converts the fare from GBP (£) to USD (\\$). The current exchange rate as of January 2024 is:\n\n> **£1 = $1.27**\n\nEnsure that the column is rounded to 2 decimal places.\n\n### **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create fare dollars and rounding the output\n\ntitanic_data <- titanic_data |> \n mutate(fare_dollars = round(fare * 1.39, digits = 2))\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n:::\n\n\n## Joining Data\n\nMuch of the information we need to answer questions of interest is featured across multiple smaller datasets, so we can **join** or **merge** them together for one cohesive dataset.\n\nWe do require something essential for this to be possible, however, a **column in common** such as a unique identifier or reference, such as:\n\n* NHS number, allowing for data linkage across the NHS.\n* Any account number allows for data linkage aross financial institutions.\n* Email, phone numbers, social media hangles allow for data linkage across social media and online shopping.\n* Addresses allow for spatial data linkage, for geospatial applications\n\n\n### **Naming Conventions for Join**{-}\n\nThe dplyr package has a family of functions for joins.\n\nThey take the form **type_join** where the prefix \"type\" denotes the type of join itself. \n\nA naming convention we must establish here is that of the tibbles themselves, namely:\n\n* The larger dataset, the one we just to join data to, is the **left tibble**.\n* The smaller dataset, the one we want to join to another, is the **right tibble**.\n\n### Types of Join\n\n* **inner_join** - A stricter join where only data common to both tibbles is retained.\n\n* **full_join** - All data from both tibbles is retained, matched up where possible.\n\n* **left_join** - All data from the left tibble is retained, and only matching rows are merged from the right tibble.\n\n* **right_join** - All data from the right tibble is retained, and only matching rows are merged from the left tibble. This is the inverse process of the left join.\n\nGraphically:\n\n{fig-alt=\"Venn diagrams for each of the prior examples, with the included data shaded.\"}\n\nThere are also Semi Joins and Anti Joins for filtering, which you can read about in Hadley Wickhams [R for Data Science Chapter 19](https://r4ds.hadley.nz/joins.html)\n\n\n### Examples\n\nJoins are best explored using examples of each type.\n\nWe will use 2 very small datasets that come with **dplyr** to build this up.\n\nThe first is band_members, which we must assign to a variable to save in the global environment.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nmembers_data <- band_members\n\nmembers_data\n```\n:::\n\n\n\n\nThe second is band instruments, which seems to have some connection to the prior dataset.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ninstruments_data <- band_instruments\n\ninstruments_data\n```\n:::\n\n\n\n\nThese data sets have one common column which is **name**, so we can join them to have both band and plays in the same dataset. \n\nLet's assume that members_data is the left dataset and instruments_data is the right.\n\nPre-empting what will happen based on the above venn diagrams:\n\n* John and Paul appear in both datasets, so will be retained for most common joins.\n* Mick only appears in the members_data, so may disappear with stricter joins.\n* Keith only appears in the instruments_data, so may disappear with stricter joins.\n\n\n### **Join Syntax**{-}\n\nThe join functions take numerous arguments, with the following being required:\n\n* x - the left tibble\n* y - the right tibble\n* by - the column to join on\n\nand take the form:\n\n> **type_join(x = left_tibble, y = right_tibble, by = join_col)** where we can pipe in the left_tibble.\n\n\n### **Inner Join**{-}\n\nStarting with the inner join, this will only retain rows common to both datasets, which would see Mick and Keith removed. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Perform an inner join on band members and instruments data.\n\nmembers_data |> \n inner_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\n\n\nAs expected, we kept John and Paul, and now have another column of information about them!\n\n### **Full Join**{-}\n \nA full join retains all rows across both datasets, but this raises the question of what happens to the entry in the column that they aren't featured? i.e.\n\n* Mick has no plays entry\n* Keith has no band entry\n\nSimply, they are filled with **NA**, as they are missing.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Perform a full join on instruments and band data\n\nmembers_data |> \n full_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\n\n\nWe see that, indeed, Mick has no entry for plays and Keith has no entry in band.\n\n### **Left Join**{-}\n\nA left join retains all rows in the left tibble, and just the matching data in the right. This means Mick will come along with an **NA** in the plays column, but Keith will be lost entirely.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Perform left join on band and instruments data\n\nmembers_data |> \n left_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\n\n\n### **Right Join**{-}\n\nA right join is the opposite of a left join, so we will retain all values in the right tibble, including Keith, but only matching data in the left tibble, which means we will lose Mick.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Right join on band and instruments data\n\nmembers_data |> \n right_join(y = instruments_data,\n by = \"name\")\n```\n:::\n\n\n\n\n\n### Matching columns with different names\n\nA very common problem that occurs when joining is matching columns being named differently.\n\nThis can sometimes be easily rectified with a **rename()**, but there will be cases where modifying the data in this way is not allowed. \n\nThis is where the **join_by()** function from dplyr comes in, providing us a way to specify that two differently named columns are indeed the same. \n\n### **Example**{-} \n\nHere we introduce the band_instruments2 data, which is similar to the former but with one key difference.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Instruments data\n\ninstruments2_data <- band_instruments2\n\ninstruments2_data\n```\n:::\n\n\n\n\nThe name variable is called \"artist\" here.\n\nWithin join_by(), we must set the column names of note equal to each other, using:\n\n> **join_by(left_col_name == right_col_name)**\n\nLet's join together band_instruments2 with the members data, using the join_by() function.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Join columns with names that don't match\n\nmembers_data |> \n full_join(y = band_instruments2,\n by = join_by(name == artist))\n```\n:::\n\n\n\n\n\n### Binding Datasets\n\nAnother common way in which datasets are combined is by binding them, where one dataset is appended on top of the other either **row by row** or **column by column**.\n\nWith row binding: \n\n* Columns are matched by name automatically, so the positioning of them does not matter. \n* Missing columns will be filled with NA, so we must be careful of this.\n\nWith column binding:\n\n* Rows are matched by position, so the tibbles we bind absolutely **must** have the same number of rows, otherwise we will get an error.\n\n\n### **Binding Rows**{-}\n\nWe use the **bind_rows()** function from dplyr, which will widen the dataset by adding more entries.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Row bind the instruments tibbles\n\ninstruments_data |> \n bind_rows(instruments2_data)\n```\n:::\n\n\n\n\nSince instruments2 has the name variable and instruments has the artist variable, these are seen as independent, and hence filled with NAs since they don't match.\n\n\n### **Binding Columns**{-}\n\nWe use the **bind_cols()** function from dplyr, which will lengthen the dataset by adding more variables. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Column bind instruments 1 and 2\n\ninstruments_data |> \n bind_cols(instruments2_data)\n```\n:::\n\n\n\n\nNotice that despite plays being a repeating column, it is binded as we asked, and differentiated by its position, with the second column being \"plays...2\" and the fourth being \"plays...4\".\n\n\n### **Why we bind**{-}\n\nWhen data is collected consistently, it is often in the same form, be that monthly, weekly, annually and so on. \n\nTo create a historic time series, data must be sequentially appended unless separate storage is required. \n\nThis is often part of an automated process where data is ingested and then appended onto the existing, larger, collected dataset. \n\n\n### Union()\n\nAnother very useful function is **union()** which will stack the data vertically, but keep only the distinct (unique) rows. \n\nThis means that any duplicated rows that exist in the current tibble are not brought over in the process.\n\nHowever, this does **NOT** remove duplicated **values**, only entire duplicated rows in the combined data, an important distinction to make. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Band members and instruments\n\ninstruments_data |> \n union(instruments2_data)\n```\n:::\n\n\n\n\nYou will see that this causes an error, because Union is very strict about it's combination, in that all columns must match. \n\nLet's create a small tibble with matching columns to test this out.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create new entries for instruments data\n\nartist <- c(\"Mick\", \"Bono\", \"Ringo\", \"John\")\n\nplays <- c(\"guitar\", \"guitar\", \"piano\", \"guitar\")\n\ninstruments3_data <- tibble(artist = artist, plays = plays)\n\ninstruments3_data\n```\n:::\n\n\n\n\nNow let's union this instruments2, who's columns match exactly:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Union the instruments datasets\n\ninstruments2_data |> \n union(instruments3_data)\n```\n:::\n\n\n\nNotice that John, who would have been duplicated in the combination, was removed as intended by union().\n\n\n# Summary \n\nWe covered alot of content around dplyr here, but the possibilities are nearly endless with this incredible data manipulation library.\n\nBy no means are you meant to remember and recall the above. Instead, what is most important is that you understand the problem you are trying to solve, and can use the resources here (or your own) to then solve it.\n\nNext up, we will look at aggregating data and obtaining summary statistics.\n\n",
+ "supporting": [
+ "CH4_tibbles_dplyr_files"
+ ],
"filters": [
"rmarkdown/pagebreak.lua"
],
diff --git a/_freeze/CH5_summary_agg/execute-results/html.json b/_freeze/CH5_summary_agg/execute-results/html.json
index 17cc3f0..0c78709 100644
--- a/_freeze/CH5_summary_agg/execute-results/html.json
+++ b/_freeze/CH5_summary_agg/execute-results/html.json
@@ -1,8 +1,11 @@
{
- "hash": "901519ab0ed5215d206a9f25ce31df6b",
+ "hash": "3b6543e5b4f45e1f84ad0074d0811ca0",
"result": {
- "markdown": "---\ntitle: \"Chapter 5: Summaries and Aggregation\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Describe numeric and categorical data using statistics such as:\n * Mean\n * Median\n * Standard Deviation\n * Variance\n\n* Aggregate data\n\n\n# Packages and Data \n\nWe will use the titanic dataset and clean its column names with janitor.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Load in packages\n\nlibrary(tidyverse)\nlibrary(janitor)\n\n# Prepare the dataset\n\ntitanic_data <- read_csv(\"Data/titanic.csv\", \n na = c(\"*\", \".\", \"\", \"NULL\"))\n\ntitanic_data <- clean_names(titanic_data)\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n# Descriptive Statistics\n\nThere are two broad types of data in our tibble:\n\n* Numerical data (i.e. ints and doubles) \n* Text data (i.e. character strings)\n\n\n## Numerical Data\n\nThe **summarise()** verb allows us to create one or more numeric variables summarising the variables we specify. \n\nThere are many summary statistics functions we can use with summarise(): \n\n* **mean()** - The average (arithmetic mean) data value in the given column.\n* **median()** - The middle value of an ordered vector of values.\n * If the vector has an odd number of values, it is the exact middle value.\n * If the vector has an even number of values, there is no middle, so the median is the average of the numbers either side (e.g. if there are 80 values, the median is the average of the 39th and 40th value).\n* **var()** - The variance measures the degree of spread of each point from the mean. It is the square of the standard deviation.\n* **sd()** - The standard deviation (spread) of values in from the mean. It is the square root of the variance. \n* **quantile()** - Produces sample quantiles corresponding to the given proportions (between 0 and 1). We can compute upper and lower quartiles with this.\n* **min()** - The smallest value in the given column.\n* **max()** - The maximum value in the given column.\n* **n()** - Counts the number of entries (rows).\n* **n_distinct()** - Counts the number of unique entries for a given variable.\n\n\n### **Examples**{-}\n\nLet's compute the mean fare paid by passengers on the titanic. \n\nThe **summarise()** verb takes the following form:\n\n> **summarise(agg_col_name = summary_function(col))** notice that we can name the column as well!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare paid \n\ntitanic_data |> \n summarise(mean(fare)) # Compute mean of fare column\n```\n:::\n\n\n>**This highlights something very important, that any operation applied to a column containing one or more missing values, produces an average of NA.** \n\nThis is because we are adding something that is Not a Number (it does not exist) to an actual number, which is not defined (think dividing by 0 or adding infinity).\n\nBy default, this will throw most of the summary functions, but there is an optional parameter we can turn on, called \"**na.rm = TRUE**\".\n\nThis will omit any NA values in our calculation and produce a more meaningful result, albeit on a subset of observed data.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare paid by passengers, removing NAs\n\ntitanic_data |> \n summarise(mean(fare, na.rm = TRUE))\n```\n:::\n\n\nTo assign this a meaningful column name, we'd pass a keyword argument before the summary function used:\n\n>**agg_col_name = summary_function(column, na.rm = TRUE)**\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare paid and naming it\n\ntitanic_data |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\n\nIf we didn't care about the tibble output summarise generates, we could simply compute using base R syntax:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare with base R\n\nmean(titanic_data$fare, na.rm = TRUE)\n```\n:::\n\n\nLike we saw with mutate() and other functions, we can compute multiple statistics through **summarise()**, separating with commas.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating multiple summary statistics with summarise()\n\ntitanic_data |> \n summarise(median_fare = median(fare, na.rm = TRUE),\n mean_fare = mean(fare, na.rm = TRUE),\n sd_fare = sd(fare, na.rm = TRUE),\n median_age = median(age_of_passenger, na.rm = TRUE), \n mean_age = mean(age_of_passenger, na.rm = TRUE), \n sd_age = sd(age_of_passenger, na.rm = TRUE))\n```\n:::\n\n\n### Quantiles\n\nWe can also calculate quantiles, such as the upper and lower quartile within summarise(). \n\nTo do this, we must specify a value between 0 and 1, which denotes the nth percentile/quantile. For example:\n\n* 0.1 denotes the 10th percentile - All values in order up to the value at the 10% spot.\n* 0.25 denotes the lower quartile - All values in order up to the value at the 25% spot.\n* 0.75 denotes the upper quartile - All values in order up to the value at the 75% spot.\n\n### **Examples**{-}\n\nThe quantile function is structured as:\n\n> **quantile(col, probs = c(0,1),..)** where probs should be the value of the quantile you want.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Computing the lower quartile\n\ntitanic_data |> \n summarise(fare_lower = quantile(fare, probs = 0.25, na.rm = TRUE))\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Computing the upper quartile\n\ntitanic_data |> \n summarise(fare_upper = quantile(fare, probs = 0.75, na.rm = TRUE))\n```\n:::\n\n\n\n## Categorical Data \n\nSimple statistics on qualitative data include:\n\n* **distinct()** - Displays the unique values in a given column. \n\n* **count()** - Displays the number of occurrences of each unique entry in a given column.\n\nThese (of course) will not work well on columns that are almost entirely unique, such as the name of passenger!\n\n\n### **Examples**{-}\n\nLet's start with **count()**, which we can sort with the extra parameter **sort = TRUE** for a descending order output. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating frequency of each unique passenger name\n\ntitanic_data |> \n count(name_of_passenger, sort = TRUE)\n```\n:::\n\n\nCompared this to a categorical variable with only a few unique categories, like embarked. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the number of passengers embarked from each port\n\ntitanic_data |> \n count(embarked, sort = TRUE)\n```\n:::\n\n\nLet's see distinct() in action:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select only unique/distinct rows from the embarked column\n \ntitanic_data |> \n distinct(embarked)\n```\n:::\n\n\n\n## Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Use summarise() to return the ages of the oldest and youngest passengers on the titanic.\n\n2. Use a summary function for categorical data to determine the number of men and women in the dataset.\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the oldest and youngest\n\ntitanic_data |> \n summarise(youngest_age = min(age_of_passenger, na.rm = TRUE),\n oldest_age = max(age_of_passenger, na.rm = TRUE))\n```\n:::\n\n\n2. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the count of men and women on the titanic\n\ntitanic_data |> \n count(sex_of_passenger)\n```\n:::\n\n\nWe see that there were almost twice as many men as there were women on the titanic. \n\n:::\n\n# Aggregation\n\nAggregation means grouping data together by a particular grouping variable and producing a summary of one or more columns for that grouping variable.\n\nFor example, we might want to see the average fare paid **by** sex or **by** port embarked from. \n\nThe **group_by()** function from dplyr is the bread and butter of this section.\n\n## Group By\n\nGroup by performs the aggregation necessary so that we can use summarise() from before to obtain numeric summaries by group. \n\nIt is formed on a principle known as **split - summarise - combine**\n\n* Split - The tibble is divided into a set of smaller tibbles, based on the grouping variable.\n For example, if we use a variable with 3 unique categories, 3 smaller tibbles are created.\n\n* Summarise - An aggregate statistic is applied to each of the groups (such as the mean of their fare paid) and a single row for each group is output.\n\n* Combine - The individual outputs from aggregation are combined into a new tibble.\n\n\n### Example\n\nLet's look at this in code by finding the mean fare for each passenger class.\n\nThe sequence of code will go as follows:\n\n> **group_by(col) |> summarise(agg_col = summary_function(col))**\n\nFirstly, let's check how many classes there are:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# How many pclasses are there?\n\ntitanic_data |>\n distinct(pclass)\n```\n:::\n\n\nSo we should expect three values, one mean fare for each of the passenger classes. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculate mean fare by passenger class\n\ntitanic_data |> \n group_by(pclass) |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\n### The similarity of count() and group_by()\n\nAn interesting point to make is that we can use the n() summary statistic to count the number of observations in that group after a group_by.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by and count the number of unique groups\n\ntitanic_data |> \n group_by(pclass) |> \n summarise(n = n())\n```\n:::\n\n\nThis looks similar to the output of another function we used!\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Replicate the above result with a different function\n\ntitanic_data |> \n count(pclass)\n```\n:::\n\n\nit is the case the count() is performing the exact same computations in the background as the combination of group_by() and summarise()! \n\nA great shortcut if a count is all you need. \n\n## Multiple Aggregation\n\nWe can also double aggregate with more complex groupings. For example, we may require the mean fare paid by first class passengers leaving from Southhampton.\n\nWe would need to group by both passenger class and embarked to achieve this. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by pclass and embarked and find mean fare\n\ntitanic_data |> \n group_by(pclass, embarked) |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\nWe see that since there are 3 passenger classes and 4 (with the null value) embarked entries, there are 3 * 4 = 12 possible combinations, with 10 outputting here (there are no second or third class null values).\n\nOrder does not matter here as it just determines what the final groupings look like, we will still get the same 12 each time.\n\nThe output itself will of course differ as it displays the groups in the order we grouped them:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by embarked and pclass and find mean fare\n\ntitanic_data |> \n group_by(embarked, pclass) |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. What is the average fare paid by men and women?\n\n\n2. What is the median fare paid by men and women in each passenger class?\n\n\n### **Show Answer**{-}\n\n1. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the average fare by sex\n\ntitanic_data |> \n group_by(sex_of_passenger) |> \n summarise(mean_fare = mean(fare,\n na.rm = TRUE))\n```\n:::\n\n\n2. \n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the median fare by sex and passenger class\n\ntitanic_data |> \n group_by(sex_of_passenger, pclass) |> \n summarise(median_fare = median(fare,\n na.rm = TRUE))\n```\n:::\n\n:::\n\n\n## The impact of NAs\n\nIdeally, we don't want the null values being a category of their own and cluttering up our summary tables.\n\nWhen investigating data, we either:\n\n* Deal with these at read in.\n* Meticulously clean them with imputation methods (fill them in).\n* Drop them entirely (be very careful with this!).\n\n**tidyr** comes to the rescue when we are dealing with NAs as it has some handy functions to work with them:\n\n* drop_na() removes all rows with missing values present.\n* replace_na() fills in the missing values with whatever we specify. \n\nLet's see a few small examples of this in practice.\n\n### Filling missing values\n\nWe should always attempt to understand why values are missing before dealing with them. \n\nDomain expertise comes into play when deciding whether it makes sense for a value to be missing, think of temperature:\n\n> **A missing temperature reading is not the same as a temperature reading of 0 degrees celsius.**\n \nAs such, it wouldn't make sense to fill the NAs with 0, as we create **bias** by over inflating the number of 0 temperature values.\n\nA better approach in cases such as this is to fill with an **average**, preferably one not impacted by outliers, such as the median.\n\n### **Example**{-}\n\nLet's consider first which numeric variables have missing values. We can check this by using the **is.na()** function.\n\nThis returns a vector of TRUEs and FALSEs, one for each cell in the table, for whether they are missing or not. \n\nWe can then sum() these up to find the total number of missing values in that column. \n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compute number of missing values in age_of_passenger\n\ntitanic_data$age_of_passenger |> \n is.na() |> \n sum()\n```\n:::\n\n\nRepeating this for each column becomes laborious quickly, so there are some options for us:\n\n* Use **colSums()** to sum the outputs of a function across columns.\n* Create a **User defined function** or **Anonymous Function** to apply across the columns of the dataset using functional programming in purrr.\n\nWhilst the latter is recommended, it is beyond the scope of this current chapter, and features in later more advanced courses. \n\nLet's try colSums():\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use colSums() to find the missing values\n\ntitanic_data |> is.na() |> \n colSums()\n```\n:::\n\n\nNow that we have understood the number of missing values, let's see some imputation.\n\n### **Filling a numeric column with an average**{-}\n\nWe know that age_of_passenger has 267 missing values, but filling these in with 0 makes no sense and will skew the data.\n\nA better approach would be to impute with an average, that way we maximise our attempt to keep the data centralised. \n\nHowever, we must also be careful which statistic we use, as some are more robust than others:\n\n* The mean is heavily influenced by outliers (as it includes them in the calculation).\n* The median is a more robust measure as it does not consider the end points of the data (not influenced by outliers).\n \n#### **Example**{-}\n\nThe replace_na() functions takes a few arguments:\n\n* The data itself\n* replace - What to fill the NAs with\n\nUsing this effectively requires us to also use **mutate()** as this modifies an existing column, as opposed to us using base R functionality to refer to columns with **$**.\n\nLet's use is.na() and colSums() to check it worked:\n \n\n::: {.cell}\n\n```{.r .cell-code}\n# Impute missing age values with median \n\ntitanic_data <- titanic_data |> # overwrite to save changes\n mutate(age_of_passenger = replace_na(age_of_passenger,\n replace = median(age_of_passenger,\n na.rm = TRUE)))\n```\n:::\n\n\nLet's check this worked:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check imputation\n\ntitanic_data |> is.na() |> \n colSums()\n```\n:::\n\n\n\n### **Filling a categorical column with an average**{-}\n\nWith categorical columns, the most robust method we can use to impute is using the most frequently occuring value, or the **mode**. \n\nThere is no built in function for this in base R, requiring an outside package in order to so. However, we can observe the mode with the output from count().\n\n#### **Example**{-}\n\nWe saw that embarked had 2 missing values, let's fill them with the mode.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find the mode of the embarked column\n\ntitanic_data |> \n count(embarked)\n```\n:::\n\n\nWe see that \"S\" or \"Southhampton\" was the most commonly departed from port among passengers.\n\nLet's fill this in with replace_na():\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Fill embarked in with the mode\n\ntitanic_data <- titanic_data |> \n mutate(embarked = replace_na(embarked, replace = \"S\")) \n```\n:::\n\n\nLet's check again:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check that embarked impute worked\n\ntitanic_data |> is.na() |> \n colSums()\n```\n:::\n\n\nImputation is a very deep topic and goes beyond the scope of the course, but we recommend researching this for other examples.\n\n\n### Dropping Missing Values\n\nWe must be very careful about doing this, as we previously noted that there may be a pattern to how or why they are missing, and as such can be treated.\n\nWe risk lowering variance across our dataset by removing them, but if analysis determines that there is no easy way to impute them, dropping them might be the only option.\n\n### **Example**{-}\n\nWe use the drop_na() function to drop null values remaining. \n\n* In our example, cabin is roughly 75% missing, and with a variety of categories of all different forms, imputation would be a nightmare. \n * As such, we would elect to exclude this column with **select()**.\n\n* Similarly, there is only one missing fare value, which it is more efficient to drop than fill with an average.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Drop the null values in fare\n\ntitanic_data <- titanic_data |> \n select(-cabin) |> \n drop_na(fare)\n```\n:::\n\n\n\n\n# Summary \n\nWell done for working your way through this whistle stop tour of aggregation and summary statistics!\n\nThis is the final compulsory chapter of the course, and as such your next steps are up to you, some recommendations we would make are:\n\n* Complete the additional chapter, chapter 6, which is a case study that tests the skills you've learnt in this course on a new dataset. \n\n* Complete the Additional Chapter, chapter 7, that covers more advanced concepts, such as:\n * Pivoting data\n * Binning numeric columns to categorical columns.\n * Functional programming tools with purrr.\n * Extra list functionality.\n\n* Complete any of the R courses that this course is a pre-requisite for on the [Learning Hub](https://learninghub.ons.gov.uk/local/catalogue/index.php), such as:\n * [Data Visualization in R](https://learninghub.ons.gov.uk/course/view.php?id=553)\n * [Statistics in R](https://learninghub.ons.gov.uk/course/view.php?id=560)\n * [Modular Programming in Python and R](https://learninghub.ons.gov.uk/course/view.php?id=574)",
- "supporting": [],
+ "engine": "knitr",
+ "markdown": "---\ntitle: \"Chapter 5: Summaries and Aggregation\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Learning Objectives\n\n* Describe numeric and categorical data using statistics such as:\n * Mean\n * Median\n * Standard Deviation\n * Variance\n\n* Aggregate data\n\n\n# Packages and Data \n\nWe will use the titanic dataset and clean its column names with janitor.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Load in packages\n\nlibrary(tidyverse)\nlibrary(janitor)\n\n# Prepare the dataset\n\ntitanic_data <- read_csv(\"Data/titanic.csv\", \n na = c(\"*\", \".\", \"\", \"NULL\"))\n\ntitanic_data <- clean_names(titanic_data)\n\nglimpse(titanic_data)\n```\n:::\n\n\n\n\n\n# Descriptive Statistics\n\nThere are two broad types of data in our tibble:\n\n* Numerical data (i.e. ints and doubles) \n* Text data (i.e. character strings)\n\n\n## Numerical Data\n\nThe **summarise()** verb allows us to create one or more numeric variables summarising the variables we specify. \n\nThere are many summary statistics functions we can use with summarise(): \n\n* **mean()** - The average (arithmetic mean) data value in the given column.\n* **median()** - The middle value of an ordered vector of values.\n * If the vector has an odd number of values, it is the exact middle value.\n * If the vector has an even number of values, there is no middle, so the median is the average of the numbers either side (e.g. if there are 80 values, the median is the average of the 39th and 40th value).\n* **var()** - The variance measures the degree of spread of each point from the mean. It is the square of the standard deviation.\n* **sd()** - The standard deviation (spread) of values in from the mean. It is the square root of the variance. \n* **quantile()** - Produces sample quantiles corresponding to the given proportions (between 0 and 1). We can compute upper and lower quartiles with this.\n* **min()** - The smallest value in the given column.\n* **max()** - The maximum value in the given column.\n* **n()** - Counts the number of entries (rows).\n* **n_distinct()** - Counts the number of unique entries for a given variable.\n\n\n### **Examples**{-}\n\nLet's compute the mean fare paid by passengers on the titanic. \n\nThe **summarise()** verb takes the following form:\n\n> **summarise(agg_col_name = summary_function(col))** notice that we can name the column as well!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare paid \n\ntitanic_data |> \n summarise(mean(fare)) # Compute mean of fare column\n```\n:::\n\n\n\n\n>**This highlights something very important, that any operation applied to a column containing one or more missing values, produces an average of NA.** \n\nThis is because we are adding something that is Not a Number (it does not exist) to an actual number, which is not defined (think dividing by 0 or adding infinity).\n\nBy default, this will throw most of the summary functions, but there is an optional parameter we can turn on, called \"**na.rm = TRUE**\".\n\nThis will omit any NA values in our calculation and produce a more meaningful result, albeit on a subset of observed data.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare paid by passengers, removing NAs\n\ntitanic_data |> \n summarise(mean(fare, na.rm = TRUE))\n```\n:::\n\n\n\n\nTo assign this a meaningful column name, we'd pass a keyword argument before the summary function used:\n\n>**agg_col_name = summary_function(column, na.rm = TRUE)**\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare paid and naming it\n\ntitanic_data |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\n\n\n\nIf we didn't care about the tibble output summarise generates, we could simply compute using base R syntax:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the mean fare with base R\n\nmean(titanic_data$fare, na.rm = TRUE)\n```\n:::\n\n\n\n\nLike we saw with mutate() and other functions, we can compute multiple statistics through **summarise()**, separating with commas.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating multiple summary statistics with summarise()\n\ntitanic_data |> \n summarise(median_fare = median(fare, na.rm = TRUE),\n mean_fare = mean(fare, na.rm = TRUE),\n sd_fare = sd(fare, na.rm = TRUE),\n median_age = median(age_of_passenger, na.rm = TRUE), \n mean_age = mean(age_of_passenger, na.rm = TRUE), \n sd_age = sd(age_of_passenger, na.rm = TRUE))\n```\n:::\n\n\n\n\n### Quantiles\n\nWe can also calculate quantiles, such as the upper and lower quartile within summarise(). \n\nTo do this, we must specify a value between 0 and 1, which denotes the nth percentile/quantile. For example:\n\n* 0.1 denotes the 10th percentile - All values in order up to the value at the 10% spot.\n* 0.25 denotes the lower quartile - All values in order up to the value at the 25% spot.\n* 0.75 denotes the upper quartile - All values in order up to the value at the 75% spot.\n\n### **Examples**{-}\n\nThe quantile function is structured as:\n\n> **quantile(col, probs = c(0,1),..)** where probs should be the value of the quantile you want.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Computing the lower quartile\n\ntitanic_data |> \n summarise(fare_lower = quantile(fare, probs = 0.25, na.rm = TRUE))\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Computing the upper quartile\n\ntitanic_data |> \n summarise(fare_upper = quantile(fare, probs = 0.75, na.rm = TRUE))\n```\n:::\n\n\n\n\n\n## Categorical Data \n\nSimple statistics on qualitative data include:\n\n* **distinct()** - Displays the unique values in a given column. \n\n* **count()** - Displays the number of occurrences of each unique entry in a given column.\n\nThese (of course) will not work well on columns that are almost entirely unique, such as the name of passenger!\n\n\n### **Examples**{-}\n\nLet's start with **count()**, which we can sort with the extra parameter **sort = TRUE** for a descending order output. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating frequency of each unique passenger name\n\ntitanic_data |> \n count(name_of_passenger, sort = TRUE)\n```\n:::\n\n\n\n\nCompared this to a categorical variable with only a few unique categories, like embarked. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the number of passengers embarked from each port\n\ntitanic_data |> \n count(embarked, sort = TRUE)\n```\n:::\n\n\n\n\nLet's see distinct() in action:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Select only unique/distinct rows from the embarked column\n \ntitanic_data |> \n distinct(embarked)\n```\n:::\n\n\n\n\n\n## Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. Use summarise() to return the ages of the oldest and youngest passengers on the titanic.\n\n2. Use a summary function for categorical data to determine the number of men and women in the dataset.\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the oldest and youngest\n\ntitanic_data |> \n summarise(youngest_age = min(age_of_passenger, na.rm = TRUE),\n oldest_age = max(age_of_passenger, na.rm = TRUE))\n```\n:::\n\n\n\n\n2. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the count of men and women on the titanic\n\ntitanic_data |> \n count(sex_of_passenger)\n```\n:::\n\n\n\n\nWe see that there were almost twice as many men as there were women on the titanic. \n\n:::\n\n# Aggregation\n\nAggregation means grouping data together by a particular grouping variable and producing a summary of one or more columns for that grouping variable.\n\nFor example, we might want to see the average fare paid **by** sex or **by** port embarked from. \n\nThe **group_by()** function from dplyr is the bread and butter of this section.\n\n## Group By\n\nGroup by performs the aggregation necessary so that we can use summarise() from before to obtain numeric summaries by group. \n\nIt is formed on a principle known as **split - summarise - combine**\n\n* Split - The tibble is divided into a set of smaller tibbles, based on the grouping variable.\n For example, if we use a variable with 3 unique categories, 3 smaller tibbles are created.\n\n* Summarise - An aggregate statistic is applied to each of the groups (such as the mean of their fare paid) and a single row for each group is output.\n\n* Combine - The individual outputs from aggregation are combined into a new tibble.\n\n\n### Example\n\nLet's look at this in code by finding the mean fare for each passenger class.\n\nThe sequence of code will go as follows:\n\n> **group_by(col) |> summarise(agg_col = summary_function(col))**\n\nFirstly, let's check how many classes there are:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# How many pclasses are there?\n\ntitanic_data |>\n distinct(pclass)\n```\n:::\n\n\n\n\nSo we should expect three values, one mean fare for each of the passenger classes. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculate mean fare by passenger class\n\ntitanic_data |> \n group_by(pclass) |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\n\n\n### The similarity of count() and group_by()\n\nAn interesting point to make is that we can use the n() summary statistic to count the number of observations in that group after a group_by.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by and count the number of unique groups\n\ntitanic_data |> \n group_by(pclass) |> \n summarise(n = n())\n```\n:::\n\n\n\n\nThis looks similar to the output of another function we used!\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Replicate the above result with a different function\n\ntitanic_data |> \n count(pclass)\n```\n:::\n\n\n\n\nit is the case the count() is performing the exact same computations in the background as the combination of group_by() and summarise()! \n\nA great shortcut if a count is all you need. \n\n## Multiple Aggregation\n\nWe can also double aggregate with more complex groupings. For example, we may require the mean fare paid by first class passengers leaving from Southhampton.\n\nWe would need to group by both passenger class and embarked to achieve this. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by pclass and embarked and find mean fare\n\ntitanic_data |> \n group_by(pclass, embarked) |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\n\n\nWe see that since there are 3 passenger classes and 4 (with the null value) embarked entries, there are 3 * 4 = 12 possible combinations, with 10 outputting here (there are no second or third class null values).\n\nOrder does not matter here as it just determines what the final groupings look like, we will still get the same 12 each time.\n\nThe output itself will of course differ as it displays the groups in the order we grouped them:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by embarked and pclass and find mean fare\n\ntitanic_data |> \n group_by(embarked, pclass) |> \n summarise(mean_fare = mean(fare, na.rm = TRUE))\n```\n:::\n\n\n\n\n### Exercise\n::: {.panel-tabset}\n\n### **Exercise**{-}\n\n1. What is the average fare paid by men and women?\n\n\n2. What is the median fare paid by men and women in each passenger class?\n\n\n### **Show Answer**{-}\n\n1. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the average fare by sex\n\ntitanic_data |> \n group_by(sex_of_passenger) |> \n summarise(mean_fare = mean(fare,\n na.rm = TRUE))\n```\n:::\n\n\n\n\n2. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Calculating the median fare by sex and passenger class\n\ntitanic_data |> \n group_by(sex_of_passenger, pclass) |> \n summarise(median_fare = median(fare,\n na.rm = TRUE))\n```\n:::\n\n\n\n:::\n\n\n## The impact of NAs\n\nIdeally, we don't want the null values being a category of their own and cluttering up our summary tables.\n\nWhen investigating data, we either:\n\n* Deal with these at read in.\n* Meticulously clean them with imputation methods (fill them in).\n* Drop them entirely (be very careful with this!).\n\n**tidyr** comes to the rescue when we are dealing with NAs as it has some handy functions to work with them:\n\n* drop_na() removes all rows with missing values present.\n* replace_na() fills in the missing values with whatever we specify. \n\nLet's see a few small examples of this in practice.\n\n### Filling missing values\n\nWe should always attempt to understand why values are missing before dealing with them. \n\nDomain expertise comes into play when deciding whether it makes sense for a value to be missing, think of temperature:\n\n> **A missing temperature reading is not the same as a temperature reading of 0 degrees celsius.**\n \nAs such, it wouldn't make sense to fill the NAs with 0, as we create **bias** by over inflating the number of 0 temperature values.\n\nA better approach in cases such as this is to fill with an **average**, preferably one not impacted by outliers, such as the median.\n\n### **Example**{-}\n\nLet's consider first which numeric variables have missing values. We can check this by using the **is.na()** function.\n\nThis returns a vector of TRUEs and FALSEs, one for each cell in the table, for whether they are missing or not. \n\nWe can then sum() these up to find the total number of missing values in that column. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compute number of missing values in age_of_passenger\n\ntitanic_data$age_of_passenger |> \n is.na() |> \n sum()\n```\n:::\n\n\n\n\nRepeating this for each column becomes laborious quickly, so there are some options for us:\n\n* Use **colSums()** to sum the outputs of a function across columns.\n* Create a **User defined function** or **Anonymous Function** to apply across the columns of the dataset using functional programming in purrr.\n\nWhilst the latter is recommended, it is beyond the scope of this current chapter, and features in later more advanced courses. \n\nLet's try colSums():\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use colSums() to find the missing values\n\ntitanic_data |> is.na() |> \n colSums()\n```\n:::\n\n\n\n\nNow that we have understood the number of missing values, let's see some imputation.\n\n### **Filling a numeric column with an average**{-}\n\nWe know that age_of_passenger has 267 missing values, but filling these in with 0 makes no sense and will skew the data.\n\nA better approach would be to impute with an average, that way we maximise our attempt to keep the data centralised. \n\nHowever, we must also be careful which statistic we use, as some are more robust than others:\n\n* The mean is heavily influenced by outliers (as it includes them in the calculation).\n* The median is a more robust measure as it does not consider the end points of the data (not influenced by outliers).\n \n#### **Example**{-}\n\nThe replace_na() functions takes a few arguments:\n\n* The data itself\n* replace - What to fill the NAs with\n\nUsing this effectively requires us to also use **mutate()** as this modifies an existing column, as opposed to us using base R functionality to refer to columns with **$**.\n\nLet's use is.na() and colSums() to check it worked:\n \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Impute missing age values with median \n\ntitanic_data <- titanic_data |> # overwrite to save changes\n mutate(age_of_passenger = replace_na(age_of_passenger,\n replace = median(age_of_passenger,\n na.rm = TRUE)))\n```\n:::\n\n\n\n\nLet's check this worked:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check imputation\n\ntitanic_data |> is.na() |> \n colSums()\n```\n:::\n\n\n\n\n\n### **Filling a categorical column with an average**{-}\n\nWith categorical columns, the most robust method we can use to impute is using the most frequently occuring value, or the **mode**. \n\nThere is no built in function for this in base R, requiring an outside package in order to so. However, we can observe the mode with the output from count().\n\n#### **Example**{-}\n\nWe saw that embarked had 2 missing values, let's fill them with the mode.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find the mode of the embarked column\n\ntitanic_data |> \n count(embarked)\n```\n:::\n\n\n\n\nWe see that \"S\" or \"Southhampton\" was the most commonly departed from port among passengers.\n\nLet's fill this in with replace_na():\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Fill embarked in with the mode\n\ntitanic_data <- titanic_data |> \n mutate(embarked = replace_na(embarked, replace = \"S\")) \n```\n:::\n\n\n\n\nLet's check again:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Check that embarked impute worked\n\ntitanic_data |> is.na() |> \n colSums()\n```\n:::\n\n\n\n\nImputation is a very deep topic and goes beyond the scope of the course, but we recommend researching this for other examples.\n\n\n### Dropping Missing Values\n\nWe must be very careful about doing this, as we previously noted that there may be a pattern to how or why they are missing, and as such can be treated.\n\nWe risk lowering variance across our dataset by removing them, but if analysis determines that there is no easy way to impute them, dropping them might be the only option.\n\n### **Example**{-}\n\nWe use the drop_na() function to drop null values remaining. \n\n* In our example, cabin is roughly 75% missing, and with a variety of categories of all different forms, imputation would be a nightmare. \n * As such, we would elect to exclude this column with **select()**.\n\n* Similarly, there is only one missing fare value, which it is more efficient to drop than fill with an average.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Drop the null values in fare\n\ntitanic_data <- titanic_data |> \n select(-cabin) |> \n drop_na(fare)\n```\n:::\n\n\n\n\n\n\n# Summary \n\nWell done for working your way through this whistle stop tour of aggregation and summary statistics!\n\nThis is the final compulsory chapter of the course, and as such your next steps are up to you, some recommendations we would make are:\n\n* Complete the additional chapter, chapter 6, which is a case study that tests the skills you've learnt in this course on a new dataset. \n\n* Complete the Additional Chapter, chapter 7, that covers more advanced concepts, such as:\n * Pivoting data\n * Binning numeric columns to categorical columns.\n * Functional programming tools with purrr.\n * Extra list functionality.\n\n* Complete any of the R courses that this course is a pre-requisite for on the [Learning Hub](https://learninghub.ons.gov.uk/local/catalogue/index.php), such as:\n * [Data Visualization in R](https://learninghub.ons.gov.uk/course/view.php?id=553)\n * [Statistics in R](https://learninghub.ons.gov.uk/course/view.php?id=560)\n * [Modular Programming in Python and R](https://learninghub.ons.gov.uk/course/view.php?id=574)",
+ "supporting": [
+ "CH5_summary_agg_files"
+ ],
"filters": [
"rmarkdown/pagebreak.lua"
],
diff --git a/_freeze/CH6_case_study/execute-results/html.json b/_freeze/CH6_case_study/execute-results/html.json
index ddce2ed..3cb00f0 100644
--- a/_freeze/CH6_case_study/execute-results/html.json
+++ b/_freeze/CH6_case_study/execute-results/html.json
@@ -1,8 +1,11 @@
{
- "hash": "88e82b34e9956af0ff61c20356828567",
+ "hash": "481df2f4aabe333625acce4158f85370",
"result": {
- "markdown": "---\ntitle: \"Chapter 6 - Case Study\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Introduction\n\nBy the end of this case study, you should have more confidence with manipulating data and using techniques from the first five chapters of Intro to R, as such, they are a **pre-requisite** for it.\n\nThese data sets and question are designed to be an initial springboard for you to continue with your data journey. \n\nAnswers are provided; but these may only show one or two ways of solving the issue. \n\n>**Your answers may differ slightly from ours, this is fine if the output is consistent, but consider whether you could achieve your answer with less or better written code.** \n\n\n## Structure:\n\nQuestions will be presented in tabs.\n\n* Tab 1 will contain the question \n* Tab 2 will contain the solution in R.\n\nPlease choose the tab with the language you wish to use.\nAn example is below.\n\n## Example \n::: {.panel-tabset}\n\n### **Question**{-}\n\nThis is an example question.\n\n### **Solution**{-} \n\n::: {.cell}\n\n```{.r .cell-code}\n# Solution cell\n\n\"Insert code here\"\n```\n:::\n\n:::\n\n\n# Question 1: Packages\n::: {.panel-tabset}\n\n## **Question**{-}\n\nLoad the following packages:\n\n* tidyverse\n* janitor\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# load packages\n\nlibrary(tidyverse)\nlibrary(janitor)\n```\n:::\n\n:::\n\n# Question 2: Data \n::: {.panel-tabset}\n\n## **Question**{-}\n\nRead in the two files from the **data** folder below, assigning them to the variables suggested:\n\nnetflix - nextflix_data.csv\nimdb_scores - imdb_scores.csv\n\nNote - The data is sourced from [Tidy Tuesday](https://github.com/rfordatascience/tidytuesday) and directly from IMDB.\n\nSome data has been altered to suit the difficulty level of this course. This is a training dataset, and so shouldn't be relied upon for 100% accuracy.\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Read in imdb and netflix data\n\nnetflix <- readr::read_csv(\"Data/netflix_data.csv\")\n\nimdb_scores <- readr::read_csv(\"Data/imdb_scores.csv\")\n```\n:::\n\n:::\n\n# Question 3 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nClean up the column names of imdb_scores\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use janitor to clean names of imdb data\n\nimdb_scores <- clean_names(imdb_scores)\n\nnames(imdb_scores)\n```\n:::\n\n:::\n\n# Question 4 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nWhat are the dimensions of the Netflix data?\n\nSee if you can output them in a sentence.\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find the dimensions with dim()\n\ndim(netflix) # Rows and columns\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Output a sentence with the dimensions\n\ncat(\"There are\", nrow(netflix), \"rows and\", ncol(netflix), \"columns in the neflix dataset.\")\n```\n:::\n\n:::\n\n# Question 5 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUse an inspection function to determine the datatypes of the columns in the Netflix data.\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Have a glimpse of netflix\n\nglimpse(netflix)\n```\n:::\n\n:::\n \n# Question 6 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nHow many missing values do we have in each dataset?\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of missings in the netflix data\n\n\ncolSums(is.na(netflix))\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of missings in imdb data\n\ncolSums(is.na(imdb_scores))\n```\n:::\n\n:::\n\n# Question 7 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nHow many times does each unique country occur in the dataset? \n\n## **Show Answer** {-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of unique categories in primary_country\n\nnetflix |> \n count(primary_country)\n```\n:::\n\n:::\n\n# Question 8\n::: {.panel-tabset}\n\n## **Question**{-}\n\nCreate a new tibble \"netflix_movies\" by filtering the netflix tibble to contain only \"Movie\". \n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create a tibble with \"Movie\"s only\n\nnetflix_movies <- netflix |> \n filter(type == \"Movie\")\n\nglimpse(netflix_movies)\n```\n:::\n\n:::\n\n# Question 9 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble, clean the duration column by:\n\n* Removing the suffix \"min\".\n* Converting the resulting column to an integer\n\nFollowing this, rename the column to \"duration_mins\".\n\n> Note, you can do this in one pipeline!\n\nEnsuring that you overwrite and reassign the dataset!\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use mutate to clean the duration column\n\nnetflix_movies <- netflix_movies |> \n mutate(duration = as.integer(str_replace(duration, \n pattern = \"min\",\n replacement = \"\"))) |> \n rename(duration_mins = duration)\n\nglimpse(netflix_movies)\n```\n:::\n\n:::\n\n# Question 10\n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble, compute:\n\n* The mean and median duration of the movies\n* The mean and standard deviation of the cast numbers.\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compute summary statistics of duration and cast number\n\nnetflix_movies |> \n summarise(mean_duration = mean(duration_mins, na.rm = TRUE),\n median_duration = median(duration_mins, na.rm = TRUE),\n mean_cast = mean(num_cast, na.rm = TRUE),\n std_cast = sd(num_cast, na.rm = TRUE))\n```\n:::\n\n:::\n\n# Question 11 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble:\n\n* Select the title, duration, director and cast numbers\n* Sort in descending order of duration\n\nWhich movie was the longest, and who directed it?\n \n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Pipeline for longest movie\n\nnetflix_movies |> \n select(title, duration_mins, director, num_cast) |> \n arrange(desc(duration_mins)) |> \n glimpse()\n```\n:::\n\nThe longest movie on Netflix is Black Mirror: Bandersnatch, at 312 minutes, with no recorded director.\n\n:::\n\n# Question 12 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble:\n\nGroup by primary_country and obtain the median cast number.\n \n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by country\n\nnetflix_movies |> \n group_by(primary_country) |> \n summarise(var_cast = median(num_cast, na.rm = TRUE))\n```\n:::\n\n:::\n\n# Question 13 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble:\n\nGroup by type and rating of the movie, producing the mean duration.\n \n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by type and rating\n\nnetflix_movies |> \n group_by(type, rating) |> \n summarise(mean_duration = mean(duration_mins, na.rm = TRUE))\n```\n:::\n\n:::\n\n# Question 14\n::: {.panel-tabset}\n\n## **Question**{-}\n\nLeft join the imdb_scores data to the **original** netflix data.\n\nCreate a new variable netflix_imdb to contain this.\n\n\n## **Show Answer**{-}\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Join imdb and netflix\n\nnetflix_imdb <- netflix |> \n left_join(y = imdb_scores,\n by = \"title\")\n\nglimpse(netflix_imdb)\n```\n:::\n\n:::\n\n# Summary \n\nIn this case study you have had the opportunity to apply data analysis techniques with the tidyverse to some additional datasets. \n\nThis is not exhaustive; have a look at the data and experiment with other techniques you can use.\n\nThis data has been provided for you to experiment with; however there is nothing better than learning with data that is meaningful to you.\n\nFor additional datasets we recommend exploring:\n\n* [Kaggle](https://www.kaggle.com/)\n* [Tidy Tuesday](https://github.com/rfordatascience/tidytuesday)\n* [Data.gov](https://data.gov.uk/)\n\n",
- "supporting": [],
+ "engine": "knitr",
+ "markdown": "---\ntitle: \"Chapter 6 - Case Study\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\n---\n\n\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Introduction\n\nBy the end of this case study, you should have more confidence with manipulating data and using techniques from the first five chapters of Intro to R, as such, they are a **pre-requisite** for it.\n\nThese data sets and question are designed to be an initial springboard for you to continue with your data journey. \n\nAnswers are provided; but these may only show one or two ways of solving the issue. \n\n>**Your answers may differ slightly from ours, this is fine if the output is consistent, but consider whether you could achieve your answer with less or better written code.** \n\n\n## Structure:\n\nQuestions will be presented in tabs.\n\n* Tab 1 will contain the question \n* Tab 2 will contain the solution in R.\n\nPlease choose the tab with the language you wish to use.\nAn example is below.\n\n## Example \n::: {.panel-tabset}\n\n### **Question**{-}\n\nThis is an example question.\n\n### **Solution**{-} \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Solution cell\n\n\"Insert code here\"\n```\n:::\n\n\n\n:::\n\n\n# Question 1: Packages\n::: {.panel-tabset}\n\n## **Question**{-}\n\nLoad the following packages:\n\n* tidyverse\n* janitor\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# load packages\n\nlibrary(tidyverse)\nlibrary(janitor)\n```\n:::\n\n\n\n:::\n\n# Question 2: Data \n::: {.panel-tabset}\n\n## **Question**{-}\n\nRead in the two files from the **data** folder below, assigning them to the variables suggested:\n\nnetflix - nextflix_data.csv\nimdb_scores - imdb_scores.csv\n\nNote - The data is sourced from [Tidy Tuesday](https://github.com/rfordatascience/tidytuesday) and directly from IMDB.\n\nSome data has been altered to suit the difficulty level of this course. This is a training dataset, and so shouldn't be relied upon for 100% accuracy.\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Read in imdb and netflix data\n\nnetflix <- readr::read_csv(\"Data/netflix_data.csv\")\n\nimdb_scores <- readr::read_csv(\"Data/imdb_scores.csv\")\n```\n:::\n\n\n\n:::\n\n# Question 3 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nClean up the column names of imdb_scores\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use janitor to clean names of imdb data\n\nimdb_scores <- clean_names(imdb_scores)\n\nnames(imdb_scores)\n```\n:::\n\n\n\n:::\n\n# Question 4 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nWhat are the dimensions of the Netflix data?\n\nSee if you can output them in a sentence.\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Find the dimensions with dim()\n\ndim(netflix) # Rows and columns\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Output a sentence with the dimensions\n\ncat(\"There are\", nrow(netflix), \"rows and\", ncol(netflix), \"columns in the neflix dataset.\")\n```\n:::\n\n\n\n:::\n\n# Question 5 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUse an inspection function to determine the datatypes of the columns in the Netflix data.\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Have a glimpse of netflix\n\nglimpse(netflix)\n```\n:::\n\n\n\n:::\n \n# Question 6 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nHow many missing values do we have in each dataset?\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of missings in the netflix data\n\n\ncolSums(is.na(netflix))\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of missings in imdb data\n\ncolSums(is.na(imdb_scores))\n```\n:::\n\n\n\n:::\n\n# Question 7 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nHow many times does each unique country occur in the dataset? \n\n## **Show Answer** {-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Number of unique categories in primary_country\n\nnetflix |> \n count(primary_country)\n```\n:::\n\n\n\n:::\n\n# Question 8\n::: {.panel-tabset}\n\n## **Question**{-}\n\nCreate a new tibble \"netflix_movies\" by filtering the netflix tibble to contain only \"Movie\". \n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create a tibble with \"Movie\"s only\n\nnetflix_movies <- netflix |> \n filter(type == \"Movie\")\n\nglimpse(netflix_movies)\n```\n:::\n\n\n\n:::\n\n# Question 9 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble, clean the duration column by:\n\n* Removing the suffix \"min\".\n* Converting the resulting column to an integer\n\nFollowing this, rename the column to \"duration_mins\".\n\n> Note, you can do this in one pipeline!\n\nEnsuring that you overwrite and reassign the dataset!\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Use mutate to clean the duration column\n\nnetflix_movies <- netflix_movies |> \n mutate(duration = as.integer(str_replace(duration, \n pattern = \"min\",\n replacement = \"\"))) |> \n rename(duration_mins = duration)\n\nglimpse(netflix_movies)\n```\n:::\n\n\n\n:::\n\n# Question 10\n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble, compute:\n\n* The mean and median duration of the movies\n* The mean and standard deviation of the cast numbers.\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Compute summary statistics of duration and cast number\n\nnetflix_movies |> \n summarise(mean_duration = mean(duration_mins, na.rm = TRUE),\n median_duration = median(duration_mins, na.rm = TRUE),\n mean_cast = mean(num_cast, na.rm = TRUE),\n std_cast = sd(num_cast, na.rm = TRUE))\n```\n:::\n\n\n\n:::\n\n# Question 11 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble:\n\n* Select the title, duration, director and cast numbers\n* Sort in descending order of duration\n\nWhich movie was the longest, and who directed it?\n \n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Pipeline for longest movie\n\nnetflix_movies |> \n select(title, duration_mins, director, num_cast) |> \n arrange(desc(duration_mins)) |> \n glimpse()\n```\n:::\n\n\n\nThe longest movie on Netflix is Black Mirror: Bandersnatch, at 312 minutes, with no recorded director.\n\n:::\n\n# Question 12 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble:\n\nGroup by primary_country and obtain the median cast number.\n \n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by country\n\nnetflix_movies |> \n group_by(primary_country) |> \n summarise(var_cast = median(num_cast, na.rm = TRUE))\n```\n:::\n\n\n\n:::\n\n# Question 13 \n::: {.panel-tabset}\n\n## **Question**{-}\n\nUsing your netflix_movies tibble:\n\nGroup by type and rating of the movie, producing the mean duration.\n \n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Group by type and rating\n\nnetflix_movies |> \n group_by(type, rating) |> \n summarise(mean_duration = mean(duration_mins, na.rm = TRUE))\n```\n:::\n\n\n\n:::\n\n# Question 14\n::: {.panel-tabset}\n\n## **Question**{-}\n\nLeft join the imdb_scores data to the **original** netflix data.\n\nCreate a new variable netflix_imdb to contain this.\n\n\n## **Show Answer**{-}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Join imdb and netflix\n\nnetflix_imdb <- netflix |> \n left_join(y = imdb_scores,\n by = \"title\")\n\nglimpse(netflix_imdb)\n```\n:::\n\n\n\n:::\n\n# Summary \n\nIn this case study you have had the opportunity to apply data analysis techniques with the tidyverse to some additional datasets. \n\nThis is not exhaustive; have a look at the data and experiment with other techniques you can use.\n\nThis data has been provided for you to experiment with; however there is nothing better than learning with data that is meaningful to you.\n\nFor additional datasets we recommend exploring:\n\n* [Kaggle](https://www.kaggle.com/)\n* [Tidy Tuesday](https://github.com/rfordatascience/tidytuesday)\n* [Data.gov](https://data.gov.uk/)\n\n",
+ "supporting": [
+ "CH6_case_study_files"
+ ],
"filters": [
"rmarkdown/pagebreak.lua"
],
diff --git a/_freeze/CH7_control_flow_loops_and_functions/execute-results/html.json b/_freeze/CH7_control_flow_loops_and_functions/execute-results/html.json
index 9a86a9b..aefe8cd 100644
--- a/_freeze/CH7_control_flow_loops_and_functions/execute-results/html.json
+++ b/_freeze/CH7_control_flow_loops_and_functions/execute-results/html.json
@@ -1,14 +1,17 @@
{
- "hash": "f6cdc595c0ab6df1c47121480842c751",
+ "hash": "558a2ca0e309e4f982634f143ab9c35c",
"result": {
- "markdown": "---\ntitle: \"Chapter 7 - Control Flow, Loops and Functions\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: true\n freeze: auto # re-render only when source changes\n---\n\n\n> To switch between light and dark modes, use the toggle in the top left\n\n\n\n\n\n# Introduction\n\nWe use R because it's great for data analysis, data visualisation communicating results. However, R is not just a data analysis environment but a programming language. Advanced R programmers can develop complex packages and even improve R itself.\n\nIn this chapter, we introduce three key programming concepts: **loops, conditional statements, and functions**. These are not just key building blocks for advanced programming, but are sometimes useful during data analysis.\n\n## Learning Outcomes\n\nBy the end of this chapter you should be able to:\n\n* Understand the programming concept of loops.\n* Use loops and understand their place in R.\n* Be able to use conditional statements: *if*, *else* and *else if*.\n* Be familiar with *else_if()* and *case_when()* from *dplyr*.\n* Know what functions are and why they are useful.\n* Be able to distinguish between a function's parameters and arguments.\n * Including different types of arguments\n* Understand the idea of 'scope'.\n * i.e. Global scope vs Local scope\n* Be able to write and apply user defined functions.\n* Be able to apply functions to **vector** and **`tibble`** objects.\n\n\nThe chapter assumes familiarity with:\n\n* Logical Operators such as less than (<) , greater than (>), equivalent to (==) etc\n* Knowledge of reading in data (using readr); basic data manipulation (using dplyr)\n* General basic knowledge of R code - this course should not be your first introduction to the language.\n\n# Packages and Datasets\n\n## Packages\n\nBelow find listed the packages used in this course. This course has been tested with the versions listed.\n\n\nThis course uses various packages from the Tidyverse collection of packages. These can be loaded individually or as a whole through **library(tidyverse)**\n\n* readr - version 1.4.0\n* dplyr - version 1.0.6\n* purr - version 0.3.4\n\nOther Packages\n\n* janitor - version 2.1.0\n* fs - 1.5.0\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(tidyverse)\n```\n\n::: {.cell-output .cell-output-stderr}\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr 1.1.4 ✔ readr 2.1.5\n✔ forcats 1.0.0 ✔ stringr 1.5.1\n✔ ggplot2 3.5.1 ✔ tibble 3.2.1\n✔ lubridate 1.9.3 ✔ tidyr 1.3.1\n✔ purrr 1.0.2 \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::group_rows() masks kableExtra::group_rows()\n✖ dplyr::lag() masks stats::lag()\nℹ Use the conflicted package (
\n\nWe can see these these are columns,\n\n* **Pclass**: Passenger’s class, 1 = 1st (Upper), 2 = 2nd(Middle), 3 = 3rd(Lower)\n* **Survived**: Survived (1) or died (0), 0 = No, 1 = Yes\n* **Name**: Passenger’s name\n* **Sex**: Passenger’s sex\n* **Age**: Passenger’s age\n* **SibSp**: Number of siblings/spouses aboard\n* **Parch**: Number of parents/children aboard\n* **Ticket**: Ticket number\n* **Fare**: Fare\n* **Cabin**: Cabin number\n* **Embarked**: Port of embarkation, C = Cherbourg, Q = Queenstown, S = Southampton\n\n\nWe can see more details on the [Data Dictionary](https://www.kaggle.com/c/titanic/data)\n\n# Loops\n\nLoops are a fundamental concept in traditional programming languages. \n\nA loop is a way to repeat a number of commands until a given condition is met.\n\nThis repetition of code is called **iteration**.\n\nA repetitive action could be \"create several similar plots\".\n\nWithin a loop, any other code can be run to produce anything we want such as plots, models, reports, and datasets.\n\nSince R is a vectorised language, loops are not as prominently used in R as in Python or other programming languages. Despite this, they are a key part of programming in general and can save you a large amount of time and typing in certain cases.\n\nThey allow you to automate parts of your code that are in need of repetition.\n\nSimilar to how functions help make our code more abstract and general, loops perform a similar purpose. We are essentially simplifying a specific case of code to a more general case.\n\nWe are going to look at `for` loops first. \n\n## For Loops\n\nThese are the most common type of loop the other type is a `while` loop which can do the same things, but in a slightly different way.\n\nFor loops follow the basic structure below.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Basic Structure of a loop\n\n# Creating the loop\nfor (each_item in my_iterable) { \n \n output <- commands\n }\n```\n:::\n\n\n* We start the loop with the word `for`,\n\n* Followed by `()` brackets where we first specify an index variable, `i` is commonly used but it can be anything that you want. Remember, we want to use clear and descriptive variable names. This is a place holder and corresponds to each different element as we move through the loop,\n\n* Then the word `in`.\n\n* Then specify an iterable. This could be a `vector`, a `list`, a `dataframe` etc. An iterable is any object that can be iterated through, one element at a time. \n\n* Followed by the `{}` curly brackets, which will have our commands within, these could be multiple lines of code.\n\n### Example\n\nLet's look at an example.\n\nWe start by creating an iterable, I have created a vector with the numbers **0 through 5**.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector\n\nexample_vector <- c(0, 1, 2, 3, 4, 5)\n```\n:::\n\n\nWe can then create our loop which doubles every value and prints it out.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating the loop\n\nfor (each_number in example_vector) {\n \n # Print the value at each step\n print(each_number * 2)\n \n }\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 0\n[1] 2\n[1] 4\n[1] 6\n[1] 8\n[1] 10\n```\n:::\n:::\n\n\n\n\\\n\n\n\n\nIn the above example we simply printed our results in the console, if we wanted to store our result, we can simply create a data structure of our choice and use the append function, as shown below.\n\n\nThe keyword `for` is followed by a variable that refers to each item in my iterable. I’ve called this variable **`each_number`**. It is good to be clear and explicit when naming variables, so they explain what the variable is. \n\nThe keyword `in` is followed by the iterable I want to loop over - `example_vector`.\n\nThe output of my command is appended to `result`. The command here is to multiply each number in `example_vector` by 2. The **`append()`** function simply adds an element to the end of a vector. We first specify the vector we want to add to which is `result` and then specify the values that we want to add to it. Within the function this is set to the parameter `values`.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create an empty output\n# Which we will fill when the loop runs\n\nresult <- c()\n\n# Creating the loop\n\nfor (each_number in example_vector) {\n \n # Print the value at each step\n print(each_number * 2)\n \n result <- append(result, values = each_number * 2)\n \n}\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 0\n[1] 2\n[1] 4\n[1] 6\n[1] 8\n[1] 10\n```\n:::\n\n```{.r .cell-code}\n# To display the data\n\nresult\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 0 2 4 6 8 10\n```\n:::\n:::\n\n\n\n\n
\n\n\nAlthough it is useful to know how to use loops in R, it is often faster to accomplish the same thing using vectorised operations in R. \n\nWe already saw examples in the Vector Arithmetic section. A vectorised function is a function that will apply the same operation on each element of the vectors.\n\nFor example:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector\n\nexample_vector <- 1:5\n\n# Using a sqrt() function on our vector\n\nsqrt(example_vector)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 1.000000 1.414214 1.732051 2.000000 2.236068\n```\n:::\n:::\n\n\n
\n\nTo make this calculation, there is no need for a loop. However, not all functions work this way. \n\nWhile there are many functions out there that vectorise particular calculations, there are still some tasks that cannot be vectorised. This is where iteration becomes useful. While we should always be looking to vectorise calculations, we can take comfort knowing that we have a back up tool to use just in case it fails us.\n\nWe also have while loops, which are used to loop until a specific condition is met. \n\nYou can a find a tutorial on them here: [While Loop](https://www.datamentor.io/r-programming/while-loop/).\n\n\n\n### Exercise 1\n\n::: {.panel-tabset}\n\n#### Exercise\n\n1. You are given a vector of measurements that are grams (g). \n\n For this exercise, we want to convert all of these measurements to kilograms (kg). \n\n **For reference, 1kg is equal to 1000 grams.**\n\n Using a for loop, create and append to a new vector called **kilograms** that contains the values converted to kilograms.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Vector \n\ngrams <- c(100000, 7899900, 967312, 49185, 6100)\n```\n:::\n\n\n\n#### Hint\n\nPlease note below is pseudocode, that is the 'recipie' for getting the answer.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Starting vector\n\ngrams <- c(100000, 7899900, 967312, 49185, 6100)\n\n# Empty vector for result storage\n\nkilograms <- c()\n\n# For loop\n\nfor (each_number in vector) {\n \n convert to kilograms\n \n append result to kilograms\n}\n\n\n# To display the data\n\nkilograms\n```\n:::\n\n\n#### Answer\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Starting vector\n\ngrams <- c(100000, 7899900, 967312, 49185, 6100)\n\n# Empty vector for result storage\n\nkilograms <- c()\n\n# For loop\n\nfor (measurement in grams) {\n # Converting grams to kg\n converted_kilogram <- measurement / 1000 \n \n # Appending to kilo_grams result vector\n kilograms <- append(kilograms, values = converted_kilogram) \n \n}\n\n# To display the data\n\nkilograms\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 100.000 7899.900 967.312 49.185 6.100\n```\n:::\n:::\n\n\n:::\n\n\n\n### Extension Exercise\n\nIf you would like to go deeper into for loops before moving on, try the extension exercise below.\n\n::: {.panel-tabset}\n\n#### Exercise\n\n1. Complete the code below, Use a for loop to load all the files in the data folder. Some steps have been given to you already.\n\n* We have loaded the packages tidyverse and fs\n\n* We then use the function `fs::dir_ls()` which will give a list of all the file paths in the data folder, we have assgined this to `file paths`.\n\n* We have created an empty list called `my_datasets` which we fill with out datasets after the loop runs.\n\n* Your task is to create a for loop to loop through the `file_paths` and store each dataset as an element in the list `my_datasets`\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Loading packages\n\nlibrary(tidyverse) # For loading data and manipulation of data\nlibrary(fs) # File system\n\n\n# Get a list of the file paths\nfile_paths <- fs::dir_ls(\"Data\") \n\n# Display the file paths\nfile_paths\n```\n\n::: {.cell-output .cell-output-stdout}\n```\nData/bikes_data_set.csv Data/imdb_scores.csv Data/netflix_data.csv \nData/police_data.xlsx Data/revenue_data_set.csv Data/titanic.csv \nData/titanic_clean.csv \n```\n:::\n\n```{.r .cell-code}\n# Create a list to store all the dataframes\nmy_datasets <- list()\n```\n:::\n\n\n#### Hint\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Loading packages\n\nlibrary(tidyverse) # For loading data and manipulation of data\nlibrary(fs) # File system\n\n\n# Get a list of the file paths\nfile_paths <- fs::dir_ls(\"Data\") \n\n# Display the file paths\nfile_paths\n\n# Create a list to store all the dataframes\nmy_datasets <- list()\n\n\n# Loop through file paths and store in the list\n\nfor (each_file_path in file_paths){\n \n # adding a new element in the my datasets list\n my_datasets <- command \n }\n```\n:::\n\n\n#### Show Answer\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(tidyverse) # For loading data and manipulation of data\nlibrary(fs) # File system\n\n\n# Get a list of the file paths\nfile_paths <- fs::dir_ls(\"Data\") \n\n# Display the file paths\nfile_paths\n```\n\n::: {.cell-output .cell-output-stdout}\n```\nData/bikes_data_set.csv Data/imdb_scores.csv Data/netflix_data.csv \nData/police_data.xlsx Data/revenue_data_set.csv Data/titanic.csv \nData/titanic_clean.csv \n```\n:::\n\n```{.r .cell-code}\n# Create a list to store all the dataframes\nmy_datasets <- list()\n\n# Loop through file paths and store in the list\n\nfor (each_file_path in file_paths){\n \n # adding a new element in the my datasets list\n my_datasets[[each_file_path]] <- readr::read_csv(file = file_paths[[each_file_path]])\n}\n\n# To display the list of dataframes\ndplyr::glimpse(my_datasets)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\nList of 7\n $ Data/bikes_data_set.csv : spc_tbl_ [737 × 12] (S3: spec_tbl_df/tbl_df/tbl/data.frame)\n ..$ Date : chr [1:737] \"04/01/2015\" \"05/01/2015\" \"04/01/2015\" \"05/01/2015\" ...\n ..$ real Temperature : num [1:737] 2.75 9 2.75 9 NA NA 8 9 9 9 ...\n ..$ empty column : logi [1:737] NA NA NA NA NA NA ...\n ..$ Feel Temperature : num [1:737] 0 7.25 0 7.25 NA NA 5.75 5.5 6.75 6.75 ...\n ..$ Humidity : num [1:737] 93 81.5 93 81.5 NA ...\n ..$ Wind Speed : num [1:737] 7.5 8.85 7.5 8.85 NA ...\n ..$ weather code : chr [1:737] \"broken_clouds\" \"broken_clouds\" \"broken_clouds\" \"broken_clouds\" ...\n ..$ DO NOT TOUCH THIS COLUMN: logi [1:737] NA NA NA NA NA NA ...\n ..$ is holiday : logi [1:737] FALSE FALSE FALSE FALSE NA NA ...\n ..$ is weekend : logi [1:737] TRUE FALSE TRUE FALSE NA NA ...\n ..$ season : chr [1:737] \"winter\" \"winter\" \"winter\" \"winter\" ...\n ..$ count : num [1:737] 9234 20372 9234 20372 NA ...\n ..- attr(*, \"spec\")=\n .. .. cols(\n .. .. Date = col_character(),\n .. .. `real Temperature` = col_double(),\n .. .. `empty column` = col_logical(),\n .. .. `Feel Temperature` = col_double(),\n .. .. Humidity = col_double(),\n .. .. `Wind Speed` = col_double(),\n .. .. `weather code` = col_character(),\n .. .. `DO NOT TOUCH THIS COLUMN` = col_logical(),\n .. .. `is holiday` = col_logical(),\n .. .. `is weekend` = col_logical(),\n .. .. season = col_character(),\n .. .. count = col_double()\n .. .. )\n ..- attr(*, \"problems\")=\n \n
\n \n \n\n pclass \n survived \n name_of_passenger \n sex_of_passenger \n age_of_passenger \n imputed_age_of_passenger \n sibsp \n parch \n ticket \n fare \n cabin \n embarked \n \n \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n 24160 \n 211.3375 \n B5 \n S \n \n \n 1 \n 1 \n Allison, Master. Hudson Trevor \n male \n 0.9167 \n 0.91670 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 0 \n Allison, Miss. Helen Loraine \n female \n 2.0000 \n 2.00000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n male \n 30.0000 \n 30.00000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n female \n 25.0000 \n 25.00000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 1 \n Anderson, Mr. Harry \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n 19952 \n 26.5500 \n E12 \n S \n \n \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n female \n 63.0000 \n 63.00000 \n 1 \n 0 \n 13502 \n 77.9583 \n D7 \n S \n \n \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n male \n NA \n 29.79431 \n 0 \n 0 \n 112050 \n 0.0000 \n A36 \n S \n \n \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n female \n NA \n 29.79431 \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17609 \n 49.5042 \n NA \n C \n \n \n 1 \n 0 \n Astor, Col. John Jacob \n male \n NA \n 29.79431 \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n 19877 \n 78.8500 \n NA \n S \n \n \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n male \n 80.0000 \n 80.00000 \n 0 \n 0 \n 27042 \n 30.0000 \n A23 \n S \n \n \n 1 \n 0 \n Baumann, Mr. John D \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17318 \n 25.9250 \n NA \n S \n \n \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n male \n 24.0000 \n 24.00000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n female \n 50.0000 \n 50.00000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n 1 \n 1 \n Bazzani, Miss. Albina \n female \n 32.0000 \n 32.00000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n 1 \n 0 \n Beattie, Mr. Thomson \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n male \n 37.0000 \n 37.00000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n female \n 47.0000 \n 47.00000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n 1 \n 1 \n Behr, Mr. Karl Howell \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 111369 \n 30.0000 \n C148 \n C \n \n \n 1 \n 1 \n Bidois, Miss. Rosalie \n female \n 42.0000 \n 42.00000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n 1 \n 1 \n Bird, Miss. Ellen \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n PC 17483 \n 221.7792 \n C97 \n S \n \n \n 1 \n 0 \n Birnbaum, Mr. Jakob \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 13905 \n 26.0000 \n NA \n C \n \n \n 1 \n 1 \n Bishop, Mr. Dickinson H \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n 1 \n 1 \n Bissette, Miss. Amelia \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C99 \n S \n \n \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 110564 \n 26.5500 \n C52 \n S \n \n \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 113784 \n 35.5000 \n T \n S \n \n \n 1 \n 1 \n Blank, Mr. Henry \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 112277 \n 31.0000 \n A31 \n C \n \n \n 1 \n 1 \n Bonnell, Miss. Caroline \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 36928 \n 164.8667 \n C7 \n S \n \n \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n female \n 58.0000 \n 58.00000 \n 0 \n 0 \n 113783 \n 26.5500 \n C103 \n S \n \n \n 1 \n 0 \n Borebank, Mr. John James \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 110489 \n 26.5500 \n D22 \n S \n \n \n 1 \n 1 \n Bowen, Miss. Grace Scott \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n NA \n C \n \n \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n female \n 22.0000 \n 22.00000 \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n male \n NA \n 29.79431 \n 0 \n 0 \n 111427 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Brady, Mr. John Bertram \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n 113054 \n 30.5000 \n A21 \n S \n \n \n 1 \n 0 \n Brandeis, Mr. Emil \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n PC 17591 \n 50.4958 \n B10 \n C \n \n \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n male \n NA \n 29.79431 \n 0 \n 0 \n 112379 \n 39.6000 \n NA \n C \n \n \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n female \n 44.0000 \n 44.00000 \n 0 \n 0 \n PC 17610 \n 27.7208 \n B4 \n C \n \n \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n female \n 59.0000 \n 59.00000 \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n female \n 60.0000 \n 60.00000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n female \n 41.0000 \n 41.00000 \n 0 \n 0 \n 16966 \n 134.5000 \n E40 \n C \n \n \n 1 \n 0 \n Butt, Major. Archibald Willingham \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 113050 \n 26.5500 \n B38 \n S \n \n \n 1 \n 0 \n Cairns, Mr. Alexander \n male \n NA \n 29.79431 \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n S \n \n \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n PC 17476 \n 26.2875 \n E24 \n S \n \n \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n female \n 53.0000 \n 53.00000 \n 0 \n 0 \n PC 17606 \n 27.4458 \n NA \n C \n \n \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n male \n 36.0000 \n 36.00000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n female \n 58.0000 \n 58.00000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 695 \n 5.0000 \n B51 B53 B55 \n S \n \n \n 1 \n 0 \n Carrau, Mr. Francisco M \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n 1 \n 1 \n Carter, Master. William Thornton II \n male \n 11.0000 \n 11.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 1 \n Carter, Miss. Lucile Polk \n female \n 14.0000 \n 14.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 1 \n Carter, Mr. William Ernest \n male \n 36.0000 \n 36.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n female \n 36.0000 \n 36.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 0 \n Case, Mr. Howard Brown \n male \n 49.0000 \n 49.00000 \n 0 \n 0 \n 19924 \n 26.0000 \n NA \n S \n \n \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n female \n NA \n 29.79431 \n 0 \n 0 \n 17770 \n 27.7208 \n NA \n C \n \n \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n female \n 76.0000 \n 76.00000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n female \n 47.0000 \n 47.00000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n female \n 33.0000 \n 33.00000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n 1 \n 1 \n Chaudanson, Miss. Victorine \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n B61 \n C \n \n \n 1 \n 1 \n Cherry, Miss. Gladys \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n PC 17594 \n 29.7000 \n A9 \n C \n \n \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n female \n NA \n 29.79431 \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n male \n NA \n 29.79431 \n 0 \n 0 \n 112051 \n 0.0000 \n NA \n S \n \n \n 1 \n 0 \n Clark, Mr. Walter Miller \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n female \n 26.0000 \n 26.00000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n 1 \n 1 \n Cleaver, Miss. Alice \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n 1 \n 0 \n Clifford, Mr. George Quincy \n male \n NA \n 29.79431 \n 0 \n 0 \n 110465 \n 52.0000 \n A14 \n S \n \n \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 5727 \n 25.5875 \n E58 \n S \n \n \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E49 \n C \n \n \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n male \n 37.0000 \n 37.00000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E52 \n C \n \n \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n female \n 64.0000 \n 64.00000 \n 0 \n 2 \n PC 17756 \n 83.1583 \n E45 \n C \n \n \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n female \n 55.0000 \n 55.00000 \n 2 \n 0 \n 11770 \n 25.7000 \n C101 \n S \n \n \n 1 \n 0 \n Crafton, Mr. John Bertram \n male \n NA \n 29.79431 \n 0 \n 0 \n 113791 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n male \n 70.0000 \n 70.00000 \n 1 \n 1 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n 1 \n 1 \n Crosby, Miss. Harriet R \n female \n 36.0000 \n 36.00000 \n 0 \n 2 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n female \n 64.0000 \n 64.00000 \n 1 \n 1 \n 112901 \n 26.5500 \n B26 \n S \n \n \n 1 \n 0 \n Cumings, Mr. John Bradley \n male \n 39.0000 \n 39.00000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n female \n 38.0000 \n 38.00000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n 1 \n 1 \n Daly, Mr. Peter Denis \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 113055 \n 26.5500 \n E17 \n S \n \n \n 1 \n 1 \n Daniel, Mr. Robert Williams \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 113804 \n 30.5000 \n NA \n S \n \n \n 1 \n 1 \n Daniels, Miss. Sarah \n female \n 33.0000 \n 33.00000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n 1 \n 0 \n Davidson, Mr. Thornton \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n female \n 27.0000 \n 27.00000 \n 1 \n 2 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n 1 \n 1 \n Dick, Mr. Albert Adrian \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n female \n 17.0000 \n 17.00000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n 1 \n 1 \n Dodge, Dr. Washington \n male \n 53.0000 \n 53.00000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n 1 \n 1 \n Dodge, Master. Washington \n male \n 4.0000 \n 4.00000 \n 0 \n 2 \n 33638 \n 81.8583 \n A34 \n S \n \n \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n 1 \n 0 \n Douglas, Mr. Walter Donald \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n female \n 27.0000 \n 27.00000 \n 1 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n female \n 48.0000 \n 48.00000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n female \n 48.0000 \n 48.00000 \n 1 \n 0 \n 11755 \n 39.6000 \n A16 \n C \n \n \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n PC 17485 \n 56.9292 \n A20 \n C \n \n \n 1 \n 0 \n Dulles, Mr. William Crothers \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n PC 17580 \n 29.7000 \n A18 \n C \n \n \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n female \n 23.0000 \n 23.00000 \n 0 \n 1 \n 11767 \n 83.1583 \n C54 \n C \n \n \n 1 \n 1 \n Endres, Miss. Caroline Louise \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n C45 \n C \n \n \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n female \n 54.0000 \n 54.00000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n 1 \n 0 \n Evans, Miss. Edith Corse \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17531 \n 31.6792 \n A29 \n C \n \n \n 1 \n 0 \n Farthing, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17483 \n 221.7792 \n C95 \n S \n \n \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n female \n NA \n 29.79431 \n 0 \n 0 \n PC 17598 \n 31.6833 \n NA \n S \n \n \n 1 \n 1 \n Fleming, Miss. Margaret \n female \n NA \n 29.79431 \n 0 \n 0 \n 17421 \n 110.8833 \n NA \n C \n \n \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17474 \n 26.3875 \n E25 \n S \n \n \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 113051 \n 27.7500 \n C111 \n C \n \n \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n female \n 24.0000 \n 24.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n female \n 28.0000 \n 28.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n female \n 23.0000 \n 23.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n male \n 19.0000 \n 19.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 0 \n Fortune, Mr. Mark \n male \n 64.0000 \n 64.00000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n female \n 60.0000 \n 60.00000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n PC 17485 \n 56.9292 \n E36 \n C \n \n \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n male \n NA \n 29.79431 \n 0 \n 0 \n 113778 \n 26.5500 \n D34 \n S \n \n \n 1 \n 1 \n Frauenthal, Dr. Henry William \n male \n 50.0000 \n 50.00000 \n 2 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n male \n 43.0000 \n 43.00000 \n 1 \n 0 \n 17765 \n 27.7208 \n D40 \n C \n \n \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n female \n NA \n 29.79431 \n 1 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n female \n 22.0000 \n 22.00000 \n 0 \n 2 \n 13568 \n 49.5000 \n B39 \n C \n \n \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n male \n 60.0000 \n 60.00000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n 1 \n 0 \n Fry, Mr. Richard \n male \n NA \n 29.79431 \n 0 \n 0 \n 112058 \n 0.0000 \n B102 \n S \n \n \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n 1 \n 0 \n Gee, Mr. Arthur H \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 111320 \n 38.5000 \n E63 \n S \n \n \n 1 \n 1 \n Geiger, Miss. Amalie \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n 113503 \n 211.5000 \n C130 \n C \n \n \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n female \n 22.0000 \n 22.00000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n female \n 45.0000 \n 45.00000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n 1 \n 0 \n Giglio, Mr. Victor \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B86 \n C \n \n \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n female \n NA \n 29.79431 \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n 1 \n 0 \n Goldschmidt, Mr. George B \n male \n 71.0000 \n 71.00000 \n 0 \n 0 \n PC 17754 \n 34.6542 \n A5 \n C \n \n \n 1 \n 1 \n Gracie, Col. Archibald IV \n male \n 53.0000 \n 53.00000 \n 0 \n 0 \n 113780 \n 28.5000 \n C51 \n C \n \n \n 1 \n 1 \n Graham, Miss. Margaret Edith \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 112053 \n 30.0000 \n B42 \n S \n \n \n 1 \n 0 \n Graham, Mr. George Edward \n male \n 38.0000 \n 38.00000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C91 \n S \n \n \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n female \n 58.0000 \n 58.00000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n 1 \n 1 \n Greenfield, Mr. William Bertram \n male \n 23.0000 \n 23.00000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n female \n 45.0000 \n 45.00000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B82 B84 \n C \n \n \n 1 \n 1 \n Harder, Mr. George Achilles \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n female \n 25.0000 \n 25.00000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n male \n 48.0000 \n 48.00000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n female \n 49.0000 \n 49.00000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n 1 \n 0 \n Harrington, Mr. Charles H \n male \n NA \n 29.79431 \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n 1 \n 0 \n Harrison, Mr. William \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 112059 \n 0.0000 \n B94 \n S \n \n \n 1 \n 1 \n Hassab, Mr. Hammad \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n PC 17572 \n 76.7292 \n D49 \n C \n \n \n 1 \n 1 \n Hawksford, Mr. Walter James \n male \n NA \n 29.79431 \n 0 \n 0 \n 16988 \n 30.0000 \n D45 \n S \n \n \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 11767 \n 83.1583 \n C54 \n C \n \n \n 1 \n 0 \n Hays, Mr. Charles Melville \n male \n 55.0000 \n 55.00000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n female \n 52.0000 \n 52.00000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n 1 \n 0 \n Head, Mr. Christopher \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 113038 \n 42.5000 \n B11 \n S \n \n \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n male \n NA \n 29.79431 \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n 1 \n 0 \n Hipkins, Mr. William Edward \n male \n 55.0000 \n 55.00000 \n 0 \n 0 \n 680 \n 50.0000 \n C39 \n S \n \n \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n female \n 16.0000 \n 16.00000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n female \n 44.0000 \n 44.00000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n female \n 51.0000 \n 51.00000 \n 1 \n 0 \n 13502 \n 77.9583 \n D11 \n S \n \n \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 111426 \n 26.5500 \n NA \n C \n \n \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n 1 \n 0 \n Hoyt, Mr. William Fisher \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17600 \n 30.6958 \n NA \n C \n \n \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n 1 \n 1 \n Icard, Miss. Amelie \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n female \n 50.0000 \n 50.00000 \n 0 \n 0 \n PC 17595 \n 28.7125 \n C49 \n C \n \n \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n male \n 49.0000 \n 49.00000 \n 0 \n 0 \n 112058 \n 0.0000 \n B52 B54 B56 \n S \n \n \n 1 \n 0 \n Jones, Mr. Charles Cresson \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n 694 \n 26.0000 \n NA \n S \n \n \n 1 \n 0 \n Julian, Mr. Henry Forbes \n male \n 50.0000 \n 50.00000 \n 0 \n 0 \n 113044 \n 26.0000 \n E60 \n S \n \n \n 1 \n 0 \n Keeping, Mr. Edwin \n male \n 32.5000 \n 32.50000 \n 0 \n 0 \n 113503 \n 211.5000 \n C132 \n C \n \n \n 1 \n 0 \n Kent, Mr. Edward Austin \n male \n 58.0000 \n 58.00000 \n 0 \n 0 \n 11771 \n 29.7000 \n B37 \n C \n \n \n 1 \n 0 \n Kenyon, Mr. Frederick R \n male \n 41.0000 \n 41.00000 \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n female \n NA \n 29.79431 \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n female \n 45.0000 \n 45.00000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n 1 \n 0 \n Klaber, Mr. Herman \n male \n NA \n 29.79431 \n 0 \n 0 \n 113028 \n 26.5500 \n C124 \n S \n \n \n 1 \n 1 \n Kreuchen, Miss. Emilie \n female \n 39.0000 \n 39.00000 \n 0 \n 0 \n 24160 \n 211.3375 \n NA \n S \n \n \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n female \n 49.0000 \n 49.00000 \n 0 \n 0 \n 17465 \n 25.9292 \n D17 \n S \n \n \n 1 \n 1 \n LeRoy, Miss. Bertha \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n PC 17761 \n 106.4250 \n NA \n C \n \n \n 1 \n 1 \n Lesurer, Mr. Gustave J \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n B101 \n C \n \n \n 1 \n 0 \n Lewy, Mr. Ervin G \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17612 \n 27.7208 \n NA \n C \n \n \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 17475 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n female \n 55.0000 \n 55.00000 \n 0 \n 0 \n 112377 \n 27.7208 \n NA \n C \n \n \n 1 \n 1 \n Lines, Miss. Mary Conover \n female \n 16.0000 \n 16.00000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n female \n 51.0000 \n 51.00000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n 1 \n 0 \n Long, Mr. Milton Clyde \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 113501 \n 30.0000 \n D6 \n S \n \n \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 13502 \n 77.9583 \n D9 \n S \n \n \n 1 \n 0 \n Loring, Mr. Joseph Holland \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 113801 \n 45.5000 \n NA \n S \n \n \n 1 \n 1 \n Lurette, Miss. Elise \n female \n 58.0000 \n 58.00000 \n 0 \n 0 \n PC 17569 \n 146.5208 \n B80 \n C \n \n \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n female \n 15.0000 \n 15.00000 \n 0 \n 1 \n 24160 \n 211.3375 \n B5 \n S \n \n \n 1 \n 0 \n Maguire, Mr. John Edward \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 110469 \n 26.0000 \n C106 \n S \n \n \n 1 \n 1 \n Maioni, Miss. Roberta \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 110152 \n 86.5000 \n B79 \n S \n \n \n 1 \n 1 \n Marechal, Mr. Pierre \n male \n NA \n 29.79431 \n 0 \n 0 \n 11774 \n 29.7000 \n C47 \n C \n \n \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n male \n 19.0000 \n 19.00000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17482 \n 49.5042 \n C90 \n C \n \n \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n 1 \n 0 \n McCarthy, Mr. Timothy J \n male \n 54.0000 \n 54.00000 \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n 1 \n 1 \n McGough, Mr. James Robert \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17473 \n 26.2875 \n E25 \n S \n \n \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n female \n NA \n 29.79431 \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n 1 \n 0 \n Millet, Mr. Francis Davis \n male \n 65.0000 \n 65.00000 \n 0 \n 0 \n 13509 \n 26.5500 \n E38 \n S \n \n \n 1 \n 0 \n Minahan, Dr. William Edward \n male \n 44.0000 \n 44.00000 \n 2 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n 1 \n 1 \n Minahan, Miss. Daisy E \n female \n 33.0000 \n 33.00000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n female \n 37.0000 \n 37.00000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n 13236 \n 57.7500 \n C78 \n C \n \n \n 1 \n 0 \n Molson, Mr. Harry Markland \n male \n 55.0000 \n 55.00000 \n 0 \n 0 \n 113787 \n 30.5000 \n C30 \n S \n \n \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n 1 \n 0 \n Natsch, Mr. Charles H \n male \n 37.0000 \n 37.00000 \n 0 \n 1 \n PC 17596 \n 29.7000 \n C118 \n C \n \n \n 1 \n 1 \n Newell, Miss. Madeleine \n female \n 31.0000 \n 31.00000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n 1 \n 1 \n Newell, Miss. Marjorie \n female \n 23.0000 \n 23.00000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n 1 \n 0 \n Newell, Mr. Arthur Webster \n male \n 58.0000 \n 58.00000 \n 0 \n 2 \n 35273 \n 113.2750 \n D48 \n C \n \n \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n female \n 19.0000 \n 19.00000 \n 0 \n 2 \n 11752 \n 26.2833 \n D47 \n S \n \n \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n male \n 64.0000 \n 64.00000 \n 0 \n 0 \n 693 \n 26.0000 \n NA \n S \n \n \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n female \n 39.0000 \n 39.00000 \n 0 \n 0 \n PC 17758 \n 108.9000 \n C105 \n C \n \n \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n male \n NA \n 29.79431 \n 0 \n 0 \n F.C. 12998 \n 25.7417 \n NA \n C \n \n \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n female \n 22.0000 \n 22.00000 \n 0 \n 1 \n 113509 \n 61.9792 \n B36 \n C \n \n \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n male \n 65.0000 \n 65.00000 \n 0 \n 1 \n 113509 \n 61.9792 \n B30 \n C \n \n \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n male \n 28.5000 \n 28.50000 \n 0 \n 0 \n PC 17562 \n 27.7208 \n D43 \n C \n \n \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n male \n NA \n 29.79431 \n 0 \n 0 \n 112052 \n 0.0000 \n NA \n S \n \n \n 1 \n 0 \n Partner, Mr. Austen \n male \n 45.5000 \n 45.50000 \n 0 \n 0 \n 113043 \n 28.5000 \n C124 \n S \n \n \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 12749 \n 93.5000 \n B24 \n S \n \n \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n female \n 22.0000 \n 22.00000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n female \n 17.0000 \n 17.00000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n 1 \n 1 \n Perreault, Miss. Anne \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 12749 \n 93.5000 \n B73 \n S \n \n \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n male \n 52.0000 \n 52.00000 \n 0 \n 0 \n 113786 \n 30.5000 \n C104 \n S \n \n \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 110465 \n 52.0000 \n C110 \n S \n \n \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n female \n 56.0000 \n 56.00000 \n 0 \n 1 \n 11767 \n 83.1583 \n C50 \n C \n \n \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n 19972 \n 0.0000 \n NA \n S \n \n \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17607 \n 39.6000 \n NA \n S \n \n \n 1 \n 0 \n Ringhini, Mr. Sante \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n NA \n C \n \n \n 1 \n 0 \n Robbins, Mr. Victor \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n female \n 43.0000 \n 43.00000 \n 0 \n 1 \n 24160 \n 211.3375 \n B3 \n S \n \n \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n PC 17590 \n 50.4958 \n A24 \n S \n \n \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 111428 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n male \n NA \n 29.79431 \n 0 \n 0 \n 113767 \n 50.0000 \n A32 \n S \n \n \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n female \n 33.0000 \n 33.00000 \n 0 \n 0 \n PC 17613 \n 27.7208 \n A11 \n C \n \n \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n 1 \n 0 \n Ross, Mr. John Hugo \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 13049 \n 40.1250 \n A10 \n C \n \n \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n female \n 33.0000 \n 33.00000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n 1 \n 0 \n Rothschild, Mr. Martin \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n female \n 54.0000 \n 54.00000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n 1 \n 0 \n Rowe, Mr. Alfred G \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 113790 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Ryerson, Master. John Borie \n male \n 13.0000 \n 13.00000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n female \n 18.0000 \n 18.00000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n female \n 21.0000 \n 21.00000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n male \n 61.0000 \n 61.00000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n female \n 48.0000 \n 48.00000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n male \n NA \n 29.79431 \n 0 \n 0 \n 19988 \n 30.5000 \n C106 \n S \n \n \n 1 \n 1 \n Sagesser, Mlle. Emma \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n 1 \n 1 \n Salomon, Mr. Abraham L \n male \n NA \n 29.79431 \n 0 \n 0 \n 111163 \n 26.0000 \n NA \n S \n \n \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 13236 \n 57.7500 \n C28 \n C \n \n \n 1 \n 1 \n Serepeca, Miss. Augusta \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n C \n \n \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 113794 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n female \n 40.0000 \n 40.00000 \n 0 \n 0 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17475 \n 26.2875 \n E24 \n S \n \n \n 1 \n 0 \n Silvey, Mr. William Baird \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n female \n 39.0000 \n 39.00000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n male \n 56.0000 \n 56.00000 \n 0 \n 0 \n 13213 \n 35.5000 \n A26 \n C \n \n \n 1 \n 1 \n Sloper, Mr. William Thompson \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 113788 \n 35.5000 \n A6 \n S \n \n \n 1 \n 0 \n Smart, Mr. John Montgomery \n male \n 56.0000 \n 56.00000 \n 0 \n 0 \n 113792 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Smith, Mr. James Clinch \n male \n 56.0000 \n 56.00000 \n 0 \n 0 \n 17764 \n 30.6958 \n A7 \n C \n \n \n 1 \n 0 \n Smith, Mr. Lucien Philip \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n 1 \n 0 \n Smith, Mr. Richard William \n male \n NA \n 29.79431 \n 0 \n 0 \n 113056 \n 26.0000 \n A19 \n S \n \n \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n female \n 23.0000 \n 23.00000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n 1 \n 1 \n Spedden, Master. Robert Douglas \n male \n 6.0000 \n 6.00000 \n 0 \n 2 \n 16966 \n 134.5000 \n E34 \n C \n \n \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n 1 \n 0 \n Spencer, Mr. William Augustus \n male \n 57.0000 \n 57.00000 \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n female \n NA \n 29.79431 \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 13214 \n 30.5000 \n B50 \n C \n \n \n 1 \n 0 \n Stead, Mr. William Thomas \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n 113514 \n 26.5500 \n C87 \n S \n \n \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n female \n 43.0000 \n 43.00000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n female \n 52.0000 \n 52.00000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n 1 \n 0 \n Stewart, Mr. Albert A \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17605 \n 27.7208 \n NA \n C \n \n \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n female \n 62.0000 \n 62.00000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n 1 \n 0 \n Straus, Mr. Isidor \n male \n 67.0000 \n 67.00000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n female \n 63.0000 \n 63.00000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n 1 \n 0 \n Sutton, Mr. Frederick \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 36963 \n 32.3208 \n D50 \n S \n \n \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n female \n 48.0000 \n 48.00000 \n 0 \n 0 \n 17466 \n 25.9292 \n D17 \n S \n \n \n 1 \n 1 \n Taussig, Miss. Ruth \n female \n 18.0000 \n 18.00000 \n 0 \n 2 \n 110413 \n 79.6500 \n E68 \n S \n \n \n 1 \n 0 \n Taussig, Mr. Emil \n male \n 52.0000 \n 52.00000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n male \n 48.0000 \n 48.00000 \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n female \n NA \n 29.79431 \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n 1 \n 0 \n Thayer, Mr. John Borland \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n male \n 17.0000 \n 17.00000 \n 0 \n 2 \n 17421 \n 110.8833 \n C70 \n C \n \n \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n female \n NA \n 29.79431 \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 2543 \n 28.5375 \n C53 \n C \n \n \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n PC 17601 \n 27.7208 \n NA \n C \n \n \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 111240 \n 33.5000 \n B19 \n S \n \n \n 1 \n 0 \n Walker, Mr. William Anderson \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 36967 \n 34.0208 \n D46 \n S \n \n \n 1 \n 1 \n Ward, Miss. Anna \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n NA \n C \n \n \n 1 \n 0 \n Warren, Mr. Frank Manley \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n female \n 60.0000 \n 60.00000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n 1 \n 0 \n Weir, Col. John \n male \n 60.0000 \n 60.00000 \n 0 \n 0 \n 113800 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n White, Mr. Percival Wayland \n male \n 54.0000 \n 54.00000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n 1 \n 0 \n White, Mr. Richard Frasar \n male \n 21.0000 \n 21.00000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n female \n 55.0000 \n 55.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n 1 \n 1 \n Wick, Miss. Mary Natalie \n female \n 31.0000 \n 31.00000 \n 0 \n 2 \n 36928 \n 164.8667 \n C7 \n S \n \n \n 1 \n 0 \n Wick, Mr. George Dennick \n male \n 57.0000 \n 57.00000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n 1 \n 0 \n Widener, Mr. George Dunton \n male \n 50.0000 \n 50.00000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n 1 \n 0 \n Widener, Mr. Harry Elkins \n male \n 27.0000 \n 27.00000 \n 0 \n 2 \n 113503 \n 211.5000 \n C82 \n C \n \n \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n female \n 50.0000 \n 50.00000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n 1 \n 1 \n Willard, Miss. Constance \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 113795 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Williams, Mr. Charles Duane \n male \n 51.0000 \n 51.00000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n 1 \n 1 \n Williams, Mr. Richard Norris II \n male \n 21.0000 \n 21.00000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n male \n NA \n 29.79431 \n 0 \n 0 \n 113510 \n 35.0000 \n C128 \n S \n \n \n 1 \n 1 \n Wilson, Miss. Helen Alice \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n 16966 \n 134.5000 \n E39 E41 \n C \n \n \n 1 \n 1 \n Woolner, Mr. Hugh \n male \n NA \n 29.79431 \n 0 \n 0 \n 19947 \n 35.5000 \n C52 \n S \n \n \n 1 \n 0 \n Wright, Mr. George \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n 113807 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Young, Miss. Marie Grice \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n 2 \n 0 \n Abelson, Mr. Samuel \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n female \n 28.0000 \n 28.00000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 248744 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 231945 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n C.A. 34050 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Angle, Mr. William A \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n female \n 36.0000 \n 36.00000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Ashby, Mr. John \n male \n 57.0000 \n 57.00000 \n 0 \n 0 \n 244346 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 29108 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n C.A. 31030 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n 28551 \n 13.0000 \n D \n S \n \n \n 2 \n 0 \n Banfield, Mr. Frederick James \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n C.A./SOTON 34068 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Bateman, Rev. Robert James \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n S.O.P. 1166 \n 12.5250 \n NA \n S \n \n \n 2 \n 1 \n Beane, Mr. Edward \n male \n 32.0000 \n 32.00000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Beauchamp, Mr. Henry James \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Becker, Master. Richard F \n male \n 1.0000 \n 1.00000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Becker, Miss. Marion Louise \n female \n 4.0000 \n 4.00000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n female \n 12.0000 \n 12.00000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n female \n 36.0000 \n 36.00000 \n 0 \n 3 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Beesley, Mr. Lawrence \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 248698 \n 13.0000 \n D56 \n S \n \n \n 2 \n 1 \n Bentham, Miss. Lilian W \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28404 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Berriman, Mr. William John \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 28425 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Botsford, Mr. William Hull \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 237670 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Bowenur, Mr. Solomon \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 211535 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Bracken, Mr. James H \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 220367 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 248733 \n 13.0000 \n F33 \n S \n \n \n 2 \n 1 \n Brown, Miss. Edith Eileen \n female \n 15.0000 \n 15.00000 \n 0 \n 2 \n 29750 \n 39.0000 \n NA \n S \n \n \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n male \n 60.0000 \n 60.00000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n female \n 20.0000 \n 20.00000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Buss, Miss. Kate \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n 27849 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 234686 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 244310 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n female \n 42.0000 \n 42.00000 \n 0 \n 0 \n 236852 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Caldwell, Master. Alden Gates \n male \n 0.8333 \n 0.83330 \n 0 \n 2 \n 248738 \n 29.0000 \n NA \n S \n \n \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n male \n 26.0000 \n 26.00000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n 2 \n 1 \n Cameron, Miss. Clear Annie \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Campbell, Mr. William \n male \n NA \n 29.79431 \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n 2 \n 0 \n Carbines, Mr. William \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28424 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n female \n 44.0000 \n 44.00000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Chapman, Mr. Charles Henry \n male \n 52.0000 \n 52.00000 \n 0 \n 0 \n 248731 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Chapman, Mr. John Henry \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Christy, Miss. Julie Rachel \n female \n 25.0000 \n 25.00000 \n 1 \n 1 \n 237789 \n 30.0000 \n NA \n S \n \n \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n female \n 45.0000 \n 45.00000 \n 0 \n 2 \n 237789 \n 30.0000 \n NA \n S \n \n \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n female \n 28.0000 \n 28.00000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n W./C. 14263 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 248740 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 28034 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n female \n 8.0000 \n 8.00000 \n 0 \n 2 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n 2 \n 0 \n Collyer, Mr. Harvey \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n W./C. 14266 \n 10.5000 \n F33 \n S \n \n \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 237249 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n female \n NA \n 29.79431 \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 29107 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n male \n NA \n 29.79431 \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n 2 \n 1 \n Davies, Master. John Morgan Jr \n male \n 8.0000 \n 8.00000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 0 \n Davies, Mr. Charles Henry \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n female \n 48.0000 \n 48.00000 \n 0 \n 2 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 1 \n Davis, Miss. Mary \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 237668 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 244360 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Deacon, Mr. Percy William \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n female \n 24.0000 \n 24.00000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n 2 \n 0 \n Denbury, Mr. Herbert \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n 2 \n 0 \n Dibden, Mr. William \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 1 \n Doling, Miss. Elsie \n female \n 18.0000 \n 18.00000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n female \n 34.0000 \n 34.00000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n 2 \n 0 \n Downton, Mr. William James \n male \n 54.0000 \n 54.00000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Drew, Master. Marshall Brines \n male \n 8.0000 \n 8.00000 \n 0 \n 2 \n 28220 \n 32.5000 \n NA \n S \n \n \n 2 \n 0 \n Drew, Mr. James Vivian \n male \n 42.0000 \n 42.00000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n female \n 34.0000 \n 34.00000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n 2 \n 1 \n Duran y More, Miss. Asuncion \n female \n 27.0000 \n 27.00000 \n 1 \n 0 \n SC/PARIS 2149 \n 13.8583 \n NA \n C \n \n \n 2 \n 1 \n Duran y More, Miss. Florentina \n female \n 30.0000 \n 30.00000 \n 1 \n 0 \n SC/PARIS 2148 \n 13.8583 \n NA \n C \n \n \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 29751 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Enander, Mr. Ingvar \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 236854 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 236171 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Faunthorpe, Mr. Harry \n male \n 40.0000 \n 40.00000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n C.A. 15185 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 229236 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n male \n NA \n 29.79431 \n 0 \n 0 \n 239854 \n 0.0000 \n NA \n S \n \n \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n 237671 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Fynney, Mr. Joseph J \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Gale, Mr. Harry \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Gale, Mr. Shadrach \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Garside, Miss. Ethel \n female \n 34.0000 \n 34.00000 \n 0 \n 0 \n 243880 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Gaskell, Mr. Alfred \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Gavey, Mr. Lawrence \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 31028 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Gilbert, Mr. William \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n C.A. 30769 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Giles, Mr. Edgar \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n 28133 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Giles, Mr. Frederick Edward \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n 28134 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Giles, Mr. Ralph \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 248726 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Gill, Mr. John William \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 233866 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Gillespie, Mr. William Henry \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 12233 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 250646 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Greenberg, Mr. Samuel \n male \n 52.0000 \n 52.00000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Hale, Mr. Reginald \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 250653 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Hamalainen, Master. Viljo \n male \n 0.6667 \n 0.66670 \n 1 \n 1 \n 250649 \n 14.5000 \n NA \n S \n \n \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n female \n 24.0000 \n 24.00000 \n 0 \n 2 \n 250649 \n 14.5000 \n NA \n S \n \n \n 2 \n 0 \n Harbeck, Mr. William H \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n 248746 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n female \n 6.0000 \n 6.00000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n 2 \n 0 \n Harper, Rev. John \n male \n 28.0000 \n 28.00000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n 2 \n 1 \n Harris, Mr. George \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n S.W./PP 752 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Harris, Mr. Walter \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n W/C 14208 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Hart, Miss. Eva Miriam \n female \n 7.0000 \n 7.00000 \n 0 \n 2 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n 2 \n 0 \n Hart, Mr. Benjamin \n male \n 43.0000 \n 43.00000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Herman, Miss. Alice \n female \n 24.0000 \n 24.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Herman, Miss. Kate \n female \n 24.0000 \n 24.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 0 \n Herman, Mr. Samuel \n male \n 49.0000 \n 49.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n female \n 48.0000 \n 48.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n female \n 55.0000 \n 55.00000 \n 0 \n 0 \n 248706 \n 16.0000 \n NA \n S \n \n \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n Hickman, Mr. Lewis \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n Hickman, Mr. Stanley George \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n Hiltunen, Miss. Marta \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n 250650 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n 29105 \n 23.0000 \n NA \n S \n \n \n 2 \n 0 \n Hocking, Mr. Richard George \n male \n 23.0000 \n 23.00000 \n 2 \n 1 \n 29104 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 242963 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n female \n 54.0000 \n 54.00000 \n 1 \n 3 \n 29105 \n 23.0000 \n NA \n S \n \n \n 2 \n 0 \n Hodges, Mr. Henry Price \n male \n 50.0000 \n 50.00000 \n 0 \n 0 \n 250643 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Hold, Mr. Stephen \n male \n 44.0000 \n 44.00000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 1 \n Hosono, Mr. Masabumi \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 237798 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Howard, Mr. Benjamin \n male \n 63.0000 \n 63.00000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n female \n 60.0000 \n 60.00000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Hunt, Mr. George Henry \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n SCO/W 1585 \n 12.2750 \n NA \n S \n \n \n 2 \n 1 \n Ilett, Miss. Bertha \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n SO/C 14885 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n 243847 \n 27.0000 \n NA \n S \n \n \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n 243847 \n 27.0000 \n NA \n S \n \n \n 2 \n 0 \n Jarvis, Mr. John Denzil \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 237565 \n 15.0000 \n NA \n S \n \n \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n male \n 22.0000 \n 22.00000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n C.A. 33111 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n SC/AH Basle 541 \n 13.7917 \n D \n C \n \n \n 2 \n 0 \n Kantor, Mr. Sinai \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n female \n 24.0000 \n 24.00000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Keane, Miss. Nora A \n female \n NA \n 29.79431 \n 0 \n 0 \n 226593 \n 12.3500 \n E101 \n Q \n \n \n 2 \n 0 \n Keane, Mr. Daniel \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 233734 \n 12.3500 \n NA \n Q \n \n \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n 223596 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n male \n 57.0000 \n 57.00000 \n 0 \n 0 \n 219533 \n 12.3500 \n NA \n Q \n \n \n 2 \n 0 \n Knight, Mr. Robert J \n male \n NA \n 29.79431 \n 0 \n 0 \n 239855 \n 0.0000 \n NA \n S \n \n \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n C.A. 18723 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Lahtinen, Rev. William \n male \n 30.0000 \n 30.00000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Lamb, Mr. John Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n 240261 \n 10.7083 \n NA \n Q \n \n \n 2 \n 1 \n Laroche, Miss. Louise \n female \n 1.0000 \n 1.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n female \n 3.0000 \n 3.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n male \n 25.0000 \n 25.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n female \n 22.0000 \n 22.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 1 \n Lehmann, Miss. Bertha \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n SC 1748 \n 12.0000 \n NA \n C \n \n \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n female \n NA \n 29.79431 \n 0 \n 0 \n 248727 \n 33.0000 \n NA \n S \n \n \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n female \n 34.0000 \n 34.00000 \n 0 \n 0 \n C.A. 34260 \n 10.5000 \n F33 \n S \n \n \n 2 \n 0 \n Levy, Mr. Rene Jacques \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n SC/Paris 2163 \n 12.8750 \n D \n C \n \n \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n C.A. 29566 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Lingane, Mr. John \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 235509 \n 12.3500 \n NA \n Q \n \n \n 2 \n 0 \n Louch, Mr. Charles Alexander \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n female \n 42.0000 \n 42.00000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Mack, Mrs. (Mary) \n female \n 57.0000 \n 57.00000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n E77 \n S \n \n \n 2 \n 0 \n Malachard, Mr. Noel \n male \n NA \n 29.79431 \n 0 \n 0 \n 237735 \n 15.0458 \n D \n C \n \n \n 2 \n 1 \n Mallet, Master. Andre \n male \n 1.0000 \n 1.00000 \n 0 \n 2 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n 2 \n 0 \n Mallet, Mr. Albert \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/A.3 2861 \n 15.5792 \n NA \n C \n \n \n 2 \n 0 \n Matthews, Mr. William John \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 28228 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 239059 \n 16.0000 \n NA \n S \n \n \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 237216 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n McCrie, Mr. James Matthew \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 233478 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n McKane, Mr. Peter David \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n female \n 13.0000 \n 13.00000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n female \n 41.0000 \n 41.00000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n 2 \n 1 \n Mellors, Mr. William John \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n SW/PP 751 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Meyer, Mr. August \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 248723 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Milling, Mr. Jacob Christian \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n 234360 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n male \n 70.0000 \n 70.00000 \n 0 \n 0 \n C.A. 24580 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Montvila, Rev. Juozas \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 211536 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Moraweck, Dr. Ernest \n male \n 54.0000 \n 54.00000 \n 0 \n 0 \n 29011 \n 14.0000 \n NA \n S \n \n \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Myles, Mr. Thomas Francis \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n 240276 \n 9.6875 \n NA \n Q \n \n \n 2 \n 0 \n Nasser, Mr. Nicholas \n male \n 32.5000 \n 32.50000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n female \n 14.0000 \n 14.00000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n 2 \n 1 \n Navratil, Master. Edmond Roger \n male \n 2.0000 \n 2.00000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n 2 \n 1 \n Navratil, Master. Michel M \n male \n 3.0000 \n 3.00000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n male \n 36.5000 \n 36.50000 \n 0 \n 2 \n 230080 \n 26.0000 \n F2 \n S \n \n \n 2 \n 0 \n Nesson, Mr. Israel \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 244368 \n 13.0000 \n F2 \n S \n \n \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n male \n 19.0000 \n 19.00000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 0 \n Norman, Mr. Robert Douglas \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 218629 \n 13.5000 \n NA \n S \n \n \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SC/PARIS 2166 \n 13.8625 \n D38 \n C \n \n \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n C.A. 29395 \n 10.5000 \n F33 \n S \n \n \n 2 \n 0 \n Otter, Mr. Richard \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 28213 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n W./C. 14260 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Padro y Manent, Mr. Julian \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/PARIS 2146 \n 13.8625 \n NA \n C \n \n \n 2 \n 0 \n Pain, Dr. Alfred \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 244278 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n SC/PARIS 2147 \n 13.8583 \n NA \n C \n \n \n 2 \n 0 \n Parker, Mr. Clifford Richard \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n SC 14888 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n male \n NA \n 29.79431 \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n female \n 50.0000 \n 50.00000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Pengelly, Mr. Frederick William \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28665 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Pernot, Mr. Rene \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/PARIS 2131 \n 15.0500 \n NA \n C \n \n \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n 237393 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n female \n 21.0000 \n 21.00000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Phillips, Mr. Escott Robert \n male \n 43.0000 \n 43.00000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n female \n 32.0000 \n 32.00000 \n 0 \n 0 \n 234604 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Ponesell, Mr. Martin \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n C.A. 34644 \n 12.7375 \n NA \n C \n \n \n 2 \n 0 \n Pulbaum, Mr. Franz \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n SC/PARIS 2168 \n 15.0333 \n NA \n C \n \n \n 2 \n 1 \n Quick, Miss. Phyllis May \n female \n 2.0000 \n 2.00000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Quick, Miss. Winifred Vera \n female \n 8.0000 \n 8.00000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n female \n 33.0000 \n 33.00000 \n 0 \n 2 \n 26360 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Reeves, Mr. David \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n C.A. 17248 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Renouf, Mr. Peter Henry \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 230434 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Richard, Mr. Emile \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n SC/PARIS 2133 \n 15.0458 \n NA \n C \n \n \n 2 \n 1 \n Richards, Master. George Sibley \n male \n 0.8333 \n 0.83330 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n 2 \n 1 \n Richards, Master. William Rowe \n male \n 3.0000 \n 3.00000 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n female \n 24.0000 \n 24.00000 \n 2 \n 3 \n 29106 \n 18.7500 \n NA \n S \n \n \n 2 \n 1 \n Ridsdale, Miss. Lucy \n female \n 50.0000 \n 50.00000 \n 0 \n 0 \n W./C. 14258 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28004 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Rugg, Miss. Emily \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n C.A. 31026 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Schmidt, Mr. August \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 248659 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 244361 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sharp, Mr. Percival James R \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n female \n 25.0000 \n 25.00000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n female \n 18.0000 \n 18.00000 \n 0 \n 2 \n 250652 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Sincock, Miss. Maude \n female \n 20.0000 \n 20.00000 \n 0 \n 0 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 1 \n Sinkkonen, Miss. Anna \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 250648 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n male \n 59.0000 \n 59.00000 \n 0 \n 0 \n 237442 \n 13.5000 \n NA \n S \n \n \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 234818 \n 12.3500 \n NA \n Q \n \n \n 2 \n 0 \n Slemen, Mr. Richard James \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 28206 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Smith, Miss. Marion Elsie \n female \n 40.0000 \n 40.00000 \n 0 \n 0 \n 31418 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n C.A. 29178 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n 237734 \n 15.0458 \n NA \n C \n \n \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n F.C.C. 13540 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Swane, Mr. George \n male \n 18.5000 \n 18.50000 \n 0 \n 0 \n 248734 \n 13.0000 \n F \n S \n \n \n 2 \n 0 \n Sweet, Mr. George Frederick \n male \n 14.0000 \n 14.00000 \n 0 \n 0 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Toomey, Miss. Ellen \n female \n 50.0000 \n 50.00000 \n 0 \n 0 \n F.C.C. 13531 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 233639 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 240929 \n 12.6500 \n NA \n S \n \n \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n female \n 27.0000 \n 27.00000 \n 0 \n 0 \n 34218 \n 10.5000 \n E101 \n S \n \n \n 2 \n 0 \n Turpin, Mr. William John Robert \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n female \n 27.0000 \n 27.00000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Veal, Mr. James \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 28221 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Walcroft, Miss. Nellie \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Ware, Mr. John James \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Ware, Mr. William Jeffery \n male \n 23.0000 \n 23.00000 \n 1 \n 0 \n 28666 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n male \n NA \n 29.79431 \n 0 \n 0 \n 239856 \n 0.0000 \n NA \n S \n \n \n 2 \n 1 \n Watt, Miss. Bertha J \n female \n 12.0000 \n 12.00000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n female \n 40.0000 \n 40.00000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n 2 \n 1 \n Webber, Miss. Susan \n female \n 32.5000 \n 32.50000 \n 0 \n 0 \n 27267 \n 13.0000 \n E101 \n S \n \n \n 2 \n 0 \n Weisz, Mr. Leopold \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Wells, Master. Ralph Lester \n male \n 2.0000 \n 2.00000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n Wells, Miss. Joan \n female \n 4.0000 \n 4.00000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n female \n 29.0000 \n 29.00000 \n 0 \n 2 \n 29103 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n West, Miss. Barbara J \n female \n 0.9167 \n 0.91670 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 1 \n West, Miss. Constance Mirium \n female \n 5.0000 \n 5.00000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 0 \n West, Mr. Edwy Arthur \n male \n 36.0000 \n 36.00000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n female \n 33.0000 \n 33.00000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 0 \n Wheadon, Mr. Edward H \n male \n 66.0000 \n 66.00000 \n 0 \n 0 \n C.A. 24579 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/PARIS 2159 \n 12.8750 \n NA \n S \n \n \n 2 \n 1 \n Wilhelms, Mr. Charles \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 244270 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Williams, Mr. Charles Eugene \n male \n NA \n 29.79431 \n 0 \n 0 \n 244373 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Wright, Miss. Marion \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n 220844 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 248747 \n 13.0000 \n NA \n S \n \n \n 3 \n 0 \n Abbing, Mr. Anthony \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n C.A. 5547 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n male \n 13.0000 \n 13.00000 \n 0 \n 2 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n male \n 16.0000 \n 16.00000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 348125 \n 7.6500 \n NA \n S \n \n \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 348122 \n 7.6500 \n F G63 \n S \n \n \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SOTON/O2 3101284 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 2657 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n C 7076 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Adams, Mr. John \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 341826 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n female \n 40.0000 \n 40.00000 \n 1 \n 0 \n 7546 \n 9.4750 \n NA \n S \n \n \n 3 \n 1 \n Aks, Master. Philip Frank \n male \n 0.8333 \n 0.83330 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n female \n 18.0000 \n 18.00000 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n 3 \n 0 \n Alexander, Mr. William \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 3474 \n 7.8875 \n NA \n S \n \n \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SOTON/O2 3101287 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Ali, Mr. Ahmed \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n SOTON/O.Q. 3101311 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Ali, Mr. William \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n SOTON/O.Q. 3101312 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Allen, Mr. William Henry \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 373450 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Allum, Mr. Owen George \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 2223 \n 8.3000 \n NA \n S \n \n \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 350046 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n male \n 4.0000 \n 4.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n female \n 6.0000 \n 6.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n female \n 2.0000 \n 2.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n female \n 17.0000 \n 17.00000 \n 4 \n 2 \n 3101281 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n female \n 38.0000 \n 38.00000 \n 4 \n 2 \n 347091 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n female \n 9.0000 \n 9.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n female \n 11.0000 \n 11.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Mr. Anders Johan \n male \n 39.0000 \n 39.00000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 350043 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347075 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n female \n 39.0000 \n 39.00000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 347466 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Angheloff, Mr. Minko \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 349202 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349911 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Asim, Mr. Adola \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n SOTON/O.Q. 3101310 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Master. Carl Edgar \n male \n 5.0000 \n 5.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n male \n 9.0000 \n 9.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n male \n 3.0000 \n 3.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Master. Filip Oscar \n male \n 13.0000 \n 13.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n female \n 5.0000 \n 5.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n male \n 40.0000 \n 40.00000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Mr. Johan Charles \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 350054 \n 7.7958 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n female \n 38.0000 \n 38.00000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n 2696 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Assaf, Mr. Gerios \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 2692 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Assam, Mr. Ali \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n SOTON/O.Q. 3101309 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Attalah, Miss. Malake \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Attalah, Mr. Sleiman \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 2694 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Augustsson, Mr. Albert \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 347468 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Ayoub, Miss. Banoura \n female \n 13.0000 \n 13.00000 \n 0 \n 0 \n 2687 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Baccos, Mr. Raffull \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 2679 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n male \n 32.0000 \n 32.00000 \n 1 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n female \n 33.0000 \n 33.00000 \n 3 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n 3 \n 1 \n Baclini, Miss. Eugenie \n female \n 0.7500 \n 0.75000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n female \n 0.7500 \n 0.75000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n female \n 5.0000 \n 5.00000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n female \n 24.0000 \n 24.00000 \n 0 \n 3 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Badman, Miss. Emily Louisa \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n A/4 31416 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Badt, Mr. Mohamed \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 2623 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Balkic, Mr. Cerin \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 349248 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Barah, Mr. Hanna Assi \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 2663 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Barbara, Miss. Saiide \n female \n 18.0000 \n 18.00000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n female \n 45.0000 \n 45.00000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Barry, Miss. Julia \n female \n 27.0000 \n 27.00000 \n 0 \n 0 \n 330844 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Barton, Mr. David John \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 324669 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Beavan, Mr. William Thomas \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 323951 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347068 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n PP 4348 \n 9.3500 \n NA \n S \n \n \n 3 \n 0 \n Betros, Master. Seman \n male \n NA \n 29.79431 \n 0 \n 0 \n 2622 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Betros, Mr. Tannous \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 2648 \n 4.0125 \n NA \n C \n \n \n 3 \n 1 \n Bing, Mr. Lee \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 312992 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347090 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 349224 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Boulos, Master. Akar \n male \n 6.0000 \n 6.00000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Boulos, Miss. Nourelain \n female \n 9.0000 \n 9.00000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Boulos, Mr. Hanna \n male \n NA \n 29.79431 \n 0 \n 0 \n 2664 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n female \n NA \n 29.79431 \n 0 \n 2 \n 2678 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Bourke, Miss. Mary \n female \n NA \n 29.79431 \n 0 \n 2 \n 364848 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Bourke, Mr. John \n male \n 40.0000 \n 40.00000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n female \n 32.0000 \n 32.00000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 334914 \n 7.7250 \n NA \n Q \n \n \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n female \n 20.0000 \n 20.00000 \n 0 \n 0 \n 347471 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Braund, Mr. Lewis Richard \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 3460 \n 7.0458 \n NA \n S \n \n \n 3 \n 0 \n Braund, Mr. Owen Harris \n male \n 22.0000 \n 22.00000 \n 1 \n 0 \n A/5 21171 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 350045 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 364512 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Buckley, Miss. Katherine \n female \n 18.5000 \n 18.50000 \n 0 \n 0 \n 329944 \n 7.2833 \n NA \n Q \n \n \n 3 \n 1 \n Buckley, Mr. Daniel \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 330920 \n 7.8208 \n NA \n Q \n \n \n 3 \n 0 \n Burke, Mr. Jeremiah \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 365222 \n 6.7500 \n NA \n Q \n \n \n 3 \n 0 \n Burns, Miss. Mary Delia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 330963 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Cacic, Miss. Manda \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 315087 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Cacic, Miss. Marija \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 315084 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Cacic, Mr. Jego Grga \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 315091 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Cacic, Mr. Luka \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n 315089 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Calic, Mr. Jovo \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315093 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Calic, Mr. Petar \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315086 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Canavan, Miss. Mary \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 364846 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Canavan, Mr. Patrick \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 364858 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Cann, Mr. Ernest Charles \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A./5. 2152 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Caram, Mr. Joseph \n male \n NA \n 29.79431 \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n female \n NA \n 29.79431 \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 350042 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 350409 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 367231 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Carr, Miss. Jeannie \n female \n 37.0000 \n 37.00000 \n 0 \n 0 \n 368364 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Carver, Mr. Alfred John \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 392095 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Celotti, Mr. Francesco \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 343275 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Charters, Mr. David \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A/5. 13032 \n 7.7333 \n NA \n Q \n \n \n 3 \n 1 \n Chip, Mr. Chang \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Christmann, Mr. Emil \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 343276 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n male \n 26.0000 \n 26.00000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SOTON/O.Q. 3101307 \n 7.0500 \n NA \n S \n \n \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n A/5 3540 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Colbert, Mr. Patrick \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 371109 \n 7.2500 \n NA \n Q \n \n \n 3 \n 0 \n Coleff, Mr. Peju \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 349210 \n 7.4958 \n NA \n S \n \n \n 3 \n 0 \n Coleff, Mr. Satio \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349209 \n 7.4958 \n NA \n S \n \n \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 21332 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n Connaghton, Mr. Michael \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 335097 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Connolly, Miss. Kate \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 370373 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Connolly, Miss. Kate \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 330972 \n 7.6292 \n NA \n Q \n \n \n 3 \n 0 \n Connors, Mr. Patrick \n male \n 70.5000 \n 70.50000 \n 0 \n 0 \n 370369 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Cook, Mr. Jacob \n male \n 43.0000 \n 43.00000 \n 0 \n 0 \n A/5 3536 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Cor, Mr. Bartol \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 349230 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Cor, Mr. Ivan \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 349229 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Cor, Mr. Liudevit \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349231 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Corn, Mr. Harry \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n SOTON/OQ 392090 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n male \n 9.0000 \n 9.00000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n male \n 3.0000 \n 3.00000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n female \n 36.0000 \n 36.00000 \n 0 \n 2 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n 3 \n 0 \n Coxon, Mr. Daniel \n male \n 59.0000 \n 59.00000 \n 0 \n 0 \n 364500 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Crease, Mr. Ernest James \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n S.P. 3464 \n 8.1583 \n NA \n S \n \n \n 3 \n 1 \n Cribb, Miss. Laura Alice \n female \n 17.0000 \n 17.00000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Cribb, Mr. John Hatfield \n male \n 44.0000 \n 44.00000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Culumovic, Mr. Jeso \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315090 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Daher, Mr. Shedid \n male \n 22.5000 \n 22.50000 \n 0 \n 0 \n 2698 \n 7.2250 \n NA \n C \n \n \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 7598 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 7552 \n 10.5167 \n NA \n S \n \n \n 3 \n 0 \n Dakic, Mr. Branko \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349228 \n 10.1708 \n NA \n S \n \n \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 382650 \n 6.9500 \n NA \n Q \n \n \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 382651 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n male \n 0.3333 \n 0.33330 \n 0 \n 2 \n 347080 \n 14.4000 \n NA \n S \n \n \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n male \n 34.0000 \n 34.00000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n female \n 28.0000 \n 28.00000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n 3 \n 0 \n Danoff, Mr. Yoto \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 349219 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 349203 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. Alfred J \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. Evan \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n SC/A4 23568 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. John Samuel \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. Joseph \n male \n 17.0000 \n 17.00000 \n 2 \n 0 \n A/4 48873 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Davison, Mr. Thomas Henry \n male \n NA \n 29.79431 \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n female \n NA \n 29.79431 \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n male \n 36.5000 \n 36.50000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n female \n 36.0000 \n 36.00000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n 3 \n 1 \n de Mulder, Mr. Theodore \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 345774 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 345778 \n 9.5000 \n NA \n S \n \n \n 3 \n 1 \n Dean, Master. Bertram Vere \n male \n 1.0000 \n 1.00000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n female \n 0.1667 \n 0.16670 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 0 \n Dean, Mr. Bertram Frank \n male \n 26.0000 \n 26.00000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n female \n 33.0000 \n 33.00000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 0 \n Delalic, Mr. Redjo \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 349250 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Demetri, Mr. Marinko \n male \n NA \n 29.79431 \n 0 \n 0 \n 349238 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Denkoff, Mr. Mitto \n male \n NA \n 29.79431 \n 0 \n 0 \n 349225 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Dennis, Mr. Samuel \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n A/5 21172 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Dennis, Mr. William \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n A/5 21175 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 330958 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Dika, Mr. Mirko \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 349232 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Dimic, Mr. Jovan \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 315088 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n male \n 43.0000 \n 43.00000 \n 0 \n 0 \n 349226 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Doharr, Mr. Tannous \n male \n NA \n 29.79431 \n 0 \n 0 \n 2686 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Dooley, Mr. Patrick \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 370376 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n A/5. 10482 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n 3 \n 0 \n Doyle, Miss. Elizabeth \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 368702 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Drapkin, Miss. Jennie \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n SOTON/OQ 392083 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Drazenoic, Mr. Jozef \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 349241 \n 7.8958 \n NA \n C \n \n \n 3 \n 0 \n Duane, Mr. Frank \n male \n 65.0000 \n 65.00000 \n 0 \n 0 \n 336439 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Duquemin, Mr. Joseph \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n S.O./P.P. 752 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n male \n 23.0000 \n 23.00000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n female \n 22.0000 \n 22.00000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 349912 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Eklund, Mr. Hans Linus \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 347074 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Ekstrom, Mr. Johan \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 347061 \n 6.9750 \n NA \n S \n \n \n 3 \n 0 \n Elias, Mr. Dibo \n male \n NA \n 29.79431 \n 0 \n 0 \n 2674 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Elias, Mr. Joseph \n male \n 39.0000 \n 39.00000 \n 0 \n 2 \n 2675 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Elias, Mr. Joseph Jr \n male \n 17.0000 \n 17.00000 \n 1 \n 1 \n 2690 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Elias, Mr. Tannous \n male \n 15.0000 \n 15.00000 \n 1 \n 1 \n 2695 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Elsbury, Mr. William James \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n A/5 3902 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n female \n 5.0000 \n 5.00000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n 3 \n 0 \n Emir, Mr. Farred Chehab \n male \n NA \n 29.79431 \n 0 \n 0 \n 2631 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Everett, Mr. Thomas James \n male \n 40.5000 \n 40.50000 \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n 3 \n 0 \n Farrell, Mr. James \n male \n 40.5000 \n 40.50000 \n 0 \n 0 \n 367232 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Finoli, Mr. Luigi \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 3101308 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 350036 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Fleming, Miss. Honora \n female \n NA \n 29.79431 \n 0 \n 0 \n 364859 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Flynn, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n 364851 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Flynn, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 368323 \n 6.9500 \n NA \n Q \n \n \n 3 \n 0 \n Foley, Mr. Joseph \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 330910 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Foley, Mr. William \n male \n NA \n 29.79431 \n 0 \n 0 \n 365235 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Foo, Mr. Choong \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n female \n 21.0000 \n 21.00000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n female \n 9.0000 \n 9.00000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mr. Arthur \n male \n NA \n 29.79431 \n 0 \n 0 \n A/5 1478 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mr. Edward Watson \n male \n 18.0000 \n 18.00000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mr. William Neal \n male \n 16.0000 \n 16.00000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n female \n 48.0000 \n 48.00000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Fox, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 368573 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 3101314 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Gallagher, Mr. Martin \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 36864 \n 7.7417 \n NA \n Q \n \n \n 3 \n 0 \n Garfirth, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349254 \n 7.8958 \n NA \n C \n \n \n 3 \n 0 \n Gilinski, Mr. Eliezer \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 14973 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 35851 \n 7.7333 \n NA \n Q \n \n \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n female \n NA \n 29.79431 \n 0 \n 0 \n 335677 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n male \n 9.0000 \n 9.00000 \n 0 \n 2 \n 363291 \n 20.5250 \n NA \n S \n \n \n 3 \n 0 \n Goldsmith, Mr. Frank John \n male \n 33.0000 \n 33.00000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n 3 \n 0 \n Goldsmith, Mr. Nathan \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n SOTON/O.Q. 3101263 \n 7.8500 \n NA \n S \n \n \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n SOTON/O.Q. 3101306 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Master. Harold Victor \n male \n 9.0000 \n 9.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n male \n 1.0000 \n 1.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Master. William Frederick \n male \n 11.0000 \n 11.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n female \n 10.0000 \n 10.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n female \n 16.0000 \n 16.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n male \n 14.0000 \n 14.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n male \n 40.0000 \n 40.00000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n female \n 43.0000 \n 43.00000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Green, Mr. George Henry \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 21440 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 8471 \n 8.3625 \n NA \n S \n \n \n 3 \n 0 \n Guest, Mr. Robert \n male \n NA \n 29.79431 \n 0 \n 0 \n 376563 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 7534 \n 9.8458 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n male \n 37.0000 \n 37.00000 \n 2 \n 0 \n 3101276 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n 3101277 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 347069 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Haas, Miss. Aloisia \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349236 \n 8.8500 \n NA \n S \n \n \n 3 \n 0 \n Hagardon, Miss. Kate \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n AQ/3. 30631 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n male \n NA \n 29.79431 \n 1 \n 0 \n 65303 \n 19.9667 \n NA \n S \n \n \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n male \n NA \n 29.79431 \n 1 \n 0 \n 65304 \n 19.9667 \n NA \n S \n \n \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n female \n 24.0000 \n 24.00000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n 3 \n 0 \n Hampe, Mr. Leon \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 345769 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Hanna, Mr. Mansour \n male \n 23.5000 \n 23.50000 \n 0 \n 0 \n 2693 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Hansen, Mr. Claus Peter \n male \n 41.0000 \n 41.00000 \n 2 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n male \n 26.0000 \n 26.00000 \n 1 \n 0 \n 350025 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350029 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n female \n 45.0000 \n 45.00000 \n 1 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n female \n NA \n 29.79431 \n 0 \n 0 \n W./C. 6609 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 374887 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Hart, Mr. Henry \n male \n NA \n 29.79431 \n 0 \n 0 \n 394140 \n 6.8583 \n NA \n Q \n \n \n 3 \n 0 \n Hassan, Mr. Houssein G N \n male \n 11.0000 \n 11.00000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 370375 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 347089 \n 6.9750 \n NA \n S \n \n \n 3 \n 1 \n Hee, Mr. Ling \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 365226 \n 6.7500 \n NA \n Q \n \n \n 3 \n 1 \n Heikkinen, Miss. Laina \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n STON/O2. 3101282 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n STON/O2. 3101290 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 7548 \n 8.9625 \n NA \n S \n \n \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 349243 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 347086 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Henry, Miss. Delia \n female \n NA \n 29.79431 \n 0 \n 0 \n 382649 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n female \n 2.0000 \n 2.00000 \n 0 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n male \n 43.0000 \n 43.00000 \n 0 \n 0 \n C 7075 \n 6.4500 \n NA \n S \n \n \n 3 \n 0 \n Holthen, Mr. Johan Martin \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n 3 \n 1 \n Honkanen, Miss. Eliina \n female \n 27.0000 \n 27.00000 \n 0 \n 0 \n STON/O2. 3101283 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Horgan, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 370377 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Howard, Miss. May Elizabeth \n female \n NA \n 29.79431 \n 0 \n 0 \n A. 2. 39186 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 348121 \n 7.6500 \n F G63 \n S \n \n \n 3 \n 1 \n Hyman, Mr. Abraham \n male \n NA \n 29.79431 \n 0 \n 0 \n 3470 \n 7.8875 \n NA \n S \n \n \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 2685 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Ilieff, Mr. Ylio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349220 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n female \n 27.0000 \n 27.00000 \n 1 \n 0 \n STON/O2. 3101270 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n female \n 25.0000 \n 25.00000 \n 1 \n 0 \n STON/O2. 3101271 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Ivanoff, Mr. Kanio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349201 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Jalsevac, Mr. Ivan \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 349240 \n 7.8958 \n NA \n C \n \n \n 3 \n 1 \n Jansson, Mr. Carl Olof \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350034 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Jardin, Mr. Jose Neto \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 3101305 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Jensen, Mr. Hans Peder \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 350050 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jensen, Mr. Niels Peder \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n 350047 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n male \n 17.0000 \n 17.00000 \n 1 \n 0 \n 350048 \n 7.0542 \n NA \n S \n \n \n 3 \n 1 \n Jermyn, Miss. Annie \n female \n NA \n 29.79431 \n 0 \n 0 \n 14313 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n male \n NA \n 29.79431 \n 0 \n 0 \n 65306 \n 8.1125 \n NA \n S \n \n \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 3101264 \n 6.4958 \n NA \n S \n \n \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347070 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Erik \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 350052 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 7540 \n 8.6542 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Karl Johan \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 347063 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Nils \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 347467 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Johnson, Master. Harold Theodor \n male \n 4.0000 \n 4.00000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n female \n 1.0000 \n 1.00000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n 3 \n 0 \n Johnson, Mr. Alfred \n male \n 49.0000 \n 49.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 347062 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n female \n 27.0000 \n 27.00000 \n 0 \n 2 \n 347742 \n 11.1333 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n male \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n female \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Mr. Andrew G \n male \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n female \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Jonkoff, Mr. Lalio \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 349204 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Jonsson, Mr. Carl \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 350417 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 350408 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jussila, Miss. Katriina \n female \n 20.0000 \n 20.00000 \n 1 \n 0 \n 4136 \n 9.8250 \n NA \n S \n \n \n 3 \n 0 \n Jussila, Miss. Mari Aina \n female \n 21.0000 \n 21.00000 \n 1 \n 0 \n 4137 \n 9.8250 \n NA \n S \n \n \n 3 \n 1 \n Jussila, Mr. Eiriik \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/O 2. 3101286 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n STON/O 2. 3101274 \n 7.1250 \n NA \n S \n \n \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 8475 \n 8.4333 \n NA \n S \n \n \n 3 \n 0 \n Karaic, Mr. Milan \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 349246 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350053 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 347465 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Karlsson, Mr. Nils August \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 350060 \n 7.5208 \n NA \n S \n \n \n 3 \n 1 \n Karun, Miss. Manca \n female \n 4.0000 \n 4.00000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n 3 \n 1 \n Karun, Mr. Franz \n male \n 39.0000 \n 39.00000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n 3 \n 0 \n Kassem, Mr. Fared \n male \n NA \n 29.79431 \n 0 \n 0 \n 2700 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n male \n 18.5000 \n 18.50000 \n 0 \n 0 \n 2682 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n male \n NA \n 29.79431 \n 0 \n 0 \n 12460 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Keefe, Mr. Arthur \n male \n NA \n 29.79431 \n 0 \n 0 \n 323592 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 9234 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Kelly, Miss. Mary \n female \n NA \n 29.79431 \n 0 \n 0 \n 14312 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Kelly, Mr. James \n male \n 34.5000 \n 34.50000 \n 0 \n 0 \n 330911 \n 7.8292 \n NA \n Q \n \n \n 3 \n 0 \n Kelly, Mr. James \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n 363592 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Kennedy, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 368783 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Khalil, Mr. Betros \n male \n NA \n 29.79431 \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n female \n NA \n 29.79431 \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Kiernan, Mr. John \n male \n NA \n 29.79431 \n 1 \n 0 \n 367227 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Kiernan, Mr. Philip \n male \n NA \n 29.79431 \n 1 \n 0 \n 367229 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n male \n NA \n 29.79431 \n 0 \n 0 \n 36865 \n 7.7375 \n NA \n Q \n \n \n 3 \n 0 \n Kink, Miss. Maria \n female \n 22.0000 \n 22.00000 \n 2 \n 0 \n 315152 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Kink, Mr. Vincenz \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n 315151 \n 8.6625 \n NA \n S \n \n \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n female \n 4.0000 \n 4.00000 \n 0 \n 2 \n 315153 \n 22.0250 \n NA \n S \n \n \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n female \n 1.0000 \n 1.00000 \n 1 \n 1 \n 350405 \n 12.1833 \n NA \n S \n \n \n 3 \n 0 \n Klasen, Mr. Klas Albin \n male \n 18.0000 \n 18.00000 \n 1 \n 1 \n 350404 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n female \n 36.0000 \n 36.00000 \n 0 \n 2 \n 350405 \n 12.1833 \n NA \n S \n \n \n 3 \n 0 \n Kraeff, Mr. Theodor \n male \n NA \n 29.79431 \n 0 \n 0 \n 349253 \n 7.8958 \n NA \n C \n \n \n 3 \n 1 \n Krekorian, Mr. Neshan \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 2654 \n 7.2292 \n F E57 \n C \n \n \n 3 \n 0 \n Lahoud, Mr. Sarkis \n male \n NA \n 29.79431 \n 0 \n 0 \n 2624 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n female \n 37.0000 \n 37.00000 \n 0 \n 0 \n 4135 \n 9.5875 \n NA \n S \n \n \n 3 \n 0 \n Laleff, Mr. Kristo \n male \n NA \n 29.79431 \n 0 \n 0 \n 349217 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Lam, Mr. Ali \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Lam, Mr. Len \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n C 7077 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Lane, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 7935 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Lang, Mr. Fang \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Larsson, Mr. August Viktor \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 7545 \n 9.4833 \n NA \n S \n \n \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 347067 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 347065 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 2620 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n male \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Miss. Ida \n female \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Miss. Jeannie \n female \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Miss. Mathilde \n female \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n female \n NA \n 29.79431 \n 0 \n 4 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/O 2. 3101292 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n male \n 34.5000 \n 34.50000 \n 0 \n 0 \n 2683 \n 6.4375 \n NA \n C \n \n \n 3 \n 0 \n Lennon, Miss. Mary \n female \n NA \n 29.79431 \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Lennon, Mr. Denis \n male \n NA \n 29.79431 \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Leonard, Mr. Lionel \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 0 \n Lester, Mr. James \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Lievens, Mr. Rene Aime \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 345781 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n female \n 25.0000 \n 25.00000 \n 0 \n 0 \n 347071 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n 347073 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n female \n 30.0000 \n 30.00000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n 3 \n 1 \n Lindqvist, Mr. Eino William \n male \n 20.0000 \n 20.00000 \n 1 \n 0 \n STON/O 2. 3101285 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Linehan, Mr. Michael \n male \n NA \n 29.79431 \n 0 \n 0 \n 330971 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Ling, Mr. Lee \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Lithman, Mr. Simon \n male \n NA \n 29.79431 \n 0 \n 0 \n S.O./P.P. 251 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Lobb, Mr. William Arthur \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n female \n 26.0000 \n 26.00000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Lockyer, Mr. Edward \n male \n NA \n 29.79431 \n 0 \n 0 \n 1222 \n 7.8792 \n NA \n S \n \n \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n male \n 20.5000 \n 20.50000 \n 0 \n 0 \n A/5 21173 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Lulic, Mr. Nikola \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 315098 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 347743 \n 7.0542 \n NA \n S \n \n \n 3 \n 1 \n Lundin, Miss. Olga Elida \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n 347469 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 350403 \n 7.5792 \n NA \n S \n \n \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n male \n NA \n 29.79431 \n 0 \n 0 \n 349235 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n MacKay, Mr. George William \n male \n NA \n 29.79431 \n 0 \n 0 \n C.A. 42795 \n 7.5500 \n NA \n S \n \n \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 370370 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n C 17369 \n 7.1417 \n NA \n S \n \n \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n STON/O 2. 3101275 \n 7.1250 \n NA \n S \n \n \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n female \n NA \n 29.79431 \n 0 \n 0 \n 330924 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Mahon, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n AQ/4 3130 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Maisner, Mr. Simon \n male \n NA \n 29.79431 \n 0 \n 0 \n A/S 2816 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n STON/O 2. 3101268 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Mamee, Mr. Hanna \n male \n NA \n 29.79431 \n 0 \n 0 \n 2677 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Mangan, Miss. Mary \n female \n 30.5000 \n 30.50000 \n 0 \n 0 \n 364850 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Mannion, Miss. Margareth \n female \n NA \n 29.79431 \n 0 \n 0 \n 36866 \n 7.7375 \n NA \n Q \n \n \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n male \n NA \n 29.79431 \n 0 \n 0 \n 2655 \n 7.2292 \n F E46 \n C \n \n \n 3 \n 0 \n Markoff, Mr. Marin \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 349213 \n 7.8958 \n NA \n C \n \n \n 3 \n 0 \n Markun, Mr. Johann \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 349257 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Masselmani, Mrs. Fatima \n female \n NA \n 29.79431 \n 0 \n 0 \n 2649 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Matinoff, Mr. Nicola \n male \n NA \n 29.79431 \n 0 \n 0 \n 349255 \n 7.8958 \n NA \n C \n \n \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 383123 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n 367228 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n McCoy, Miss. Agnes \n female \n NA \n 29.79431 \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n 3 \n 1 \n McCoy, Miss. Alicia \n female \n NA \n 29.79431 \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n 3 \n 1 \n McCoy, Mr. Bernard \n male \n NA \n 29.79431 \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n female \n NA \n 29.79431 \n 0 \n 0 \n 330932 \n 7.7875 \n NA \n Q \n \n \n 3 \n 0 \n McEvoy, Mr. Michael \n male \n NA \n 29.79431 \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n 3 \n 1 \n McGovern, Miss. Mary \n female \n NA \n 29.79431 \n 0 \n 0 \n 330931 \n 7.8792 \n NA \n Q \n \n \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n female \n 15.0000 \n 15.00000 \n 0 \n 0 \n 330923 \n 8.0292 \n NA \n Q \n \n \n 3 \n 0 \n McGowan, Miss. Katherine \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n 9232 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n McMahon, Mr. Martin \n male \n NA \n 29.79431 \n 0 \n 0 \n 370372 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n McNamee, Mr. Neal \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n McNeill, Miss. Bridget \n female \n NA \n 29.79431 \n 0 \n 0 \n 370368 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n female \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 392087 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n female \n NA \n 29.79431 \n 0 \n 0 \n 343095 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Meo, Mr. Alfonzo \n male \n 55.5000 \n 55.50000 \n 0 \n 0 \n A.5. 11206 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Mernagh, Mr. Robert \n male \n NA \n 29.79431 \n 0 \n 0 \n 368703 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 345501 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Miles, Mr. Frank \n male \n NA \n 29.79431 \n 0 \n 0 \n 359306 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Mineff, Mr. Ivan \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349233 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Minkoff, Mr. Lazar \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 349211 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 349207 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Mitkoff, Mr. Mito \n male \n NA \n 29.79431 \n 0 \n 0 \n 349221 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 330980 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 348123 \n 7.6500 \n F G73 \n S \n \n \n 3 \n 1 \n Moor, Master. Meier \n male \n 6.0000 \n 6.00000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n 3 \n 1 \n Moor, Mrs. (Beila) \n female \n 27.0000 \n 27.00000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n 3 \n 0 \n Moore, Mr. Leonard Charles \n male \n NA \n 29.79431 \n 0 \n 0 \n A4. 54510 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Moran, Miss. Bertha \n female \n NA \n 29.79431 \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n 3 \n 0 \n Moran, Mr. Daniel J \n male \n NA \n 29.79431 \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n 3 \n 0 \n Moran, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n 330877 \n 8.4583 \n NA \n Q \n \n \n 3 \n 0 \n Morley, Mr. William \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 364506 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n male \n NA \n 29.79431 \n 0 \n 0 \n 372622 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Moss, Mr. Albert Johan \n male \n NA \n 29.79431 \n 0 \n 0 \n 312991 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Moubarek, Master. Gerios \n male \n NA \n 29.79431 \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n male \n NA \n 29.79431 \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n female \n NA \n 29.79431 \n 0 \n 2 \n 2661 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n female \n NA \n 29.79431 \n 0 \n 0 \n 2626 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n male \n NA \n 29.79431 \n 0 \n 0 \n 374746 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 35852 \n 7.7333 \n NA \n Q \n \n \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 382653 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Murdlin, Mr. Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n A./5. 3235 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n female \n NA \n 29.79431 \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n female \n NA \n 29.79431 \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n 3 \n 1 \n Murphy, Miss. Nora \n female \n NA \n 29.79431 \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347078 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Naidenoff, Mr. Penko \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 349206 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n female \n 15.0000 \n 15.00000 \n 0 \n 0 \n 2667 \n 7.2250 \n NA \n C \n \n \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n female \n 1.0000 \n 1.00000 \n 0 \n 2 \n 2653 \n 15.7417 \n NA \n C \n \n \n 3 \n 1 \n Nakid, Mr. Sahid \n male \n 20.0000 \n 20.00000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n 3 \n 0 \n Nancarrow, Mr. William Henry \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n A./5. 3338 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Nankoff, Mr. Minko \n male \n NA \n 29.79431 \n 0 \n 0 \n 349218 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Nasr, Mr. Mustafa \n male \n NA \n 29.79431 \n 0 \n 0 \n 2652 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Naughton, Miss. Hannah \n female \n NA \n 29.79431 \n 0 \n 0 \n 365237 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Nenkoff, Mr. Christo \n male \n NA \n 29.79431 \n 0 \n 0 \n 349234 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n male \n 12.0000 \n 12.00000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n female \n 14.0000 \n 14.00000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n 3101297 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Niklasson, Mr. Samuel \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 363611 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347066 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347470 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350410 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n SOTON/O2 3101272 \n 7.1250 \n NA \n S \n \n \n 3 \n 1 \n Niskanen, Mr. Juha \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n STON/O 2. 3101289 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A/4. 39886 \n 7.8000 \n NA \n S \n \n \n 3 \n 0 \n Novel, Mr. Mansouer \n male \n 28.5000 \n 28.50000 \n 0 \n 0 \n 2697 \n 7.2292 \n NA \n C \n \n \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 347081 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 345364 \n 6.2375 \n NA \n S \n \n \n 3 \n 0 \n O'Brien, Mr. Thomas \n male \n NA \n 29.79431 \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n O'Brien, Mr. Timothy \n male \n NA \n 29.79431 \n 0 \n 0 \n 330979 \n 7.8292 \n NA \n Q \n \n \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n female \n NA \n 29.79431 \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n O'Connell, Mr. Patrick D \n male \n NA \n 29.79431 \n 0 \n 0 \n 334912 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n O'Connor, Mr. Maurice \n male \n NA \n 29.79431 \n 0 \n 0 \n 371060 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n O'Connor, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 366713 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Odahl, Mr. Nils Martin \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 7267 \n 9.2250 \n NA \n S \n \n \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n female \n NA \n 29.79431 \n 0 \n 0 \n 364856 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n female \n NA \n 29.79431 \n 0 \n 0 \n 14311 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 330959 \n 7.8792 \n NA \n Q \n \n \n 3 \n 1 \n Ohman, Miss. Velin \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 347085 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n O'Keefe, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 368402 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 330919 \n 7.8292 \n NA \n Q \n \n \n 3 \n 1 \n Olsen, Master. Artur Karl \n male \n 9.0000 \n 9.00000 \n 0 \n 1 \n C 17368 \n 3.1708 \n NA \n S \n \n \n 3 \n 0 \n Olsen, Mr. Henry Margido \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n male \n 42.0000 \n 42.00000 \n 0 \n 1 \n 4579 \n 8.4042 \n NA \n S \n \n \n 3 \n 0 \n Olsen, Mr. Ole Martin \n male \n NA \n 29.79431 \n 0 \n 0 \n Fa 265302 \n 7.3125 \n NA \n S \n \n \n 3 \n 0 \n Olsson, Miss. Elina \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n 350407 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 347464 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 347079 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 6563 \n 9.2250 \n NA \n S \n \n \n 3 \n 0 \n Oreskovic, Miss. Jelka \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n 315085 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Oreskovic, Miss. Marija \n female \n 20.0000 \n 20.00000 \n 0 \n 0 \n 315096 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Oreskovic, Mr. Luka \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 315094 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Osen, Mr. Olaf Elon \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 7534 \n 9.2167 \n NA \n S \n \n \n 3 \n 1 \n Osman, Mrs. Mara \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n 349244 \n 8.6833 \n NA \n S \n \n \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n female \n NA \n 29.79431 \n 0 \n 0 \n 330909 \n 7.6292 \n NA \n Q \n \n \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n male \n 2.0000 \n 2.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Master. Paul Folke \n male \n 6.0000 \n 6.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Miss. Stina Viola \n female \n 3.0000 \n 3.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n female \n 8.0000 \n 8.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n female \n 29.0000 \n 29.00000 \n 0 \n 4 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Panula, Master. Eino Viljami \n male \n 1.0000 \n 1.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Master. Juha Niilo \n male \n 7.0000 \n 7.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Master. Urho Abraham \n male \n 2.0000 \n 2.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n male \n 16.0000 \n 16.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n male \n 14.0000 \n 14.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n female \n 41.0000 \n 41.00000 \n 0 \n 5 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Pasic, Mr. Jakob \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 315097 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Patchett, Mr. George \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Paulner, Mr. Uscher \n male \n NA \n 29.79431 \n 0 \n 0 \n 3411 \n 8.7125 \n NA \n C \n \n \n 3 \n 0 \n Pavlovic, Mr. Stefo \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 349242 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Peacock, Master. Alfred Edward \n male \n 0.7500 \n 0.75000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n 3 \n 0 \n Peacock, Miss. Treasteall \n female \n 3.0000 \n 3.00000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n female \n 26.0000 \n 26.00000 \n 0 \n 2 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n 3 \n 0 \n Pearce, Mr. Ernest \n male \n NA \n 29.79431 \n 0 \n 0 \n 343271 \n 7.0000 \n NA \n S \n \n \n 3 \n 0 \n Pedersen, Mr. Olaf \n male \n NA \n 29.79431 \n 0 \n 0 \n 345498 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Peduzzi, Mr. Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n A/5 2817 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n STON/O 2. 3101294 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n STON/O 2. 3101291 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Perkin, Mr. John Henry \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n A/5 21174 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 347083 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Peter, Master. Michael J \n male \n NA \n 29.79431 \n 1 \n 1 \n 2668 \n 22.3583 \n NA \n C \n \n \n 3 \n 1 \n Peter, Miss. Anna \n female \n NA \n 29.79431 \n 1 \n 1 \n 2668 \n 22.3583 \n F E69 \n C \n \n \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n female \n NA \n 29.79431 \n 0 \n 2 \n 2668 \n 22.3583 \n NA \n C \n \n \n 3 \n 0 \n Peters, Miss. Katie \n female \n NA \n 29.79431 \n 0 \n 0 \n 330935 \n 8.1375 \n NA \n Q \n \n \n 3 \n 0 \n Petersen, Mr. Marius \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 342441 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Petranec, Miss. Matilda \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 349245 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Petroff, Mr. Nedelio \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349212 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n male \n NA \n 29.79431 \n 0 \n 0 \n 349215 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Petterson, Mr. Johan Emil \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 347076 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347087 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n SOTON/O.Q. 392078 \n 8.0500 \n E10 \n S \n \n \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n male \n NA \n 29.79431 \n 0 \n 0 \n 349227 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Pokrnic, Mr. Mate \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315095 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Pokrnic, Mr. Tome \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 315092 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Radeff, Mr. Alexander \n male \n NA \n 29.79431 \n 0 \n 0 \n 349223 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n female \n NA \n 29.79431 \n 0 \n 0 \n 65305 \n 8.1125 \n NA \n S \n \n \n 3 \n 0 \n Razi, Mr. Raihed \n male \n NA \n 29.79431 \n 0 \n 0 \n 2629 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Reed, Mr. James George \n male \n NA \n 29.79431 \n 0 \n 0 \n 362316 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Rekic, Mr. Tido \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n 349249 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Reynolds, Mr. Harold J \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 342684 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rice, Master. Albert \n male \n 10.0000 \n 10.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. Arthur \n male \n 4.0000 \n 4.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. Eric \n male \n 7.0000 \n 7.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. Eugene \n male \n 2.0000 \n 2.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. George Hugh \n male \n 8.0000 \n 8.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n female \n 39.0000 \n 39.00000 \n 0 \n 5 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Rintamaki, Mr. Matti \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n STON/O 2. 3101273 \n 7.1250 \n NA \n S \n \n \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 334915 \n 7.7208 \n NA \n Q \n \n \n 3 \n 0 \n Risien, Mr. Samuel Beard \n male \n NA \n 29.79431 \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n female \n NA \n 29.79431 \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Robins, Mr. Alexander A \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n female \n 47.0000 \n 47.00000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Rogers, Mr. William John \n male \n NA \n 29.79431 \n 0 \n 0 \n S.C./A.4. 23567 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n male \n NA \n 29.79431 \n 0 \n 0 \n 312993 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n female \n 2.0000 \n 2.00000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n male \n 18.0000 \n 18.00000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n female \n 41.0000 \n 41.00000 \n 0 \n 2 \n 370129 \n 20.2125 \n NA \n S \n \n \n 3 \n 1 \n Roth, Miss. Sarah A \n female \n NA \n 29.79431 \n 0 \n 0 \n 342712 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rouse, Mr. Richard Henry \n male \n 50.0000 \n 50.00000 \n 0 \n 0 \n A/5 3594 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rush, Mr. Alfred George John \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n A/4. 20589 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Ryan, Mr. Edward \n male \n NA \n 29.79431 \n 0 \n 0 \n 383162 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Ryan, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n 3 \n 0 \n Saad, Mr. Amin \n male \n NA \n 29.79431 \n 0 \n 0 \n 2671 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Saad, Mr. Khalil \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 2672 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Saade, Mr. Jean Nassr \n male \n NA \n 29.79431 \n 0 \n 0 \n 2676 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Sadlier, Mr. Matthew \n male \n NA \n 29.79431 \n 0 \n 0 \n 367655 \n 7.7292 \n NA \n Q \n \n \n 3 \n 0 \n Sadowitz, Mr. Harry \n male \n NA \n 29.79431 \n 0 \n 0 \n LP 1588 \n 7.5750 \n NA \n S \n \n \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n male \n 38.5000 \n 38.50000 \n 0 \n 0 \n SOTON/O.Q. 3101262 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Master. Thomas Henry \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Master. William Henry \n male \n 14.5000 \n 14.50000 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Ada \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Constance Gladys \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Stella Anna \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. Frederick \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. George John Jr \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. John George \n male \n NA \n 29.79431 \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n female \n NA \n 29.79431 \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Salander, Mr. Karl Johan \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 7266 \n 9.3250 \n NA \n S \n \n \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 343120 \n 7.6500 \n NA \n S \n \n \n 3 \n 0 \n Salonen, Mr. Johan Werner \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 3101296 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Samaan, Mr. Elias \n male \n NA \n 29.79431 \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n 3 \n 0 \n Samaan, Mr. Hanna \n male \n NA \n 29.79431 \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n 3 \n 0 \n Samaan, Mr. Youssef \n male \n NA \n 29.79431 \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n female \n 1.0000 \n 1.00000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n female \n 24.0000 \n 24.00000 \n 0 \n 2 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n female \n 4.0000 \n 4.00000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n 3 \n 1 \n Sap, Mr. Julius \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 345768 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Saundercock, Mr. William Henry \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n A/5. 2151 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n male \n 24.5000 \n 24.50000 \n 0 \n 0 \n 342826 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Scanlan, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n 36209 \n 7.7250 \n NA \n Q \n \n \n 3 \n 0 \n Sdycoff, Mr. Todor \n male \n NA \n 29.79431 \n 0 \n 0 \n 349222 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 370374 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 345779 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Shellard, Mr. Frederick William \n male \n NA \n 29.79431 \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n female \n NA \n 29.79431 \n 0 \n 0 \n 330968 \n 7.7792 \n NA \n Q \n \n \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n 374910 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Simmons, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/OQ 392082 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Sirayanian, Mr. Orsen \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 2669 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Sirota, Mr. Maurice \n male \n NA \n 29.79431 \n 0 \n 0 \n 392092 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Sivic, Mr. Husein \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 349251 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n STON/O 2. 3101280 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 3101265 \n 7.4958 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Master. Harald \n male \n 4.0000 \n 4.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n male \n 10.0000 \n 10.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Miss. Mabel \n female \n 9.0000 \n 9.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n female \n 2.0000 \n 2.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Mr. Wilhelm \n male \n 40.0000 \n 40.00000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n female \n 45.0000 \n 45.00000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Slabenoff, Mr. Petco \n male \n NA \n 29.79431 \n 0 \n 0 \n 349214 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/OQ 392086 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Smiljanic, Mr. Mile \n male \n NA \n 29.79431 \n 0 \n 0 \n 315037 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Smith, Mr. Thomas \n male \n NA \n 29.79431 \n 0 \n 0 \n 384461 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Smyth, Miss. Julia \n female \n NA \n 29.79431 \n 0 \n 0 \n 335432 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 348124 \n 7.6500 \n F G73 \n S \n \n \n 3 \n 0 \n Somerton, Mr. Francis William \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n A.5. 18509 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Spector, Mr. Woolf \n male \n NA \n 29.79431 \n 0 \n 0 \n A.5. 3236 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Spinner, Mr. Henry John \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/OQ. 369943 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Staneff, Mr. Ivan \n male \n NA \n 29.79431 \n 0 \n 0 \n 349208 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Stankovic, Mr. Ivan \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 349239 \n 8.6625 \n NA \n C \n \n \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n CA. 2314 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Stanley, Mr. Edward Roland \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A/4 45380 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Storey, Mr. Thomas \n male \n 60.5000 \n 60.50000 \n 0 \n 0 \n 3701 \n NA \n NA \n S \n \n \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349205 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 7553 \n 9.8375 \n NA \n S \n \n \n 3 \n 1 \n Stranden, Mr. Juho \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n STON/O 2. 3101288 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Strilic, Mr. Ivan \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 315083 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Strom, Miss. Telma Matilda \n female \n 2.0000 \n 2.00000 \n 0 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n female \n 29.0000 \n 29.00000 \n 1 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n SOTON/OQ 392089 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Sundman, Mr. Johan Julian \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n STON/O 2. 3101269 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n SOTON/OQ 392076 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Svensson, Mr. Johan \n male \n 74.0000 \n 74.00000 \n 0 \n 0 \n 347060 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n male \n 14.0000 \n 14.00000 \n 0 \n 0 \n 7538 \n 9.2250 \n NA \n S \n \n \n 3 \n 0 \n Svensson, Mr. Olof \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 350035 \n 7.7958 \n NA \n S \n \n \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 350033 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 363294 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Thomas, Master. Assad Alexander \n male \n 0.4167 \n 0.41670 \n 0 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n 3 \n 0 \n Thomas, Mr. Charles P \n male \n NA \n 29.79431 \n 1 \n 0 \n 2621 \n 6.4375 \n NA \n C \n \n \n 3 \n 0 \n Thomas, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 2681 \n 6.4375 \n NA \n C \n \n \n 3 \n 0 \n Thomas, Mr. Tannous \n male \n NA \n 29.79431 \n 0 \n 0 \n 2684 \n 7.2250 \n NA \n C \n \n \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n male \n NA \n 29.79431 \n 0 \n 0 \n 32302 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Thorneycroft, Mr. Percival \n male \n NA \n 29.79431 \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n female \n NA \n 29.79431 \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Tikkanen, Mr. Juho \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/O 2. 3101293 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Tobin, Mr. Roger \n male \n NA \n 29.79431 \n 0 \n 0 \n 383121 \n 7.7500 \n F38 \n Q \n \n \n 3 \n 0 \n Todoroff, Mr. Lalio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349216 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n male \n 30.5000 \n 30.50000 \n 0 \n 0 \n 364499 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Torber, Mr. Ernst William \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n 364511 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Torfa, Mr. Assad \n male \n NA \n 29.79431 \n 0 \n 0 \n 2673 \n 7.2292 \n NA \n C \n \n \n 3 \n 1 \n Tornquist, Mr. William Henry \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 0 \n Toufik, Mr. Nakli \n male \n NA \n 29.79431 \n 0 \n 0 \n 2641 \n 7.2292 \n NA \n C \n \n \n 3 \n 1 \n Touma, Master. Georges Youssef \n male \n 7.0000 \n 7.00000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Touma, Miss. Maria Youssef \n female \n 9.0000 \n 9.00000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n female \n 29.0000 \n 29.00000 \n 0 \n 2 \n 2650 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Turcin, Mr. Stjepan \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 349247 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Turja, Miss. Anna Sofia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 4138 \n 9.8417 \n NA \n S \n \n \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n female \n 63.0000 \n 63.00000 \n 0 \n 0 \n 4134 \n 9.5875 \n NA \n S \n \n \n 3 \n 0 \n van Billiard, Master. James William \n male \n NA \n 29.79431 \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n van Billiard, Master. Walter John \n male \n 11.5000 \n 11.50000 \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n male \n 40.5000 \n 40.50000 \n 0 \n 2 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Van Impe, Miss. Catharina \n female \n 10.0000 \n 10.00000 \n 0 \n 2 \n 345773 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n male \n NA \n 29.79431 \n 0 \n 0 \n 345777 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 345780 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 345770 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 345783 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 345765 \n 9.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n female \n 18.0000 \n 18.00000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Mr. Julius \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n male \n 16.0000 \n 16.00000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n female \n 31.0000 \n 31.00000 \n 1 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n 3 \n 1 \n Vartanian, Mr. David \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 2658 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 350416 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n female \n 14.0000 \n 14.00000 \n 0 \n 0 \n 350406 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Vovk, Mr. Janko \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 349252 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Waelens, Mr. Achille \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 345767 \n 9.0000 \n NA \n S \n \n \n 3 \n 0 \n Ware, Mr. Frederick \n male \n NA \n 29.79431 \n 0 \n 0 \n 359309 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Warren, Mr. Charles William \n male \n NA \n 29.79431 \n 0 \n 0 \n C.A. 49867 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Webber, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/OQ 3101316 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Wenzel, Mr. Linhart \n male \n 32.5000 \n 32.50000 \n 0 \n 0 \n 345775 \n 9.5000 \n NA \n S \n \n \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n 2688 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 347064 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n 3101267 \n 6.4958 \n NA \n S \n \n \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n 3101266 \n 6.4958 \n NA \n S \n \n \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n female \n 47.0000 \n 47.00000 \n 1 \n 0 \n 363272 \n 7.0000 \n NA \n S \n \n \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n male \n NA \n 29.79431 \n 0 \n 0 \n 3410 \n 8.7125 \n NA \n S \n \n \n 3 \n 0 \n Willey, Mr. Edward \n male \n NA \n 29.79431 \n 0 \n 0 \n S.O./P.P. 751 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n male \n NA \n 29.79431 \n 0 \n 0 \n A/5 2466 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Williams, Mr. Leslie \n male \n 28.5000 \n 28.50000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Windelov, Mr. Einar \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n SOTON/OQ 3101317 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Wirz, Mr. Albert \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 315154 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Wiseman, Mr. Phillippe \n male \n NA \n 29.79431 \n 0 \n 0 \n A/4. 34244 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Wittevrongel, Mr. Camille \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 345771 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Yasbeck, Mr. Antoni \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n female \n 15.0000 \n 15.00000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Youseff, Mr. Gerious \n male \n 45.5000 \n 45.50000 \n 0 \n 0 \n 2628 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Yousif, Mr. Wazli \n male \n NA \n 29.79431 \n 0 \n 0 \n 2647 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Yousseff, Mr. Gerious \n male \n NA \n 29.79431 \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Zabour, Miss. Hileni \n female \n 14.5000 \n 14.50000 \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Zabour, Miss. Thamine \n female \n NA \n 29.79431 \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n male \n 26.5000 \n 26.50000 \n 0 \n 0 \n 2656 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Zakarian, Mr. Ortin \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 2670 \n 7.2250 \n NA \n C \n \n \n\n 3 \n 0 \n Zimmerman, Mr. Leo \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 315082 \n 7.8750 \n NA \n S \n \n \n
\n \n \n\n embarked \n country_embarked \n pclass \n survived \n name_of_passenger \n sex_of_passenger \n age_of_passenger \n sibsp \n parch \n ticket \n fare \n cabin \n \n \n S \n England \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n female \n 29.0000 \n 0 \n 0 \n 24160 \n 211.3375 \n B5 \n \n \n S \n England \n 1 \n 1 \n Allison, Master. Hudson Trevor \n male \n 0.9167 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 0 \n Allison, Miss. Helen Loraine \n female \n 2.0000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n male \n 30.0000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n female \n 25.0000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 1 \n Anderson, Mr. Harry \n male \n 48.0000 \n 0 \n 0 \n 19952 \n 26.5500 \n E12 \n \n \n S \n England \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n female \n 63.0000 \n 1 \n 0 \n 13502 \n 77.9583 \n D7 \n \n \n S \n England \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n male \n NA \n 0 \n 0 \n 112050 \n 0.0000 \n A36 \n \n \n S \n England \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n female \n NA \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n \n \n C \n France \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n male \n NA \n 0 \n 0 \n PC 17609 \n 49.5042 \n NA \n \n \n C \n France \n 1 \n 0 \n Astor, Col. John Jacob \n male \n NA \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n \n \n C \n France \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n female \n 18.0000 \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n \n \n C \n France \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n \n \n S \n England \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n female \n 26.0000 \n 0 \n 0 \n 19877 \n 78.8500 \n NA \n \n \n S \n England \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n male \n 80.0000 \n 0 \n 0 \n 27042 \n 30.0000 \n A23 \n \n \n S \n England \n 1 \n 0 \n Baumann, Mr. John D \n male \n NA \n 0 \n 0 \n PC 17318 \n 25.9250 \n NA \n \n \n C \n France \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n male \n 24.0000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n \n \n C \n France \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n female \n 50.0000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n \n \n C \n France \n 1 \n 1 \n Bazzani, Miss. Albina \n female \n 32.0000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n \n \n C \n France \n 1 \n 0 \n Beattie, Mr. Thomson \n male \n 36.0000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n \n \n S \n England \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n male \n 37.0000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n \n \n S \n England \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n female \n 47.0000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n \n \n C \n France \n 1 \n 1 \n Behr, Mr. Karl Howell \n male \n 26.0000 \n 0 \n 0 \n 111369 \n 30.0000 \n C148 \n \n \n C \n France \n 1 \n 1 \n Bidois, Miss. Rosalie \n female \n 42.0000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n \n \n S \n England \n 1 \n 1 \n Bird, Miss. Ellen \n female \n 29.0000 \n 0 \n 0 \n PC 17483 \n 221.7792 \n C97 \n \n \n C \n France \n 1 \n 0 \n Birnbaum, Mr. Jakob \n male \n 25.0000 \n 0 \n 0 \n 13905 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Bishop, Mr. Dickinson H \n male \n 25.0000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n \n \n C \n France \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n female \n 19.0000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n \n \n S \n England \n 1 \n 1 \n Bissette, Miss. Amelia \n female \n 35.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C99 \n \n \n S \n England \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n male \n 28.0000 \n 0 \n 0 \n 110564 \n 26.5500 \n C52 \n \n \n S \n England \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n male \n 45.0000 \n 0 \n 0 \n 113784 \n 35.5000 \n T \n \n \n C \n France \n 1 \n 1 \n Blank, Mr. Henry \n male \n 40.0000 \n 0 \n 0 \n 112277 \n 31.0000 \n A31 \n \n \n S \n England \n 1 \n 1 \n Bonnell, Miss. Caroline \n female \n 30.0000 \n 0 \n 0 \n 36928 \n 164.8667 \n C7 \n \n \n S \n England \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n female \n 58.0000 \n 0 \n 0 \n 113783 \n 26.5500 \n C103 \n \n \n S \n England \n 1 \n 0 \n Borebank, Mr. John James \n male \n 42.0000 \n 0 \n 0 \n 110489 \n 26.5500 \n D22 \n \n \n C \n France \n 1 \n 1 \n Bowen, Miss. Grace Scott \n female \n 45.0000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n NA \n \n \n S \n England \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n female \n 22.0000 \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n \n \n S \n England \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n male \n NA \n 0 \n 0 \n 111427 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Brady, Mr. John Bertram \n male \n 41.0000 \n 0 \n 0 \n 113054 \n 30.5000 \n A21 \n \n \n C \n France \n 1 \n 0 \n Brandeis, Mr. Emil \n male \n 48.0000 \n 0 \n 0 \n PC 17591 \n 50.4958 \n B10 \n \n \n C \n France \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n male \n NA \n 0 \n 0 \n 112379 \n 39.6000 \n NA \n \n \n C \n France \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n female \n 44.0000 \n 0 \n 0 \n PC 17610 \n 27.7208 \n B4 \n \n \n S \n England \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n female \n 59.0000 \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n \n \n C \n France \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n female \n 60.0000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n \n \n C \n France \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n female \n 41.0000 \n 0 \n 0 \n 16966 \n 134.5000 \n E40 \n \n \n S \n England \n 1 \n 0 \n Butt, Major. Archibald Willingham \n male \n 45.0000 \n 0 \n 0 \n 113050 \n 26.5500 \n B38 \n \n \n S \n England \n 1 \n 0 \n Cairns, Mr. Alexander \n male \n NA \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n male \n 42.0000 \n 0 \n 0 \n PC 17476 \n 26.2875 \n E24 \n \n \n C \n France \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n female \n 53.0000 \n 0 \n 0 \n PC 17606 \n 27.4458 \n NA \n \n \n C \n France \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n male \n 36.0000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n \n \n C \n France \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n female \n 58.0000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n \n \n S \n England \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n male \n 33.0000 \n 0 \n 0 \n 695 \n 5.0000 \n B51 B53 B55 \n \n \n S \n England \n 1 \n 0 \n Carrau, Mr. Francisco M \n male \n 28.0000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n \n \n S \n England \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n male \n 17.0000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n \n \n S \n England \n 1 \n 1 \n Carter, Master. William Thornton II \n male \n 11.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 1 \n Carter, Miss. Lucile Polk \n female \n 14.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 1 \n Carter, Mr. William Ernest \n male \n 36.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n female \n 36.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 0 \n Case, Mr. Howard Brown \n male \n 49.0000 \n 0 \n 0 \n 19924 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n female \n NA \n 0 \n 0 \n 17770 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n male \n 36.0000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n \n \n S \n England \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n female \n 76.0000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n \n \n S \n England \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n male \n 46.0000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n \n \n S \n England \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n female \n 47.0000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n \n \n S \n England \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n male \n 27.0000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n \n \n S \n England \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n female \n 33.0000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n \n \n C \n France \n 1 \n 1 \n Chaudanson, Miss. Victorine \n female \n 36.0000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n B61 \n \n \n S \n England \n 1 \n 1 \n Cherry, Miss. Gladys \n female \n 30.0000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n \n \n C \n France \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n male \n 45.0000 \n 0 \n 0 \n PC 17594 \n 29.7000 \n A9 \n \n \n S \n England \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n female \n NA \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n \n \n S \n England \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n male \n NA \n 0 \n 0 \n 112051 \n 0.0000 \n NA \n \n \n C \n France \n 1 \n 0 \n Clark, Mr. Walter Miller \n male \n 27.0000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n \n \n C \n France \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n female \n 26.0000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n \n \n S \n England \n 1 \n 1 \n Cleaver, Miss. Alice \n female \n 22.0000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Clifford, Mr. George Quincy \n male \n NA \n 0 \n 0 \n 110465 \n 52.0000 \n A14 \n \n \n S \n England \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n male \n 47.0000 \n 0 \n 0 \n 5727 \n 25.5875 \n E58 \n \n \n C \n France \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n female \n 39.0000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E49 \n \n \n C \n France \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n male \n 37.0000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E52 \n \n \n C \n France \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n female \n 64.0000 \n 0 \n 2 \n PC 17756 \n 83.1583 \n E45 \n \n \n S \n England \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n female \n 55.0000 \n 2 \n 0 \n 11770 \n 25.7000 \n C101 \n \n \n S \n England \n 1 \n 0 \n Crafton, Mr. John Bertram \n male \n NA \n 0 \n 0 \n 113791 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n male \n 70.0000 \n 1 \n 1 \n WE/P 5735 \n 71.0000 \n B22 \n \n \n S \n England \n 1 \n 1 \n Crosby, Miss. Harriet R \n female \n 36.0000 \n 0 \n 2 \n WE/P 5735 \n 71.0000 \n B22 \n \n \n S \n England \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n female \n 64.0000 \n 1 \n 1 \n 112901 \n 26.5500 \n B26 \n \n \n C \n France \n 1 \n 0 \n Cumings, Mr. John Bradley \n male \n 39.0000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n \n \n C \n France \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n female \n 38.0000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n \n \n S \n England \n 1 \n 1 \n Daly, Mr. Peter Denis \n male \n 51.0000 \n 0 \n 0 \n 113055 \n 26.5500 \n E17 \n \n \n S \n England \n 1 \n 1 \n Daniel, Mr. Robert Williams \n male \n 27.0000 \n 0 \n 0 \n 113804 \n 30.5000 \n NA \n \n \n S \n England \n 1 \n 1 \n Daniels, Miss. Sarah \n female \n 33.0000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Davidson, Mr. Thornton \n male \n 31.0000 \n 1 \n 0 \n F.C. 12750 \n 52.0000 \n B71 \n \n \n S \n England \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n female \n 27.0000 \n 1 \n 2 \n F.C. 12750 \n 52.0000 \n B71 \n \n \n S \n England \n 1 \n 1 \n Dick, Mr. Albert Adrian \n male \n 31.0000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n \n \n S \n England \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n female \n 17.0000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n \n \n S \n England \n 1 \n 1 \n Dodge, Dr. Washington \n male \n 53.0000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n \n \n S \n England \n 1 \n 1 \n Dodge, Master. Washington \n male \n 4.0000 \n 0 \n 2 \n 33638 \n 81.8583 \n A34 \n \n \n S \n England \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n female \n 54.0000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n \n \n C \n France \n 1 \n 0 \n Douglas, Mr. Walter Donald \n male \n 50.0000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n \n \n C \n France \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n female \n 27.0000 \n 1 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n \n \n C \n France \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n female \n 48.0000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n \n \n C \n France \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n female \n 48.0000 \n 1 \n 0 \n 11755 \n 39.6000 \n A16 \n \n \n C \n France \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n male \n 49.0000 \n 1 \n 0 \n PC 17485 \n 56.9292 \n A20 \n \n \n C \n France \n 1 \n 0 \n Dulles, Mr. William Crothers \n male \n 39.0000 \n 0 \n 0 \n PC 17580 \n 29.7000 \n A18 \n \n \n C \n France \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n female \n 23.0000 \n 0 \n 1 \n 11767 \n 83.1583 \n C54 \n \n \n C \n France \n 1 \n 1 \n Endres, Miss. Caroline Louise \n female \n 38.0000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n C45 \n \n \n C \n France \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n female \n 54.0000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n \n \n C \n France \n 1 \n 0 \n Evans, Miss. Edith Corse \n female \n 36.0000 \n 0 \n 0 \n PC 17531 \n 31.6792 \n A29 \n \n \n S \n England \n 1 \n 0 \n Farthing, Mr. John \n male \n NA \n 0 \n 0 \n PC 17483 \n 221.7792 \n C95 \n \n \n S \n England \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n female \n NA \n 0 \n 0 \n PC 17598 \n 31.6833 \n NA \n \n \n C \n France \n 1 \n 1 \n Fleming, Miss. Margaret \n female \n NA \n 0 \n 0 \n 17421 \n 110.8833 \n NA \n \n \n S \n England \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n male \n 36.0000 \n 0 \n 0 \n PC 17474 \n 26.3875 \n E25 \n \n \n C \n France \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n male \n 30.0000 \n 0 \n 0 \n 113051 \n 27.7500 \n C111 \n \n \n S \n England \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n female \n 24.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n female \n 28.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n female \n 23.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n male \n 19.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 0 \n Fortune, Mr. Mark \n male \n 64.0000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n female \n 60.0000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n C \n France \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n female \n 30.0000 \n 0 \n 0 \n PC 17485 \n 56.9292 \n E36 \n \n \n S \n England \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n male \n NA \n 0 \n 0 \n 113778 \n 26.5500 \n D34 \n \n \n S \n England \n 1 \n 1 \n Frauenthal, Dr. Henry William \n male \n 50.0000 \n 2 \n 0 \n PC 17611 \n 133.6500 \n NA \n \n \n C \n France \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n male \n 43.0000 \n 1 \n 0 \n 17765 \n 27.7208 \n D40 \n \n \n S \n England \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n female \n NA \n 1 \n 0 \n PC 17611 \n 133.6500 \n NA \n \n \n C \n France \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n female \n 22.0000 \n 0 \n 2 \n 13568 \n 49.5000 \n B39 \n \n \n C \n France \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n male \n 60.0000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n \n \n C \n France \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n female \n 48.0000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n \n \n S \n England \n 1 \n 0 \n Fry, Mr. Richard \n male \n NA \n 0 \n 0 \n 112058 \n 0.0000 \n B102 \n \n \n S \n England \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n male \n 37.0000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n \n \n S \n England \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n female \n 35.0000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n \n \n S \n England \n 1 \n 0 \n Gee, Mr. Arthur H \n male \n 47.0000 \n 0 \n 0 \n 111320 \n 38.5000 \n E63 \n \n \n C \n France \n 1 \n 1 \n Geiger, Miss. Amalie \n female \n 35.0000 \n 0 \n 0 \n 113503 \n 211.5000 \n C130 \n \n \n C \n France \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n female \n 22.0000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n \n \n C \n France \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n female \n 45.0000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n \n \n C \n France \n 1 \n 0 \n Giglio, Mr. Victor \n male \n 24.0000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B86 \n \n \n C \n France \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n male \n 49.0000 \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n \n \n C \n France \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n female \n NA \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n \n \n C \n France \n 1 \n 0 \n Goldschmidt, Mr. George B \n male \n 71.0000 \n 0 \n 0 \n PC 17754 \n 34.6542 \n A5 \n \n \n C \n France \n 1 \n 1 \n Gracie, Col. Archibald IV \n male \n 53.0000 \n 0 \n 0 \n 113780 \n 28.5000 \n C51 \n \n \n S \n England \n 1 \n 1 \n Graham, Miss. Margaret Edith \n female \n 19.0000 \n 0 \n 0 \n 112053 \n 30.0000 \n B42 \n \n \n S \n England \n 1 \n 0 \n Graham, Mr. George Edward \n male \n 38.0000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C91 \n \n \n S \n England \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n female \n 58.0000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C125 \n \n \n C \n France \n 1 \n 1 \n Greenfield, Mr. William Bertram \n male \n 23.0000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n \n \n C \n France \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n female \n 45.0000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n \n \n C \n France \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n male \n 46.0000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B82 B84 \n \n \n C \n France \n 1 \n 1 \n Harder, Mr. George Achilles \n male \n 25.0000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n \n \n C \n France \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n female \n 25.0000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n \n \n C \n France \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n male \n 48.0000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n \n \n C \n France \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n female \n 49.0000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n \n \n S \n England \n 1 \n 0 \n Harrington, Mr. Charles H \n male \n NA \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n \n \n S \n England \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n male \n 45.0000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n \n \n S \n England \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n female \n 35.0000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n \n \n S \n England \n 1 \n 0 \n Harrison, Mr. William \n male \n 40.0000 \n 0 \n 0 \n 112059 \n 0.0000 \n B94 \n \n \n C \n France \n 1 \n 1 \n Hassab, Mr. Hammad \n male \n 27.0000 \n 0 \n 0 \n PC 17572 \n 76.7292 \n D49 \n \n \n S \n England \n 1 \n 1 \n Hawksford, Mr. Walter James \n male \n NA \n 0 \n 0 \n 16988 \n 30.0000 \n D45 \n \n \n C \n France \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n female \n 24.0000 \n 0 \n 0 \n 11767 \n 83.1583 \n C54 \n \n \n S \n England \n 1 \n 0 \n Hays, Mr. Charles Melville \n male \n 55.0000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n \n \n S \n England \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n female \n 52.0000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n \n \n S \n England \n 1 \n 0 \n Head, Mr. Christopher \n male \n 42.0000 \n 0 \n 0 \n 113038 \n 42.5000 \n B11 \n \n \n S \n England \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n male \n NA \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n \n \n S \n England \n 1 \n 0 \n Hipkins, Mr. William Edward \n male \n 55.0000 \n 0 \n 0 \n 680 \n 50.0000 \n C39 \n \n \n C \n France \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n female \n 16.0000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n \n \n C \n France \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n female \n 44.0000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n \n \n S \n England \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n female \n 51.0000 \n 1 \n 0 \n 13502 \n 77.9583 \n D11 \n \n \n S \n England \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n male \n 42.0000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n female \n 35.0000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n male \n 35.0000 \n 0 \n 0 \n 111426 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n male \n 38.0000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n \n \n C \n France \n 1 \n 0 \n Hoyt, Mr. William Fisher \n male \n NA \n 0 \n 0 \n PC 17600 \n 30.6958 \n NA \n \n \n S \n England \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n female \n 35.0000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n \n \n NA \n Unknown \n 1 \n 1 \n Icard, Miss. Amelie \n female \n 38.0000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n \n \n C \n France \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n female \n 50.0000 \n 0 \n 0 \n PC 17595 \n 28.7125 \n C49 \n \n \n S \n England \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n male \n 49.0000 \n 0 \n 0 \n 112058 \n 0.0000 \n B52 B54 B56 \n \n \n S \n England \n 1 \n 0 \n Jones, Mr. Charles Cresson \n male \n 46.0000 \n 0 \n 0 \n 694 \n 26.0000 \n NA \n \n \n S \n England \n 1 \n 0 \n Julian, Mr. Henry Forbes \n male \n 50.0000 \n 0 \n 0 \n 113044 \n 26.0000 \n E60 \n \n \n C \n France \n 1 \n 0 \n Keeping, Mr. Edwin \n male \n 32.5000 \n 0 \n 0 \n 113503 \n 211.5000 \n C132 \n \n \n C \n France \n 1 \n 0 \n Kent, Mr. Edward Austin \n male \n 58.0000 \n 0 \n 0 \n 11771 \n 29.7000 \n B37 \n \n \n S \n England \n 1 \n 0 \n Kenyon, Mr. Frederick R \n male \n 41.0000 \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n \n \n S \n England \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n female \n NA \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n \n \n S \n England \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n male \n 42.0000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n \n \n S \n England \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n female \n 45.0000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n \n \n S \n England \n 1 \n 0 \n Klaber, Mr. Herman \n male \n NA \n 0 \n 0 \n 113028 \n 26.5500 \n C124 \n \n \n S \n England \n 1 \n 1 \n Kreuchen, Miss. Emilie \n female \n 39.0000 \n 0 \n 0 \n 24160 \n 211.3375 \n NA \n \n \n S \n England \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n female \n 49.0000 \n 0 \n 0 \n 17465 \n 25.9292 \n D17 \n \n \n C \n France \n 1 \n 1 \n LeRoy, Miss. Bertha \n female \n 30.0000 \n 0 \n 0 \n PC 17761 \n 106.4250 \n NA \n \n \n C \n France \n 1 \n 1 \n Lesurer, Mr. Gustave J \n male \n 35.0000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n B101 \n \n \n C \n France \n 1 \n 0 \n Lewy, Mr. Ervin G \n male \n NA \n 0 \n 0 \n PC 17612 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n male \n 42.0000 \n 0 \n 0 \n 17475 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n female \n 55.0000 \n 0 \n 0 \n 112377 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 1 \n Lines, Miss. Mary Conover \n female \n 16.0000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n \n \n S \n England \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n female \n 51.0000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n \n \n S \n England \n 1 \n 0 \n Long, Mr. Milton Clyde \n male \n 29.0000 \n 0 \n 0 \n 113501 \n 30.0000 \n D6 \n \n \n S \n England \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n female \n 21.0000 \n 0 \n 0 \n 13502 \n 77.9583 \n D9 \n \n \n S \n England \n 1 \n 0 \n Loring, Mr. Joseph Holland \n male \n 30.0000 \n 0 \n 0 \n 113801 \n 45.5000 \n NA \n \n \n C \n France \n 1 \n 1 \n Lurette, Miss. Elise \n female \n 58.0000 \n 0 \n 0 \n PC 17569 \n 146.5208 \n B80 \n \n \n S \n England \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n female \n 15.0000 \n 0 \n 1 \n 24160 \n 211.3375 \n B5 \n \n \n S \n England \n 1 \n 0 \n Maguire, Mr. John Edward \n male \n 30.0000 \n 0 \n 0 \n 110469 \n 26.0000 \n C106 \n \n \n S \n England \n 1 \n 1 \n Maioni, Miss. Roberta \n female \n 16.0000 \n 0 \n 0 \n 110152 \n 86.5000 \n B79 \n \n \n C \n France \n 1 \n 1 \n Marechal, Mr. Pierre \n male \n NA \n 0 \n 0 \n 11774 \n 29.7000 \n C47 \n \n \n S \n England \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n male \n 19.0000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n \n \n S \n England \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n female \n 18.0000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n \n \n C \n France \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n female \n 24.0000 \n 0 \n 0 \n PC 17482 \n 49.5042 \n C90 \n \n \n C \n France \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n male \n 46.0000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n \n \n S \n England \n 1 \n 0 \n McCarthy, Mr. Timothy J \n male \n 54.0000 \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n \n \n S \n England \n 1 \n 1 \n McGough, Mr. James Robert \n male \n 36.0000 \n 0 \n 0 \n PC 17473 \n 26.2875 \n E25 \n \n \n C \n France \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n male \n 28.0000 \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n \n \n C \n France \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n female \n NA \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n \n \n S \n England \n 1 \n 0 \n Millet, Mr. Francis Davis \n male \n 65.0000 \n 0 \n 0 \n 13509 \n 26.5500 \n E38 \n \n \n Q \n Ireland \n 1 \n 0 \n Minahan, Dr. William Edward \n male \n 44.0000 \n 2 \n 0 \n 19928 \n 90.0000 \n C78 \n \n \n Q \n Ireland \n 1 \n 1 \n Minahan, Miss. Daisy E \n female \n 33.0000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n \n \n Q \n Ireland \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n female \n 37.0000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n \n \n C \n France \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n male \n 30.0000 \n 1 \n 0 \n 13236 \n 57.7500 \n C78 \n \n \n S \n England \n 1 \n 0 \n Molson, Mr. Harry Markland \n male \n 55.0000 \n 0 \n 0 \n 113787 \n 30.5000 \n C30 \n \n \n S \n England \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n male \n 47.0000 \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n \n \n C \n France \n 1 \n 0 \n Natsch, Mr. Charles H \n male \n 37.0000 \n 0 \n 1 \n PC 17596 \n 29.7000 \n C118 \n \n \n C \n France \n 1 \n 1 \n Newell, Miss. Madeleine \n female \n 31.0000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n \n \n C \n France \n 1 \n 1 \n Newell, Miss. Marjorie \n female \n 23.0000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n \n \n C \n France \n 1 \n 0 \n Newell, Mr. Arthur Webster \n male \n 58.0000 \n 0 \n 2 \n 35273 \n 113.2750 \n D48 \n \n \n S \n England \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n female \n 19.0000 \n 0 \n 2 \n 11752 \n 26.2833 \n D47 \n \n \n S \n England \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n male \n 64.0000 \n 0 \n 0 \n 693 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n female \n 39.0000 \n 0 \n 0 \n PC 17758 \n 108.9000 \n C105 \n \n \n C \n France \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n male \n NA \n 0 \n 0 \n F.C. 12998 \n 25.7417 \n NA \n \n \n C \n France \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n female \n 22.0000 \n 0 \n 1 \n 113509 \n 61.9792 \n B36 \n \n \n C \n France \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n male \n 65.0000 \n 0 \n 1 \n 113509 \n 61.9792 \n B30 \n \n \n C \n France \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n male \n 28.5000 \n 0 \n 0 \n PC 17562 \n 27.7208 \n D43 \n \n \n S \n England \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n male \n NA \n 0 \n 0 \n 112052 \n 0.0000 \n NA \n \n \n S \n England \n 1 \n 0 \n Partner, Mr. Austen \n male \n 45.5000 \n 0 \n 0 \n 113043 \n 28.5000 \n C124 \n \n \n S \n England \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n male \n 23.0000 \n 0 \n 0 \n 12749 \n 93.5000 \n B24 \n \n \n S \n England \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n male \n 29.0000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n \n \n S \n England \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n female \n 22.0000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n \n \n C \n France \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n male \n 18.0000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n \n \n C \n France \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n female \n 17.0000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n \n \n S \n England \n 1 \n 1 \n Perreault, Miss. Anne \n female \n 30.0000 \n 0 \n 0 \n 12749 \n 93.5000 \n B73 \n \n \n S \n England \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n male \n 52.0000 \n 0 \n 0 \n 113786 \n 30.5000 \n C104 \n \n \n S \n England \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n male \n 47.0000 \n 0 \n 0 \n 110465 \n 52.0000 \n C110 \n \n \n C \n France \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n female \n 56.0000 \n 0 \n 1 \n 11767 \n 83.1583 \n C50 \n \n \n S \n England \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n male \n 38.0000 \n 0 \n 0 \n 19972 \n 0.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n male \n NA \n 0 \n 0 \n PC 17607 \n 39.6000 \n NA \n \n \n C \n France \n 1 \n 0 \n Ringhini, Mr. Sante \n male \n 22.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n NA \n \n \n C \n France \n 1 \n 0 \n Robbins, Mr. Victor \n male \n NA \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n \n \n S \n England \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n female \n 43.0000 \n 0 \n 1 \n 24160 \n 211.3375 \n B3 \n \n \n S \n England \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n male \n 31.0000 \n 0 \n 0 \n PC 17590 \n 50.4958 \n A24 \n \n \n S \n England \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n male \n 45.0000 \n 0 \n 0 \n 111428 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n male \n NA \n 0 \n 0 \n 113767 \n 50.0000 \n A32 \n \n \n C \n France \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n female \n 33.0000 \n 0 \n 0 \n PC 17613 \n 27.7208 \n A11 \n \n \n C \n France \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n male \n 46.0000 \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n \n \n C \n France \n 1 \n 0 \n Ross, Mr. John Hugo \n male \n 36.0000 \n 0 \n 0 \n 13049 \n 40.1250 \n A10 \n \n \n S \n England \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n female \n 33.0000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n \n \n C \n France \n 1 \n 0 \n Rothschild, Mr. Martin \n male \n 55.0000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n \n \n C \n France \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n female \n 54.0000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n \n \n S \n England \n 1 \n 0 \n Rowe, Mr. Alfred G \n male \n 33.0000 \n 0 \n 0 \n 113790 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 1 \n Ryerson, Master. John Borie \n male \n 13.0000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n female \n 18.0000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n female \n 21.0000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n male \n 61.0000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n female \n 48.0000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n S \n England \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n male \n NA \n 0 \n 0 \n 19988 \n 30.5000 \n C106 \n \n \n C \n France \n 1 \n 1 \n Sagesser, Mlle. Emma \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n \n \n S \n England \n 1 \n 1 \n Salomon, Mr. Abraham L \n male \n NA \n 0 \n 0 \n 111163 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n female \n 35.0000 \n 1 \n 0 \n 13236 \n 57.7500 \n C28 \n \n \n C \n France \n 1 \n 1 \n Serepeca, Miss. Augusta \n female \n 30.0000 \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n male \n 34.0000 \n 0 \n 0 \n 113794 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n female \n 40.0000 \n 0 \n 0 \n PC 17582 \n 153.4625 \n C125 \n \n \n S \n England \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n male \n 35.0000 \n 0 \n 0 \n PC 17475 \n 26.2875 \n E24 \n \n \n S \n England \n 1 \n 0 \n Silvey, Mr. William Baird \n male \n 50.0000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n \n \n S \n England \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n female \n 39.0000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n \n \n C \n France \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n male \n 56.0000 \n 0 \n 0 \n 13213 \n 35.5000 \n A26 \n \n \n S \n England \n 1 \n 1 \n Sloper, Mr. William Thompson \n male \n 28.0000 \n 0 \n 0 \n 113788 \n 35.5000 \n A6 \n \n \n S \n England \n 1 \n 0 \n Smart, Mr. John Montgomery \n male \n 56.0000 \n 0 \n 0 \n 113792 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 0 \n Smith, Mr. James Clinch \n male \n 56.0000 \n 0 \n 0 \n 17764 \n 30.6958 \n A7 \n \n \n S \n England \n 1 \n 0 \n Smith, Mr. Lucien Philip \n male \n 24.0000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n \n \n S \n England \n 1 \n 0 \n Smith, Mr. Richard William \n male \n NA \n 0 \n 0 \n 113056 \n 26.0000 \n A19 \n \n \n S \n England \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n female \n 18.0000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n \n \n S \n England \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n male \n 24.0000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n \n \n S \n England \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n female \n 23.0000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n \n \n C \n France \n 1 \n 1 \n Spedden, Master. Robert Douglas \n male \n 6.0000 \n 0 \n 2 \n 16966 \n 134.5000 \n E34 \n \n \n C \n France \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n male \n 45.0000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n \n \n C \n France \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n female \n 40.0000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n \n \n C \n France \n 1 \n 0 \n Spencer, Mr. William Augustus \n male \n 57.0000 \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n \n \n C \n France \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n female \n NA \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n \n \n C \n France \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n male \n 32.0000 \n 0 \n 0 \n 13214 \n 30.5000 \n B50 \n \n \n S \n England \n 1 \n 0 \n Stead, Mr. William Thomas \n male \n 62.0000 \n 0 \n 0 \n 113514 \n 26.5500 \n C87 \n \n \n C \n France \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n male \n 54.0000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n \n \n C \n France \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n female \n 43.0000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n \n \n C \n France \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n female \n 52.0000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n \n \n C \n France \n 1 \n 0 \n Stewart, Mr. Albert A \n male \n NA \n 0 \n 0 \n PC 17605 \n 27.7208 \n NA \n \n \n NA \n Unknown \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n female \n 62.0000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n \n \n S \n England \n 1 \n 0 \n Straus, Mr. Isidor \n male \n 67.0000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n \n \n S \n England \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n female \n 63.0000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n \n \n S \n England \n 1 \n 0 \n Sutton, Mr. Frederick \n male \n 61.0000 \n 0 \n 0 \n 36963 \n 32.3208 \n D50 \n \n \n S \n England \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n female \n 48.0000 \n 0 \n 0 \n 17466 \n 25.9292 \n D17 \n \n \n S \n England \n 1 \n 1 \n Taussig, Miss. Ruth \n female \n 18.0000 \n 0 \n 2 \n 110413 \n 79.6500 \n E68 \n \n \n S \n England \n 1 \n 0 \n Taussig, Mr. Emil \n male \n 52.0000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n \n \n S \n England \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n female \n 39.0000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n \n \n S \n England \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n male \n 48.0000 \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n \n \n S \n England \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n female \n NA \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n \n \n C \n France \n 1 \n 0 \n Thayer, Mr. John Borland \n male \n 49.0000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n \n \n C \n France \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n male \n 17.0000 \n 0 \n 2 \n 17421 \n 110.8833 \n C70 \n \n \n C \n France \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n female \n 39.0000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n \n \n C \n France \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n female \n NA \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n \n \n C \n France \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n male \n 31.0000 \n 0 \n 0 \n 2543 \n 28.5375 \n C53 \n \n \n C \n France \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n male \n 40.0000 \n 0 \n 0 \n PC 17601 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n male \n 61.0000 \n 0 \n 0 \n 111240 \n 33.5000 \n B19 \n \n \n S \n England \n 1 \n 0 \n Walker, Mr. William Anderson \n male \n 47.0000 \n 0 \n 0 \n 36967 \n 34.0208 \n D46 \n \n \n C \n France \n 1 \n 1 \n Ward, Miss. Anna \n female \n 35.0000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n NA \n \n \n C \n France \n 1 \n 0 \n Warren, Mr. Frank Manley \n male \n 64.0000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n \n \n C \n France \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n female \n 60.0000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n \n \n S \n England \n 1 \n 0 \n Weir, Col. John \n male \n 60.0000 \n 0 \n 0 \n 113800 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n White, Mr. Percival Wayland \n male \n 54.0000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n \n \n S \n England \n 1 \n 0 \n White, Mr. Richard Frasar \n male \n 21.0000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n \n \n C \n France \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n female \n 55.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n \n \n S \n England \n 1 \n 1 \n Wick, Miss. Mary Natalie \n female \n 31.0000 \n 0 \n 2 \n 36928 \n 164.8667 \n C7 \n \n \n S \n England \n 1 \n 0 \n Wick, Mr. George Dennick \n male \n 57.0000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n \n \n S \n England \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n female \n 45.0000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n \n \n C \n France \n 1 \n 0 \n Widener, Mr. George Dunton \n male \n 50.0000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n \n \n C \n France \n 1 \n 0 \n Widener, Mr. Harry Elkins \n male \n 27.0000 \n 0 \n 2 \n 113503 \n 211.5000 \n C82 \n \n \n C \n France \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n female \n 50.0000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n \n \n S \n England \n 1 \n 1 \n Willard, Miss. Constance \n female \n 21.0000 \n 0 \n 0 \n 113795 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 0 \n Williams, Mr. Charles Duane \n male \n 51.0000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n \n \n C \n France \n 1 \n 1 \n Williams, Mr. Richard Norris II \n male \n 21.0000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n \n \n S \n England \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n male \n NA \n 0 \n 0 \n 113510 \n 35.0000 \n C128 \n \n \n C \n France \n 1 \n 1 \n Wilson, Miss. Helen Alice \n female \n 31.0000 \n 0 \n 0 \n 16966 \n 134.5000 \n E39 E41 \n \n \n S \n England \n 1 \n 1 \n Woolner, Mr. Hugh \n male \n NA \n 0 \n 0 \n 19947 \n 35.5000 \n C52 \n \n \n S \n England \n 1 \n 0 \n Wright, Mr. George \n male \n 62.0000 \n 0 \n 0 \n 113807 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 1 \n Young, Miss. Marie Grice \n female \n 36.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n \n \n C \n France \n 2 \n 0 \n Abelson, Mr. Samuel \n male \n 30.0000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n \n \n C \n France \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n female \n 28.0000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n male \n 30.0000 \n 0 \n 0 \n 248744 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n male \n 18.0000 \n 0 \n 0 \n 231945 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n male \n 25.0000 \n 0 \n 0 \n C.A. 34050 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Angle, Mr. William A \n male \n 34.0000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n female \n 36.0000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ashby, Mr. John \n male \n 57.0000 \n 0 \n 0 \n 244346 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n male \n 18.0000 \n 0 \n 0 \n 29108 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n male \n 23.0000 \n 0 \n 0 \n C.A. 31030 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n female \n 36.0000 \n 0 \n 0 \n 28551 \n 13.0000 \n D \n \n \n S \n England \n 2 \n 0 \n Banfield, Mr. Frederick James \n male \n 28.0000 \n 0 \n 0 \n C.A./SOTON 34068 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bateman, Rev. Robert James \n male \n 51.0000 \n 0 \n 0 \n S.O.P. 1166 \n 12.5250 \n NA \n \n \n S \n England \n 2 \n 1 \n Beane, Mr. Edward \n male \n 32.0000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n female \n 19.0000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Beauchamp, Mr. Henry James \n male \n 28.0000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Becker, Master. Richard F \n male \n 1.0000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Becker, Miss. Marion Louise \n female \n 4.0000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n female \n 12.0000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n female \n 36.0000 \n 0 \n 3 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Beesley, Mr. Lawrence \n male \n 34.0000 \n 0 \n 0 \n 248698 \n 13.0000 \n D56 \n \n \n S \n England \n 2 \n 1 \n Bentham, Miss. Lilian W \n female \n 19.0000 \n 0 \n 0 \n 28404 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Berriman, Mr. William John \n male \n 23.0000 \n 0 \n 0 \n 28425 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Botsford, Mr. William Hull \n male \n 26.0000 \n 0 \n 0 \n 237670 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bowenur, Mr. Solomon \n male \n 42.0000 \n 0 \n 0 \n 211535 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bracken, Mr. James H \n male \n 27.0000 \n 0 \n 0 \n 220367 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n female \n 24.0000 \n 0 \n 0 \n 248733 \n 13.0000 \n F33 \n \n \n S \n England \n 2 \n 1 \n Brown, Miss. Edith Eileen \n female \n 15.0000 \n 0 \n 2 \n 29750 \n 39.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n male \n 60.0000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n female \n 40.0000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n female \n 20.0000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n male \n 25.0000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Buss, Miss. Kate \n female \n 36.0000 \n 0 \n 0 \n 27849 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n male \n 25.0000 \n 0 \n 0 \n 234686 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n male \n 42.0000 \n 0 \n 0 \n 244310 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n female \n 42.0000 \n 0 \n 0 \n 236852 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Caldwell, Master. Alden Gates \n male \n 0.8333 \n 0 \n 2 \n 248738 \n 29.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n male \n 26.0000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n female \n 22.0000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Cameron, Miss. Clear Annie \n female \n 35.0000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Campbell, Mr. William \n male \n NA \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Carbines, Mr. William \n male \n 19.0000 \n 0 \n 0 \n 28424 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n female \n 44.0000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n male \n 54.0000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Chapman, Mr. Charles Henry \n male \n 52.0000 \n 0 \n 0 \n 248731 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Chapman, Mr. John Henry \n male \n 37.0000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n female \n 29.0000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Christy, Miss. Julie Rachel \n female \n 25.0000 \n 1 \n 1 \n 237789 \n 30.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n female \n 45.0000 \n 0 \n 2 \n 237789 \n 30.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n male \n 29.0000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n female \n 28.0000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n male \n 29.0000 \n 0 \n 0 \n W./C. 14263 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n male \n 28.0000 \n 0 \n 0 \n 248740 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n male \n 24.0000 \n 0 \n 0 \n 28034 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n female \n 8.0000 \n 0 \n 2 \n C.A. 31921 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 0 \n Collyer, Mr. Harvey \n male \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n female \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n female \n 22.0000 \n 0 \n 0 \n W./C. 14266 \n 10.5000 \n F33 \n \n \n S \n England \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n female \n 30.0000 \n 0 \n 0 \n 237249 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n female \n NA \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n male \n 21.0000 \n 0 \n 0 \n 29107 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n male \n NA \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Davies, Master. John Morgan Jr \n male \n 8.0000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n Davies, Mr. Charles Henry \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n female \n 48.0000 \n 0 \n 2 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Davis, Miss. Mary \n female \n 28.0000 \n 0 \n 0 \n 237668 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n male \n 32.0000 \n 0 \n 0 \n 244360 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Deacon, Mr. Percy William \n male \n 17.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n C \n France \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n male \n 29.0000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n \n \n C \n France \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n female \n 24.0000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n \n \n S \n England \n 2 \n 0 \n Denbury, Mr. Herbert \n male \n 25.0000 \n 0 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Dibden, Mr. William \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Doling, Miss. Elsie \n female \n 18.0000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n female \n 34.0000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Downton, Mr. William James \n male \n 54.0000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Drew, Master. Marshall Brines \n male \n 8.0000 \n 0 \n 2 \n 28220 \n 32.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Drew, Mr. James Vivian \n male \n 42.0000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n female \n 34.0000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Duran y More, Miss. Asuncion \n female \n 27.0000 \n 1 \n 0 \n SC/PARIS 2149 \n 13.8583 \n NA \n \n \n C \n France \n 2 \n 1 \n Duran y More, Miss. Florentina \n female \n 30.0000 \n 1 \n 0 \n SC/PARIS 2148 \n 13.8583 \n NA \n \n \n S \n England \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n male \n 23.0000 \n 0 \n 0 \n 29751 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Enander, Mr. Ingvar \n male \n 21.0000 \n 0 \n 0 \n 236854 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n male \n 18.0000 \n 0 \n 0 \n 236171 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Faunthorpe, Mr. Harry \n male \n 40.0000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n female \n 29.0000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n male \n 18.0000 \n 0 \n 0 \n C.A. 15185 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n male \n 36.0000 \n 0 \n 0 \n 229236 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n male \n NA \n 0 \n 0 \n 239854 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n female \n 38.0000 \n 0 \n 0 \n 237671 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fynney, Mr. Joseph J \n male \n 35.0000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gale, Mr. Harry \n male \n 38.0000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gale, Mr. Shadrach \n male \n 34.0000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Garside, Miss. Ethel \n female \n 34.0000 \n 0 \n 0 \n 243880 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gaskell, Mr. Alfred \n male \n 16.0000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gavey, Mr. Lawrence \n male \n 26.0000 \n 0 \n 0 \n 31028 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gilbert, Mr. William \n male \n 47.0000 \n 0 \n 0 \n C.A. 30769 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Giles, Mr. Edgar \n male \n 21.0000 \n 1 \n 0 \n 28133 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Giles, Mr. Frederick Edward \n male \n 21.0000 \n 1 \n 0 \n 28134 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Giles, Mr. Ralph \n male \n 24.0000 \n 0 \n 0 \n 248726 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gill, Mr. John William \n male \n 24.0000 \n 0 \n 0 \n 233866 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gillespie, Mr. William Henry \n male \n 34.0000 \n 0 \n 0 \n 12233 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n male \n 30.0000 \n 0 \n 0 \n 250646 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Greenberg, Mr. Samuel \n male \n 52.0000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hale, Mr. Reginald \n male \n 30.0000 \n 0 \n 0 \n 250653 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hamalainen, Master. Viljo \n male \n 0.6667 \n 1 \n 1 \n 250649 \n 14.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n female \n 24.0000 \n 0 \n 2 \n 250649 \n 14.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Harbeck, Mr. William H \n male \n 44.0000 \n 0 \n 0 \n 248746 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n female \n 6.0000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Harper, Rev. John \n male \n 28.0000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Harris, Mr. George \n male \n 62.0000 \n 0 \n 0 \n S.W./PP 752 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Harris, Mr. Walter \n male \n 30.0000 \n 0 \n 0 \n W/C 14208 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hart, Miss. Eva Miriam \n female \n 7.0000 \n 0 \n 2 \n F.C.C. 13529 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 0 \n Hart, Mr. Benjamin \n male \n 43.0000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n female \n 45.0000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Herman, Miss. Alice \n female \n 24.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Herman, Miss. Kate \n female \n 24.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Herman, Mr. Samuel \n male \n 49.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n female \n 48.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n female \n 55.0000 \n 0 \n 0 \n 248706 \n 16.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n male \n 24.0000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hickman, Mr. Lewis \n male \n 32.0000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hickman, Mr. Stanley George \n male \n 21.0000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hiltunen, Miss. Marta \n female \n 18.0000 \n 1 \n 1 \n 250650 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n female \n 20.0000 \n 2 \n 1 \n 29105 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hocking, Mr. Richard George \n male \n 23.0000 \n 2 \n 1 \n 29104 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n male \n 36.0000 \n 0 \n 0 \n 242963 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n female \n 54.0000 \n 1 \n 3 \n 29105 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hodges, Mr. Henry Price \n male \n 50.0000 \n 0 \n 0 \n 250643 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hold, Mr. Stephen \n male \n 44.0000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n female \n 29.0000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n male \n 21.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hosono, Mr. Masabumi \n male \n 42.0000 \n 0 \n 0 \n 237798 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Howard, Mr. Benjamin \n male \n 63.0000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n female \n 60.0000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hunt, Mr. George Henry \n male \n 33.0000 \n 0 \n 0 \n SCO/W 1585 \n 12.2750 \n NA \n \n \n S \n England \n 2 \n 1 \n Ilett, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SO/C 14885 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n male \n 42.0000 \n 1 \n 0 \n 243847 \n 27.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n female \n 24.0000 \n 2 \n 1 \n 243847 \n 27.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jarvis, Mr. John Denzil \n male \n 47.0000 \n 0 \n 0 \n 237565 \n 15.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n male \n 24.0000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n male \n 22.0000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n male \n 32.0000 \n 0 \n 0 \n C.A. 33111 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n female \n 23.0000 \n 0 \n 0 \n SC/AH Basle 541 \n 13.7917 \n D \n \n \n S \n England \n 2 \n 0 \n Kantor, Mr. Sinai \n male \n 34.0000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n female \n 24.0000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n female \n 22.0000 \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n \n \n Q \n Ireland \n 2 \n 1 \n Keane, Miss. Nora A \n female \n NA \n 0 \n 0 \n 226593 \n 12.3500 \n E101 \n \n \n Q \n Ireland \n 2 \n 0 \n Keane, Mr. Daniel \n male \n 35.0000 \n 0 \n 0 \n 233734 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n female \n 45.0000 \n 0 \n 0 \n 223596 \n 13.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n male \n 57.0000 \n 0 \n 0 \n 219533 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 0 \n Knight, Mr. Robert J \n male \n NA \n 0 \n 0 \n 239855 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n male \n 31.0000 \n 0 \n 0 \n C.A. 18723 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n female \n 26.0000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Lahtinen, Rev. William \n male \n 30.0000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Lamb, Mr. John Joseph \n male \n NA \n 0 \n 0 \n 240261 \n 10.7083 \n NA \n \n \n C \n France \n 2 \n 1 \n Laroche, Miss. Louise \n female \n 1.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n female \n 3.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n male \n 25.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n female \n 22.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 1 \n Lehmann, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SC 1748 \n 12.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n female \n NA \n 0 \n 0 \n 248727 \n 33.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n female \n 34.0000 \n 0 \n 0 \n C.A. 34260 \n 10.5000 \n F33 \n \n \n C \n France \n 2 \n 0 \n Levy, Mr. Rene Jacques \n male \n 36.0000 \n 0 \n 0 \n SC/Paris 2163 \n 12.8750 \n D \n \n \n S \n England \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n male \n 24.0000 \n 0 \n 0 \n C.A. 29566 \n 10.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Lingane, Mr. John \n male \n 61.0000 \n 0 \n 0 \n 235509 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 0 \n Louch, Mr. Charles Alexander \n male \n 50.0000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n female \n 42.0000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Mack, Mrs. (Mary) \n female \n 57.0000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n E77 \n \n \n C \n France \n 2 \n 0 \n Malachard, Mr. Noel \n male \n NA \n 0 \n 0 \n 237735 \n 15.0458 \n D \n \n \n C \n France \n 2 \n 1 \n Mallet, Master. Andre \n male \n 1.0000 \n 0 \n 2 \n S.C./PARIS 2079 \n 37.0042 \n NA \n \n \n C \n France \n 2 \n 0 \n Mallet, Mr. Albert \n male \n 31.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n \n \n C \n France \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n female \n 24.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n \n \n C \n France \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n male \n NA \n 0 \n 0 \n SC/A.3 2861 \n 15.5792 \n NA \n \n \n S \n England \n 2 \n 0 \n Matthews, Mr. William John \n male \n 30.0000 \n 0 \n 0 \n 28228 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n male \n 40.0000 \n 0 \n 0 \n 239059 \n 16.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n male \n 32.0000 \n 0 \n 0 \n 237216 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n McCrie, Mr. James Matthew \n male \n 30.0000 \n 0 \n 0 \n 233478 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n McKane, Mr. Peter David \n male \n 46.0000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n female \n 13.0000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n female \n 41.0000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Mellors, Mr. William John \n male \n 19.0000 \n 0 \n 0 \n SW/PP 751 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Meyer, Mr. August \n male \n 39.0000 \n 0 \n 0 \n 248723 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Milling, Mr. Jacob Christian \n male \n 48.0000 \n 0 \n 0 \n 234360 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n male \n 70.0000 \n 0 \n 0 \n C.A. 24580 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Montvila, Rev. Juozas \n male \n 27.0000 \n 0 \n 0 \n 211536 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Moraweck, Dr. Ernest \n male \n 54.0000 \n 0 \n 0 \n 29011 \n 14.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n male \n 39.0000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n male \n 16.0000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Myles, Mr. Thomas Francis \n male \n 62.0000 \n 0 \n 0 \n 240276 \n 9.6875 \n NA \n \n \n C \n France \n 2 \n 0 \n Nasser, Mr. Nicholas \n male \n 32.5000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n \n \n C \n France \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n female \n 14.0000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n \n \n S \n England \n 2 \n 1 \n Navratil, Master. Edmond Roger \n male \n 2.0000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n \n \n S \n England \n 2 \n 1 \n Navratil, Master. Michel M \n male \n 3.0000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n \n \n S \n England \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n male \n 36.5000 \n 0 \n 2 \n 230080 \n 26.0000 \n F2 \n \n \n S \n England \n 2 \n 0 \n Nesson, Mr. Israel \n male \n 26.0000 \n 0 \n 0 \n 244368 \n 13.0000 \n F2 \n \n \n S \n England \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n male \n 19.0000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n Norman, Mr. Robert Douglas \n male \n 28.0000 \n 0 \n 0 \n 218629 \n 13.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n male \n 20.0000 \n 0 \n 0 \n SC/PARIS 2166 \n 13.8625 \n D38 \n \n \n S \n England \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n female \n 29.0000 \n 0 \n 0 \n C.A. 29395 \n 10.5000 \n F33 \n \n \n S \n England \n 2 \n 0 \n Otter, Mr. Richard \n male \n 39.0000 \n 0 \n 0 \n 28213 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n male \n 22.0000 \n 0 \n 0 \n W./C. 14260 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Padro y Manent, Mr. Julian \n male \n NA \n 0 \n 0 \n SC/PARIS 2146 \n 13.8625 \n NA \n \n \n S \n England \n 2 \n 0 \n Pain, Dr. Alfred \n male \n 23.0000 \n 0 \n 0 \n 244278 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n male \n 29.0000 \n 0 \n 0 \n SC/PARIS 2147 \n 13.8583 \n NA \n \n \n S \n England \n 2 \n 0 \n Parker, Mr. Clifford Richard \n male \n 28.0000 \n 0 \n 0 \n SC 14888 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n male \n NA \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n female \n 50.0000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Pengelly, Mr. Frederick William \n male \n 19.0000 \n 0 \n 0 \n 28665 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 0 \n Pernot, Mr. Rene \n male \n NA \n 0 \n 0 \n SC/PARIS 2131 \n 15.0500 \n NA \n \n \n S \n England \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n male \n 41.0000 \n 0 \n 0 \n 237393 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n female \n 21.0000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n female \n 19.0000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Phillips, Mr. Escott Robert \n male \n 43.0000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n female \n 32.0000 \n 0 \n 0 \n 234604 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ponesell, Mr. Martin \n male \n 34.0000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n \n \n C \n France \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n male \n 30.0000 \n 0 \n 0 \n C.A. 34644 \n 12.7375 \n NA \n \n \n C \n France \n 2 \n 0 \n Pulbaum, Mr. Franz \n male \n 27.0000 \n 0 \n 0 \n SC/PARIS 2168 \n 15.0333 \n NA \n \n \n S \n England \n 2 \n 1 \n Quick, Miss. Phyllis May \n female \n 2.0000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Quick, Miss. Winifred Vera \n female \n 8.0000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n female \n 33.0000 \n 0 \n 2 \n 26360 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Reeves, Mr. David \n male \n 36.0000 \n 0 \n 0 \n C.A. 17248 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Renouf, Mr. Peter Henry \n male \n 34.0000 \n 1 \n 0 \n 31027 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n female \n 30.0000 \n 3 \n 0 \n 31027 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n female \n 28.0000 \n 0 \n 0 \n 230434 \n 13.0000 \n NA \n \n \n C \n France \n 2 \n 0 \n Richard, Mr. Emile \n male \n 23.0000 \n 0 \n 0 \n SC/PARIS 2133 \n 15.0458 \n NA \n \n \n S \n England \n 2 \n 1 \n Richards, Master. George Sibley \n male \n 0.8333 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Richards, Master. William Rowe \n male \n 3.0000 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n female \n 24.0000 \n 2 \n 3 \n 29106 \n 18.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Ridsdale, Miss. Lucy \n female \n 50.0000 \n 0 \n 0 \n W./C. 14258 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n male \n 19.0000 \n 0 \n 0 \n 28004 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Rugg, Miss. Emily \n female \n 21.0000 \n 0 \n 0 \n C.A. 31026 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Schmidt, Mr. August \n male \n 26.0000 \n 0 \n 0 \n 248659 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n male \n 25.0000 \n 0 \n 0 \n 244361 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sharp, Mr. Percival James R \n male \n 27.0000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n female \n 25.0000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n female \n 18.0000 \n 0 \n 2 \n 250652 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Sincock, Miss. Maude \n female \n 20.0000 \n 0 \n 0 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Sinkkonen, Miss. Anna \n female \n 30.0000 \n 0 \n 0 \n 250648 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n male \n 59.0000 \n 0 \n 0 \n 237442 \n 13.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n female \n 30.0000 \n 0 \n 0 \n 234818 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 0 \n Slemen, Mr. Richard James \n male \n 35.0000 \n 0 \n 0 \n 28206 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Smith, Miss. Marion Elsie \n female \n 40.0000 \n 0 \n 0 \n 31418 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n male \n 25.0000 \n 0 \n 0 \n C.A. 29178 \n 13.0000 \n NA \n \n \n C \n France \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n male \n 41.0000 \n 0 \n 0 \n 237734 \n 15.0458 \n NA \n \n \n S \n England \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n male \n 25.0000 \n 0 \n 0 \n F.C.C. 13540 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Swane, Mr. George \n male \n 18.5000 \n 0 \n 0 \n 248734 \n 13.0000 \n F \n \n \n S \n England \n 2 \n 0 \n Sweet, Mr. George Frederick \n male \n 14.0000 \n 0 \n 0 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Toomey, Miss. Ellen \n female \n 50.0000 \n 0 \n 0 \n F.C.C. 13531 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n male \n 23.0000 \n 0 \n 0 \n 233639 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n female \n 28.0000 \n 0 \n 0 \n 240929 \n 12.6500 \n NA \n \n \n S \n England \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n female \n 27.0000 \n 0 \n 0 \n 34218 \n 10.5000 \n E101 \n \n \n S \n England \n 2 \n 0 \n Turpin, Mr. William John Robert \n male \n 29.0000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n female \n 27.0000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Veal, Mr. James \n male \n 40.0000 \n 0 \n 0 \n 28221 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Walcroft, Miss. Nellie \n female \n 31.0000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ware, Mr. John James \n male \n 30.0000 \n 1 \n 0 \n CA 31352 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ware, Mr. William Jeffery \n male \n 23.0000 \n 1 \n 0 \n 28666 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n female \n 31.0000 \n 0 \n 0 \n CA 31352 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n male \n NA \n 0 \n 0 \n 239856 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Watt, Miss. Bertha J \n female \n 12.0000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n female \n 40.0000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Webber, Miss. Susan \n female \n 32.5000 \n 0 \n 0 \n 27267 \n 13.0000 \n E101 \n \n \n S \n England \n 2 \n 0 \n Weisz, Mr. Leopold \n male \n 27.0000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n female \n 29.0000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wells, Master. Ralph Lester \n male \n 2.0000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wells, Miss. Joan \n female \n 4.0000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n female \n 29.0000 \n 0 \n 2 \n 29103 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n West, Miss. Barbara J \n female \n 0.9167 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n West, Miss. Constance Mirium \n female \n 5.0000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n West, Mr. Edwy Arthur \n male \n 36.0000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n female \n 33.0000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n Wheadon, Mr. Edward H \n male \n 66.0000 \n 0 \n 0 \n C.A. 24579 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n male \n NA \n 0 \n 0 \n SC/PARIS 2159 \n 12.8750 \n NA \n \n \n S \n England \n 2 \n 1 \n Wilhelms, Mr. Charles \n male \n 31.0000 \n 0 \n 0 \n 244270 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Williams, Mr. Charles Eugene \n male \n NA \n 0 \n 0 \n 244373 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wright, Miss. Marion \n female \n 26.0000 \n 0 \n 0 \n 220844 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n female \n 24.0000 \n 0 \n 0 \n 248747 \n 13.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Abbing, Mr. Anthony \n male \n 42.0000 \n 0 \n 0 \n C.A. 5547 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n male \n 13.0000 \n 0 \n 2 \n C.A. 2673 \n 20.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n male \n 16.0000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n female \n 35.0000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n female \n 16.0000 \n 0 \n 0 \n 348125 \n 7.6500 \n NA \n \n \n S \n England \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n male \n 25.0000 \n 0 \n 0 \n 348122 \n 7.6500 \n F G63 \n \n \n S \n England \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101284 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n female \n 18.0000 \n 0 \n 0 \n 2657 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n male \n 30.0000 \n 0 \n 0 \n C 7076 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Adams, Mr. John \n male \n 26.0000 \n 0 \n 0 \n 341826 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n female \n 40.0000 \n 1 \n 0 \n 7546 \n 9.4750 \n NA \n \n \n S \n England \n 3 \n 1 \n Aks, Master. Philip Frank \n male \n 0.8333 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n \n \n S \n England \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n female \n 18.0000 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n \n \n C \n France \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n male \n 26.0000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n \n \n S \n England \n 3 \n 0 \n Alexander, Mr. William \n male \n 26.0000 \n 0 \n 0 \n 3474 \n 7.8875 \n NA \n \n \n S \n England \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101287 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Ali, Mr. Ahmed \n male \n 24.0000 \n 0 \n 0 \n SOTON/O.Q. 3101311 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Ali, Mr. William \n male \n 25.0000 \n 0 \n 0 \n SOTON/O.Q. 3101312 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Allen, Mr. William Henry \n male \n 35.0000 \n 0 \n 0 \n 373450 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Allum, Mr. Owen George \n male \n 18.0000 \n 0 \n 0 \n 2223 \n 8.3000 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n male \n 32.0000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n \n \n S \n England \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n female \n 19.0000 \n 1 \n 0 \n 350046 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n male \n 4.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n female \n 6.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n female \n 2.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n female \n 17.0000 \n 4 \n 2 \n 3101281 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n female \n 38.0000 \n 4 \n 2 \n 347091 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n female \n 9.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n female \n 11.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Mr. Anders Johan \n male \n 39.0000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n male \n 27.0000 \n 0 \n 0 \n 350043 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n male \n 26.0000 \n 0 \n 0 \n 347075 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n female \n 39.0000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n male \n 20.0000 \n 0 \n 0 \n 347466 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Angheloff, Mr. Minko \n male \n 26.0000 \n 0 \n 0 \n 349202 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n male \n 25.0000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n \n \n S \n England \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n female \n 18.0000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n \n \n S \n England \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n male \n 24.0000 \n 0 \n 0 \n 349911 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Asim, Mr. Adola \n male \n 35.0000 \n 0 \n 0 \n SOTON/O.Q. 3101310 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Master. Carl Edgar \n male \n 5.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n male \n 9.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n male \n 3.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Master. Filip Oscar \n male \n 13.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n female \n 5.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n male \n 40.0000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Mr. Johan Charles \n male \n 23.0000 \n 0 \n 0 \n 350054 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n female \n 38.0000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n \n \n C \n France \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n female \n 45.0000 \n 0 \n 0 \n 2696 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Assaf, Mr. Gerios \n male \n 21.0000 \n 0 \n 0 \n 2692 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Assam, Mr. Ali \n male \n 23.0000 \n 0 \n 0 \n SOTON/O.Q. 3101309 \n 7.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Attalah, Miss. Malake \n female \n 17.0000 \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n \n \n C \n France \n 3 \n 0 \n Attalah, Mr. Sleiman \n male \n 30.0000 \n 0 \n 0 \n 2694 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Augustsson, Mr. Albert \n male \n 23.0000 \n 0 \n 0 \n 347468 \n 7.8542 \n NA \n \n \n C \n France \n 3 \n 1 \n Ayoub, Miss. Banoura \n female \n 13.0000 \n 0 \n 0 \n 2687 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Baccos, Mr. Raffull \n male \n 20.0000 \n 0 \n 0 \n 2679 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n male \n 32.0000 \n 1 \n 0 \n 3101278 \n 15.8500 \n NA \n \n \n S \n England \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n female \n 33.0000 \n 3 \n 0 \n 3101278 \n 15.8500 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Miss. Eugenie \n female \n 0.7500 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n female \n 0.7500 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n female \n 5.0000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n female \n 24.0000 \n 0 \n 3 \n 2666 \n 19.2583 \n NA \n \n \n S \n England \n 3 \n 1 \n Badman, Miss. Emily Louisa \n female \n 18.0000 \n 0 \n 0 \n A/4 31416 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Badt, Mr. Mohamed \n male \n 40.0000 \n 0 \n 0 \n 2623 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Balkic, Mr. Cerin \n male \n 26.0000 \n 0 \n 0 \n 349248 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Barah, Mr. Hanna Assi \n male \n 20.0000 \n 0 \n 0 \n 2663 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Barbara, Miss. Saiide \n female \n 18.0000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n female \n 45.0000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Barry, Miss. Julia \n female \n 27.0000 \n 0 \n 0 \n 330844 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Barton, Mr. David John \n male \n 22.0000 \n 0 \n 0 \n 324669 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Beavan, Mr. William Thomas \n male \n 19.0000 \n 0 \n 0 \n 323951 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n male \n 26.0000 \n 0 \n 0 \n 347068 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n male \n 22.0000 \n 0 \n 0 \n PP 4348 \n 9.3500 \n NA \n \n \n C \n France \n 3 \n 0 \n Betros, Master. Seman \n male \n NA \n 0 \n 0 \n 2622 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Betros, Mr. Tannous \n male \n 20.0000 \n 0 \n 0 \n 2648 \n 4.0125 \n NA \n \n \n S \n England \n 3 \n 1 \n Bing, Mr. Lee \n male \n 32.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n male \n 21.0000 \n 0 \n 0 \n 312992 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n male \n 18.0000 \n 0 \n 0 \n 347090 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n male \n 26.0000 \n 0 \n 0 \n 349224 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Master. Akar \n male \n 6.0000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Miss. Nourelain \n female \n 9.0000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2664 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n female \n NA \n 0 \n 2 \n 2678 \n 15.2458 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Bourke, Miss. Mary \n female \n NA \n 0 \n 2 \n 364848 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Bourke, Mr. John \n male \n 40.0000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n female \n 32.0000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n male \n 21.0000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n female \n 22.0000 \n 0 \n 0 \n 334914 \n 7.7250 \n NA \n \n \n S \n England \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n female \n 20.0000 \n 0 \n 0 \n 347471 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Braund, Mr. Lewis Richard \n male \n 29.0000 \n 1 \n 0 \n 3460 \n 7.0458 \n NA \n \n \n S \n England \n 3 \n 0 \n Braund, Mr. Owen Harris \n male \n 22.0000 \n 1 \n 0 \n A/5 21171 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n male \n 22.0000 \n 0 \n 0 \n 350045 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n male \n 35.0000 \n 0 \n 0 \n 364512 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Buckley, Miss. Katherine \n female \n 18.5000 \n 0 \n 0 \n 329944 \n 7.2833 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Buckley, Mr. Daniel \n male \n 21.0000 \n 0 \n 0 \n 330920 \n 7.8208 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Burke, Mr. Jeremiah \n male \n 19.0000 \n 0 \n 0 \n 365222 \n 6.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Burns, Miss. Mary Delia \n female \n 18.0000 \n 0 \n 0 \n 330963 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Miss. Manda \n female \n 21.0000 \n 0 \n 0 \n 315087 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Miss. Marija \n female \n 30.0000 \n 0 \n 0 \n 315084 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Mr. Jego Grga \n male \n 18.0000 \n 0 \n 0 \n 315091 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Mr. Luka \n male \n 38.0000 \n 0 \n 0 \n 315089 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Calic, Mr. Jovo \n male \n 17.0000 \n 0 \n 0 \n 315093 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Calic, Mr. Petar \n male \n 17.0000 \n 0 \n 0 \n 315086 \n 8.6625 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Canavan, Miss. Mary \n female \n 21.0000 \n 0 \n 0 \n 364846 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Canavan, Mr. Patrick \n male \n 21.0000 \n 0 \n 0 \n 364858 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Cann, Mr. Ernest Charles \n male \n 21.0000 \n 0 \n 0 \n A./5. 2152 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Caram, Mr. Joseph \n male \n NA \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n \n \n C \n France \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n female \n NA \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n \n \n S \n England \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n male \n 28.0000 \n 0 \n 0 \n 350042 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n male \n 24.0000 \n 0 \n 0 \n 350409 \n 7.8542 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n female \n 16.0000 \n 0 \n 0 \n 367231 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Carr, Miss. Jeannie \n female \n 37.0000 \n 0 \n 0 \n 368364 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Carver, Mr. Alfred John \n male \n 28.0000 \n 0 \n 0 \n 392095 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Celotti, Mr. Francesco \n male \n 24.0000 \n 0 \n 0 \n 343275 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Charters, Mr. David \n male \n 21.0000 \n 0 \n 0 \n A/5. 13032 \n 7.7333 \n NA \n \n \n S \n England \n 3 \n 1 \n Chip, Mr. Chang \n male \n 32.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Christmann, Mr. Emil \n male \n 29.0000 \n 0 \n 0 \n 343276 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n male \n 26.0000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n male \n 18.0000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n \n \n S \n England \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n male \n 20.0000 \n 0 \n 0 \n SOTON/O.Q. 3101307 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n male \n 18.0000 \n 0 \n 0 \n A/5 3540 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Colbert, Mr. Patrick \n male \n 24.0000 \n 0 \n 0 \n 371109 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Coleff, Mr. Peju \n male \n 36.0000 \n 0 \n 0 \n 349210 \n 7.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Coleff, Mr. Satio \n male \n 24.0000 \n 0 \n 0 \n 349209 \n 7.4958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n male \n 31.0000 \n 0 \n 0 \n 21332 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Connaghton, Mr. Michael \n male \n 31.0000 \n 0 \n 0 \n 335097 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Connolly, Miss. Kate \n female \n 22.0000 \n 0 \n 0 \n 370373 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Connolly, Miss. Kate \n female \n 30.0000 \n 0 \n 0 \n 330972 \n 7.6292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Connors, Mr. Patrick \n male \n 70.5000 \n 0 \n 0 \n 370369 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Cook, Mr. Jacob \n male \n 43.0000 \n 0 \n 0 \n A/5 3536 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Cor, Mr. Bartol \n male \n 35.0000 \n 0 \n 0 \n 349230 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Cor, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 349229 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Cor, Mr. Liudevit \n male \n 19.0000 \n 0 \n 0 \n 349231 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Corn, Mr. Harry \n male \n 30.0000 \n 0 \n 0 \n SOTON/OQ 392090 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n male \n 9.0000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n \n \n S \n England \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n male \n 3.0000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n \n \n S \n England \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n female \n 36.0000 \n 0 \n 2 \n C.A. 37671 \n 15.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Coxon, Mr. Daniel \n male \n 59.0000 \n 0 \n 0 \n 364500 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Crease, Mr. Ernest James \n male \n 19.0000 \n 0 \n 0 \n S.P. 3464 \n 8.1583 \n NA \n \n \n S \n England \n 3 \n 1 \n Cribb, Miss. Laura Alice \n female \n 17.0000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Cribb, Mr. John Hatfield \n male \n 44.0000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Culumovic, Mr. Jeso \n male \n 17.0000 \n 0 \n 0 \n 315090 \n 8.6625 \n NA \n \n \n C \n France \n 3 \n 0 \n Daher, Mr. Shedid \n male \n 22.5000 \n 0 \n 0 \n 2698 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n male \n 45.0000 \n 0 \n 0 \n 7598 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n female \n 22.0000 \n 0 \n 0 \n 7552 \n 10.5167 \n NA \n \n \n S \n England \n 3 \n 0 \n Dakic, Mr. Branko \n male \n 19.0000 \n 0 \n 0 \n 349228 \n 10.1708 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n female \n 30.0000 \n 0 \n 0 \n 382650 \n 6.9500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n male \n 29.0000 \n 0 \n 0 \n 382651 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n male \n 0.3333 \n 0 \n 2 \n 347080 \n 14.4000 \n NA \n \n \n S \n England \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n male \n 34.0000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n \n \n S \n England \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n female \n 28.0000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n \n \n S \n England \n 3 \n 0 \n Danoff, Mr. Yoto \n male \n 27.0000 \n 0 \n 0 \n 349219 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n male \n 25.0000 \n 0 \n 0 \n 349203 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. Alfred J \n male \n 24.0000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. Evan \n male \n 22.0000 \n 0 \n 0 \n SC/A4 23568 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. John Samuel \n male \n 21.0000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. Joseph \n male \n 17.0000 \n 2 \n 0 \n A/4 48873 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davison, Mr. Thomas Henry \n male \n NA \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n female \n NA \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n male \n 36.5000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n \n \n S \n England \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n female \n 36.0000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n \n \n S \n England \n 3 \n 1 \n de Mulder, Mr. Theodore \n male \n 30.0000 \n 0 \n 0 \n 345774 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n male \n 16.0000 \n 0 \n 0 \n 345778 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 1 \n Dean, Master. Bertram Vere \n male \n 1.0000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n female \n 0.1667 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 0 \n Dean, Mr. Bertram Frank \n male \n 26.0000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n female \n 33.0000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 0 \n Delalic, Mr. Redjo \n male \n 25.0000 \n 0 \n 0 \n 349250 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Demetri, Mr. Marinko \n male \n NA \n 0 \n 0 \n 349238 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Denkoff, Mr. Mitto \n male \n NA \n 0 \n 0 \n 349225 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Dennis, Mr. Samuel \n male \n 22.0000 \n 0 \n 0 \n A/5 21172 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Dennis, Mr. William \n male \n 36.0000 \n 0 \n 0 \n A/5 21175 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n female \n 19.0000 \n 0 \n 0 \n 330958 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Dika, Mr. Mirko \n male \n 17.0000 \n 0 \n 0 \n 349232 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Dimic, Mr. Jovan \n male \n 42.0000 \n 0 \n 0 \n 315088 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n male \n 43.0000 \n 0 \n 0 \n 349226 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Doharr, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2686 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Dooley, Mr. Patrick \n male \n 32.0000 \n 0 \n 0 \n 370376 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n male \n 19.0000 \n 0 \n 0 \n A/5. 10482 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n female \n 30.0000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Doyle, Miss. Elizabeth \n female \n 24.0000 \n 0 \n 0 \n 368702 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Drapkin, Miss. Jennie \n female \n 23.0000 \n 0 \n 0 \n SOTON/OQ 392083 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Drazenoic, Mr. Jozef \n male \n 33.0000 \n 0 \n 0 \n 349241 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Duane, Mr. Frank \n male \n 65.0000 \n 0 \n 0 \n 336439 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Duquemin, Mr. Joseph \n male \n 24.0000 \n 0 \n 0 \n S.O./P.P. 752 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n male \n 23.0000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n \n \n S \n England \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n female \n 22.0000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n male \n 18.0000 \n 0 \n 0 \n 349912 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Eklund, Mr. Hans Linus \n male \n 16.0000 \n 0 \n 0 \n 347074 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ekstrom, Mr. Johan \n male \n 45.0000 \n 0 \n 0 \n 347061 \n 6.9750 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Dibo \n male \n NA \n 0 \n 0 \n 2674 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Joseph \n male \n 39.0000 \n 0 \n 2 \n 2675 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Joseph Jr \n male \n 17.0000 \n 1 \n 1 \n 2690 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Tannous \n male \n 15.0000 \n 1 \n 1 \n 2695 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Elsbury, Mr. William James \n male \n 47.0000 \n 0 \n 0 \n A/5 3902 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n female \n 5.0000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n \n \n C \n France \n 3 \n 0 \n Emir, Mr. Farred Chehab \n male \n NA \n 0 \n 0 \n 2631 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Everett, Mr. Thomas James \n male \n 40.5000 \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Farrell, Mr. James \n male \n 40.5000 \n 0 \n 0 \n 367232 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Finoli, Mr. Luigi \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101308 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n male \n 18.0000 \n 0 \n 0 \n 350036 \n 7.7958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Fleming, Miss. Honora \n female \n NA \n 0 \n 0 \n 364859 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Flynn, Mr. James \n male \n NA \n 0 \n 0 \n 364851 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Flynn, Mr. John \n male \n NA \n 0 \n 0 \n 368323 \n 6.9500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Foley, Mr. Joseph \n male \n 26.0000 \n 0 \n 0 \n 330910 \n 7.8792 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Foley, Mr. William \n male \n NA \n 0 \n 0 \n 365235 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Foo, Mr. Choong \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n female \n 21.0000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n female \n 9.0000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mr. Arthur \n male \n NA \n 0 \n 0 \n A/5 1478 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mr. Edward Watson \n male \n 18.0000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mr. William Neal \n male \n 16.0000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n female \n 48.0000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Fox, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368573 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101314 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Gallagher, Mr. Martin \n male \n 25.0000 \n 0 \n 0 \n 36864 \n 7.7417 \n NA \n \n \n S \n England \n 3 \n 0 \n Garfirth, Mr. John \n male \n NA \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n male \n NA \n 0 \n 0 \n 349254 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Gilinski, Mr. Eliezer \n male \n 22.0000 \n 0 \n 0 \n 14973 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n female \n 16.0000 \n 0 \n 0 \n 35851 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n female \n NA \n 0 \n 0 \n 335677 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n male \n 9.0000 \n 0 \n 2 \n 363291 \n 20.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Goldsmith, Mr. Frank John \n male \n 33.0000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Goldsmith, Mr. Nathan \n male \n 41.0000 \n 0 \n 0 \n SOTON/O.Q. 3101263 \n 7.8500 \n NA \n \n \n S \n England \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n female \n 31.0000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n male \n 38.0000 \n 0 \n 0 \n SOTON/O.Q. 3101306 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Master. Harold Victor \n male \n 9.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n male \n 1.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Master. William Frederick \n male \n 11.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n female \n 10.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n female \n 16.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n male \n 14.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n male \n 40.0000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n female \n 43.0000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Green, Mr. George Henry \n male \n 51.0000 \n 0 \n 0 \n 21440 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n male \n 32.0000 \n 0 \n 0 \n 8471 \n 8.3625 \n NA \n \n \n S \n England \n 3 \n 0 \n Guest, Mr. Robert \n male \n NA \n 0 \n 0 \n 376563 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n male \n 20.0000 \n 0 \n 0 \n 7534 \n 9.8458 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n male \n 37.0000 \n 2 \n 0 \n 3101276 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n male \n 28.0000 \n 2 \n 0 \n 3101277 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n male \n 19.0000 \n 0 \n 0 \n 347069 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Haas, Miss. Aloisia \n female \n 24.0000 \n 0 \n 0 \n 349236 \n 8.8500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Hagardon, Miss. Kate \n female \n 17.0000 \n 0 \n 0 \n AQ/3. 30631 \n 7.7333 \n NA \n \n \n S \n England \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n male \n NA \n 1 \n 0 \n 65303 \n 19.9667 \n NA \n \n \n S \n England \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n male \n NA \n 1 \n 0 \n 65304 \n 19.9667 \n NA \n \n \n S \n England \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n male \n 28.0000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n \n \n S \n England \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n female \n 24.0000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n \n \n S \n England \n 3 \n 0 \n Hampe, Mr. Leon \n male \n 20.0000 \n 0 \n 0 \n 345769 \n 9.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Hanna, Mr. Mansour \n male \n 23.5000 \n 0 \n 0 \n 2693 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Hansen, Mr. Claus Peter \n male \n 41.0000 \n 2 \n 0 \n 350026 \n 14.1083 \n NA \n \n \n S \n England \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n male \n 26.0000 \n 1 \n 0 \n 350025 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n male \n 21.0000 \n 0 \n 0 \n 350029 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n female \n 45.0000 \n 1 \n 0 \n 350026 \n 14.1083 \n NA \n \n \n S \n England \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n female \n NA \n 0 \n 0 \n W./C. 6609 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n male \n 25.0000 \n 0 \n 0 \n 374887 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Hart, Mr. Henry \n male \n NA \n 0 \n 0 \n 394140 \n 6.8583 \n NA \n \n \n C \n France \n 3 \n 0 \n Hassan, Mr. Houssein G N \n male \n 11.0000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n female \n NA \n 0 \n 0 \n 370375 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n male \n 27.0000 \n 0 \n 0 \n 347089 \n 6.9750 \n NA \n \n \n S \n England \n 3 \n 1 \n Hee, Mr. Ling \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n female \n 18.0000 \n 0 \n 0 \n 365226 \n 6.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Heikkinen, Miss. Laina \n female \n 26.0000 \n 0 \n 0 \n STON/O2. 3101282 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n female \n 23.0000 \n 0 \n 0 \n STON/O2. 3101290 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n female \n 22.0000 \n 0 \n 0 \n 7548 \n 8.9625 \n NA \n \n \n S \n England \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n male \n 28.0000 \n 0 \n 0 \n 349243 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n female \n 28.0000 \n 0 \n 0 \n 347086 \n 7.7750 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Henry, Miss. Delia \n female \n NA \n 0 \n 0 \n 382649 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n female \n 2.0000 \n 0 \n 1 \n 3101298 \n 12.2875 \n NA \n \n \n S \n England \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n female \n 22.0000 \n 1 \n 1 \n 3101298 \n 12.2875 \n NA \n \n \n S \n England \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n male \n 43.0000 \n 0 \n 0 \n C 7075 \n 6.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Holthen, Mr. Johan Martin \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n \n \n S \n England \n 3 \n 1 \n Honkanen, Miss. Eliina \n female \n 27.0000 \n 0 \n 0 \n STON/O2. 3101283 \n 7.9250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Horgan, Mr. John \n male \n NA \n 0 \n 0 \n 370377 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Howard, Miss. May Elizabeth \n female \n NA \n 0 \n 0 \n A. 2. 39186 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n male \n 42.0000 \n 0 \n 0 \n 348121 \n 7.6500 \n F G63 \n \n \n S \n England \n 3 \n 1 \n Hyman, Mr. Abraham \n male \n NA \n 0 \n 0 \n 3470 \n 7.8875 \n NA \n \n \n C \n France \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n male \n 30.0000 \n 0 \n 0 \n 2685 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Ilieff, Mr. Ylio \n male \n NA \n 0 \n 0 \n 349220 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n female \n 27.0000 \n 1 \n 0 \n STON/O2. 3101270 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n female \n 25.0000 \n 1 \n 0 \n STON/O2. 3101271 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Ivanoff, Mr. Kanio \n male \n NA \n 0 \n 0 \n 349201 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Jalsevac, Mr. Ivan \n male \n 29.0000 \n 0 \n 0 \n 349240 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Jansson, Mr. Carl Olof \n male \n 21.0000 \n 0 \n 0 \n 350034 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Jardin, Mr. Jose Neto \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101305 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Jensen, Mr. Hans Peder \n male \n 20.0000 \n 0 \n 0 \n 350050 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jensen, Mr. Niels Peder \n male \n 48.0000 \n 0 \n 0 \n 350047 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n male \n 17.0000 \n 1 \n 0 \n 350048 \n 7.0542 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Jermyn, Miss. Annie \n female \n NA \n 0 \n 0 \n 14313 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n male \n NA \n 0 \n 0 \n 65306 \n 8.1125 \n NA \n \n \n S \n England \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n male \n 34.0000 \n 0 \n 0 \n 3101264 \n 6.4958 \n NA \n \n \n S \n England \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n male \n 26.0000 \n 0 \n 0 \n 347070 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Erik \n male \n 22.0000 \n 0 \n 0 \n 350052 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n male \n 33.0000 \n 0 \n 0 \n 7540 \n 8.6542 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Karl Johan \n male \n 31.0000 \n 0 \n 0 \n 347063 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Nils \n male \n 29.0000 \n 0 \n 0 \n 347467 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Johnson, Master. Harold Theodor \n male \n 4.0000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n \n \n S \n England \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n female \n 1.0000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnson, Mr. Alfred \n male \n 49.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n male \n 33.0000 \n 0 \n 0 \n 347062 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n male \n 19.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n S \n England \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n female \n 27.0000 \n 0 \n 2 \n 347742 \n 11.1333 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n male \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n female \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Mr. Andrew G \n male \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n female \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Jonkoff, Mr. Lalio \n male \n 23.0000 \n 0 \n 0 \n 349204 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Jonsson, Mr. Carl \n male \n 32.0000 \n 0 \n 0 \n 350417 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n male \n 27.0000 \n 0 \n 0 \n 350408 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jussila, Miss. Katriina \n female \n 20.0000 \n 1 \n 0 \n 4136 \n 9.8250 \n NA \n \n \n S \n England \n 3 \n 0 \n Jussila, Miss. Mari Aina \n female \n 21.0000 \n 1 \n 0 \n 4137 \n 9.8250 \n NA \n \n \n S \n England \n 3 \n 1 \n Jussila, Mr. Eiriik \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101286 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n male \n 17.0000 \n 0 \n 0 \n STON/O 2. 3101274 \n 7.1250 \n NA \n \n \n S \n England \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n male \n 21.0000 \n 0 \n 0 \n 8475 \n 8.4333 \n NA \n \n \n S \n England \n 3 \n 0 \n Karaic, Mr. Milan \n male \n 30.0000 \n 0 \n 0 \n 349246 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n male \n 21.0000 \n 0 \n 0 \n 350053 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n male \n 33.0000 \n 0 \n 0 \n 347465 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Karlsson, Mr. Nils August \n male \n 22.0000 \n 0 \n 0 \n 350060 \n 7.5208 \n NA \n \n \n C \n France \n 3 \n 1 \n Karun, Miss. Manca \n female \n 4.0000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n \n \n C \n France \n 3 \n 1 \n Karun, Mr. Franz \n male \n 39.0000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n \n \n C \n France \n 3 \n 0 \n Kassem, Mr. Fared \n male \n NA \n 0 \n 0 \n 2700 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n male \n 18.5000 \n 0 \n 0 \n 2682 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n male \n NA \n 0 \n 0 \n 12460 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Keefe, Mr. Arthur \n male \n NA \n 0 \n 0 \n 323592 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n female \n NA \n 0 \n 0 \n 9234 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Kelly, Miss. Mary \n female \n NA \n 0 \n 0 \n 14312 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kelly, Mr. James \n male \n 34.5000 \n 0 \n 0 \n 330911 \n 7.8292 \n NA \n \n \n S \n England \n 3 \n 0 \n Kelly, Mr. James \n male \n 44.0000 \n 0 \n 0 \n 363592 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Kennedy, Mr. John \n male \n NA \n 0 \n 0 \n 368783 \n 7.7500 \n NA \n \n \n C \n France \n 3 \n 0 \n Khalil, Mr. Betros \n male \n NA \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n female \n NA \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kiernan, Mr. John \n male \n NA \n 1 \n 0 \n 367227 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kiernan, Mr. Philip \n male \n NA \n 1 \n 0 \n 367229 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n male \n NA \n 0 \n 0 \n 36865 \n 7.7375 \n NA \n \n \n S \n England \n 3 \n 0 \n Kink, Miss. Maria \n female \n 22.0000 \n 2 \n 0 \n 315152 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Kink, Mr. Vincenz \n male \n 26.0000 \n 2 \n 0 \n 315151 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n female \n 4.0000 \n 0 \n 2 \n 315153 \n 22.0250 \n NA \n \n \n S \n England \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n male \n 29.0000 \n 3 \n 1 \n 315153 \n 22.0250 \n NA \n \n \n S \n England \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n female \n 26.0000 \n 1 \n 1 \n 315153 \n 22.0250 \n NA \n \n \n S \n England \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n female \n 1.0000 \n 1 \n 1 \n 350405 \n 12.1833 \n NA \n \n \n S \n England \n 3 \n 0 \n Klasen, Mr. Klas Albin \n male \n 18.0000 \n 1 \n 1 \n 350404 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n female \n 36.0000 \n 0 \n 2 \n 350405 \n 12.1833 \n NA \n \n \n C \n France \n 3 \n 0 \n Kraeff, Mr. Theodor \n male \n NA \n 0 \n 0 \n 349253 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Krekorian, Mr. Neshan \n male \n 25.0000 \n 0 \n 0 \n 2654 \n 7.2292 \n F E57 \n \n \n C \n France \n 3 \n 0 \n Lahoud, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2624 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n female \n 37.0000 \n 0 \n 0 \n 4135 \n 9.5875 \n NA \n \n \n S \n England \n 3 \n 0 \n Laleff, Mr. Kristo \n male \n NA \n 0 \n 0 \n 349217 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Lam, Mr. Ali \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Lam, Mr. Len \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n female \n 22.0000 \n 0 \n 0 \n C 7077 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Lane, Mr. Patrick \n male \n NA \n 0 \n 0 \n 7935 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Lang, Mr. Fang \n male \n 26.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Larsson, Mr. August Viktor \n male \n 29.0000 \n 0 \n 0 \n 7545 \n 9.4833 \n NA \n \n \n S \n England \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n male \n 29.0000 \n 0 \n 0 \n 347067 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n male \n 22.0000 \n 0 \n 0 \n 347065 \n 7.7750 \n NA \n \n \n C \n France \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n male \n 22.0000 \n 0 \n 0 \n 2620 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n male \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Miss. Ida \n female \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Miss. Jeannie \n female \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Miss. Mathilde \n female \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n female \n NA \n 0 \n 4 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101292 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n male \n 34.5000 \n 0 \n 0 \n 2683 \n 6.4375 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Lennon, Miss. Mary \n female \n NA \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Lennon, Mr. Denis \n male \n NA \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Leonard, Mr. Lionel \n male \n 36.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lester, Mr. James \n male \n 39.0000 \n 0 \n 0 \n A/4 48871 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lievens, Mr. Rene Aime \n male \n 24.0000 \n 0 \n 0 \n 345781 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n female \n 25.0000 \n 0 \n 0 \n 347071 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n female \n 45.0000 \n 0 \n 0 \n 347073 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n male \n 36.0000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n female \n 30.0000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n \n \n S \n England \n 3 \n 1 \n Lindqvist, Mr. Eino William \n male \n 20.0000 \n 1 \n 0 \n STON/O 2. 3101285 \n 7.9250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Linehan, Mr. Michael \n male \n NA \n 0 \n 0 \n 330971 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Ling, Mr. Lee \n male \n 28.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Lithman, Mr. Simon \n male \n NA \n 0 \n 0 \n S.O./P.P. 251 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lobb, Mr. William Arthur \n male \n 30.0000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n female \n 26.0000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lockyer, Mr. Edward \n male \n NA \n 0 \n 0 \n 1222 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n male \n 20.5000 \n 0 \n 0 \n A/5 21173 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Lulic, Mr. Nikola \n male \n 27.0000 \n 0 \n 0 \n 315098 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n male \n 51.0000 \n 0 \n 0 \n 347743 \n 7.0542 \n NA \n \n \n S \n England \n 3 \n 1 \n Lundin, Miss. Olga Elida \n female \n 23.0000 \n 0 \n 0 \n 347469 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n male \n 32.0000 \n 0 \n 0 \n 350403 \n 7.5792 \n NA \n \n \n S \n England \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n male \n NA \n 0 \n 0 \n 349235 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n MacKay, Mr. George William \n male \n NA \n 0 \n 0 \n C.A. 42795 \n 7.5500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n female \n NA \n 0 \n 0 \n 370370 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n male \n 24.0000 \n 0 \n 0 \n C 17369 \n 7.1417 \n NA \n \n \n S \n England \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n male \n 22.0000 \n 0 \n 0 \n STON/O 2. 3101275 \n 7.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n female \n NA \n 0 \n 0 \n 330924 \n 7.8792 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mahon, Mr. John \n male \n NA \n 0 \n 0 \n AQ/4 3130 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Maisner, Mr. Simon \n male \n NA \n 0 \n 0 \n A/S 2816 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n male \n 29.0000 \n 0 \n 0 \n STON/O 2. 3101268 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 1 \n Mamee, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2677 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mangan, Miss. Mary \n female \n 30.5000 \n 0 \n 0 \n 364850 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mannion, Miss. Margareth \n female \n NA \n 0 \n 0 \n 36866 \n 7.7375 \n NA \n \n \n C \n France \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2655 \n 7.2292 \n F E46 \n \n \n C \n France \n 3 \n 0 \n Markoff, Mr. Marin \n male \n 35.0000 \n 0 \n 0 \n 349213 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Markun, Mr. Johann \n male \n 33.0000 \n 0 \n 0 \n 349257 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Masselmani, Mrs. Fatima \n female \n NA \n 0 \n 0 \n 2649 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Matinoff, Mr. Nicola \n male \n NA \n 0 \n 0 \n 349255 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n female \n NA \n 0 \n 0 \n 383123 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n male \n NA \n 0 \n 0 \n 367228 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCoy, Miss. Agnes \n female \n NA \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCoy, Miss. Alicia \n female \n NA \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCoy, Mr. Bernard \n male \n NA \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n female \n NA \n 0 \n 0 \n 330932 \n 7.7875 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McEvoy, Mr. Michael \n male \n NA \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McGovern, Miss. Mary \n female \n NA \n 0 \n 0 \n 330931 \n 7.8792 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n female \n 15.0000 \n 0 \n 0 \n 330923 \n 8.0292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McGowan, Miss. Katherine \n female \n 35.0000 \n 0 \n 0 \n 9232 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McMahon, Mr. Martin \n male \n NA \n 0 \n 0 \n 370372 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n McNamee, Mr. Neal \n male \n 24.0000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n female \n 19.0000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McNeill, Miss. Bridget \n female \n NA \n 0 \n 0 \n 370368 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n female \n NA \n 0 \n 0 \n SOTON/O.Q. 392087 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n female \n NA \n 0 \n 0 \n 343095 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Meo, Mr. Alfonzo \n male \n 55.5000 \n 0 \n 0 \n A.5. 11206 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mernagh, Mr. Robert \n male \n NA \n 0 \n 0 \n 368703 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n male \n 21.0000 \n 0 \n 0 \n 345501 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Miles, Mr. Frank \n male \n NA \n 0 \n 0 \n 359306 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Mineff, Mr. Ivan \n male \n 24.0000 \n 0 \n 0 \n 349233 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Minkoff, Mr. Lazar \n male \n 21.0000 \n 0 \n 0 \n 349211 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n male \n 28.0000 \n 0 \n 0 \n 349207 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Mitkoff, Mr. Mito \n male \n NA \n 0 \n 0 \n 349221 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n female \n NA \n 0 \n 0 \n 330980 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n male \n 25.0000 \n 0 \n 0 \n 348123 \n 7.6500 \n F G73 \n \n \n S \n England \n 3 \n 1 \n Moor, Master. Meier \n male \n 6.0000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n \n \n S \n England \n 3 \n 1 \n Moor, Mrs. (Beila) \n female \n 27.0000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n \n \n S \n England \n 3 \n 0 \n Moore, Mr. Leonard Charles \n male \n NA \n 0 \n 0 \n A4. 54510 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Moran, Miss. Bertha \n female \n NA \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Moran, Mr. Daniel J \n male \n NA \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Moran, Mr. James \n male \n NA \n 0 \n 0 \n 330877 \n 8.4583 \n NA \n \n \n S \n England \n 3 \n 0 \n Morley, Mr. William \n male \n 34.0000 \n 0 \n 0 \n 364506 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n male \n NA \n 0 \n 0 \n 372622 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Moss, Mr. Albert Johan \n male \n NA \n 0 \n 0 \n 312991 \n 7.7750 \n NA \n \n \n C \n France \n 3 \n 1 \n Moubarek, Master. Gerios \n male \n NA \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n male \n NA \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n female \n NA \n 0 \n 2 \n 2661 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n female \n NA \n 0 \n 0 \n 2626 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n male \n NA \n 0 \n 0 \n 374746 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n female \n NA \n 0 \n 0 \n 35852 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n female \n 24.0000 \n 0 \n 0 \n 382653 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Murdlin, Mr. Joseph \n male \n NA \n 0 \n 0 \n A./5. 3235 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n female \n NA \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n female \n NA \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Murphy, Miss. Nora \n female \n NA \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n male \n 18.0000 \n 0 \n 0 \n 347078 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Naidenoff, Mr. Penko \n male \n 22.0000 \n 0 \n 0 \n 349206 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n female \n 15.0000 \n 0 \n 0 \n 2667 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n female \n 1.0000 \n 0 \n 2 \n 2653 \n 15.7417 \n NA \n \n \n C \n France \n 3 \n 1 \n Nakid, Mr. Sahid \n male \n 20.0000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n \n \n C \n France \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n female \n 19.0000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n \n \n S \n England \n 3 \n 0 \n Nancarrow, Mr. William Henry \n male \n 33.0000 \n 0 \n 0 \n A./5. 3338 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Nankoff, Mr. Minko \n male \n NA \n 0 \n 0 \n 349218 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Nasr, Mr. Mustafa \n male \n NA \n 0 \n 0 \n 2652 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Naughton, Miss. Hannah \n female \n NA \n 0 \n 0 \n 365237 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Nenkoff, Mr. Christo \n male \n NA \n 0 \n 0 \n 349234 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n male \n 12.0000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n \n \n C \n France \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n female \n 14.0000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n \n \n S \n England \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n female \n 29.0000 \n 0 \n 0 \n 3101297 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Niklasson, Mr. Samuel \n male \n 28.0000 \n 0 \n 0 \n 363611 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n female \n 18.0000 \n 0 \n 0 \n 347066 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n female \n 26.0000 \n 0 \n 0 \n 347470 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n male \n 21.0000 \n 0 \n 0 \n 350410 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n male \n 41.0000 \n 0 \n 0 \n SOTON/O2 3101272 \n 7.1250 \n NA \n \n \n S \n England \n 3 \n 1 \n Niskanen, Mr. Juha \n male \n 39.0000 \n 0 \n 0 \n STON/O 2. 3101289 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n male \n 21.0000 \n 0 \n 0 \n A/4. 39886 \n 7.8000 \n NA \n \n \n C \n France \n 3 \n 0 \n Novel, Mr. Mansouer \n male \n 28.5000 \n 0 \n 0 \n 2697 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n female \n 22.0000 \n 0 \n 0 \n 347081 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n male \n 61.0000 \n 0 \n 0 \n 345364 \n 6.2375 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Brien, Mr. Thomas \n male \n NA \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Brien, Mr. Timothy \n male \n NA \n 0 \n 0 \n 330979 \n 7.8292 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n female \n NA \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Connell, Mr. Patrick D \n male \n NA \n 0 \n 0 \n 334912 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Connor, Mr. Maurice \n male \n NA \n 0 \n 0 \n 371060 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Connor, Mr. Patrick \n male \n NA \n 0 \n 0 \n 366713 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Odahl, Mr. Nils Martin \n male \n 23.0000 \n 0 \n 0 \n 7267 \n 9.2250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n female \n NA \n 0 \n 0 \n 364856 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n female \n NA \n 0 \n 0 \n 14311 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n female \n NA \n 0 \n 0 \n 330959 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 1 \n Ohman, Miss. Velin \n female \n 22.0000 \n 0 \n 0 \n 347085 \n 7.7750 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Keefe, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368402 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n female \n NA \n 0 \n 0 \n 330919 \n 7.8292 \n NA \n \n \n S \n England \n 3 \n 1 \n Olsen, Master. Artur Karl \n male \n 9.0000 \n 0 \n 1 \n C 17368 \n 3.1708 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsen, Mr. Henry Margido \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n male \n 42.0000 \n 0 \n 1 \n 4579 \n 8.4042 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsen, Mr. Ole Martin \n male \n NA \n 0 \n 0 \n Fa 265302 \n 7.3125 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsson, Miss. Elina \n female \n 31.0000 \n 0 \n 0 \n 350407 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n male \n 28.0000 \n 0 \n 0 \n 347464 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n male \n 32.0000 \n 0 \n 0 \n 347079 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n male \n 20.0000 \n 0 \n 0 \n 6563 \n 9.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Oreskovic, Miss. Jelka \n female \n 23.0000 \n 0 \n 0 \n 315085 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Oreskovic, Miss. Marija \n female \n 20.0000 \n 0 \n 0 \n 315096 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Oreskovic, Mr. Luka \n male \n 20.0000 \n 0 \n 0 \n 315094 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Osen, Mr. Olaf Elon \n male \n 16.0000 \n 0 \n 0 \n 7534 \n 9.2167 \n NA \n \n \n S \n England \n 3 \n 1 \n Osman, Mrs. Mara \n female \n 31.0000 \n 0 \n 0 \n 349244 \n 8.6833 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n female \n NA \n 0 \n 0 \n 330909 \n 7.6292 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n male \n 2.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Master. Paul Folke \n male \n 6.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Miss. Stina Viola \n female \n 3.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n female \n 8.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n female \n 29.0000 \n 0 \n 4 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Master. Eino Viljami \n male \n 1.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Master. Juha Niilo \n male \n 7.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Master. Urho Abraham \n male \n 2.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n male \n 16.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n male \n 14.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n female \n 41.0000 \n 0 \n 5 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Pasic, Mr. Jakob \n male \n 21.0000 \n 0 \n 0 \n 315097 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Patchett, Mr. George \n male \n 19.0000 \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Paulner, Mr. Uscher \n male \n NA \n 0 \n 0 \n 3411 \n 8.7125 \n NA \n \n \n S \n England \n 3 \n 0 \n Pavlovic, Mr. Stefo \n male \n 32.0000 \n 0 \n 0 \n 349242 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Peacock, Master. Alfred Edward \n male \n 0.7500 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Peacock, Miss. Treasteall \n female \n 3.0000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n female \n 26.0000 \n 0 \n 2 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Pearce, Mr. Ernest \n male \n NA \n 0 \n 0 \n 343271 \n 7.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Pedersen, Mr. Olaf \n male \n NA \n 0 \n 0 \n 345498 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Peduzzi, Mr. Joseph \n male \n NA \n 0 \n 0 \n A/5 2817 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101294 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n male \n 25.0000 \n 0 \n 0 \n STON/O 2. 3101291 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Perkin, Mr. John Henry \n male \n 22.0000 \n 0 \n 0 \n A/5 21174 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n male \n 25.0000 \n 1 \n 0 \n 347083 \n 7.7750 \n NA \n \n \n C \n France \n 3 \n 1 \n Peter, Master. Michael J \n male \n NA \n 1 \n 1 \n 2668 \n 22.3583 \n NA \n \n \n C \n France \n 3 \n 1 \n Peter, Miss. Anna \n female \n NA \n 1 \n 1 \n 2668 \n 22.3583 \n F E69 \n \n \n C \n France \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n female \n NA \n 0 \n 2 \n 2668 \n 22.3583 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Peters, Miss. Katie \n female \n NA \n 0 \n 0 \n 330935 \n 8.1375 \n NA \n \n \n S \n England \n 3 \n 0 \n Petersen, Mr. Marius \n male \n 24.0000 \n 0 \n 0 \n 342441 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Petranec, Miss. Matilda \n female \n 28.0000 \n 0 \n 0 \n 349245 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Petroff, Mr. Nedelio \n male \n 19.0000 \n 0 \n 0 \n 349212 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n male \n NA \n 0 \n 0 \n 349215 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Petterson, Mr. Johan Emil \n male \n 25.0000 \n 1 \n 0 \n 347076 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n female \n 18.0000 \n 0 \n 0 \n 347087 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n male \n 32.0000 \n 0 \n 0 \n SOTON/O.Q. 392078 \n 8.0500 \n E10 \n \n \n S \n England \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n male \n NA \n 0 \n 0 \n 349227 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Pokrnic, Mr. Mate \n male \n 17.0000 \n 0 \n 0 \n 315095 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Pokrnic, Mr. Tome \n male \n 24.0000 \n 0 \n 0 \n 315092 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Radeff, Mr. Alexander \n male \n NA \n 0 \n 0 \n 349223 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n female \n NA \n 0 \n 0 \n 65305 \n 8.1125 \n NA \n \n \n C \n France \n 3 \n 0 \n Razi, Mr. Raihed \n male \n NA \n 0 \n 0 \n 2629 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Reed, Mr. James George \n male \n NA \n 0 \n 0 \n 362316 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rekic, Mr. Tido \n male \n 38.0000 \n 0 \n 0 \n 349249 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Reynolds, Mr. Harold J \n male \n 21.0000 \n 0 \n 0 \n 342684 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Albert \n male \n 10.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Arthur \n male \n 4.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Eric \n male \n 7.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Eugene \n male \n 2.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. George Hugh \n male \n 8.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n female \n 39.0000 \n 0 \n 5 \n 382652 \n 29.1250 \n NA \n \n \n S \n England \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n female \n 22.0000 \n 0 \n 0 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Rintamaki, Mr. Matti \n male \n 35.0000 \n 0 \n 0 \n STON/O 2. 3101273 \n 7.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n female \n NA \n 0 \n 0 \n 334915 \n 7.7208 \n NA \n \n \n S \n England \n 3 \n 0 \n Risien, Mr. Samuel Beard \n male \n NA \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n female \n NA \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Robins, Mr. Alexander A \n male \n 50.0000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n female \n 47.0000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Rogers, Mr. William John \n male \n NA \n 0 \n 0 \n S.C./A.4. 23567 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n male \n NA \n 0 \n 0 \n 312993 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n female \n 2.0000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n \n \n S \n England \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n male \n 18.0000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n \n \n S \n England \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n female \n 41.0000 \n 0 \n 2 \n 370129 \n 20.2125 \n NA \n \n \n S \n England \n 3 \n 1 \n Roth, Miss. Sarah A \n female \n NA \n 0 \n 0 \n 342712 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rouse, Mr. Richard Henry \n male \n 50.0000 \n 0 \n 0 \n A/5 3594 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rush, Mr. Alfred George John \n male \n 16.0000 \n 0 \n 0 \n A/4. 20589 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Ryan, Mr. Edward \n male \n NA \n 0 \n 0 \n 383162 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Ryan, Mr. Patrick \n male \n NA \n 0 \n 0 \n 371110 \n 24.1500 \n NA \n \n \n C \n France \n 3 \n 0 \n Saad, Mr. Amin \n male \n NA \n 0 \n 0 \n 2671 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Saad, Mr. Khalil \n male \n 25.0000 \n 0 \n 0 \n 2672 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Saade, Mr. Jean Nassr \n male \n NA \n 0 \n 0 \n 2676 \n 7.2250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Sadlier, Mr. Matthew \n male \n NA \n 0 \n 0 \n 367655 \n 7.7292 \n NA \n \n \n S \n England \n 3 \n 0 \n Sadowitz, Mr. Harry \n male \n NA \n 0 \n 0 \n LP 1588 \n 7.5750 \n NA \n \n \n S \n England \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n male \n 38.5000 \n 0 \n 0 \n SOTON/O.Q. 3101262 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Master. Thomas Henry \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Master. William Henry \n male \n 14.5000 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Ada \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Constance Gladys \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Stella Anna \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. Frederick \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. George John Jr \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. John George \n male \n NA \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n female \n NA \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Salander, Mr. Karl Johan \n male \n 24.0000 \n 0 \n 0 \n 7266 \n 9.3250 \n NA \n \n \n S \n England \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n female \n 21.0000 \n 0 \n 0 \n 343120 \n 7.6500 \n NA \n \n \n S \n England \n 3 \n 0 \n Salonen, Mr. Johan Werner \n male \n 39.0000 \n 0 \n 0 \n 3101296 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 0 \n Samaan, Mr. Elias \n male \n NA \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n \n \n C \n France \n 3 \n 0 \n Samaan, Mr. Hanna \n male \n NA \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n \n \n C \n France \n 3 \n 0 \n Samaan, Mr. Youssef \n male \n NA \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n \n \n S \n England \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n female \n 1.0000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n female \n 24.0000 \n 0 \n 2 \n PP 9549 \n 16.7000 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n female \n 4.0000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sap, Mr. Julius \n male \n 25.0000 \n 0 \n 0 \n 345768 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Saundercock, Mr. William Henry \n male \n 20.0000 \n 0 \n 0 \n A/5. 2151 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n male \n 24.5000 \n 0 \n 0 \n 342826 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Scanlan, Mr. James \n male \n NA \n 0 \n 0 \n 36209 \n 7.7250 \n NA \n \n \n S \n England \n 3 \n 0 \n Sdycoff, Mr. Todor \n male \n NA \n 0 \n 0 \n 349222 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n male \n NA \n 0 \n 0 \n 370374 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n male \n 29.0000 \n 0 \n 0 \n 345779 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Shellard, Mr. Frederick William \n male \n NA \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n female \n NA \n 0 \n 0 \n 330968 \n 7.7792 \n NA \n \n \n S \n England \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n male \n NA \n 0 \n 0 \n 374910 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Simmons, Mr. John \n male \n NA \n 0 \n 0 \n SOTON/OQ 392082 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Sirayanian, Mr. Orsen \n male \n 22.0000 \n 0 \n 0 \n 2669 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Sirota, Mr. Maurice \n male \n NA \n 0 \n 0 \n 392092 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sivic, Mr. Husein \n male \n 40.0000 \n 0 \n 0 \n 349251 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101280 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 3101265 \n 7.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Master. Harald \n male \n 4.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n male \n 10.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Miss. Mabel \n female \n 9.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n female \n 2.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Mr. Wilhelm \n male \n 40.0000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n female \n 45.0000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Slabenoff, Mr. Petco \n male \n NA \n 0 \n 0 \n 349214 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n male \n NA \n 0 \n 0 \n SOTON/OQ 392086 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Smiljanic, Mr. Mile \n male \n NA \n 0 \n 0 \n 315037 \n 8.6625 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Smith, Mr. Thomas \n male \n NA \n 0 \n 0 \n 384461 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Smyth, Miss. Julia \n female \n NA \n 0 \n 0 \n 335432 \n 7.7333 \n NA \n \n \n S \n England \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n male \n 19.0000 \n 0 \n 0 \n 348124 \n 7.6500 \n F G73 \n \n \n S \n England \n 3 \n 0 \n Somerton, Mr. Francis William \n male \n 30.0000 \n 0 \n 0 \n A.5. 18509 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Spector, Mr. Woolf \n male \n NA \n 0 \n 0 \n A.5. 3236 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Spinner, Mr. Henry John \n male \n 32.0000 \n 0 \n 0 \n STON/OQ. 369943 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Staneff, Mr. Ivan \n male \n NA \n 0 \n 0 \n 349208 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Stankovic, Mr. Ivan \n male \n 33.0000 \n 0 \n 0 \n 349239 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n female \n 23.0000 \n 0 \n 0 \n CA. 2314 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Stanley, Mr. Edward Roland \n male \n 21.0000 \n 0 \n 0 \n A/4 45380 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Storey, Mr. Thomas \n male \n 60.5000 \n 0 \n 0 \n 3701 \n NA \n NA \n \n \n S \n England \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n male \n 19.0000 \n 0 \n 0 \n 349205 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n female \n 22.0000 \n 0 \n 0 \n 7553 \n 9.8375 \n NA \n \n \n S \n England \n 3 \n 1 \n Stranden, Mr. Juho \n male \n 31.0000 \n 0 \n 0 \n STON/O 2. 3101288 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Strilic, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 315083 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Strom, Miss. Telma Matilda \n female \n 2.0000 \n 0 \n 1 \n 347054 \n 10.4625 \n G6 \n \n \n S \n England \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n female \n 29.0000 \n 1 \n 1 \n 347054 \n 10.4625 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n male \n 16.0000 \n 0 \n 0 \n SOTON/OQ 392089 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Sundman, Mr. Johan Julian \n male \n 44.0000 \n 0 \n 0 \n STON/O 2. 3101269 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n male \n 25.0000 \n 0 \n 0 \n SOTON/OQ 392076 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Svensson, Mr. Johan \n male \n 74.0000 \n 0 \n 0 \n 347060 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n male \n 14.0000 \n 0 \n 0 \n 7538 \n 9.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Svensson, Mr. Olof \n male \n 24.0000 \n 0 \n 0 \n 350035 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n male \n 25.0000 \n 0 \n 0 \n 350033 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n male \n 34.0000 \n 0 \n 0 \n 363294 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 1 \n Thomas, Master. Assad Alexander \n male \n 0.4167 \n 0 \n 1 \n 2625 \n 8.5167 \n NA \n \n \n C \n France \n 3 \n 0 \n Thomas, Mr. Charles P \n male \n NA \n 1 \n 0 \n 2621 \n 6.4375 \n NA \n \n \n C \n France \n 3 \n 0 \n Thomas, Mr. John \n male \n NA \n 0 \n 0 \n 2681 \n 6.4375 \n NA \n \n \n C \n France \n 3 \n 0 \n Thomas, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2684 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n female \n 16.0000 \n 1 \n 1 \n 2625 \n 8.5167 \n NA \n \n \n S \n England \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n male \n NA \n 0 \n 0 \n 32302 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Thorneycroft, Mr. Percival \n male \n NA \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n female \n NA \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Tikkanen, Mr. Juho \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101293 \n 7.9250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Tobin, Mr. Roger \n male \n NA \n 0 \n 0 \n 383121 \n 7.7500 \n F38 \n \n \n S \n England \n 3 \n 0 \n Todoroff, Mr. Lalio \n male \n NA \n 0 \n 0 \n 349216 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n male \n 30.5000 \n 0 \n 0 \n 364499 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Torber, Mr. Ernst William \n male \n 44.0000 \n 0 \n 0 \n 364511 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Torfa, Mr. Assad \n male \n NA \n 0 \n 0 \n 2673 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 1 \n Tornquist, Mr. William Henry \n male \n 25.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n C \n France \n 3 \n 0 \n Toufik, Mr. Nakli \n male \n NA \n 0 \n 0 \n 2641 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 1 \n Touma, Master. Georges Youssef \n male \n 7.0000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Touma, Miss. Maria Youssef \n female \n 9.0000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n female \n 29.0000 \n 0 \n 2 \n 2650 \n 15.2458 \n NA \n \n \n S \n England \n 3 \n 0 \n Turcin, Mr. Stjepan \n male \n 36.0000 \n 0 \n 0 \n 349247 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Turja, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 4138 \n 9.8417 \n NA \n \n \n S \n England \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n female \n 63.0000 \n 0 \n 0 \n 4134 \n 9.5875 \n NA \n \n \n S \n England \n 3 \n 0 \n van Billiard, Master. James William \n male \n NA \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n van Billiard, Master. Walter John \n male \n 11.5000 \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n male \n 40.5000 \n 0 \n 2 \n A/5. 851 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Van Impe, Miss. Catharina \n female \n 10.0000 \n 0 \n 2 \n 345773 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n male \n 36.0000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n female \n 30.0000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n male \n NA \n 0 \n 0 \n 345777 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n male \n 33.0000 \n 0 \n 0 \n 345780 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n male \n 28.0000 \n 0 \n 0 \n 345770 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n male \n 28.0000 \n 0 \n 0 \n 345783 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n male \n 47.0000 \n 0 \n 0 \n 345765 \n 9.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n female \n 18.0000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Mr. Julius \n male \n 31.0000 \n 3 \n 0 \n 345763 \n 18.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n male \n 16.0000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n female \n 31.0000 \n 1 \n 0 \n 345763 \n 18.0000 \n NA \n \n \n C \n France \n 3 \n 1 \n Vartanian, Mr. David \n male \n 22.0000 \n 0 \n 0 \n 2658 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n male \n 20.0000 \n 0 \n 0 \n 350416 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n female \n 14.0000 \n 0 \n 0 \n 350406 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Vovk, Mr. Janko \n male \n 22.0000 \n 0 \n 0 \n 349252 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Waelens, Mr. Achille \n male \n 22.0000 \n 0 \n 0 \n 345767 \n 9.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Ware, Mr. Frederick \n male \n NA \n 0 \n 0 \n 359309 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Warren, Mr. Charles William \n male \n NA \n 0 \n 0 \n C.A. 49867 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Webber, Mr. James \n male \n NA \n 0 \n 0 \n SOTON/OQ 3101316 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wenzel, Mr. Linhart \n male \n 32.5000 \n 0 \n 0 \n 345775 \n 9.5000 \n NA \n \n \n C \n France \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n female \n 38.0000 \n 0 \n 0 \n 2688 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n male \n 51.0000 \n 0 \n 0 \n 347064 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n male \n 18.0000 \n 1 \n 0 \n 3101267 \n 6.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n male \n 21.0000 \n 1 \n 0 \n 3101266 \n 6.4958 \n NA \n \n \n S \n England \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n female \n 47.0000 \n 1 \n 0 \n 363272 \n 7.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n male \n NA \n 0 \n 0 \n 3410 \n 8.7125 \n NA \n \n \n S \n England \n 3 \n 0 \n Willey, Mr. Edward \n male \n NA \n 0 \n 0 \n S.O./P.P. 751 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n male \n NA \n 0 \n 0 \n A/5 2466 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Williams, Mr. Leslie \n male \n 28.5000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Windelov, Mr. Einar \n male \n 21.0000 \n 0 \n 0 \n SOTON/OQ 3101317 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wirz, Mr. Albert \n male \n 27.0000 \n 0 \n 0 \n 315154 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Wiseman, Mr. Phillippe \n male \n NA \n 0 \n 0 \n A/4. 34244 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wittevrongel, Mr. Camille \n male \n 36.0000 \n 0 \n 0 \n 345771 \n 9.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Yasbeck, Mr. Antoni \n male \n 27.0000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n female \n 15.0000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Youseff, Mr. Gerious \n male \n 45.5000 \n 0 \n 0 \n 2628 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Yousif, Mr. Wazli \n male \n NA \n 0 \n 0 \n 2647 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Yousseff, Mr. Gerious \n male \n NA \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n \n \n C \n France \n 3 \n 0 \n Zabour, Miss. Hileni \n female \n 14.5000 \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Zabour, Miss. Thamine \n female \n NA \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n male \n 26.5000 \n 0 \n 0 \n 2656 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Zakarian, Mr. Ortin \n male \n 27.0000 \n 0 \n 0 \n 2670 \n 7.2250 \n NA \n \n \n\n S \n England \n 3 \n 0 \n Zimmerman, Mr. Leo \n male \n 29.0000 \n 0 \n 0 \n 315082 \n 7.8750 \n NA \n \n \n
\n \n \n\n fare_level \n fare \n pclass \n survived \n name_of_passenger \n sex_of_passenger \n age_of_passenger \n sibsp \n parch \n ticket \n cabin \n embarked \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n female \n 29.0000 \n 0 \n 0 \n 24160 \n B5 \n S \n \n \n middling \n 151.5500 \n 1 \n 1 \n Allison, Master. Hudson Trevor \n male \n 0.9167 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n middling \n 151.5500 \n 1 \n 0 \n Allison, Miss. Helen Loraine \n female \n 2.0000 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n middling \n 151.5500 \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n male \n 30.0000 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n middling \n 151.5500 \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n female \n 25.0000 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Anderson, Mr. Harry \n male \n 48.0000 \n 0 \n 0 \n 19952 \n E12 \n S \n \n \n cheap \n 77.9583 \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n female \n 63.0000 \n 1 \n 0 \n 13502 \n D7 \n S \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n male \n NA \n 0 \n 0 \n 112050 \n A36 \n S \n \n \n cheap \n 51.4792 \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n female \n NA \n 2 \n 0 \n 11769 \n C101 \n S \n \n \n cheap \n 49.5042 \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n male \n NA \n 0 \n 0 \n PC 17609 \n NA \n C \n \n \n expensive \n 227.5250 \n 1 \n 0 \n Astor, Col. John Jacob \n male \n NA \n 1 \n 0 \n PC 17757 \n C62 C64 \n C \n \n \n expensive \n 227.5250 \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n female \n 18.0000 \n 1 \n 0 \n PC 17757 \n C62 C64 \n C \n \n \n cheap \n 69.3000 \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n B35 \n C \n \n \n cheap \n 78.8500 \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n female \n 26.0000 \n 0 \n 0 \n 19877 \n NA \n S \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n male \n 80.0000 \n 0 \n 0 \n 27042 \n A23 \n S \n \n \n cheap \n 25.9250 \n 1 \n 0 \n Baumann, Mr. John D \n male \n NA \n 0 \n 0 \n PC 17318 \n NA \n S \n \n \n expensive \n 247.5208 \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n male \n 24.0000 \n 0 \n 1 \n PC 17558 \n B58 B60 \n C \n \n \n expensive \n 247.5208 \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n female \n 50.0000 \n 0 \n 1 \n PC 17558 \n B58 B60 \n C \n \n \n cheap \n 76.2917 \n 1 \n 1 \n Bazzani, Miss. Albina \n female \n 32.0000 \n 0 \n 0 \n 11813 \n D15 \n C \n \n \n cheap \n 75.2417 \n 1 \n 0 \n Beattie, Mr. Thomson \n male \n 36.0000 \n 0 \n 0 \n 13050 \n C6 \n C \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n male \n 37.0000 \n 1 \n 1 \n 11751 \n D35 \n S \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n female \n 47.0000 \n 1 \n 1 \n 11751 \n D35 \n S \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Behr, Mr. Karl Howell \n male \n 26.0000 \n 0 \n 0 \n 111369 \n C148 \n C \n \n \n expensive \n 227.5250 \n 1 \n 1 \n Bidois, Miss. Rosalie \n female \n 42.0000 \n 0 \n 0 \n PC 17757 \n NA \n C \n \n \n expensive \n 221.7792 \n 1 \n 1 \n Bird, Miss. Ellen \n female \n 29.0000 \n 0 \n 0 \n PC 17483 \n C97 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Birnbaum, Mr. Jakob \n male \n 25.0000 \n 0 \n 0 \n 13905 \n NA \n C \n \n \n cheap \n 91.0792 \n 1 \n 1 \n Bishop, Mr. Dickinson H \n male \n 25.0000 \n 1 \n 0 \n 11967 \n B49 \n C \n \n \n cheap \n 91.0792 \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n female \n 19.0000 \n 1 \n 0 \n 11967 \n B49 \n C \n \n \n middling \n 135.6333 \n 1 \n 1 \n Bissette, Miss. Amelia \n female \n 35.0000 \n 0 \n 0 \n PC 17760 \n C99 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n male \n 28.0000 \n 0 \n 0 \n 110564 \n C52 \n S \n \n \n cheap \n 35.5000 \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n male \n 45.0000 \n 0 \n 0 \n 113784 \n T \n S \n \n \n cheap \n 31.0000 \n 1 \n 1 \n Blank, Mr. Henry \n male \n 40.0000 \n 0 \n 0 \n 112277 \n A31 \n C \n \n \n middling \n 164.8667 \n 1 \n 1 \n Bonnell, Miss. Caroline \n female \n 30.0000 \n 0 \n 0 \n 36928 \n C7 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n female \n 58.0000 \n 0 \n 0 \n 113783 \n C103 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Borebank, Mr. John James \n male \n 42.0000 \n 0 \n 0 \n 110489 \n D22 \n S \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Bowen, Miss. Grace Scott \n female \n 45.0000 \n 0 \n 0 \n PC 17608 \n NA \n C \n \n \n cheap \n 55.0000 \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n female \n 22.0000 \n 0 \n 1 \n 113505 \n E33 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n male \n NA \n 0 \n 0 \n 111427 \n NA \n S \n \n \n cheap \n 30.5000 \n 1 \n 0 \n Brady, Mr. John Bertram \n male \n 41.0000 \n 0 \n 0 \n 113054 \n A21 \n S \n \n \n cheap \n 50.4958 \n 1 \n 0 \n Brandeis, Mr. Emil \n male \n 48.0000 \n 0 \n 0 \n PC 17591 \n B10 \n C \n \n \n cheap \n 39.6000 \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n male \n NA \n 0 \n 0 \n 112379 \n NA \n C \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n female \n 44.0000 \n 0 \n 0 \n PC 17610 \n B4 \n C \n \n \n cheap \n 51.4792 \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n female \n 59.0000 \n 2 \n 0 \n 11769 \n C101 \n S \n \n \n cheap \n 76.2917 \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n female \n 60.0000 \n 0 \n 0 \n 11813 \n D15 \n C \n \n \n middling \n 134.5000 \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n female \n 41.0000 \n 0 \n 0 \n 16966 \n E40 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Butt, Major. Archibald Willingham \n male \n 45.0000 \n 0 \n 0 \n 113050 \n B38 \n S \n \n \n cheap \n 31.0000 \n 1 \n 0 \n Cairns, Mr. Alexander \n male \n NA \n 0 \n 0 \n 113798 \n NA \n S \n \n \n cheap \n 26.2875 \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n male \n 42.0000 \n 0 \n 0 \n PC 17476 \n E24 \n S \n \n \n cheap \n 27.4458 \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n female \n 53.0000 \n 0 \n 0 \n PC 17606 \n NA \n C \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n male \n 36.0000 \n 0 \n 1 \n PC 17755 \n B51 B53 B55 \n C \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n female \n 58.0000 \n 0 \n 1 \n PC 17755 \n B51 B53 B55 \n C \n \n \n cheap \n 5.0000 \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n male \n 33.0000 \n 0 \n 0 \n 695 \n B51 B53 B55 \n S \n \n \n cheap \n 47.1000 \n 1 \n 0 \n Carrau, Mr. Francisco M \n male \n 28.0000 \n 0 \n 0 \n 113059 \n NA \n S \n \n \n cheap \n 47.1000 \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n male \n 17.0000 \n 0 \n 0 \n 113059 \n NA \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Master. William Thornton II \n male \n 11.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Miss. Lucile Polk \n female \n 14.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Mr. William Ernest \n male \n 36.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n female \n 36.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Case, Mr. Howard Brown \n male \n 49.0000 \n 0 \n 0 \n 19924 \n NA \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n female \n NA \n 0 \n 0 \n 17770 \n NA \n C \n \n \n cheap \n 78.8500 \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n male \n 36.0000 \n 1 \n 0 \n 19877 \n C46 \n S \n \n \n cheap \n 78.8500 \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n female \n 76.0000 \n 1 \n 0 \n 19877 \n C46 \n S \n \n \n cheap \n 61.1750 \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n male \n 46.0000 \n 1 \n 0 \n W.E.P. 5734 \n E31 \n S \n \n \n cheap \n 61.1750 \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n female \n 47.0000 \n 1 \n 0 \n W.E.P. 5734 \n E31 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n male \n 27.0000 \n 1 \n 0 \n 113806 \n E8 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n female \n 33.0000 \n 1 \n 0 \n 113806 \n E8 \n S \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Chaudanson, Miss. Victorine \n female \n 36.0000 \n 0 \n 0 \n PC 17608 \n B61 \n C \n \n \n cheap \n 86.5000 \n 1 \n 1 \n Cherry, Miss. Gladys \n female \n 30.0000 \n 0 \n 0 \n 110152 \n B77 \n S \n \n \n cheap \n 29.7000 \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n male \n 45.0000 \n 0 \n 0 \n PC 17594 \n A9 \n C \n \n \n cheap \n 55.0000 \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n female \n NA \n 0 \n 1 \n 113505 \n E33 \n S \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n male \n NA \n 0 \n 0 \n 112051 \n NA \n S \n \n \n middling \n 136.7792 \n 1 \n 0 \n Clark, Mr. Walter Miller \n male \n 27.0000 \n 1 \n 0 \n 13508 \n C89 \n C \n \n \n middling \n 136.7792 \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n female \n 26.0000 \n 1 \n 0 \n 13508 \n C89 \n C \n \n \n middling \n 151.5500 \n 1 \n 1 \n Cleaver, Miss. Alice \n female \n 22.0000 \n 0 \n 0 \n 113781 \n NA \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Clifford, Mr. George Quincy \n male \n NA \n 0 \n 0 \n 110465 \n A14 \n S \n \n \n cheap \n 25.5875 \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n male \n 47.0000 \n 0 \n 0 \n 5727 \n E58 \n S \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n female \n 39.0000 \n 1 \n 1 \n PC 17756 \n E49 \n C \n \n \n cheap \n 83.1583 \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n male \n 37.0000 \n 1 \n 1 \n PC 17756 \n E52 \n C \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n female \n 64.0000 \n 0 \n 2 \n PC 17756 \n E45 \n C \n \n \n cheap \n 25.7000 \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n female \n 55.0000 \n 2 \n 0 \n 11770 \n C101 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Crafton, Mr. John Bertram \n male \n NA \n 0 \n 0 \n 113791 \n NA \n S \n \n \n cheap \n 71.0000 \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n male \n 70.0000 \n 1 \n 1 \n WE/P 5735 \n B22 \n S \n \n \n cheap \n 71.0000 \n 1 \n 1 \n Crosby, Miss. Harriet R \n female \n 36.0000 \n 0 \n 2 \n WE/P 5735 \n B22 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n female \n 64.0000 \n 1 \n 1 \n 112901 \n B26 \n S \n \n \n cheap \n 71.2833 \n 1 \n 0 \n Cumings, Mr. John Bradley \n male \n 39.0000 \n 1 \n 0 \n PC 17599 \n C85 \n C \n \n \n cheap \n 71.2833 \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n female \n 38.0000 \n 1 \n 0 \n PC 17599 \n C85 \n C \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Daly, Mr. Peter Denis \n male \n 51.0000 \n 0 \n 0 \n 113055 \n E17 \n S \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Daniel, Mr. Robert Williams \n male \n 27.0000 \n 0 \n 0 \n 113804 \n NA \n S \n \n \n middling \n 151.5500 \n 1 \n 1 \n Daniels, Miss. Sarah \n female \n 33.0000 \n 0 \n 0 \n 113781 \n NA \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Davidson, Mr. Thornton \n male \n 31.0000 \n 1 \n 0 \n F.C. 12750 \n B71 \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n female \n 27.0000 \n 1 \n 2 \n F.C. 12750 \n B71 \n S \n \n \n cheap \n 57.0000 \n 1 \n 1 \n Dick, Mr. Albert Adrian \n male \n 31.0000 \n 1 \n 0 \n 17474 \n B20 \n S \n \n \n cheap \n 57.0000 \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n female \n 17.0000 \n 1 \n 0 \n 17474 \n B20 \n S \n \n \n cheap \n 81.8583 \n 1 \n 1 \n Dodge, Dr. Washington \n male \n 53.0000 \n 1 \n 1 \n 33638 \n A34 \n S \n \n \n cheap \n 81.8583 \n 1 \n 1 \n Dodge, Master. Washington \n male \n 4.0000 \n 0 \n 2 \n 33638 \n A34 \n S \n \n \n cheap \n 81.8583 \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n female \n 54.0000 \n 1 \n 1 \n 33638 \n A34 \n S \n \n \n middling \n 106.4250 \n 1 \n 0 \n Douglas, Mr. Walter Donald \n male \n 50.0000 \n 1 \n 0 \n PC 17761 \n C86 \n C \n \n \n expensive \n 247.5208 \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n female \n 27.0000 \n 1 \n 1 \n PC 17558 \n B58 B60 \n C \n \n \n middling \n 106.4250 \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n female \n 48.0000 \n 1 \n 0 \n PC 17761 \n C86 \n C \n \n \n cheap \n 39.6000 \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n female \n 48.0000 \n 1 \n 0 \n 11755 \n A16 \n C \n \n \n cheap \n 56.9292 \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n male \n 49.0000 \n 1 \n 0 \n PC 17485 \n A20 \n C \n \n \n cheap \n 29.7000 \n 1 \n 0 \n Dulles, Mr. William Crothers \n male \n 39.0000 \n 0 \n 0 \n PC 17580 \n A18 \n C \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n female \n 23.0000 \n 0 \n 1 \n 11767 \n C54 \n C \n \n \n expensive \n 227.5250 \n 1 \n 1 \n Endres, Miss. Caroline Louise \n female \n 38.0000 \n 0 \n 0 \n PC 17757 \n C45 \n C \n \n \n cheap \n 78.2667 \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n female \n 54.0000 \n 1 \n 0 \n 36947 \n D20 \n C \n \n \n cheap \n 31.6792 \n 1 \n 0 \n Evans, Miss. Edith Corse \n female \n 36.0000 \n 0 \n 0 \n PC 17531 \n A29 \n C \n \n \n expensive \n 221.7792 \n 1 \n 0 \n Farthing, Mr. John \n male \n NA \n 0 \n 0 \n PC 17483 \n C95 \n S \n \n \n cheap \n 31.6833 \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n female \n NA \n 0 \n 0 \n PC 17598 \n NA \n S \n \n \n middling \n 110.8833 \n 1 \n 1 \n Fleming, Miss. Margaret \n female \n NA \n 0 \n 0 \n 17421 \n NA \n C \n \n \n cheap \n 26.3875 \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n male \n 36.0000 \n 0 \n 0 \n PC 17474 \n E25 \n S \n \n \n cheap \n 27.7500 \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n male \n 30.0000 \n 0 \n 0 \n 113051 \n C111 \n C \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n female \n 24.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n female \n 28.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n female \n 23.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n male \n 19.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 0 \n Fortune, Mr. Mark \n male \n 64.0000 \n 1 \n 4 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n female \n 60.0000 \n 1 \n 4 \n 19950 \n C23 C25 C27 \n S \n \n \n cheap \n 56.9292 \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n female \n 30.0000 \n 0 \n 0 \n PC 17485 \n E36 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n male \n NA \n 0 \n 0 \n 113778 \n D34 \n S \n \n \n middling \n 133.6500 \n 1 \n 1 \n Frauenthal, Dr. Henry William \n male \n 50.0000 \n 2 \n 0 \n PC 17611 \n NA \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n male \n 43.0000 \n 1 \n 0 \n 17765 \n D40 \n C \n \n \n middling \n 133.6500 \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n female \n NA \n 1 \n 0 \n PC 17611 \n NA \n S \n \n \n cheap \n 49.5000 \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n female \n 22.0000 \n 0 \n 2 \n 13568 \n B39 \n C \n \n \n cheap \n 79.2000 \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n male \n 60.0000 \n 1 \n 1 \n 13567 \n B41 \n C \n \n \n cheap \n 79.2000 \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n female \n 48.0000 \n 1 \n 1 \n 13567 \n B41 \n C \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Fry, Mr. Richard \n male \n NA \n 0 \n 0 \n 112058 \n B102 \n S \n \n \n cheap \n 53.1000 \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n male \n 37.0000 \n 1 \n 0 \n 113803 \n C123 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n female \n 35.0000 \n 1 \n 0 \n 113803 \n C123 \n S \n \n \n cheap \n 38.5000 \n 1 \n 0 \n Gee, Mr. Arthur H \n male \n 47.0000 \n 0 \n 0 \n 111320 \n E63 \n S \n \n \n expensive \n 211.5000 \n 1 \n 1 \n Geiger, Miss. Amalie \n female \n 35.0000 \n 0 \n 0 \n 113503 \n C130 \n C \n \n \n cheap \n 59.4000 \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n female \n 22.0000 \n 0 \n 1 \n 112378 \n NA \n C \n \n \n cheap \n 59.4000 \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n female \n 45.0000 \n 0 \n 1 \n 112378 \n NA \n C \n \n \n cheap \n 79.2000 \n 1 \n 0 \n Giglio, Mr. Victor \n male \n 24.0000 \n 0 \n 0 \n PC 17593 \n B86 \n C \n \n \n cheap \n 89.1042 \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n male \n 49.0000 \n 1 \n 0 \n 17453 \n C92 \n C \n \n \n cheap \n 89.1042 \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n female \n NA \n 1 \n 0 \n 17453 \n C92 \n C \n \n \n cheap \n 34.6542 \n 1 \n 0 \n Goldschmidt, Mr. George B \n male \n 71.0000 \n 0 \n 0 \n PC 17754 \n A5 \n C \n \n \n cheap \n 28.5000 \n 1 \n 1 \n Gracie, Col. Archibald IV \n male \n 53.0000 \n 0 \n 0 \n 113780 \n C51 \n C \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Graham, Miss. Margaret Edith \n female \n 19.0000 \n 0 \n 0 \n 112053 \n B42 \n S \n \n \n middling \n 153.4625 \n 1 \n 0 \n Graham, Mr. George Edward \n male \n 38.0000 \n 0 \n 1 \n PC 17582 \n C91 \n S \n \n \n middling \n 153.4625 \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n female \n 58.0000 \n 0 \n 1 \n PC 17582 \n C125 \n S \n \n \n cheap \n 63.3583 \n 1 \n 1 \n Greenfield, Mr. William Bertram \n male \n 23.0000 \n 0 \n 1 \n PC 17759 \n D10 D12 \n C \n \n \n cheap \n 63.3583 \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n female \n 45.0000 \n 0 \n 1 \n PC 17759 \n D10 D12 \n C \n \n \n cheap \n 79.2000 \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n male \n 46.0000 \n 0 \n 0 \n PC 17593 \n B82 B84 \n C \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Harder, Mr. George Achilles \n male \n 25.0000 \n 1 \n 0 \n 11765 \n E50 \n C \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n female \n 25.0000 \n 1 \n 0 \n 11765 \n E50 \n C \n \n \n cheap \n 76.7292 \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n male \n 48.0000 \n 1 \n 0 \n PC 17572 \n D33 \n C \n \n \n cheap \n 76.7292 \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n female \n 49.0000 \n 1 \n 0 \n PC 17572 \n D33 \n C \n \n \n cheap \n 42.4000 \n 1 \n 0 \n Harrington, Mr. Charles H \n male \n NA \n 0 \n 0 \n 113796 \n NA \n S \n \n \n cheap \n 83.4750 \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n male \n 45.0000 \n 1 \n 0 \n 36973 \n C83 \n S \n \n \n cheap \n 83.4750 \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n female \n 35.0000 \n 1 \n 0 \n 36973 \n C83 \n S \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Harrison, Mr. William \n male \n 40.0000 \n 0 \n 0 \n 112059 \n B94 \n S \n \n \n cheap \n 76.7292 \n 1 \n 1 \n Hassab, Mr. Hammad \n male \n 27.0000 \n 0 \n 0 \n PC 17572 \n D49 \n C \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Hawksford, Mr. Walter James \n male \n NA \n 0 \n 0 \n 16988 \n D45 \n S \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n female \n 24.0000 \n 0 \n 0 \n 11767 \n C54 \n C \n \n \n cheap \n 93.5000 \n 1 \n 0 \n Hays, Mr. Charles Melville \n male \n 55.0000 \n 1 \n 1 \n 12749 \n B69 \n S \n \n \n cheap \n 93.5000 \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n female \n 52.0000 \n 1 \n 1 \n 12749 \n B69 \n S \n \n \n cheap \n 42.5000 \n 1 \n 0 \n Head, Mr. Christopher \n male \n 42.0000 \n 0 \n 0 \n 113038 \n B11 \n S \n \n \n cheap \n 51.8625 \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n male \n NA \n 0 \n 0 \n 17463 \n E46 \n S \n \n \n cheap \n 50.0000 \n 1 \n 0 \n Hipkins, Mr. William Edward \n male \n 55.0000 \n 0 \n 0 \n 680 \n C39 \n S \n \n \n cheap \n 57.9792 \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n female \n 16.0000 \n 0 \n 1 \n 111361 \n B18 \n C \n \n \n cheap \n 57.9792 \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n female \n 44.0000 \n 0 \n 1 \n 111361 \n B18 \n C \n \n \n cheap \n 77.9583 \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n female \n 51.0000 \n 1 \n 0 \n 13502 \n D11 \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n male \n 42.0000 \n 1 \n 0 \n 113789 \n NA \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n female \n 35.0000 \n 1 \n 0 \n 113789 \n NA \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n male \n 35.0000 \n 0 \n 0 \n 111426 \n NA \n C \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n male \n 38.0000 \n 1 \n 0 \n 19943 \n C93 \n S \n \n \n cheap \n 30.6958 \n 1 \n 0 \n Hoyt, Mr. William Fisher \n male \n NA \n 0 \n 0 \n PC 17600 \n NA \n C \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n female \n 35.0000 \n 1 \n 0 \n 19943 \n C93 \n S \n \n \n cheap \n 80.0000 \n 1 \n 1 \n Icard, Miss. Amelie \n female \n 38.0000 \n 0 \n 0 \n 113572 \n B28 \n NA \n \n \n cheap \n 28.7125 \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n female \n 50.0000 \n 0 \n 0 \n PC 17595 \n C49 \n C \n \n \n cheap \n 0.0000 \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n male \n 49.0000 \n 0 \n 0 \n 112058 \n B52 B54 B56 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Jones, Mr. Charles Cresson \n male \n 46.0000 \n 0 \n 0 \n 694 \n NA \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Julian, Mr. Henry Forbes \n male \n 50.0000 \n 0 \n 0 \n 113044 \n E60 \n S \n \n \n expensive \n 211.5000 \n 1 \n 0 \n Keeping, Mr. Edwin \n male \n 32.5000 \n 0 \n 0 \n 113503 \n C132 \n C \n \n \n cheap \n 29.7000 \n 1 \n 0 \n Kent, Mr. Edward Austin \n male \n 58.0000 \n 0 \n 0 \n 11771 \n B37 \n C \n \n \n cheap \n 51.8625 \n 1 \n 0 \n Kenyon, Mr. Frederick R \n male \n 41.0000 \n 1 \n 0 \n 17464 \n D21 \n S \n \n \n cheap \n 51.8625 \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n female \n NA \n 1 \n 0 \n 17464 \n D21 \n S \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n male \n 42.0000 \n 1 \n 0 \n 11753 \n D19 \n S \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n female \n 45.0000 \n 1 \n 0 \n 11753 \n D19 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Klaber, Mr. Herman \n male \n NA \n 0 \n 0 \n 113028 \n C124 \n S \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Kreuchen, Miss. Emilie \n female \n 39.0000 \n 0 \n 0 \n 24160 \n NA \n S \n \n \n cheap \n 25.9292 \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n female \n 49.0000 \n 0 \n 0 \n 17465 \n D17 \n S \n \n \n middling \n 106.4250 \n 1 \n 1 \n LeRoy, Miss. Bertha \n female \n 30.0000 \n 0 \n 0 \n PC 17761 \n NA \n C \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Lesurer, Mr. Gustave J \n male \n 35.0000 \n 0 \n 0 \n PC 17755 \n B101 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Lewy, Mr. Ervin G \n male \n NA \n 0 \n 0 \n PC 17612 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n male \n 42.0000 \n 0 \n 0 \n 17475 \n NA \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n female \n 55.0000 \n 0 \n 0 \n 112377 \n NA \n C \n \n \n cheap \n 39.4000 \n 1 \n 1 \n Lines, Miss. Mary Conover \n female \n 16.0000 \n 0 \n 1 \n PC 17592 \n D28 \n S \n \n \n cheap \n 39.4000 \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n female \n 51.0000 \n 0 \n 1 \n PC 17592 \n D28 \n S \n \n \n cheap \n 30.0000 \n 1 \n 0 \n Long, Mr. Milton Clyde \n male \n 29.0000 \n 0 \n 0 \n 113501 \n D6 \n S \n \n \n cheap \n 77.9583 \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n female \n 21.0000 \n 0 \n 0 \n 13502 \n D9 \n S \n \n \n cheap \n 45.5000 \n 1 \n 0 \n Loring, Mr. Joseph Holland \n male \n 30.0000 \n 0 \n 0 \n 113801 \n NA \n S \n \n \n middling \n 146.5208 \n 1 \n 1 \n Lurette, Miss. Elise \n female \n 58.0000 \n 0 \n 0 \n PC 17569 \n B80 \n C \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n female \n 15.0000 \n 0 \n 1 \n 24160 \n B5 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Maguire, Mr. John Edward \n male \n 30.0000 \n 0 \n 0 \n 110469 \n C106 \n S \n \n \n cheap \n 86.5000 \n 1 \n 1 \n Maioni, Miss. Roberta \n female \n 16.0000 \n 0 \n 0 \n 110152 \n B79 \n S \n \n \n cheap \n 29.7000 \n 1 \n 1 \n Marechal, Mr. Pierre \n male \n NA \n 0 \n 0 \n 11774 \n C47 \n C \n \n \n cheap \n 53.1000 \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n male \n 19.0000 \n 1 \n 0 \n 113773 \n D30 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n female \n 18.0000 \n 1 \n 0 \n 113773 \n D30 \n S \n \n \n cheap \n 49.5042 \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n female \n 24.0000 \n 0 \n 0 \n PC 17482 \n C90 \n C \n \n \n cheap \n 75.2417 \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n male \n 46.0000 \n 0 \n 0 \n 13050 \n C6 \n C \n \n \n cheap \n 51.8625 \n 1 \n 0 \n McCarthy, Mr. Timothy J \n male \n 54.0000 \n 0 \n 0 \n 17463 \n E46 \n S \n \n \n cheap \n 26.2875 \n 1 \n 1 \n McGough, Mr. James Robert \n male \n 36.0000 \n 0 \n 0 \n PC 17473 \n E25 \n S \n \n \n cheap \n 82.1708 \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n male \n 28.0000 \n 1 \n 0 \n PC 17604 \n NA \n C \n \n \n cheap \n 82.1708 \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n female \n NA \n 1 \n 0 \n PC 17604 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Millet, Mr. Francis Davis \n male \n 65.0000 \n 0 \n 0 \n 13509 \n E38 \n S \n \n \n cheap \n 90.0000 \n 1 \n 0 \n Minahan, Dr. William Edward \n male \n 44.0000 \n 2 \n 0 \n 19928 \n C78 \n Q \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Minahan, Miss. Daisy E \n female \n 33.0000 \n 1 \n 0 \n 19928 \n C78 \n Q \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n female \n 37.0000 \n 1 \n 0 \n 19928 \n C78 \n Q \n \n \n cheap \n 57.7500 \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n male \n 30.0000 \n 1 \n 0 \n 13236 \n C78 \n C \n \n \n cheap \n 30.5000 \n 1 \n 0 \n Molson, Mr. Harry Markland \n male \n 55.0000 \n 0 \n 0 \n 113787 \n C30 \n S \n \n \n cheap \n 42.4000 \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n male \n 47.0000 \n 0 \n 0 \n 113796 \n NA \n S \n \n \n cheap \n 29.7000 \n 1 \n 0 \n Natsch, Mr. Charles H \n male \n 37.0000 \n 0 \n 1 \n PC 17596 \n C118 \n C \n \n \n middling \n 113.2750 \n 1 \n 1 \n Newell, Miss. Madeleine \n female \n 31.0000 \n 1 \n 0 \n 35273 \n D36 \n C \n \n \n middling \n 113.2750 \n 1 \n 1 \n Newell, Miss. Marjorie \n female \n 23.0000 \n 1 \n 0 \n 35273 \n D36 \n C \n \n \n middling \n 113.2750 \n 1 \n 0 \n Newell, Mr. Arthur Webster \n male \n 58.0000 \n 0 \n 2 \n 35273 \n D48 \n C \n \n \n cheap \n 26.2833 \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n female \n 19.0000 \n 0 \n 2 \n 11752 \n D47 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n male \n 64.0000 \n 0 \n 0 \n 693 \n NA \n S \n \n \n middling \n 108.9000 \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n female \n 39.0000 \n 0 \n 0 \n PC 17758 \n C105 \n C \n \n \n cheap \n 25.7417 \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n male \n NA \n 0 \n 0 \n F.C. 12998 \n NA \n C \n \n \n cheap \n 61.9792 \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n female \n 22.0000 \n 0 \n 1 \n 113509 \n B36 \n C \n \n \n cheap \n 61.9792 \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n male \n 65.0000 \n 0 \n 1 \n 113509 \n B30 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n male \n 28.5000 \n 0 \n 0 \n PC 17562 \n D43 \n C \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n male \n NA \n 0 \n 0 \n 112052 \n NA \n S \n \n \n cheap \n 28.5000 \n 1 \n 0 \n Partner, Mr. Austen \n male \n 45.5000 \n 0 \n 0 \n 113043 \n C124 \n S \n \n \n cheap \n 93.5000 \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n male \n 23.0000 \n 0 \n 0 \n 12749 \n B24 \n S \n \n \n cheap \n 66.6000 \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n male \n 29.0000 \n 1 \n 0 \n 113776 \n C2 \n S \n \n \n cheap \n 66.6000 \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n female \n 22.0000 \n 1 \n 0 \n 113776 \n C2 \n S \n \n \n middling \n 108.9000 \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n male \n 18.0000 \n 1 \n 0 \n PC 17758 \n C65 \n C \n \n \n middling \n 108.9000 \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n female \n 17.0000 \n 1 \n 0 \n PC 17758 \n C65 \n C \n \n \n cheap \n 93.5000 \n 1 \n 1 \n Perreault, Miss. Anne \n female \n 30.0000 \n 0 \n 0 \n 12749 \n B73 \n S \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n male \n 52.0000 \n 0 \n 0 \n 113786 \n C104 \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n male \n 47.0000 \n 0 \n 0 \n 110465 \n C110 \n S \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n female \n 56.0000 \n 0 \n 1 \n 11767 \n C50 \n C \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n male \n 38.0000 \n 0 \n 0 \n 19972 \n NA \n S \n \n \n cheap \n 39.6000 \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n male \n NA \n 0 \n 0 \n PC 17607 \n NA \n S \n \n \n middling \n 135.6333 \n 1 \n 0 \n Ringhini, Mr. Sante \n male \n 22.0000 \n 0 \n 0 \n PC 17760 \n NA \n C \n \n \n expensive \n 227.5250 \n 1 \n 0 \n Robbins, Mr. Victor \n male \n NA \n 0 \n 0 \n PC 17757 \n NA \n C \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n female \n 43.0000 \n 0 \n 1 \n 24160 \n B3 \n S \n \n \n cheap \n 50.4958 \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n male \n 31.0000 \n 0 \n 0 \n PC 17590 \n A24 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n male \n 45.0000 \n 0 \n 0 \n 111428 \n NA \n S \n \n \n cheap \n 50.0000 \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n male \n NA \n 0 \n 0 \n 113767 \n A32 \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n female \n 33.0000 \n 0 \n 0 \n PC 17613 \n A11 \n C \n \n \n cheap \n 79.2000 \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n male \n 46.0000 \n 0 \n 0 \n PC 17585 \n NA \n C \n \n \n cheap \n 40.1250 \n 1 \n 0 \n Ross, Mr. John Hugo \n male \n 36.0000 \n 0 \n 0 \n 13049 \n A10 \n C \n \n \n cheap \n 86.5000 \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n female \n 33.0000 \n 0 \n 0 \n 110152 \n B77 \n S \n \n \n cheap \n 59.4000 \n 1 \n 0 \n Rothschild, Mr. Martin \n male \n 55.0000 \n 1 \n 0 \n PC 17603 \n NA \n C \n \n \n cheap \n 59.4000 \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n female \n 54.0000 \n 1 \n 0 \n PC 17603 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Rowe, Mr. Alfred G \n male \n 33.0000 \n 0 \n 0 \n 113790 \n NA \n S \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Master. John Borie \n male \n 13.0000 \n 2 \n 2 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n female \n 18.0000 \n 2 \n 2 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n female \n 21.0000 \n 2 \n 2 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n male \n 61.0000 \n 1 \n 3 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n female \n 48.0000 \n 1 \n 3 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n male \n NA \n 0 \n 0 \n 19988 \n C106 \n S \n \n \n cheap \n 69.3000 \n 1 \n 1 \n Sagesser, Mlle. Emma \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n B35 \n C \n \n \n cheap \n 26.0000 \n 1 \n 1 \n Salomon, Mr. Abraham L \n male \n NA \n 0 \n 0 \n 111163 \n NA \n S \n \n \n cheap \n 57.7500 \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n female \n 35.0000 \n 1 \n 0 \n 13236 \n C28 \n C \n \n \n cheap \n 31.0000 \n 1 \n 1 \n Serepeca, Miss. Augusta \n female \n 30.0000 \n 0 \n 0 \n 113798 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n male \n 34.0000 \n 0 \n 0 \n 113794 \n NA \n S \n \n \n middling \n 153.4625 \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n female \n 40.0000 \n 0 \n 0 \n PC 17582 \n C125 \n S \n \n \n cheap \n 26.2875 \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n male \n 35.0000 \n 0 \n 0 \n PC 17475 \n E24 \n S \n \n \n cheap \n 55.9000 \n 1 \n 0 \n Silvey, Mr. William Baird \n male \n 50.0000 \n 1 \n 0 \n 13507 \n E44 \n S \n \n \n cheap \n 55.9000 \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n female \n 39.0000 \n 1 \n 0 \n 13507 \n E44 \n S \n \n \n cheap \n 35.5000 \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n male \n 56.0000 \n 0 \n 0 \n 13213 \n A26 \n C \n \n \n cheap \n 35.5000 \n 1 \n 1 \n Sloper, Mr. William Thompson \n male \n 28.0000 \n 0 \n 0 \n 113788 \n A6 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Smart, Mr. John Montgomery \n male \n 56.0000 \n 0 \n 0 \n 113792 \n NA \n S \n \n \n cheap \n 30.6958 \n 1 \n 0 \n Smith, Mr. James Clinch \n male \n 56.0000 \n 0 \n 0 \n 17764 \n A7 \n C \n \n \n cheap \n 60.0000 \n 1 \n 0 \n Smith, Mr. Lucien Philip \n male \n 24.0000 \n 1 \n 0 \n 13695 \n C31 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Smith, Mr. Richard William \n male \n NA \n 0 \n 0 \n 113056 \n A19 \n S \n \n \n cheap \n 60.0000 \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n female \n 18.0000 \n 1 \n 0 \n 13695 \n C31 \n S \n \n \n cheap \n 82.2667 \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n male \n 24.0000 \n 1 \n 0 \n 21228 \n B45 \n S \n \n \n cheap \n 82.2667 \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n female \n 23.0000 \n 1 \n 0 \n 21228 \n B45 \n S \n \n \n middling \n 134.5000 \n 1 \n 1 \n Spedden, Master. Robert Douglas \n male \n 6.0000 \n 0 \n 2 \n 16966 \n E34 \n C \n \n \n middling \n 134.5000 \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n male \n 45.0000 \n 1 \n 1 \n 16966 \n E34 \n C \n \n \n middling \n 134.5000 \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n female \n 40.0000 \n 1 \n 1 \n 16966 \n E34 \n C \n \n \n middling \n 146.5208 \n 1 \n 0 \n Spencer, Mr. William Augustus \n male \n 57.0000 \n 1 \n 0 \n PC 17569 \n B78 \n C \n \n \n middling \n 146.5208 \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n female \n NA \n 1 \n 0 \n PC 17569 \n B78 \n C \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n male \n 32.0000 \n 0 \n 0 \n 13214 \n B50 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Stead, Mr. William Thomas \n male \n 62.0000 \n 0 \n 0 \n 113514 \n C87 \n S \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n male \n 54.0000 \n 1 \n 0 \n 11778 \n C116 \n C \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n female \n 43.0000 \n 1 \n 0 \n 11778 \n C116 \n C \n \n \n cheap \n 78.2667 \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n female \n 52.0000 \n 1 \n 0 \n 36947 \n D20 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Stewart, Mr. Albert A \n male \n NA \n 0 \n 0 \n PC 17605 \n NA \n C \n \n \n cheap \n 80.0000 \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n female \n 62.0000 \n 0 \n 0 \n 113572 \n B28 \n NA \n \n \n expensive \n 221.7792 \n 1 \n 0 \n Straus, Mr. Isidor \n male \n 67.0000 \n 1 \n 0 \n PC 17483 \n C55 C57 \n S \n \n \n expensive \n 221.7792 \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n female \n 63.0000 \n 1 \n 0 \n PC 17483 \n C55 C57 \n S \n \n \n cheap \n 32.3208 \n 1 \n 0 \n Sutton, Mr. Frederick \n male \n 61.0000 \n 0 \n 0 \n 36963 \n D50 \n S \n \n \n cheap \n 25.9292 \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n female \n 48.0000 \n 0 \n 0 \n 17466 \n D17 \n S \n \n \n cheap \n 79.6500 \n 1 \n 1 \n Taussig, Miss. Ruth \n female \n 18.0000 \n 0 \n 2 \n 110413 \n E68 \n S \n \n \n cheap \n 79.6500 \n 1 \n 0 \n Taussig, Mr. Emil \n male \n 52.0000 \n 1 \n 1 \n 110413 \n E67 \n S \n \n \n cheap \n 79.6500 \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n female \n 39.0000 \n 1 \n 1 \n 110413 \n E67 \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n male \n 48.0000 \n 1 \n 0 \n 19996 \n C126 \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n female \n NA \n 1 \n 0 \n 19996 \n C126 \n S \n \n \n middling \n 110.8833 \n 1 \n 0 \n Thayer, Mr. John Borland \n male \n 49.0000 \n 1 \n 1 \n 17421 \n C68 \n C \n \n \n middling \n 110.8833 \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n male \n 17.0000 \n 0 \n 2 \n 17421 \n C70 \n C \n \n \n middling \n 110.8833 \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n female \n 39.0000 \n 1 \n 1 \n 17421 \n C68 \n C \n \n \n cheap \n 79.2000 \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n female \n NA \n 0 \n 0 \n PC 17585 \n NA \n C \n \n \n cheap \n 28.5375 \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n male \n 31.0000 \n 0 \n 0 \n 2543 \n C53 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n male \n 40.0000 \n 0 \n 0 \n PC 17601 \n NA \n C \n \n \n cheap \n 33.5000 \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n male \n 61.0000 \n 0 \n 0 \n 111240 \n B19 \n S \n \n \n cheap \n 34.0208 \n 1 \n 0 \n Walker, Mr. William Anderson \n male \n 47.0000 \n 0 \n 0 \n 36967 \n D46 \n S \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Ward, Miss. Anna \n female \n 35.0000 \n 0 \n 0 \n PC 17755 \n NA \n C \n \n \n cheap \n 75.2500 \n 1 \n 0 \n Warren, Mr. Frank Manley \n male \n 64.0000 \n 1 \n 0 \n 110813 \n D37 \n C \n \n \n cheap \n 75.2500 \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n female \n 60.0000 \n 1 \n 0 \n 110813 \n D37 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Weir, Col. John \n male \n 60.0000 \n 0 \n 0 \n 113800 \n NA \n S \n \n \n cheap \n 77.2875 \n 1 \n 0 \n White, Mr. Percival Wayland \n male \n 54.0000 \n 0 \n 1 \n 35281 \n D26 \n S \n \n \n cheap \n 77.2875 \n 1 \n 0 \n White, Mr. Richard Frasar \n male \n 21.0000 \n 0 \n 1 \n 35281 \n D26 \n S \n \n \n middling \n 135.6333 \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n female \n 55.0000 \n 0 \n 0 \n PC 17760 \n C32 \n C \n \n \n middling \n 164.8667 \n 1 \n 1 \n Wick, Miss. Mary Natalie \n female \n 31.0000 \n 0 \n 2 \n 36928 \n C7 \n S \n \n \n middling \n 164.8667 \n 1 \n 0 \n Wick, Mr. George Dennick \n male \n 57.0000 \n 1 \n 1 \n 36928 \n NA \n S \n \n \n middling \n 164.8667 \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n female \n 45.0000 \n 1 \n 1 \n 36928 \n NA \n S \n \n \n expensive \n 211.5000 \n 1 \n 0 \n Widener, Mr. George Dunton \n male \n 50.0000 \n 1 \n 1 \n 113503 \n C80 \n C \n \n \n expensive \n 211.5000 \n 1 \n 0 \n Widener, Mr. Harry Elkins \n male \n 27.0000 \n 0 \n 2 \n 113503 \n C82 \n C \n \n \n expensive \n 211.5000 \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n female \n 50.0000 \n 1 \n 1 \n 113503 \n C80 \n C \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Willard, Miss. Constance \n female \n 21.0000 \n 0 \n 0 \n 113795 \n NA \n S \n \n \n cheap \n 61.3792 \n 1 \n 0 \n Williams, Mr. Charles Duane \n male \n 51.0000 \n 0 \n 1 \n PC 17597 \n NA \n C \n \n \n cheap \n 61.3792 \n 1 \n 1 \n Williams, Mr. Richard Norris II \n male \n 21.0000 \n 0 \n 1 \n PC 17597 \n NA \n C \n \n \n cheap \n 35.0000 \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n male \n NA \n 0 \n 0 \n 113510 \n C128 \n S \n \n \n middling \n 134.5000 \n 1 \n 1 \n Wilson, Miss. Helen Alice \n female \n 31.0000 \n 0 \n 0 \n 16966 \n E39 E41 \n C \n \n \n cheap \n 35.5000 \n 1 \n 1 \n Woolner, Mr. Hugh \n male \n NA \n 0 \n 0 \n 19947 \n C52 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Wright, Mr. George \n male \n 62.0000 \n 0 \n 0 \n 113807 \n NA \n S \n \n \n middling \n 135.6333 \n 1 \n 1 \n Young, Miss. Marie Grice \n female \n 36.0000 \n 0 \n 0 \n PC 17760 \n C32 \n C \n \n \n cheap \n 24.0000 \n 2 \n 0 \n Abelson, Mr. Samuel \n male \n 30.0000 \n 1 \n 0 \n P/PP 3381 \n NA \n C \n \n \n cheap \n 24.0000 \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n female \n 28.0000 \n 1 \n 0 \n P/PP 3381 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n male \n 30.0000 \n 0 \n 0 \n 248744 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n male \n 18.0000 \n 0 \n 0 \n 231945 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n male \n 25.0000 \n 0 \n 0 \n C.A. 34050 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Angle, Mr. William A \n male \n 34.0000 \n 1 \n 0 \n 226875 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n female \n 36.0000 \n 1 \n 0 \n 226875 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Ashby, Mr. John \n male \n 57.0000 \n 0 \n 0 \n 244346 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n male \n 18.0000 \n 0 \n 0 \n 29108 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n male \n 23.0000 \n 0 \n 0 \n C.A. 31030 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n female \n 36.0000 \n 0 \n 0 \n 28551 \n D \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Banfield, Mr. Frederick James \n male \n 28.0000 \n 0 \n 0 \n C.A./SOTON 34068 \n NA \n S \n \n \n cheap \n 12.5250 \n 2 \n 0 \n Bateman, Rev. Robert James \n male \n 51.0000 \n 0 \n 0 \n S.O.P. 1166 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Beane, Mr. Edward \n male \n 32.0000 \n 1 \n 0 \n 2908 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n female \n 19.0000 \n 1 \n 0 \n 2908 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Beauchamp, Mr. Henry James \n male \n 28.0000 \n 0 \n 0 \n 244358 \n NA \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Master. Richard F \n male \n 1.0000 \n 2 \n 1 \n 230136 \n F4 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Miss. Marion Louise \n female \n 4.0000 \n 2 \n 1 \n 230136 \n F4 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n female \n 12.0000 \n 2 \n 1 \n 230136 \n F4 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n female \n 36.0000 \n 0 \n 3 \n 230136 \n F4 \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Beesley, Mr. Lawrence \n male \n 34.0000 \n 0 \n 0 \n 248698 \n D56 \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Bentham, Miss. Lilian W \n female \n 19.0000 \n 0 \n 0 \n 28404 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Berriman, Mr. William John \n male \n 23.0000 \n 0 \n 0 \n 28425 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Botsford, Mr. William Hull \n male \n 26.0000 \n 0 \n 0 \n 237670 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Bowenur, Mr. Solomon \n male \n 42.0000 \n 0 \n 0 \n 211535 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Bracken, Mr. James H \n male \n 27.0000 \n 0 \n 0 \n 220367 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n female \n 24.0000 \n 0 \n 0 \n 248733 \n F33 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Brown, Miss. Edith Eileen \n female \n 15.0000 \n 0 \n 2 \n 29750 \n NA \n S \n \n \n cheap \n 39.0000 \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n male \n 60.0000 \n 1 \n 1 \n 29750 \n NA \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n female \n 40.0000 \n 1 \n 1 \n 29750 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n female \n 20.0000 \n 1 \n 0 \n 236853 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n male \n 25.0000 \n 1 \n 0 \n 236853 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Buss, Miss. Kate \n female \n 36.0000 \n 0 \n 0 \n 27849 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n male \n 25.0000 \n 0 \n 0 \n 234686 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n male \n 42.0000 \n 0 \n 0 \n 244310 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n female \n 42.0000 \n 0 \n 0 \n 236852 \n NA \n S \n \n \n cheap \n 29.0000 \n 2 \n 1 \n Caldwell, Master. Alden Gates \n male \n 0.8333 \n 0 \n 2 \n 248738 \n NA \n S \n \n \n cheap \n 29.0000 \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n male \n 26.0000 \n 1 \n 1 \n 248738 \n NA \n S \n \n \n cheap \n 29.0000 \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n female \n 22.0000 \n 1 \n 1 \n 248738 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Cameron, Miss. Clear Annie \n female \n 35.0000 \n 0 \n 0 \n F.C.C. 13528 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Campbell, Mr. William \n male \n NA \n 0 \n 0 \n 239853 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Carbines, Mr. William \n male \n 19.0000 \n 0 \n 0 \n 28424 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n female \n 44.0000 \n 1 \n 0 \n 244252 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n male \n 54.0000 \n 1 \n 0 \n 244252 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Chapman, Mr. Charles Henry \n male \n 52.0000 \n 0 \n 0 \n 248731 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Chapman, Mr. John Henry \n male \n 37.0000 \n 1 \n 0 \n SC/AH 29037 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n female \n 29.0000 \n 1 \n 0 \n SC/AH 29037 \n NA \n S \n \n \n cheap \n 30.0000 \n 2 \n 1 \n Christy, Miss. Julie Rachel \n female \n 25.0000 \n 1 \n 1 \n 237789 \n NA \n S \n \n \n cheap \n 30.0000 \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n female \n 45.0000 \n 0 \n 2 \n 237789 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n male \n 29.0000 \n 1 \n 0 \n 2003 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n female \n 28.0000 \n 1 \n 0 \n 2003 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n male \n 29.0000 \n 0 \n 0 \n W./C. 14263 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n male \n 28.0000 \n 0 \n 0 \n 248740 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n male \n 24.0000 \n 0 \n 0 \n 28034 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n female \n 8.0000 \n 0 \n 2 \n C.A. 31921 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 0 \n Collyer, Mr. Harvey \n male \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n female \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n female \n 22.0000 \n 0 \n 0 \n W./C. 14266 \n F33 \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n female \n 30.0000 \n 0 \n 0 \n 237249 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n female \n NA \n 0 \n 0 \n F.C.C. 13534 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n male \n 21.0000 \n 0 \n 0 \n 29107 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n male \n NA \n 0 \n 0 \n 239853 \n NA \n S \n \n \n cheap \n 36.7500 \n 2 \n 1 \n Davies, Master. John Morgan Jr \n male \n 8.0000 \n 1 \n 1 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Davies, Mr. Charles Henry \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 36.7500 \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n female \n 48.0000 \n 0 \n 2 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Davis, Miss. Mary \n female \n 28.0000 \n 0 \n 0 \n 237668 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n male \n 32.0000 \n 0 \n 0 \n 244360 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Deacon, Mr. Percy William \n male \n 17.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 27.7208 \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n male \n 29.0000 \n 1 \n 0 \n SC/PARIS 2167 \n NA \n C \n \n \n cheap \n 27.7208 \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n female \n 24.0000 \n 1 \n 0 \n SC/PARIS 2167 \n NA \n C \n \n \n cheap \n 31.5000 \n 2 \n 0 \n Denbury, Mr. Herbert \n male \n 25.0000 \n 0 \n 0 \n C.A. 31029 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Dibden, Mr. William \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Doling, Miss. Elsie \n female \n 18.0000 \n 0 \n 1 \n 231919 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n female \n 34.0000 \n 0 \n 1 \n 231919 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Downton, Mr. William James \n male \n 54.0000 \n 0 \n 0 \n 28403 \n NA \n S \n \n \n cheap \n 32.5000 \n 2 \n 1 \n Drew, Master. Marshall Brines \n male \n 8.0000 \n 0 \n 2 \n 28220 \n NA \n S \n \n \n cheap \n 32.5000 \n 2 \n 0 \n Drew, Mr. James Vivian \n male \n 42.0000 \n 1 \n 1 \n 28220 \n NA \n S \n \n \n cheap \n 32.5000 \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n female \n 34.0000 \n 1 \n 1 \n 28220 \n NA \n S \n \n \n cheap \n 13.8583 \n 2 \n 1 \n Duran y More, Miss. Asuncion \n female \n 27.0000 \n 1 \n 0 \n SC/PARIS 2149 \n NA \n C \n \n \n cheap \n 13.8583 \n 2 \n 1 \n Duran y More, Miss. Florentina \n female \n 30.0000 \n 1 \n 0 \n SC/PARIS 2148 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n male \n 23.0000 \n 0 \n 0 \n 29751 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Enander, Mr. Ingvar \n male \n 21.0000 \n 0 \n 0 \n 236854 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n male \n 18.0000 \n 0 \n 0 \n 236171 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Faunthorpe, Mr. Harry \n male \n 40.0000 \n 1 \n 0 \n 2926 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n female \n 29.0000 \n 1 \n 0 \n 2926 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n male \n 18.0000 \n 0 \n 0 \n C.A. 15185 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n male \n 36.0000 \n 0 \n 0 \n 229236 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n male \n NA \n 0 \n 0 \n 239854 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n female \n 38.0000 \n 0 \n 0 \n 237671 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Fynney, Mr. Joseph J \n male \n 35.0000 \n 0 \n 0 \n 239865 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Gale, Mr. Harry \n male \n 38.0000 \n 1 \n 0 \n 28664 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Gale, Mr. Shadrach \n male \n 34.0000 \n 1 \n 0 \n 28664 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Garside, Miss. Ethel \n female \n 34.0000 \n 0 \n 0 \n 243880 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Gaskell, Mr. Alfred \n male \n 16.0000 \n 0 \n 0 \n 239865 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Gavey, Mr. Lawrence \n male \n 26.0000 \n 0 \n 0 \n 31028 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Gilbert, Mr. William \n male \n 47.0000 \n 0 \n 0 \n C.A. 30769 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Giles, Mr. Edgar \n male \n 21.0000 \n 1 \n 0 \n 28133 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Giles, Mr. Frederick Edward \n male \n 21.0000 \n 1 \n 0 \n 28134 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Giles, Mr. Ralph \n male \n 24.0000 \n 0 \n 0 \n 248726 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Gill, Mr. John William \n male \n 24.0000 \n 0 \n 0 \n 233866 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Gillespie, Mr. William Henry \n male \n 34.0000 \n 0 \n 0 \n 12233 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n male \n 30.0000 \n 0 \n 0 \n 250646 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Greenberg, Mr. Samuel \n male \n 52.0000 \n 0 \n 0 \n 250647 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hale, Mr. Reginald \n male \n 30.0000 \n 0 \n 0 \n 250653 \n NA \n S \n \n \n cheap \n 14.5000 \n 2 \n 1 \n Hamalainen, Master. Viljo \n male \n 0.6667 \n 1 \n 1 \n 250649 \n NA \n S \n \n \n cheap \n 14.5000 \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n female \n 24.0000 \n 0 \n 2 \n 250649 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Harbeck, Mr. William H \n male \n 44.0000 \n 0 \n 0 \n 248746 \n NA \n S \n \n \n cheap \n 33.0000 \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n female \n 6.0000 \n 0 \n 1 \n 248727 \n NA \n S \n \n \n cheap \n 33.0000 \n 2 \n 0 \n Harper, Rev. John \n male \n 28.0000 \n 0 \n 1 \n 248727 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Harris, Mr. George \n male \n 62.0000 \n 0 \n 0 \n S.W./PP 752 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Harris, Mr. Walter \n male \n 30.0000 \n 0 \n 0 \n W/C 14208 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Hart, Miss. Eva Miriam \n female \n 7.0000 \n 0 \n 2 \n F.C.C. 13529 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 0 \n Hart, Mr. Benjamin \n male \n 43.0000 \n 1 \n 1 \n F.C.C. 13529 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n female \n 45.0000 \n 1 \n 1 \n F.C.C. 13529 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 1 \n Herman, Miss. Alice \n female \n 24.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 1 \n Herman, Miss. Kate \n female \n 24.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 0 \n Herman, Mr. Samuel \n male \n 49.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n female \n 48.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 16.0000 \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n female \n 55.0000 \n 0 \n 0 \n 248706 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n male \n 24.0000 \n 2 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hickman, Mr. Lewis \n male \n 32.0000 \n 2 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hickman, Mr. Stanley George \n male \n 21.0000 \n 2 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hiltunen, Miss. Marta \n female \n 18.0000 \n 1 \n 1 \n 250650 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n female \n 20.0000 \n 2 \n 1 \n 29105 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Hocking, Mr. Richard George \n male \n 23.0000 \n 2 \n 1 \n 29104 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n male \n 36.0000 \n 0 \n 0 \n 242963 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n female \n 54.0000 \n 1 \n 3 \n 29105 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hodges, Mr. Henry Price \n male \n 50.0000 \n 0 \n 0 \n 250643 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Hold, Mr. Stephen \n male \n 44.0000 \n 1 \n 0 \n 26707 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n female \n 29.0000 \n 1 \n 0 \n 26707 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n male \n 21.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Hosono, Mr. Masabumi \n male \n 42.0000 \n 0 \n 0 \n 237798 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Howard, Mr. Benjamin \n male \n 63.0000 \n 1 \n 0 \n 24065 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n female \n 60.0000 \n 1 \n 0 \n 24065 \n NA \n S \n \n \n cheap \n 12.2750 \n 2 \n 0 \n Hunt, Mr. George Henry \n male \n 33.0000 \n 0 \n 0 \n SCO/W 1585 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Ilett, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SO/C 14885 \n NA \n S \n \n \n cheap \n 27.0000 \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n male \n 42.0000 \n 1 \n 0 \n 243847 \n NA \n S \n \n \n cheap \n 27.0000 \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n female \n 24.0000 \n 2 \n 1 \n 243847 \n NA \n S \n \n \n cheap \n 15.0000 \n 2 \n 0 \n Jarvis, Mr. John Denzil \n male \n 47.0000 \n 0 \n 0 \n 237565 \n NA \n S \n \n \n cheap \n 31.5000 \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n male \n 24.0000 \n 2 \n 0 \n C.A. 31029 \n NA \n S \n \n \n cheap \n 31.5000 \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n male \n 22.0000 \n 2 \n 0 \n C.A. 31029 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n male \n 32.0000 \n 0 \n 0 \n C.A. 33111 \n NA \n S \n \n \n cheap \n 13.7917 \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n female \n 23.0000 \n 0 \n 0 \n SC/AH Basle 541 \n D \n C \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Kantor, Mr. Sinai \n male \n 34.0000 \n 1 \n 0 \n 244367 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n female \n 24.0000 \n 1 \n 0 \n 244367 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n female \n 22.0000 \n 0 \n 0 \n F.C.C. 13534 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 1 \n Keane, Miss. Nora A \n female \n NA \n 0 \n 0 \n 226593 \n E101 \n Q \n \n \n cheap \n 12.3500 \n 2 \n 0 \n Keane, Mr. Daniel \n male \n 35.0000 \n 0 \n 0 \n 233734 \n NA \n Q \n \n \n cheap \n 13.5000 \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n female \n 45.0000 \n 0 \n 0 \n 223596 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n male \n 57.0000 \n 0 \n 0 \n 219533 \n NA \n Q \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Knight, Mr. Robert J \n male \n NA \n 0 \n 0 \n 239855 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n male \n 31.0000 \n 0 \n 0 \n C.A. 18723 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n female \n 26.0000 \n 1 \n 1 \n 250651 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Lahtinen, Rev. William \n male \n 30.0000 \n 1 \n 1 \n 250651 \n NA \n S \n \n \n cheap \n 10.7083 \n 2 \n 0 \n Lamb, Mr. John Joseph \n male \n NA \n 0 \n 0 \n 240261 \n NA \n Q \n \n \n cheap \n 41.5792 \n 2 \n 1 \n Laroche, Miss. Louise \n female \n 1.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 41.5792 \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n female \n 3.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 41.5792 \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n male \n 25.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 41.5792 \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n female \n 22.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 12.0000 \n 2 \n 1 \n Lehmann, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SC 1748 \n NA \n C \n \n \n cheap \n 33.0000 \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n female \n NA \n 0 \n 0 \n 248727 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n female \n 34.0000 \n 0 \n 0 \n C.A. 34260 \n F33 \n S \n \n \n cheap \n 12.8750 \n 2 \n 0 \n Levy, Mr. Rene Jacques \n male \n 36.0000 \n 0 \n 0 \n SC/Paris 2163 \n D \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n male \n 24.0000 \n 0 \n 0 \n C.A. 29566 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 0 \n Lingane, Mr. John \n male \n 61.0000 \n 0 \n 0 \n 235509 \n NA \n Q \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Louch, Mr. Charles Alexander \n male \n 50.0000 \n 1 \n 0 \n SC/AH 3085 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n female \n 42.0000 \n 1 \n 0 \n SC/AH 3085 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Mack, Mrs. (Mary) \n female \n 57.0000 \n 0 \n 0 \n S.O./P.P. 3 \n E77 \n S \n \n \n cheap \n 15.0458 \n 2 \n 0 \n Malachard, Mr. Noel \n male \n NA \n 0 \n 0 \n 237735 \n D \n C \n \n \n cheap \n 37.0042 \n 2 \n 1 \n Mallet, Master. Andre \n male \n 1.0000 \n 0 \n 2 \n S.C./PARIS 2079 \n NA \n C \n \n \n cheap \n 37.0042 \n 2 \n 0 \n Mallet, Mr. Albert \n male \n 31.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n NA \n C \n \n \n cheap \n 37.0042 \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n female \n 24.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n NA \n C \n \n \n cheap \n 15.5792 \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n male \n NA \n 0 \n 0 \n SC/A.3 2861 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Matthews, Mr. William John \n male \n 30.0000 \n 0 \n 0 \n 28228 \n NA \n S \n \n \n cheap \n 16.0000 \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n male \n 40.0000 \n 0 \n 0 \n 239059 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n male \n 32.0000 \n 0 \n 0 \n 237216 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n McCrie, Mr. James Matthew \n male \n 30.0000 \n 0 \n 0 \n 233478 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n McKane, Mr. Peter David \n male \n 46.0000 \n 0 \n 0 \n 28403 \n NA \n S \n \n \n cheap \n 19.5000 \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n female \n 13.0000 \n 0 \n 1 \n 250644 \n NA \n S \n \n \n cheap \n 19.5000 \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n female \n 41.0000 \n 0 \n 1 \n 250644 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Mellors, Mr. William John \n male \n 19.0000 \n 0 \n 0 \n SW/PP 751 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Meyer, Mr. August \n male \n 39.0000 \n 0 \n 0 \n 248723 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Milling, Mr. Jacob Christian \n male \n 48.0000 \n 0 \n 0 \n 234360 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n male \n 70.0000 \n 0 \n 0 \n C.A. 24580 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Montvila, Rev. Juozas \n male \n 27.0000 \n 0 \n 0 \n 211536 \n NA \n S \n \n \n cheap \n 14.0000 \n 2 \n 0 \n Moraweck, Dr. Ernest \n male \n 54.0000 \n 0 \n 0 \n 29011 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n male \n 39.0000 \n 0 \n 0 \n 250655 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n male \n 16.0000 \n 0 \n 0 \n S.O./P.P. 3 \n NA \n S \n \n \n cheap \n 9.6875 \n 2 \n 0 \n Myles, Mr. Thomas Francis \n male \n 62.0000 \n 0 \n 0 \n 240276 \n NA \n Q \n \n \n cheap \n 30.0708 \n 2 \n 0 \n Nasser, Mr. Nicholas \n male \n 32.5000 \n 1 \n 0 \n 237736 \n NA \n C \n \n \n cheap \n 30.0708 \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n female \n 14.0000 \n 1 \n 0 \n 237736 \n NA \n C \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Navratil, Master. Edmond Roger \n male \n 2.0000 \n 1 \n 1 \n 230080 \n F2 \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Navratil, Master. Michel M \n male \n 3.0000 \n 1 \n 1 \n 230080 \n F2 \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n male \n 36.5000 \n 0 \n 2 \n 230080 \n F2 \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Nesson, Mr. Israel \n male \n 26.0000 \n 0 \n 0 \n 244368 \n F2 \n S \n \n \n cheap \n 36.7500 \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n male \n 19.0000 \n 1 \n 1 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Norman, Mr. Robert Douglas \n male \n 28.0000 \n 0 \n 0 \n 218629 \n NA \n S \n \n \n cheap \n 13.8625 \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n male \n 20.0000 \n 0 \n 0 \n SC/PARIS 2166 \n D38 \n C \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n female \n 29.0000 \n 0 \n 0 \n C.A. 29395 \n F33 \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Otter, Mr. Richard \n male \n 39.0000 \n 0 \n 0 \n 28213 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n male \n 22.0000 \n 0 \n 0 \n W./C. 14260 \n NA \n S \n \n \n cheap \n 13.8625 \n 2 \n 1 \n Padro y Manent, Mr. Julian \n male \n NA \n 0 \n 0 \n SC/PARIS 2146 \n NA \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Pain, Dr. Alfred \n male \n 23.0000 \n 0 \n 0 \n 244278 \n NA \n S \n \n \n cheap \n 13.8583 \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n male \n 29.0000 \n 0 \n 0 \n SC/PARIS 2147 \n NA \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Parker, Mr. Clifford Richard \n male \n 28.0000 \n 0 \n 0 \n SC 14888 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n male \n NA \n 0 \n 0 \n 239853 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n female \n 50.0000 \n 0 \n 1 \n 230433 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Pengelly, Mr. Frederick William \n male \n 19.0000 \n 0 \n 0 \n 28665 \n NA \n S \n \n \n cheap \n 15.0500 \n 2 \n 0 \n Pernot, Mr. Rene \n male \n NA \n 0 \n 0 \n SC/PARIS 2131 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n male \n 41.0000 \n 0 \n 0 \n 237393 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n female \n 21.0000 \n 0 \n 1 \n S.O./P.P. 2 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n female \n 19.0000 \n 0 \n 0 \n 250655 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Phillips, Mr. Escott Robert \n male \n 43.0000 \n 0 \n 1 \n S.O./P.P. 2 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n female \n 32.0000 \n 0 \n 0 \n 234604 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Ponesell, Mr. Martin \n male \n 34.0000 \n 0 \n 0 \n 250647 \n NA \n S \n \n \n cheap \n 12.7375 \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n male \n 30.0000 \n 0 \n 0 \n C.A. 34644 \n NA \n C \n \n \n cheap \n 15.0333 \n 2 \n 0 \n Pulbaum, Mr. Franz \n male \n 27.0000 \n 0 \n 0 \n SC/PARIS 2168 \n NA \n C \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Quick, Miss. Phyllis May \n female \n 2.0000 \n 1 \n 1 \n 26360 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Quick, Miss. Winifred Vera \n female \n 8.0000 \n 1 \n 1 \n 26360 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n female \n 33.0000 \n 0 \n 2 \n 26360 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Reeves, Mr. David \n male \n 36.0000 \n 0 \n 0 \n C.A. 17248 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Renouf, Mr. Peter Henry \n male \n 34.0000 \n 1 \n 0 \n 31027 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n female \n 30.0000 \n 3 \n 0 \n 31027 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n female \n 28.0000 \n 0 \n 0 \n 230434 \n NA \n S \n \n \n cheap \n 15.0458 \n 2 \n 0 \n Richard, Mr. Emile \n male \n 23.0000 \n 0 \n 0 \n SC/PARIS 2133 \n NA \n C \n \n \n cheap \n 18.7500 \n 2 \n 1 \n Richards, Master. George Sibley \n male \n 0.8333 \n 1 \n 1 \n 29106 \n NA \n S \n \n \n cheap \n 18.7500 \n 2 \n 1 \n Richards, Master. William Rowe \n male \n 3.0000 \n 1 \n 1 \n 29106 \n NA \n S \n \n \n cheap \n 18.7500 \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n female \n 24.0000 \n 2 \n 3 \n 29106 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Ridsdale, Miss. Lucy \n female \n 50.0000 \n 0 \n 0 \n W./C. 14258 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n male \n 19.0000 \n 0 \n 0 \n 28004 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Rugg, Miss. Emily \n female \n 21.0000 \n 0 \n 0 \n C.A. 31026 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Schmidt, Mr. August \n male \n 26.0000 \n 0 \n 0 \n 248659 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n male \n 25.0000 \n 0 \n 0 \n 244361 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Sharp, Mr. Percival James R \n male \n 27.0000 \n 0 \n 0 \n 244358 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n female \n 25.0000 \n 0 \n 1 \n 230433 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n female \n 18.0000 \n 0 \n 2 \n 250652 \n NA \n S \n \n \n cheap \n 36.7500 \n 2 \n 1 \n Sincock, Miss. Maude \n female \n 20.0000 \n 0 \n 0 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Sinkkonen, Miss. Anna \n female \n 30.0000 \n 0 \n 0 \n 250648 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n male \n 59.0000 \n 0 \n 0 \n 237442 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n female \n 30.0000 \n 0 \n 0 \n 234818 \n NA \n Q \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Slemen, Mr. Richard James \n male \n 35.0000 \n 0 \n 0 \n 28206 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Smith, Miss. Marion Elsie \n female \n 40.0000 \n 0 \n 0 \n 31418 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n male \n 25.0000 \n 0 \n 0 \n C.A. 29178 \n NA \n S \n \n \n cheap \n 15.0458 \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n male \n 41.0000 \n 0 \n 0 \n 237734 \n NA \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n male \n 25.0000 \n 0 \n 0 \n F.C.C. 13540 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Swane, Mr. George \n male \n 18.5000 \n 0 \n 0 \n 248734 \n F \n S \n \n \n cheap \n 65.0000 \n 2 \n 0 \n Sweet, Mr. George Frederick \n male \n 14.0000 \n 0 \n 0 \n 220845 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Toomey, Miss. Ellen \n female \n 50.0000 \n 0 \n 0 \n F.C.C. 13531 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n male \n 23.0000 \n 0 \n 0 \n 233639 \n NA \n S \n \n \n cheap \n 12.6500 \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n female \n 28.0000 \n 0 \n 0 \n 240929 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n female \n 27.0000 \n 0 \n 0 \n 34218 \n E101 \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Turpin, Mr. William John Robert \n male \n 29.0000 \n 1 \n 0 \n 11668 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n female \n 27.0000 \n 1 \n 0 \n 11668 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Veal, Mr. James \n male \n 40.0000 \n 0 \n 0 \n 28221 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Walcroft, Miss. Nellie \n female \n 31.0000 \n 0 \n 0 \n F.C.C. 13528 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Ware, Mr. John James \n male \n 30.0000 \n 1 \n 0 \n CA 31352 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Ware, Mr. William Jeffery \n male \n 23.0000 \n 1 \n 0 \n 28666 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n female \n 31.0000 \n 0 \n 0 \n CA 31352 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n male \n NA \n 0 \n 0 \n 239856 \n NA \n S \n \n \n cheap \n 15.7500 \n 2 \n 1 \n Watt, Miss. Bertha J \n female \n 12.0000 \n 0 \n 0 \n C.A. 33595 \n NA \n S \n \n \n cheap \n 15.7500 \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n female \n 40.0000 \n 0 \n 0 \n C.A. 33595 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Webber, Miss. Susan \n female \n 32.5000 \n 0 \n 0 \n 27267 \n E101 \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Weisz, Mr. Leopold \n male \n 27.0000 \n 1 \n 0 \n 228414 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n female \n 29.0000 \n 1 \n 0 \n 228414 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Wells, Master. Ralph Lester \n male \n 2.0000 \n 1 \n 1 \n 29103 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Wells, Miss. Joan \n female \n 4.0000 \n 1 \n 1 \n 29103 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n female \n 29.0000 \n 0 \n 2 \n 29103 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 1 \n West, Miss. Barbara J \n female \n 0.9167 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 1 \n West, Miss. Constance Mirium \n female \n 5.0000 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 0 \n West, Mr. Edwy Arthur \n male \n 36.0000 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n female \n 33.0000 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Wheadon, Mr. Edward H \n male \n 66.0000 \n 0 \n 0 \n C.A. 24579 \n NA \n S \n \n \n cheap \n 12.8750 \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n male \n NA \n 0 \n 0 \n SC/PARIS 2159 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Wilhelms, Mr. Charles \n male \n 31.0000 \n 0 \n 0 \n 244270 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Williams, Mr. Charles Eugene \n male \n NA \n 0 \n 0 \n 244373 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 1 \n Wright, Miss. Marion \n female \n 26.0000 \n 0 \n 0 \n 220844 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n female \n 24.0000 \n 0 \n 0 \n 248747 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Abbing, Mr. Anthony \n male \n 42.0000 \n 0 \n 0 \n C.A. 5547 \n NA \n S \n \n \n cheap \n 20.2500 \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n male \n 13.0000 \n 0 \n 2 \n C.A. 2673 \n NA \n S \n \n \n cheap \n 20.2500 \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n male \n 16.0000 \n 1 \n 1 \n C.A. 2673 \n NA \n S \n \n \n cheap \n 20.2500 \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n female \n 35.0000 \n 1 \n 1 \n C.A. 2673 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n female \n 16.0000 \n 0 \n 0 \n 348125 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n male \n 25.0000 \n 0 \n 0 \n 348122 \n F G63 \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101284 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n female \n 18.0000 \n 0 \n 0 \n 2657 \n NA \n C \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n male \n 30.0000 \n 0 \n 0 \n C 7076 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Adams, Mr. John \n male \n 26.0000 \n 0 \n 0 \n 341826 \n NA \n S \n \n \n cheap \n 9.4750 \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n female \n 40.0000 \n 1 \n 0 \n 7546 \n NA \n S \n \n \n cheap \n 9.3500 \n 3 \n 1 \n Aks, Master. Philip Frank \n male \n 0.8333 \n 0 \n 1 \n 392091 \n NA \n S \n \n \n cheap \n 9.3500 \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n female \n 18.0000 \n 0 \n 1 \n 392091 \n NA \n S \n \n \n cheap \n 18.7875 \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n male \n 26.0000 \n 0 \n 0 \n 2699 \n NA \n C \n \n \n cheap \n 7.8875 \n 3 \n 0 \n Alexander, Mr. William \n male \n 26.0000 \n 0 \n 0 \n 3474 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101287 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Ali, Mr. Ahmed \n male \n 24.0000 \n 0 \n 0 \n SOTON/O.Q. 3101311 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Ali, Mr. William \n male \n 25.0000 \n 0 \n 0 \n SOTON/O.Q. 3101312 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Allen, Mr. William Henry \n male \n 35.0000 \n 0 \n 0 \n 373450 \n NA \n S \n \n \n cheap \n 8.3000 \n 3 \n 0 \n Allum, Mr. Owen George \n male \n 18.0000 \n 0 \n 0 \n 2223 \n NA \n S \n \n \n cheap \n 22.5250 \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n male \n 32.0000 \n 0 \n 0 \n C 4001 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n female \n 19.0000 \n 1 \n 0 \n 350046 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n male \n 4.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n female \n 6.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n female \n 2.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n female \n 17.0000 \n 4 \n 2 \n 3101281 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n female \n 38.0000 \n 4 \n 2 \n 347091 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n female \n 9.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n female \n 11.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Mr. Anders Johan \n male \n 39.0000 \n 1 \n 5 \n 347082 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n male \n 27.0000 \n 0 \n 0 \n 350043 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n male \n 26.0000 \n 0 \n 0 \n 347075 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n female \n 39.0000 \n 1 \n 5 \n 347082 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n male \n 20.0000 \n 0 \n 0 \n 347466 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Angheloff, Mr. Minko \n male \n 26.0000 \n 0 \n 0 \n 349202 \n NA \n S \n \n \n cheap \n 17.8000 \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n male \n 25.0000 \n 1 \n 0 \n 349237 \n NA \n S \n \n \n cheap \n 17.8000 \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n female \n 18.0000 \n 1 \n 0 \n 349237 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n male \n 24.0000 \n 0 \n 0 \n 349911 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Asim, Mr. Adola \n male \n 35.0000 \n 0 \n 0 \n SOTON/O.Q. 3101310 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Master. Carl Edgar \n male \n 5.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n male \n 9.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n male \n 3.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Master. Filip Oscar \n male \n 13.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n female \n 5.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n male \n 40.0000 \n 1 \n 5 \n 347077 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Asplund, Mr. Johan Charles \n male \n 23.0000 \n 0 \n 0 \n 350054 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n female \n 38.0000 \n 1 \n 5 \n 347077 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n female \n 45.0000 \n 0 \n 0 \n 2696 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Assaf, Mr. Gerios \n male \n 21.0000 \n 0 \n 0 \n 2692 \n NA \n C \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Assam, Mr. Ali \n male \n 23.0000 \n 0 \n 0 \n SOTON/O.Q. 3101309 \n NA \n S \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Attalah, Miss. Malake \n female \n 17.0000 \n 0 \n 0 \n 2627 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Attalah, Mr. Sleiman \n male \n 30.0000 \n 0 \n 0 \n 2694 \n NA \n C \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Augustsson, Mr. Albert \n male \n 23.0000 \n 0 \n 0 \n 347468 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Ayoub, Miss. Banoura \n female \n 13.0000 \n 0 \n 0 \n 2687 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Baccos, Mr. Raffull \n male \n 20.0000 \n 0 \n 0 \n 2679 \n NA \n C \n \n \n cheap \n 15.8500 \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n male \n 32.0000 \n 1 \n 0 \n 3101278 \n NA \n S \n \n \n cheap \n 15.8500 \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n female \n 33.0000 \n 3 \n 0 \n 3101278 \n NA \n S \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Miss. Eugenie \n female \n 0.7500 \n 2 \n 1 \n 2666 \n NA \n C \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n female \n 0.7500 \n 2 \n 1 \n 2666 \n NA \n C \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n female \n 5.0000 \n 2 \n 1 \n 2666 \n NA \n C \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n female \n 24.0000 \n 0 \n 3 \n 2666 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Badman, Miss. Emily Louisa \n female \n 18.0000 \n 0 \n 0 \n A/4 31416 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Badt, Mr. Mohamed \n male \n 40.0000 \n 0 \n 0 \n 2623 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Balkic, Mr. Cerin \n male \n 26.0000 \n 0 \n 0 \n 349248 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Barah, Mr. Hanna Assi \n male \n 20.0000 \n 0 \n 0 \n 2663 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Barbara, Miss. Saiide \n female \n 18.0000 \n 0 \n 1 \n 2691 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n female \n 45.0000 \n 0 \n 1 \n 2691 \n NA \n C \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Barry, Miss. Julia \n female \n 27.0000 \n 0 \n 0 \n 330844 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Barton, Mr. David John \n male \n 22.0000 \n 0 \n 0 \n 324669 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Beavan, Mr. William Thomas \n male \n 19.0000 \n 0 \n 0 \n 323951 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n male \n 26.0000 \n 0 \n 0 \n 347068 \n NA \n S \n \n \n cheap \n 9.3500 \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n male \n 22.0000 \n 0 \n 0 \n PP 4348 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Betros, Master. Seman \n male \n NA \n 0 \n 0 \n 2622 \n NA \n C \n \n \n cheap \n 4.0125 \n 3 \n 0 \n Betros, Mr. Tannous \n male \n 20.0000 \n 0 \n 0 \n 2648 \n NA \n C \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Bing, Mr. Lee \n male \n 32.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n male \n 21.0000 \n 0 \n 0 \n 312992 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n male \n 18.0000 \n 0 \n 0 \n 347090 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n male \n 26.0000 \n 0 \n 0 \n 349224 \n NA \n S \n \n \n cheap \n 15.2458 \n 3 \n 0 \n Boulos, Master. Akar \n male \n 6.0000 \n 1 \n 1 \n 2678 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 0 \n Boulos, Miss. Nourelain \n female \n 9.0000 \n 1 \n 1 \n 2678 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Boulos, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2664 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n female \n NA \n 0 \n 2 \n 2678 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Bourke, Miss. Mary \n female \n NA \n 0 \n 2 \n 364848 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Bourke, Mr. John \n male \n 40.0000 \n 1 \n 1 \n 364849 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n female \n 32.0000 \n 1 \n 1 \n 364849 \n NA \n Q \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n male \n 21.0000 \n 0 \n 0 \n 54636 \n NA \n S \n \n \n cheap \n 7.7250 \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n female \n 22.0000 \n 0 \n 0 \n 334914 \n NA \n Q \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n female \n 20.0000 \n 0 \n 0 \n 347471 \n NA \n S \n \n \n cheap \n 7.0458 \n 3 \n 0 \n Braund, Mr. Lewis Richard \n male \n 29.0000 \n 1 \n 0 \n 3460 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Braund, Mr. Owen Harris \n male \n 22.0000 \n 1 \n 0 \n A/5 21171 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n male \n 22.0000 \n 0 \n 0 \n 350045 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n male \n 35.0000 \n 0 \n 0 \n 364512 \n NA \n S \n \n \n cheap \n 7.2833 \n 3 \n 0 \n Buckley, Miss. Katherine \n female \n 18.5000 \n 0 \n 0 \n 329944 \n NA \n Q \n \n \n cheap \n 7.8208 \n 3 \n 1 \n Buckley, Mr. Daniel \n male \n 21.0000 \n 0 \n 0 \n 330920 \n NA \n Q \n \n \n cheap \n 6.7500 \n 3 \n 0 \n Burke, Mr. Jeremiah \n male \n 19.0000 \n 0 \n 0 \n 365222 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Burns, Miss. Mary Delia \n female \n 18.0000 \n 0 \n 0 \n 330963 \n NA \n Q \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Miss. Manda \n female \n 21.0000 \n 0 \n 0 \n 315087 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Miss. Marija \n female \n 30.0000 \n 0 \n 0 \n 315084 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Mr. Jego Grga \n male \n 18.0000 \n 0 \n 0 \n 315091 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Mr. Luka \n male \n 38.0000 \n 0 \n 0 \n 315089 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Calic, Mr. Jovo \n male \n 17.0000 \n 0 \n 0 \n 315093 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Calic, Mr. Petar \n male \n 17.0000 \n 0 \n 0 \n 315086 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Canavan, Miss. Mary \n female \n 21.0000 \n 0 \n 0 \n 364846 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Canavan, Mr. Patrick \n male \n 21.0000 \n 0 \n 0 \n 364858 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Cann, Mr. Ernest Charles \n male \n 21.0000 \n 0 \n 0 \n A./5. 2152 \n NA \n S \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Caram, Mr. Joseph \n male \n NA \n 1 \n 0 \n 2689 \n NA \n C \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n female \n NA \n 1 \n 0 \n 2689 \n NA \n C \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n male \n 28.0000 \n 0 \n 0 \n 350042 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n male \n 24.0000 \n 0 \n 0 \n 350409 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n female \n 16.0000 \n 0 \n 0 \n 367231 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Carr, Miss. Jeannie \n female \n 37.0000 \n 0 \n 0 \n 368364 \n NA \n Q \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Carver, Mr. Alfred John \n male \n 28.0000 \n 0 \n 0 \n 392095 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Celotti, Mr. Francesco \n male \n 24.0000 \n 0 \n 0 \n 343275 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 0 \n Charters, Mr. David \n male \n 21.0000 \n 0 \n 0 \n A/5. 13032 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Chip, Mr. Chang \n male \n 32.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Christmann, Mr. Emil \n male \n 29.0000 \n 0 \n 0 \n 343276 \n NA \n S \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n male \n 26.0000 \n 1 \n 0 \n 2680 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n male \n 18.0000 \n 1 \n 0 \n 2680 \n NA \n C \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n male \n 20.0000 \n 0 \n 0 \n SOTON/O.Q. 3101307 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n male \n 18.0000 \n 0 \n 0 \n A/5 3540 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Colbert, Mr. Patrick \n male \n 24.0000 \n 0 \n 0 \n 371109 \n NA \n Q \n \n \n cheap \n 7.4958 \n 3 \n 0 \n Coleff, Mr. Peju \n male \n 36.0000 \n 0 \n 0 \n 349210 \n NA \n S \n \n \n cheap \n 7.4958 \n 3 \n 0 \n Coleff, Mr. Satio \n male \n 24.0000 \n 0 \n 0 \n 349209 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n male \n 31.0000 \n 0 \n 0 \n 21332 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Connaghton, Mr. Michael \n male \n 31.0000 \n 0 \n 0 \n 335097 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Connolly, Miss. Kate \n female \n 22.0000 \n 0 \n 0 \n 370373 \n NA \n Q \n \n \n cheap \n 7.6292 \n 3 \n 0 \n Connolly, Miss. Kate \n female \n 30.0000 \n 0 \n 0 \n 330972 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Connors, Mr. Patrick \n male \n 70.5000 \n 0 \n 0 \n 370369 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Cook, Mr. Jacob \n male \n 43.0000 \n 0 \n 0 \n A/5 3536 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Cor, Mr. Bartol \n male \n 35.0000 \n 0 \n 0 \n 349230 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Cor, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 349229 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Cor, Mr. Liudevit \n male \n 19.0000 \n 0 \n 0 \n 349231 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Corn, Mr. Harry \n male \n 30.0000 \n 0 \n 0 \n SOTON/OQ 392090 \n NA \n S \n \n \n cheap \n 15.9000 \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n male \n 9.0000 \n 1 \n 1 \n C.A. 37671 \n NA \n S \n \n \n cheap \n 15.9000 \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n male \n 3.0000 \n 1 \n 1 \n C.A. 37671 \n NA \n S \n \n \n cheap \n 15.9000 \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n female \n 36.0000 \n 0 \n 2 \n C.A. 37671 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Coxon, Mr. Daniel \n male \n 59.0000 \n 0 \n 0 \n 364500 \n NA \n S \n \n \n cheap \n 8.1583 \n 3 \n 0 \n Crease, Mr. Ernest James \n male \n 19.0000 \n 0 \n 0 \n S.P. 3464 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 1 \n Cribb, Miss. Laura Alice \n female \n 17.0000 \n 0 \n 1 \n 371362 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Cribb, Mr. John Hatfield \n male \n 44.0000 \n 0 \n 1 \n 371362 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Culumovic, Mr. Jeso \n male \n 17.0000 \n 0 \n 0 \n 315090 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Daher, Mr. Shedid \n male \n 22.5000 \n 0 \n 0 \n 2698 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n male \n 45.0000 \n 0 \n 0 \n 7598 \n NA \n S \n \n \n cheap \n 10.5167 \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n female \n 22.0000 \n 0 \n 0 \n 7552 \n NA \n S \n \n \n cheap \n 10.1708 \n 3 \n 0 \n Dakic, Mr. Branko \n male \n 19.0000 \n 0 \n 0 \n 349228 \n NA \n S \n \n \n cheap \n 6.9500 \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n female \n 30.0000 \n 0 \n 0 \n 382650 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n male \n 29.0000 \n 0 \n 0 \n 382651 \n NA \n Q \n \n \n cheap \n 14.4000 \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n male \n 0.3333 \n 0 \n 2 \n 347080 \n NA \n S \n \n \n cheap \n 14.4000 \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n male \n 34.0000 \n 1 \n 1 \n 347080 \n NA \n S \n \n \n cheap \n 14.4000 \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n female \n 28.0000 \n 1 \n 1 \n 347080 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Danoff, Mr. Yoto \n male \n 27.0000 \n 0 \n 0 \n 349219 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n male \n 25.0000 \n 0 \n 0 \n 349203 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Davies, Mr. Alfred J \n male \n 24.0000 \n 2 \n 0 \n A/4 48871 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Davies, Mr. Evan \n male \n 22.0000 \n 0 \n 0 \n SC/A4 23568 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Davies, Mr. John Samuel \n male \n 21.0000 \n 2 \n 0 \n A/4 48871 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Davies, Mr. Joseph \n male \n 17.0000 \n 2 \n 0 \n A/4 48873 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Davison, Mr. Thomas Henry \n male \n NA \n 1 \n 0 \n 386525 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n female \n NA \n 1 \n 0 \n 386525 \n NA \n S \n \n \n cheap \n 17.4000 \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n male \n 36.5000 \n 1 \n 0 \n 345572 \n NA \n S \n \n \n cheap \n 17.4000 \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n female \n 36.0000 \n 1 \n 0 \n 345572 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 1 \n de Mulder, Mr. Theodore \n male \n 30.0000 \n 0 \n 0 \n 345774 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n male \n 16.0000 \n 0 \n 0 \n 345778 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 1 \n Dean, Master. Bertram Vere \n male \n 1.0000 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n female \n 0.1667 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 0 \n Dean, Mr. Bertram Frank \n male \n 26.0000 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n female \n 33.0000 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Delalic, Mr. Redjo \n male \n 25.0000 \n 0 \n 0 \n 349250 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Demetri, Mr. Marinko \n male \n NA \n 0 \n 0 \n 349238 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Denkoff, Mr. Mitto \n male \n NA \n 0 \n 0 \n 349225 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Dennis, Mr. Samuel \n male \n 22.0000 \n 0 \n 0 \n A/5 21172 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Dennis, Mr. William \n male \n 36.0000 \n 0 \n 0 \n A/5 21175 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n female \n 19.0000 \n 0 \n 0 \n 330958 \n NA \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Dika, Mr. Mirko \n male \n 17.0000 \n 0 \n 0 \n 349232 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Dimic, Mr. Jovan \n male \n 42.0000 \n 0 \n 0 \n 315088 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n male \n 43.0000 \n 0 \n 0 \n 349226 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Doharr, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2686 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Dooley, Mr. Patrick \n male \n 32.0000 \n 0 \n 0 \n 370376 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n male \n 19.0000 \n 0 \n 0 \n A/5. 10482 \n NA \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n female \n 30.0000 \n 0 \n 0 \n 364516 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Doyle, Miss. Elizabeth \n female \n 24.0000 \n 0 \n 0 \n 368702 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Drapkin, Miss. Jennie \n female \n 23.0000 \n 0 \n 0 \n SOTON/OQ 392083 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Drazenoic, Mr. Jozef \n male \n 33.0000 \n 0 \n 0 \n 349241 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Duane, Mr. Frank \n male \n 65.0000 \n 0 \n 0 \n 336439 \n NA \n Q \n \n \n cheap \n 7.5500 \n 3 \n 1 \n Duquemin, Mr. Joseph \n male \n 24.0000 \n 0 \n 0 \n S.O./P.P. 752 \n NA \n S \n \n \n cheap \n 13.9000 \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n male \n 23.0000 \n 1 \n 0 \n 347072 \n NA \n S \n \n \n cheap \n 13.9000 \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n female \n 22.0000 \n 1 \n 0 \n 347072 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n male \n 18.0000 \n 0 \n 0 \n 349912 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Eklund, Mr. Hans Linus \n male \n 16.0000 \n 0 \n 0 \n 347074 \n NA \n S \n \n \n cheap \n 6.9750 \n 3 \n 0 \n Ekstrom, Mr. Johan \n male \n 45.0000 \n 0 \n 0 \n 347061 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Elias, Mr. Dibo \n male \n NA \n 0 \n 0 \n 2674 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Elias, Mr. Joseph \n male \n 39.0000 \n 0 \n 2 \n 2675 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Elias, Mr. Joseph Jr \n male \n 17.0000 \n 1 \n 1 \n 2690 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Elias, Mr. Tannous \n male \n 15.0000 \n 1 \n 1 \n 2695 \n NA \n C \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Elsbury, Mr. William James \n male \n 47.0000 \n 0 \n 0 \n A/5 3902 \n NA \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n female \n 5.0000 \n 0 \n 0 \n 364516 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Emir, Mr. Farred Chehab \n male \n NA \n 0 \n 0 \n 2631 \n NA \n C \n \n \n cheap \n 15.1000 \n 3 \n 0 \n Everett, Mr. Thomas James \n male \n 40.5000 \n 0 \n 0 \n C.A. 6212 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Farrell, Mr. James \n male \n 40.5000 \n 0 \n 0 \n 367232 \n NA \n Q \n \n \n cheap \n 7.0500 \n 3 \n 1 \n Finoli, Mr. Luigi \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101308 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n male \n 18.0000 \n 0 \n 0 \n 350036 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Fleming, Miss. Honora \n female \n NA \n 0 \n 0 \n 364859 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Flynn, Mr. James \n male \n NA \n 0 \n 0 \n 364851 \n NA \n Q \n \n \n cheap \n 6.9500 \n 3 \n 0 \n Flynn, Mr. John \n male \n NA \n 0 \n 0 \n 368323 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Foley, Mr. Joseph \n male \n 26.0000 \n 0 \n 0 \n 330910 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Foley, Mr. William \n male \n NA \n 0 \n 0 \n 365235 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Foo, Mr. Choong \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n female \n 21.0000 \n 2 \n 2 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n female \n 9.0000 \n 2 \n 2 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Ford, Mr. Arthur \n male \n NA \n 0 \n 0 \n A/5 1478 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Mr. Edward Watson \n male \n 18.0000 \n 2 \n 2 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Mr. William Neal \n male \n 16.0000 \n 1 \n 3 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n female \n 48.0000 \n 1 \n 3 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Fox, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368573 \n NA \n Q \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101314 \n NA \n S \n \n \n cheap \n 7.7417 \n 3 \n 0 \n Gallagher, Mr. Martin \n male \n 25.0000 \n 0 \n 0 \n 36864 \n NA \n Q \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Garfirth, Mr. John \n male \n NA \n 0 \n 0 \n 358585 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n male \n NA \n 0 \n 0 \n 349254 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Gilinski, Mr. Eliezer \n male \n 22.0000 \n 0 \n 0 \n 14973 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n female \n 16.0000 \n 0 \n 0 \n 35851 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n female \n NA \n 0 \n 0 \n 335677 \n NA \n Q \n \n \n cheap \n 20.5250 \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n male \n 9.0000 \n 0 \n 2 \n 363291 \n NA \n S \n \n \n cheap \n 20.5250 \n 3 \n 0 \n Goldsmith, Mr. Frank John \n male \n 33.0000 \n 1 \n 1 \n 363291 \n NA \n S \n \n \n cheap \n 7.8500 \n 3 \n 0 \n Goldsmith, Mr. Nathan \n male \n 41.0000 \n 0 \n 0 \n SOTON/O.Q. 3101263 \n NA \n S \n \n \n cheap \n 20.5250 \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n female \n 31.0000 \n 1 \n 1 \n 363291 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n male \n 38.0000 \n 0 \n 0 \n SOTON/O.Q. 3101306 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Master. Harold Victor \n male \n 9.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n male \n 1.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Master. William Frederick \n male \n 11.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n female \n 10.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n female \n 16.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n male \n 14.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n male \n 40.0000 \n 1 \n 6 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n female \n 43.0000 \n 1 \n 6 \n CA 2144 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Green, Mr. George Henry \n male \n 51.0000 \n 0 \n 0 \n 21440 \n NA \n S \n \n \n cheap \n 8.3625 \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n male \n 32.0000 \n 0 \n 0 \n 8471 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Guest, Mr. Robert \n male \n NA \n 0 \n 0 \n 376563 \n NA \n S \n \n \n cheap \n 9.8458 \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n male \n 20.0000 \n 0 \n 0 \n 7534 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n male \n 37.0000 \n 2 \n 0 \n 3101276 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n male \n 28.0000 \n 2 \n 0 \n 3101277 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n male \n 19.0000 \n 0 \n 0 \n 347069 \n NA \n S \n \n \n cheap \n 8.8500 \n 3 \n 0 \n Haas, Miss. Aloisia \n female \n 24.0000 \n 0 \n 0 \n 349236 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 0 \n Hagardon, Miss. Kate \n female \n 17.0000 \n 0 \n 0 \n AQ/3. 30631 \n NA \n Q \n \n \n cheap \n 19.9667 \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n male \n NA \n 1 \n 0 \n 65303 \n NA \n S \n \n \n cheap \n 19.9667 \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n male \n NA \n 1 \n 0 \n 65304 \n NA \n S \n \n \n cheap \n 15.8500 \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n male \n 28.0000 \n 1 \n 0 \n STON/O2. 3101279 \n NA \n S \n \n \n cheap \n 15.8500 \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n female \n 24.0000 \n 1 \n 0 \n STON/O2. 3101279 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Hampe, Mr. Leon \n male \n 20.0000 \n 0 \n 0 \n 345769 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Hanna, Mr. Mansour \n male \n 23.5000 \n 0 \n 0 \n 2693 \n NA \n C \n \n \n cheap \n 14.1083 \n 3 \n 0 \n Hansen, Mr. Claus Peter \n male \n 41.0000 \n 2 \n 0 \n 350026 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n male \n 26.0000 \n 1 \n 0 \n 350025 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n male \n 21.0000 \n 0 \n 0 \n 350029 \n NA \n S \n \n \n cheap \n 14.1083 \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n female \n 45.0000 \n 1 \n 0 \n 350026 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n female \n NA \n 0 \n 0 \n W./C. 6609 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n male \n 25.0000 \n 0 \n 0 \n 374887 \n NA \n S \n \n \n cheap \n 6.8583 \n 3 \n 0 \n Hart, Mr. Henry \n male \n NA \n 0 \n 0 \n 394140 \n NA \n Q \n \n \n cheap \n 18.7875 \n 3 \n 0 \n Hassan, Mr. Houssein G N \n male \n 11.0000 \n 0 \n 0 \n 2699 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n female \n NA \n 0 \n 0 \n 370375 \n NA \n Q \n \n \n cheap \n 6.9750 \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n male \n 27.0000 \n 0 \n 0 \n 347089 \n NA \n S \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Hee, Mr. Ling \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 6.7500 \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n female \n 18.0000 \n 0 \n 0 \n 365226 \n NA \n Q \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Heikkinen, Miss. Laina \n female \n 26.0000 \n 0 \n 0 \n STON/O2. 3101282 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n female \n 23.0000 \n 0 \n 0 \n STON/O2. 3101290 \n NA \n S \n \n \n cheap \n 8.9625 \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n female \n 22.0000 \n 0 \n 0 \n 7548 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n male \n 28.0000 \n 0 \n 0 \n 349243 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n female \n 28.0000 \n 0 \n 0 \n 347086 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Henry, Miss. Delia \n female \n NA \n 0 \n 0 \n 382649 \n NA \n Q \n \n \n cheap \n 12.2875 \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n female \n 2.0000 \n 0 \n 1 \n 3101298 \n NA \n S \n \n \n cheap \n 12.2875 \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n female \n 22.0000 \n 1 \n 1 \n 3101298 \n NA \n S \n \n \n cheap \n 6.4500 \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n male \n 43.0000 \n 0 \n 0 \n C 7075 \n NA \n S \n \n \n cheap \n 22.5250 \n 3 \n 0 \n Holthen, Mr. Johan Martin \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Honkanen, Miss. Eliina \n female \n 27.0000 \n 0 \n 0 \n STON/O2. 3101283 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Horgan, Mr. John \n male \n NA \n 0 \n 0 \n 370377 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Howard, Miss. May Elizabeth \n female \n NA \n 0 \n 0 \n A. 2. 39186 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n male \n 42.0000 \n 0 \n 0 \n 348121 \n F G63 \n S \n \n \n cheap \n 7.8875 \n 3 \n 1 \n Hyman, Mr. Abraham \n male \n NA \n 0 \n 0 \n 3470 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n male \n 30.0000 \n 0 \n 0 \n 2685 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Ilieff, Mr. Ylio \n male \n NA \n 0 \n 0 \n 349220 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n female \n 27.0000 \n 1 \n 0 \n STON/O2. 3101270 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n female \n 25.0000 \n 1 \n 0 \n STON/O2. 3101271 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Ivanoff, Mr. Kanio \n male \n NA \n 0 \n 0 \n 349201 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 1 \n Jalsevac, Mr. Ivan \n male \n 29.0000 \n 0 \n 0 \n 349240 \n NA \n C \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Jansson, Mr. Carl Olof \n male \n 21.0000 \n 0 \n 0 \n 350034 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Jardin, Mr. Jose Neto \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101305 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Jensen, Mr. Hans Peder \n male \n 20.0000 \n 0 \n 0 \n 350050 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Jensen, Mr. Niels Peder \n male \n 48.0000 \n 0 \n 0 \n 350047 \n NA \n S \n \n \n cheap \n 7.0542 \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n male \n 17.0000 \n 1 \n 0 \n 350048 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Jermyn, Miss. Annie \n female \n NA \n 0 \n 0 \n 14313 \n NA \n Q \n \n \n cheap \n 8.1125 \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n male \n NA \n 0 \n 0 \n 65306 \n NA \n S \n \n \n cheap \n 6.4958 \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n male \n 34.0000 \n 0 \n 0 \n 3101264 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n male \n 26.0000 \n 0 \n 0 \n 347070 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Johansson, Mr. Erik \n male \n 22.0000 \n 0 \n 0 \n 350052 \n NA \n S \n \n \n cheap \n 8.6542 \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n male \n 33.0000 \n 0 \n 0 \n 7540 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Johansson, Mr. Karl Johan \n male \n 31.0000 \n 0 \n 0 \n 347063 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Johansson, Mr. Nils \n male \n 29.0000 \n 0 \n 0 \n 347467 \n NA \n S \n \n \n cheap \n 11.1333 \n 3 \n 1 \n Johnson, Master. Harold Theodor \n male \n 4.0000 \n 1 \n 1 \n 347742 \n NA \n S \n \n \n cheap \n 11.1333 \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n female \n 1.0000 \n 1 \n 1 \n 347742 \n NA \n S \n \n \n cheap \n 0.0000 \n 3 \n 0 \n Johnson, Mr. Alfred \n male \n 49.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n male \n 33.0000 \n 0 \n 0 \n 347062 \n NA \n S \n \n \n cheap \n 0.0000 \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n male \n 19.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 11.1333 \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n female \n 27.0000 \n 0 \n 2 \n 347742 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n male \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n female \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Mr. Andrew G \n male \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n female \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Jonkoff, Mr. Lalio \n male \n 23.0000 \n 0 \n 0 \n 349204 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Jonsson, Mr. Carl \n male \n 32.0000 \n 0 \n 0 \n 350417 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n male \n 27.0000 \n 0 \n 0 \n 350408 \n NA \n S \n \n \n cheap \n 9.8250 \n 3 \n 0 \n Jussila, Miss. Katriina \n female \n 20.0000 \n 1 \n 0 \n 4136 \n NA \n S \n \n \n cheap \n 9.8250 \n 3 \n 0 \n Jussila, Miss. Mari Aina \n female \n 21.0000 \n 1 \n 0 \n 4137 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Jussila, Mr. Eiriik \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101286 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n male \n 17.0000 \n 0 \n 0 \n STON/O 2. 3101274 \n NA \n S \n \n \n cheap \n 8.4333 \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n male \n 21.0000 \n 0 \n 0 \n 8475 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Karaic, Mr. Milan \n male \n 30.0000 \n 0 \n 0 \n 349246 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n male \n 21.0000 \n 0 \n 0 \n 350053 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n male \n 33.0000 \n 0 \n 0 \n 347465 \n NA \n S \n \n \n cheap \n 7.5208 \n 3 \n 0 \n Karlsson, Mr. Nils August \n male \n 22.0000 \n 0 \n 0 \n 350060 \n NA \n S \n \n \n cheap \n 13.4167 \n 3 \n 1 \n Karun, Miss. Manca \n female \n 4.0000 \n 0 \n 1 \n 349256 \n NA \n C \n \n \n cheap \n 13.4167 \n 3 \n 1 \n Karun, Mr. Franz \n male \n 39.0000 \n 0 \n 1 \n 349256 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Kassem, Mr. Fared \n male \n NA \n 0 \n 0 \n 2700 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n male \n 18.5000 \n 0 \n 0 \n 2682 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n male \n NA \n 0 \n 0 \n 12460 \n NA \n Q \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Keefe, Mr. Arthur \n male \n NA \n 0 \n 0 \n 323592 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n female \n NA \n 0 \n 0 \n 9234 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Kelly, Miss. Mary \n female \n NA \n 0 \n 0 \n 14312 \n NA \n Q \n \n \n cheap \n 7.8292 \n 3 \n 0 \n Kelly, Mr. James \n male \n 34.5000 \n 0 \n 0 \n 330911 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Kelly, Mr. James \n male \n 44.0000 \n 0 \n 0 \n 363592 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Kennedy, Mr. John \n male \n NA \n 0 \n 0 \n 368783 \n NA \n Q \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Khalil, Mr. Betros \n male \n NA \n 1 \n 0 \n 2660 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n female \n NA \n 1 \n 0 \n 2660 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Kiernan, Mr. John \n male \n NA \n 1 \n 0 \n 367227 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Kiernan, Mr. Philip \n male \n NA \n 1 \n 0 \n 367229 \n NA \n Q \n \n \n cheap \n 7.7375 \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n male \n NA \n 0 \n 0 \n 36865 \n NA \n Q \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Kink, Miss. Maria \n female \n 22.0000 \n 2 \n 0 \n 315152 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Kink, Mr. Vincenz \n male \n 26.0000 \n 2 \n 0 \n 315151 \n NA \n S \n \n \n cheap \n 22.0250 \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n female \n 4.0000 \n 0 \n 2 \n 315153 \n NA \n S \n \n \n cheap \n 22.0250 \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n male \n 29.0000 \n 3 \n 1 \n 315153 \n NA \n S \n \n \n cheap \n 22.0250 \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n female \n 26.0000 \n 1 \n 1 \n 315153 \n NA \n S \n \n \n cheap \n 12.1833 \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n female \n 1.0000 \n 1 \n 1 \n 350405 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Klasen, Mr. Klas Albin \n male \n 18.0000 \n 1 \n 1 \n 350404 \n NA \n S \n \n \n cheap \n 12.1833 \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n female \n 36.0000 \n 0 \n 2 \n 350405 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Kraeff, Mr. Theodor \n male \n NA \n 0 \n 0 \n 349253 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Krekorian, Mr. Neshan \n male \n 25.0000 \n 0 \n 0 \n 2654 \n F E57 \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Lahoud, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2624 \n NA \n C \n \n \n cheap \n 9.5875 \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n female \n 37.0000 \n 0 \n 0 \n 4135 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Laleff, Mr. Kristo \n male \n NA \n 0 \n 0 \n 349217 \n NA \n S \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Lam, Mr. Ali \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 56.4958 \n 3 \n 0 \n Lam, Mr. Len \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n female \n 22.0000 \n 0 \n 0 \n C 7077 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Lane, Mr. Patrick \n male \n NA \n 0 \n 0 \n 7935 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Lang, Mr. Fang \n male \n 26.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 9.4833 \n 3 \n 0 \n Larsson, Mr. August Viktor \n male \n 29.0000 \n 0 \n 0 \n 7545 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n male \n 29.0000 \n 0 \n 0 \n 347067 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n male \n 22.0000 \n 0 \n 0 \n 347065 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n male \n 22.0000 \n 0 \n 0 \n 2620 \n NA \n C \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n male \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Miss. Ida \n female \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Miss. Jeannie \n female \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Miss. Mathilde \n female \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n female \n NA \n 0 \n 4 \n 4133 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101292 \n NA \n S \n \n \n cheap \n 6.4375 \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n male \n 34.5000 \n 0 \n 0 \n 2683 \n NA \n C \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Lennon, Miss. Mary \n female \n NA \n 1 \n 0 \n 370371 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Lennon, Mr. Denis \n male \n NA \n 1 \n 0 \n 370371 \n NA \n Q \n \n \n cheap \n 0.0000 \n 3 \n 0 \n Leonard, Mr. Lionel \n male \n 36.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Lester, Mr. James \n male \n 39.0000 \n 0 \n 0 \n A/4 48871 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Lievens, Mr. Rene Aime \n male \n 24.0000 \n 0 \n 0 \n 345781 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n female \n 25.0000 \n 0 \n 0 \n 347071 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n female \n 45.0000 \n 0 \n 0 \n 347073 \n NA \n S \n \n \n cheap \n 15.5500 \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n male \n 36.0000 \n 1 \n 0 \n 349910 \n NA \n S \n \n \n cheap \n 15.5500 \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n female \n 30.0000 \n 1 \n 0 \n 349910 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Lindqvist, Mr. Eino William \n male \n 20.0000 \n 1 \n 0 \n STON/O 2. 3101285 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Linehan, Mr. Michael \n male \n NA \n 0 \n 0 \n 330971 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 0 \n Ling, Mr. Lee \n male \n 28.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Lithman, Mr. Simon \n male \n NA \n 0 \n 0 \n S.O./P.P. 251 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Lobb, Mr. William Arthur \n male \n 30.0000 \n 1 \n 0 \n A/5. 3336 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n female \n 26.0000 \n 1 \n 0 \n A/5. 3336 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Lockyer, Mr. Edward \n male \n NA \n 0 \n 0 \n 1222 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n male \n 20.5000 \n 0 \n 0 \n A/5 21173 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 1 \n Lulic, Mr. Nikola \n male \n 27.0000 \n 0 \n 0 \n 315098 \n NA \n S \n \n \n cheap \n 7.0542 \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n male \n 51.0000 \n 0 \n 0 \n 347743 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Lundin, Miss. Olga Elida \n female \n 23.0000 \n 0 \n 0 \n 347469 \n NA \n S \n \n \n cheap \n 7.5792 \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n male \n 32.0000 \n 0 \n 0 \n 350403 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n male \n NA \n 0 \n 0 \n 349235 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n MacKay, Mr. George William \n male \n NA \n 0 \n 0 \n C.A. 42795 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n female \n NA \n 0 \n 0 \n 370370 \n NA \n Q \n \n \n cheap \n 7.1417 \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n male \n 24.0000 \n 0 \n 0 \n C 17369 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n male \n 22.0000 \n 0 \n 0 \n STON/O 2. 3101275 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n female \n NA \n 0 \n 0 \n 330924 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Mahon, Mr. John \n male \n NA \n 0 \n 0 \n AQ/4 3130 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Maisner, Mr. Simon \n male \n NA \n 0 \n 0 \n A/S 2816 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n male \n 29.0000 \n 0 \n 0 \n STON/O 2. 3101268 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Mamee, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2677 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Mangan, Miss. Mary \n female \n 30.5000 \n 0 \n 0 \n 364850 \n NA \n Q \n \n \n cheap \n 7.7375 \n 3 \n 1 \n Mannion, Miss. Margareth \n female \n NA \n 0 \n 0 \n 36866 \n NA \n Q \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2655 \n F E46 \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Markoff, Mr. Marin \n male \n 35.0000 \n 0 \n 0 \n 349213 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Markun, Mr. Johann \n male \n 33.0000 \n 0 \n 0 \n 349257 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Masselmani, Mrs. Fatima \n female \n NA \n 0 \n 0 \n 2649 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Matinoff, Mr. Nicola \n male \n NA \n 0 \n 0 \n 349255 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n female \n NA \n 0 \n 0 \n 383123 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n male \n NA \n 0 \n 0 \n 367228 \n NA \n Q \n \n \n cheap \n 23.2500 \n 3 \n 1 \n McCoy, Miss. Agnes \n female \n NA \n 2 \n 0 \n 367226 \n NA \n Q \n \n \n cheap \n 23.2500 \n 3 \n 1 \n McCoy, Miss. Alicia \n female \n NA \n 2 \n 0 \n 367226 \n NA \n Q \n \n \n cheap \n 23.2500 \n 3 \n 1 \n McCoy, Mr. Bernard \n male \n NA \n 2 \n 0 \n 367226 \n NA \n Q \n \n \n cheap \n 7.7875 \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n female \n NA \n 0 \n 0 \n 330932 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n McEvoy, Mr. Michael \n male \n NA \n 0 \n 0 \n 36568 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 1 \n McGovern, Miss. Mary \n female \n NA \n 0 \n 0 \n 330931 \n NA \n Q \n \n \n cheap \n 8.0292 \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n female \n 15.0000 \n 0 \n 0 \n 330923 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n McGowan, Miss. Katherine \n female \n 35.0000 \n 0 \n 0 \n 9232 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n McMahon, Mr. Martin \n male \n NA \n 0 \n 0 \n 370372 \n NA \n Q \n \n \n cheap \n 16.1000 \n 3 \n 0 \n McNamee, Mr. Neal \n male \n 24.0000 \n 1 \n 0 \n 376566 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n female \n 19.0000 \n 1 \n 0 \n 376566 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n McNeill, Miss. Bridget \n female \n NA \n 0 \n 0 \n 370368 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n female \n NA \n 0 \n 0 \n SOTON/O.Q. 392087 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n female \n NA \n 0 \n 0 \n 343095 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Meo, Mr. Alfonzo \n male \n 55.5000 \n 0 \n 0 \n A.5. 11206 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Mernagh, Mr. Robert \n male \n NA \n 0 \n 0 \n 368703 \n NA \n Q \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n male \n 21.0000 \n 0 \n 0 \n 345501 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Miles, Mr. Frank \n male \n NA \n 0 \n 0 \n 359306 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Mineff, Mr. Ivan \n male \n 24.0000 \n 0 \n 0 \n 349233 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Minkoff, Mr. Lazar \n male \n 21.0000 \n 0 \n 0 \n 349211 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n male \n 28.0000 \n 0 \n 0 \n 349207 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Mitkoff, Mr. Mito \n male \n NA \n 0 \n 0 \n 349221 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n female \n NA \n 0 \n 0 \n 330980 \n NA \n Q \n \n \n cheap \n 7.6500 \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n male \n 25.0000 \n 0 \n 0 \n 348123 \n F G73 \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Moor, Master. Meier \n male \n 6.0000 \n 0 \n 1 \n 392096 \n E121 \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Moor, Mrs. (Beila) \n female \n 27.0000 \n 0 \n 1 \n 392096 \n E121 \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Moore, Mr. Leonard Charles \n male \n NA \n 0 \n 0 \n A4. 54510 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 1 \n Moran, Miss. Bertha \n female \n NA \n 1 \n 0 \n 371110 \n NA \n Q \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Moran, Mr. Daniel J \n male \n NA \n 1 \n 0 \n 371110 \n NA \n Q \n \n \n cheap \n 8.4583 \n 3 \n 0 \n Moran, Mr. James \n male \n NA \n 0 \n 0 \n 330877 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Morley, Mr. William \n male \n 34.0000 \n 0 \n 0 \n 364506 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n male \n NA \n 0 \n 0 \n 372622 \n NA \n Q \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Moss, Mr. Albert Johan \n male \n NA \n 0 \n 0 \n 312991 \n NA \n S \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Moubarek, Master. Gerios \n male \n NA \n 1 \n 1 \n 2661 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n male \n NA \n 1 \n 1 \n 2661 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n female \n NA \n 0 \n 2 \n 2661 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n female \n NA \n 0 \n 0 \n 2626 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n male \n NA \n 0 \n 0 \n 374746 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n female \n NA \n 0 \n 0 \n 35852 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n female \n 24.0000 \n 0 \n 0 \n 382653 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Murdlin, Mr. Joseph \n male \n NA \n 0 \n 0 \n A./5. 3235 \n NA \n S \n \n \n cheap \n 15.5000 \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n female \n NA \n 1 \n 0 \n 367230 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n female \n NA \n 1 \n 0 \n 367230 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 1 \n Murphy, Miss. Nora \n female \n NA \n 0 \n 0 \n 36568 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n male \n 18.0000 \n 0 \n 0 \n 347078 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Naidenoff, Mr. Penko \n male \n 22.0000 \n 0 \n 0 \n 349206 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n female \n 15.0000 \n 0 \n 0 \n 2667 \n NA \n C \n \n \n cheap \n 15.7417 \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n female \n 1.0000 \n 0 \n 2 \n 2653 \n NA \n C \n \n \n cheap \n 15.7417 \n 3 \n 1 \n Nakid, Mr. Sahid \n male \n 20.0000 \n 1 \n 1 \n 2653 \n NA \n C \n \n \n cheap \n 15.7417 \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n female \n 19.0000 \n 1 \n 1 \n 2653 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Nancarrow, Mr. William Henry \n male \n 33.0000 \n 0 \n 0 \n A./5. 3338 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Nankoff, Mr. Minko \n male \n NA \n 0 \n 0 \n 349218 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Nasr, Mr. Mustafa \n male \n NA \n 0 \n 0 \n 2652 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Naughton, Miss. Hannah \n female \n NA \n 0 \n 0 \n 365237 \n NA \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Nenkoff, Mr. Christo \n male \n NA \n 0 \n 0 \n 349234 \n NA \n S \n \n \n cheap \n 11.2417 \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n male \n 12.0000 \n 1 \n 0 \n 2651 \n NA \n C \n \n \n cheap \n 11.2417 \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n female \n 14.0000 \n 1 \n 0 \n 2651 \n NA \n C \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n female \n 29.0000 \n 0 \n 0 \n 3101297 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Niklasson, Mr. Samuel \n male \n 28.0000 \n 0 \n 0 \n 363611 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n female \n 18.0000 \n 0 \n 0 \n 347066 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n female \n 26.0000 \n 0 \n 0 \n 347470 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n male \n 21.0000 \n 0 \n 0 \n 350410 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n male \n 41.0000 \n 0 \n 0 \n SOTON/O2 3101272 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Niskanen, Mr. Juha \n male \n 39.0000 \n 0 \n 0 \n STON/O 2. 3101289 \n NA \n S \n \n \n cheap \n 7.8000 \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n male \n 21.0000 \n 0 \n 0 \n A/4. 39886 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Novel, Mr. Mansouer \n male \n 28.5000 \n 0 \n 0 \n 2697 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n female \n 22.0000 \n 0 \n 0 \n 347081 \n NA \n S \n \n \n cheap \n 6.2375 \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n male \n 61.0000 \n 0 \n 0 \n 345364 \n NA \n S \n \n \n cheap \n 15.5000 \n 3 \n 0 \n O'Brien, Mr. Thomas \n male \n NA \n 1 \n 0 \n 370365 \n NA \n Q \n \n \n cheap \n 7.8292 \n 3 \n 0 \n O'Brien, Mr. Timothy \n male \n NA \n 0 \n 0 \n 330979 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n female \n NA \n 1 \n 0 \n 370365 \n NA \n Q \n \n \n cheap \n 7.7333 \n 3 \n 0 \n O'Connell, Mr. Patrick D \n male \n NA \n 0 \n 0 \n 334912 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n O'Connor, Mr. Maurice \n male \n NA \n 0 \n 0 \n 371060 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n O'Connor, Mr. Patrick \n male \n NA \n 0 \n 0 \n 366713 \n NA \n Q \n \n \n cheap \n 9.2250 \n 3 \n 0 \n Odahl, Mr. Nils Martin \n male \n 23.0000 \n 0 \n 0 \n 7267 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n female \n NA \n 0 \n 0 \n 364856 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n female \n NA \n 0 \n 0 \n 14311 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n female \n NA \n 0 \n 0 \n 330959 \n NA \n Q \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Ohman, Miss. Velin \n female \n 22.0000 \n 0 \n 0 \n 347085 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n O'Keefe, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368402 \n NA \n Q \n \n \n cheap \n 7.8292 \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n female \n NA \n 0 \n 0 \n 330919 \n NA \n Q \n \n \n cheap \n 3.1708 \n 3 \n 1 \n Olsen, Master. Artur Karl \n male \n 9.0000 \n 0 \n 1 \n C 17368 \n NA \n S \n \n \n cheap \n 22.5250 \n 3 \n 0 \n Olsen, Mr. Henry Margido \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n NA \n S \n \n \n cheap \n 8.4042 \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n male \n 42.0000 \n 0 \n 1 \n 4579 \n NA \n S \n \n \n cheap \n 7.3125 \n 3 \n 0 \n Olsen, Mr. Ole Martin \n male \n NA \n 0 \n 0 \n Fa 265302 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Olsson, Miss. Elina \n female \n 31.0000 \n 0 \n 0 \n 350407 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n male \n 28.0000 \n 0 \n 0 \n 347464 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n male \n 32.0000 \n 0 \n 0 \n 347079 \n NA \n S \n \n \n cheap \n 9.2250 \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n male \n 20.0000 \n 0 \n 0 \n 6563 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Oreskovic, Miss. Jelka \n female \n 23.0000 \n 0 \n 0 \n 315085 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Oreskovic, Miss. Marija \n female \n 20.0000 \n 0 \n 0 \n 315096 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Oreskovic, Mr. Luka \n male \n 20.0000 \n 0 \n 0 \n 315094 \n NA \n S \n \n \n cheap \n 9.2167 \n 3 \n 0 \n Osen, Mr. Olaf Elon \n male \n 16.0000 \n 0 \n 0 \n 7534 \n NA \n S \n \n \n cheap \n 8.6833 \n 3 \n 1 \n Osman, Mrs. Mara \n female \n 31.0000 \n 0 \n 0 \n 349244 \n NA \n S \n \n \n cheap \n 7.6292 \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n female \n NA \n 0 \n 0 \n 330909 \n NA \n Q \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n male \n 2.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Master. Paul Folke \n male \n 6.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Miss. Stina Viola \n female \n 3.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n female \n 8.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n female \n 29.0000 \n 0 \n 4 \n 349909 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Master. Eino Viljami \n male \n 1.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Master. Juha Niilo \n male \n 7.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Master. Urho Abraham \n male \n 2.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n male \n 16.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n male \n 14.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n female \n 41.0000 \n 0 \n 5 \n 3101295 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Pasic, Mr. Jakob \n male \n 21.0000 \n 0 \n 0 \n 315097 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Patchett, Mr. George \n male \n 19.0000 \n 0 \n 0 \n 358585 \n NA \n S \n \n \n cheap \n 8.7125 \n 3 \n 0 \n Paulner, Mr. Uscher \n male \n NA \n 0 \n 0 \n 3411 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Pavlovic, Mr. Stefo \n male \n 32.0000 \n 0 \n 0 \n 349242 \n NA \n S \n \n \n cheap \n 13.7750 \n 3 \n 0 \n Peacock, Master. Alfred Edward \n male \n 0.7500 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n NA \n S \n \n \n cheap \n 13.7750 \n 3 \n 0 \n Peacock, Miss. Treasteall \n female \n 3.0000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n NA \n S \n \n \n cheap \n 13.7750 \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n female \n 26.0000 \n 0 \n 2 \n SOTON/O.Q. 3101315 \n NA \n S \n \n \n cheap \n 7.0000 \n 3 \n 0 \n Pearce, Mr. Ernest \n male \n NA \n 0 \n 0 \n 343271 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Pedersen, Mr. Olaf \n male \n NA \n 0 \n 0 \n 345498 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Peduzzi, Mr. Joseph \n male \n NA \n 0 \n 0 \n A/5 2817 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101294 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n male \n 25.0000 \n 0 \n 0 \n STON/O 2. 3101291 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Perkin, Mr. John Henry \n male \n 22.0000 \n 0 \n 0 \n A/5 21174 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n male \n 25.0000 \n 1 \n 0 \n 347083 \n NA \n S \n \n \n cheap \n 22.3583 \n 3 \n 1 \n Peter, Master. Michael J \n male \n NA \n 1 \n 1 \n 2668 \n NA \n C \n \n \n cheap \n 22.3583 \n 3 \n 1 \n Peter, Miss. Anna \n female \n NA \n 1 \n 1 \n 2668 \n F E69 \n C \n \n \n cheap \n 22.3583 \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n female \n NA \n 0 \n 2 \n 2668 \n NA \n C \n \n \n cheap \n 8.1375 \n 3 \n 0 \n Peters, Miss. Katie \n female \n NA \n 0 \n 0 \n 330935 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Petersen, Mr. Marius \n male \n 24.0000 \n 0 \n 0 \n 342441 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Petranec, Miss. Matilda \n female \n 28.0000 \n 0 \n 0 \n 349245 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Petroff, Mr. Nedelio \n male \n 19.0000 \n 0 \n 0 \n 349212 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n male \n NA \n 0 \n 0 \n 349215 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Petterson, Mr. Johan Emil \n male \n 25.0000 \n 1 \n 0 \n 347076 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n female \n 18.0000 \n 0 \n 0 \n 347087 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n male \n 32.0000 \n 0 \n 0 \n SOTON/O.Q. 392078 \n E10 \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n male \n NA \n 0 \n 0 \n 349227 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Pokrnic, Mr. Mate \n male \n 17.0000 \n 0 \n 0 \n 315095 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Pokrnic, Mr. Tome \n male \n 24.0000 \n 0 \n 0 \n 315092 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Radeff, Mr. Alexander \n male \n NA \n 0 \n 0 \n 349223 \n NA \n S \n \n \n cheap \n 8.1125 \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n female \n NA \n 0 \n 0 \n 65305 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Razi, Mr. Raihed \n male \n NA \n 0 \n 0 \n 2629 \n NA \n C \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Reed, Mr. James George \n male \n NA \n 0 \n 0 \n 362316 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Rekic, Mr. Tido \n male \n 38.0000 \n 0 \n 0 \n 349249 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Reynolds, Mr. Harold J \n male \n 21.0000 \n 0 \n 0 \n 342684 \n NA \n S \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Albert \n male \n 10.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Arthur \n male \n 4.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Eric \n male \n 7.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Eugene \n male \n 2.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. George Hugh \n male \n 8.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n female \n 39.0000 \n 0 \n 5 \n 382652 \n NA \n Q \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n female \n 22.0000 \n 0 \n 0 \n 3101295 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Rintamaki, Mr. Matti \n male \n 35.0000 \n 0 \n 0 \n STON/O 2. 3101273 \n NA \n S \n \n \n cheap \n 7.7208 \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n female \n NA \n 0 \n 0 \n 334915 \n NA \n Q \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Risien, Mr. Samuel Beard \n male \n NA \n 0 \n 0 \n 364498 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n female \n NA \n 0 \n 0 \n 364498 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Robins, Mr. Alexander A \n male \n 50.0000 \n 1 \n 0 \n A/5. 3337 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n female \n 47.0000 \n 1 \n 0 \n A/5. 3337 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Rogers, Mr. William John \n male \n NA \n 0 \n 0 \n S.C./A.4. 23567 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n male \n NA \n 0 \n 0 \n 312993 \n NA \n S \n \n \n cheap \n 20.2125 \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n female \n 2.0000 \n 1 \n 1 \n 370129 \n NA \n S \n \n \n cheap \n 20.2125 \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n male \n 18.0000 \n 1 \n 1 \n 370129 \n NA \n S \n \n \n cheap \n 20.2125 \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n female \n 41.0000 \n 0 \n 2 \n 370129 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Roth, Miss. Sarah A \n female \n NA \n 0 \n 0 \n 342712 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Rouse, Mr. Richard Henry \n male \n 50.0000 \n 0 \n 0 \n A/5 3594 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Rush, Mr. Alfred George John \n male \n 16.0000 \n 0 \n 0 \n A/4. 20589 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Ryan, Mr. Edward \n male \n NA \n 0 \n 0 \n 383162 \n NA \n Q \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Ryan, Mr. Patrick \n male \n NA \n 0 \n 0 \n 371110 \n NA \n Q \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Saad, Mr. Amin \n male \n NA \n 0 \n 0 \n 2671 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Saad, Mr. Khalil \n male \n 25.0000 \n 0 \n 0 \n 2672 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Saade, Mr. Jean Nassr \n male \n NA \n 0 \n 0 \n 2676 \n NA \n C \n \n \n cheap \n 7.7292 \n 3 \n 0 \n Sadlier, Mr. Matthew \n male \n NA \n 0 \n 0 \n 367655 \n NA \n Q \n \n \n cheap \n 7.5750 \n 3 \n 0 \n Sadowitz, Mr. Harry \n male \n NA \n 0 \n 0 \n LP 1588 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n male \n 38.5000 \n 0 \n 0 \n SOTON/O.Q. 3101262 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Master. Thomas Henry \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Master. William Henry \n male \n 14.5000 \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Ada \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Constance Gladys \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Stella Anna \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. Frederick \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. George John Jr \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. John George \n male \n NA \n 1 \n 9 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n female \n NA \n 1 \n 9 \n CA. 2343 \n NA \n S \n \n \n cheap \n 9.3250 \n 3 \n 0 \n Salander, Mr. Karl Johan \n male \n 24.0000 \n 0 \n 0 \n 7266 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n female \n 21.0000 \n 0 \n 0 \n 343120 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Salonen, Mr. Johan Werner \n male \n 39.0000 \n 0 \n 0 \n 3101296 \n NA \n S \n \n \n cheap \n 21.6792 \n 3 \n 0 \n Samaan, Mr. Elias \n male \n NA \n 2 \n 0 \n 2662 \n NA \n C \n \n \n cheap \n 21.6792 \n 3 \n 0 \n Samaan, Mr. Hanna \n male \n NA \n 2 \n 0 \n 2662 \n NA \n C \n \n \n cheap \n 21.6792 \n 3 \n 0 \n Samaan, Mr. Youssef \n male \n NA \n 2 \n 0 \n 2662 \n NA \n C \n \n \n cheap \n 16.7000 \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n female \n 1.0000 \n 1 \n 1 \n PP 9549 \n G6 \n S \n \n \n cheap \n 16.7000 \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n female \n 24.0000 \n 0 \n 2 \n PP 9549 \n G6 \n S \n \n \n cheap \n 16.7000 \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n female \n 4.0000 \n 1 \n 1 \n PP 9549 \n G6 \n S \n \n \n cheap \n 9.5000 \n 3 \n 1 \n Sap, Mr. Julius \n male \n 25.0000 \n 0 \n 0 \n 345768 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Saundercock, Mr. William Henry \n male \n 20.0000 \n 0 \n 0 \n A/5. 2151 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n male \n 24.5000 \n 0 \n 0 \n 342826 \n NA \n S \n \n \n cheap \n 7.7250 \n 3 \n 0 \n Scanlan, Mr. James \n male \n NA \n 0 \n 0 \n 36209 \n NA \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Sdycoff, Mr. Todor \n male \n NA \n 0 \n 0 \n 349222 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n male \n NA \n 0 \n 0 \n 370374 \n NA \n Q \n \n \n cheap \n 9.5000 \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n male \n 29.0000 \n 0 \n 0 \n 345779 \n NA \n S \n \n \n cheap \n 15.1000 \n 3 \n 0 \n Shellard, Mr. Frederick William \n male \n NA \n 0 \n 0 \n C.A. 6212 \n NA \n S \n \n \n cheap \n 7.7792 \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n female \n NA \n 0 \n 0 \n 330968 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n male \n NA \n 0 \n 0 \n 374910 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Simmons, Mr. John \n male \n NA \n 0 \n 0 \n SOTON/OQ 392082 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Sirayanian, Mr. Orsen \n male \n 22.0000 \n 0 \n 0 \n 2669 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Sirota, Mr. Maurice \n male \n NA \n 0 \n 0 \n 392092 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Sivic, Mr. Husein \n male \n 40.0000 \n 0 \n 0 \n 349251 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101280 \n NA \n S \n \n \n cheap \n 7.4958 \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 3101265 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Master. Harald \n male \n 4.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n male \n 10.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Miss. Mabel \n female \n 9.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n female \n 2.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Mr. Wilhelm \n male \n 40.0000 \n 1 \n 4 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n female \n 45.0000 \n 1 \n 4 \n 347088 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Slabenoff, Mr. Petco \n male \n NA \n 0 \n 0 \n 349214 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n male \n NA \n 0 \n 0 \n SOTON/OQ 392086 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Smiljanic, Mr. Mile \n male \n NA \n 0 \n 0 \n 315037 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Smith, Mr. Thomas \n male \n NA \n 0 \n 0 \n 384461 \n NA \n Q \n \n \n cheap \n 7.7333 \n 3 \n 1 \n Smyth, Miss. Julia \n female \n NA \n 0 \n 0 \n 335432 \n NA \n Q \n \n \n cheap \n 7.6500 \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n male \n 19.0000 \n 0 \n 0 \n 348124 \n F G73 \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Somerton, Mr. Francis William \n male \n 30.0000 \n 0 \n 0 \n A.5. 18509 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Spector, Mr. Woolf \n male \n NA \n 0 \n 0 \n A.5. 3236 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Spinner, Mr. Henry John \n male \n 32.0000 \n 0 \n 0 \n STON/OQ. 369943 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Staneff, Mr. Ivan \n male \n NA \n 0 \n 0 \n 349208 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Stankovic, Mr. Ivan \n male \n 33.0000 \n 0 \n 0 \n 349239 \n NA \n C \n \n \n cheap \n 7.5500 \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n female \n 23.0000 \n 0 \n 0 \n CA. 2314 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Stanley, Mr. Edward Roland \n male \n 21.0000 \n 0 \n 0 \n A/4 45380 \n NA \n S \n \n \n unknown \n NA \n 3 \n 0 \n Storey, Mr. Thomas \n male \n 60.5000 \n 0 \n 0 \n 3701 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n male \n 19.0000 \n 0 \n 0 \n 349205 \n NA \n S \n \n \n cheap \n 9.8375 \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n female \n 22.0000 \n 0 \n 0 \n 7553 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Stranden, Mr. Juho \n male \n 31.0000 \n 0 \n 0 \n STON/O 2. 3101288 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Strilic, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 315083 \n NA \n S \n \n \n cheap \n 10.4625 \n 3 \n 0 \n Strom, Miss. Telma Matilda \n female \n 2.0000 \n 0 \n 1 \n 347054 \n G6 \n S \n \n \n cheap \n 10.4625 \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n female \n 29.0000 \n 1 \n 1 \n 347054 \n G6 \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n male \n 16.0000 \n 0 \n 0 \n SOTON/OQ 392089 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Sundman, Mr. Johan Julian \n male \n 44.0000 \n 0 \n 0 \n STON/O 2. 3101269 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n male \n 25.0000 \n 0 \n 0 \n SOTON/OQ 392076 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Svensson, Mr. Johan \n male \n 74.0000 \n 0 \n 0 \n 347060 \n NA \n S \n \n \n cheap \n 9.2250 \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n male \n 14.0000 \n 0 \n 0 \n 7538 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Svensson, Mr. Olof \n male \n 24.0000 \n 0 \n 0 \n 350035 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n male \n 25.0000 \n 0 \n 0 \n 350033 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n male \n 34.0000 \n 0 \n 0 \n 363294 \n NA \n S \n \n \n cheap \n 8.5167 \n 3 \n 1 \n Thomas, Master. Assad Alexander \n male \n 0.4167 \n 0 \n 1 \n 2625 \n NA \n C \n \n \n cheap \n 6.4375 \n 3 \n 0 \n Thomas, Mr. Charles P \n male \n NA \n 1 \n 0 \n 2621 \n NA \n C \n \n \n cheap \n 6.4375 \n 3 \n 0 \n Thomas, Mr. John \n male \n NA \n 0 \n 0 \n 2681 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Thomas, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2684 \n NA \n C \n \n \n cheap \n 8.5167 \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n female \n 16.0000 \n 1 \n 1 \n 2625 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n male \n NA \n 0 \n 0 \n 32302 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Thorneycroft, Mr. Percival \n male \n NA \n 1 \n 0 \n 376564 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n female \n NA \n 1 \n 0 \n 376564 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Tikkanen, Mr. Juho \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101293 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Tobin, Mr. Roger \n male \n NA \n 0 \n 0 \n 383121 \n F38 \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Todoroff, Mr. Lalio \n male \n NA \n 0 \n 0 \n 349216 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n male \n 30.5000 \n 0 \n 0 \n 364499 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Torber, Mr. Ernst William \n male \n 44.0000 \n 0 \n 0 \n 364511 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Torfa, Mr. Assad \n male \n NA \n 0 \n 0 \n 2673 \n NA \n C \n \n \n cheap \n 0.0000 \n 3 \n 1 \n Tornquist, Mr. William Henry \n male \n 25.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Toufik, Mr. Nakli \n male \n NA \n 0 \n 0 \n 2641 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Touma, Master. Georges Youssef \n male \n 7.0000 \n 1 \n 1 \n 2650 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Touma, Miss. Maria Youssef \n female \n 9.0000 \n 1 \n 1 \n 2650 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n female \n 29.0000 \n 0 \n 2 \n 2650 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Turcin, Mr. Stjepan \n male \n 36.0000 \n 0 \n 0 \n 349247 \n NA \n S \n \n \n cheap \n 9.8417 \n 3 \n 1 \n Turja, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 4138 \n NA \n S \n \n \n cheap \n 9.5875 \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n female \n 63.0000 \n 0 \n 0 \n 4134 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n van Billiard, Master. James William \n male \n NA \n 1 \n 1 \n A/5. 851 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n van Billiard, Master. Walter John \n male \n 11.5000 \n 1 \n 1 \n A/5. 851 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n male \n 40.5000 \n 0 \n 2 \n A/5. 851 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Van Impe, Miss. Catharina \n female \n 10.0000 \n 0 \n 2 \n 345773 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n male \n 36.0000 \n 1 \n 1 \n 345773 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n female \n 30.0000 \n 1 \n 1 \n 345773 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n male \n NA \n 0 \n 0 \n 345777 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n male \n 33.0000 \n 0 \n 0 \n 345780 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n male \n 28.0000 \n 0 \n 0 \n 345770 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n male \n 28.0000 \n 0 \n 0 \n 345783 \n NA \n S \n \n \n cheap \n 9.0000 \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n male \n 47.0000 \n 0 \n 0 \n 345765 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n female \n 18.0000 \n 2 \n 0 \n 345764 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Mr. Julius \n male \n 31.0000 \n 3 \n 0 \n 345763 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n male \n 16.0000 \n 2 \n 0 \n 345764 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n female \n 31.0000 \n 1 \n 0 \n 345763 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Vartanian, Mr. David \n male \n 22.0000 \n 0 \n 0 \n 2658 \n NA \n C \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n male \n 20.0000 \n 0 \n 0 \n 350416 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n female \n 14.0000 \n 0 \n 0 \n 350406 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Vovk, Mr. Janko \n male \n 22.0000 \n 0 \n 0 \n 349252 \n NA \n S \n \n \n cheap \n 9.0000 \n 3 \n 0 \n Waelens, Mr. Achille \n male \n 22.0000 \n 0 \n 0 \n 345767 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Ware, Mr. Frederick \n male \n NA \n 0 \n 0 \n 359309 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Warren, Mr. Charles William \n male \n NA \n 0 \n 0 \n C.A. 49867 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Webber, Mr. James \n male \n NA \n 0 \n 0 \n SOTON/OQ 3101316 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Wenzel, Mr. Linhart \n male \n 32.5000 \n 0 \n 0 \n 345775 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n female \n 38.0000 \n 0 \n 0 \n 2688 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n male \n 51.0000 \n 0 \n 0 \n 347064 \n NA \n S \n \n \n cheap \n 6.4958 \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n male \n 18.0000 \n 1 \n 0 \n 3101267 \n NA \n S \n \n \n cheap \n 6.4958 \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n male \n 21.0000 \n 1 \n 0 \n 3101266 \n NA \n S \n \n \n cheap \n 7.0000 \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n female \n 47.0000 \n 1 \n 0 \n 363272 \n NA \n S \n \n \n cheap \n 8.7125 \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n male \n NA \n 0 \n 0 \n 3410 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Willey, Mr. Edward \n male \n NA \n 0 \n 0 \n S.O./P.P. 751 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n male \n NA \n 0 \n 0 \n A/5 2466 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Williams, Mr. Leslie \n male \n 28.5000 \n 0 \n 0 \n 54636 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Windelov, Mr. Einar \n male \n 21.0000 \n 0 \n 0 \n SOTON/OQ 3101317 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Wirz, Mr. Albert \n male \n 27.0000 \n 0 \n 0 \n 315154 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Wiseman, Mr. Phillippe \n male \n NA \n 0 \n 0 \n A/4. 34244 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Wittevrongel, Mr. Camille \n male \n 36.0000 \n 0 \n 0 \n 345771 \n NA \n S \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Yasbeck, Mr. Antoni \n male \n 27.0000 \n 1 \n 0 \n 2659 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n female \n 15.0000 \n 1 \n 0 \n 2659 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Youseff, Mr. Gerious \n male \n 45.5000 \n 0 \n 0 \n 2628 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Yousif, Mr. Wazli \n male \n NA \n 0 \n 0 \n 2647 \n NA \n C \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Yousseff, Mr. Gerious \n male \n NA \n 0 \n 0 \n 2627 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Zabour, Miss. Hileni \n female \n 14.5000 \n 1 \n 0 \n 2665 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Zabour, Miss. Thamine \n female \n NA \n 1 \n 0 \n 2665 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n male \n 26.5000 \n 0 \n 0 \n 2656 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Zakarian, Mr. Ortin \n male \n 27.0000 \n 0 \n 0 \n 2670 \n NA \n C \n \n \n\n cheap \n 7.8750 \n 3 \n 0 \n Zimmerman, Mr. Leo \n male \n 29.0000 \n 0 \n 0 \n 315082 \n NA \n S \n \n \n
\n \n \n\n sex_of_passenger \n age_of_passenger \n imputed_age_of_passenger \n pclass \n survived \n name_of_passenger \n sibsp \n parch \n ticket \n fare \n cabin \n embarked \n \n \n female \n 29.0000 \n 29.00000 \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n 0 \n 0 \n 24160 \n 211.3375 \n B5 \n S \n \n \n male \n 0.9167 \n 0.91670 \n 1 \n 1 \n Allison, Master. Hudson Trevor \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n female \n 2.0000 \n 2.00000 \n 1 \n 0 \n Allison, Miss. Helen Loraine \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n female \n 25.0000 \n 25.00000 \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 1 \n Anderson, Mr. Harry \n 0 \n 0 \n 19952 \n 26.5500 \n E12 \n S \n \n \n female \n 63.0000 \n 63.00000 \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n 1 \n 0 \n 13502 \n 77.9583 \n D7 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n 0 \n 0 \n 112050 \n 0.0000 \n A36 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n 0 \n 0 \n PC 17609 \n 49.5042 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Astor, Col. John Jacob \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n 0 \n 0 \n 19877 \n 78.8500 \n NA \n S \n \n \n male \n 80.0000 \n 80.00000 \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n 0 \n 0 \n 27042 \n 30.0000 \n A23 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Baumann, Mr. John D \n 0 \n 0 \n PC 17318 \n 25.9250 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n female \n 50.0000 \n 50.00000 \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n female \n 32.0000 \n 32.00000 \n 1 \n 1 \n Bazzani, Miss. Albina \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n Beattie, Mr. Thomson \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n female \n 47.0000 \n 47.00000 \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n male \n 26.0000 \n 26.00000 \n 1 \n 1 \n Behr, Mr. Karl Howell \n 0 \n 0 \n 111369 \n 30.0000 \n C148 \n C \n \n \n female \n 42.0000 \n 42.00000 \n 1 \n 1 \n Bidois, Miss. Rosalie \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n female \n 29.0000 \n 29.00000 \n 1 \n 1 \n Bird, Miss. Ellen \n 0 \n 0 \n PC 17483 \n 221.7792 \n C97 \n S \n \n \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n Birnbaum, Mr. Jakob \n 0 \n 0 \n 13905 \n 26.0000 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 1 \n 1 \n Bishop, Mr. Dickinson H \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Bissette, Miss. Amelia \n 0 \n 0 \n PC 17760 \n 135.6333 \n C99 \n S \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n 0 \n 0 \n 110564 \n 26.5500 \n C52 \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n 0 \n 0 \n 113784 \n 35.5000 \n T \n S \n \n \n male \n 40.0000 \n 40.00000 \n 1 \n 1 \n Blank, Mr. Henry \n 0 \n 0 \n 112277 \n 31.0000 \n A31 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Bonnell, Miss. Caroline \n 0 \n 0 \n 36928 \n 164.8667 \n C7 \n S \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n 0 \n 0 \n 113783 \n 26.5500 \n C103 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Borebank, Mr. John James \n 0 \n 0 \n 110489 \n 26.5500 \n D22 \n S \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Bowen, Miss. Grace Scott \n 0 \n 0 \n PC 17608 \n 262.3750 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n 0 \n 0 \n 111427 \n 26.5500 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 1 \n 0 \n Brady, Mr. John Bertram \n 0 \n 0 \n 113054 \n 30.5000 \n A21 \n S \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 0 \n Brandeis, Mr. Emil \n 0 \n 0 \n PC 17591 \n 50.4958 \n B10 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n 0 \n 0 \n 112379 \n 39.6000 \n NA \n C \n \n \n female \n 44.0000 \n 44.00000 \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n 0 \n 0 \n PC 17610 \n 27.7208 \n B4 \n C \n \n \n female \n 59.0000 \n 59.00000 \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n female \n 60.0000 \n 60.00000 \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n female \n 41.0000 \n 41.00000 \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n 0 \n 0 \n 16966 \n 134.5000 \n E40 \n C \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n Butt, Major. Archibald Willingham \n 0 \n 0 \n 113050 \n 26.5500 \n B38 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Cairns, Mr. Alexander \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n 0 \n 0 \n PC 17476 \n 26.2875 \n E24 \n S \n \n \n female \n 53.0000 \n 53.00000 \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n 0 \n 0 \n PC 17606 \n 27.4458 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n male \n 33.0000 \n 33.00000 \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n 0 \n 0 \n 695 \n 5.0000 \n B51 B53 B55 \n S \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n Carrau, Mr. Francisco M \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n male \n 11.0000 \n 11.00000 \n 1 \n 1 \n Carter, Master. William Thornton II \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n female \n 14.0000 \n 14.00000 \n 1 \n 1 \n Carter, Miss. Lucile Polk \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n Carter, Mr. William Ernest \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n Case, Mr. Howard Brown \n 0 \n 0 \n 19924 \n 26.0000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n 0 \n 0 \n 17770 \n 27.7208 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n female \n 76.0000 \n 76.00000 \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n female \n 47.0000 \n 47.00000 \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Chaudanson, Miss. Victorine \n 0 \n 0 \n PC 17608 \n 262.3750 \n B61 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Cherry, Miss. Gladys \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n 0 \n 0 \n PC 17594 \n 29.7000 \n A9 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n 0 \n 0 \n 112051 \n 0.0000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n Clark, Mr. Walter Miller \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Cleaver, Miss. Alice \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Clifford, Mr. George Quincy \n 0 \n 0 \n 110465 \n 52.0000 \n A14 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n 0 \n 0 \n 5727 \n 25.5875 \n E58 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n 1 \n 1 \n PC 17756 \n 83.1583 \n E49 \n C \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n 1 \n 1 \n PC 17756 \n 83.1583 \n E52 \n C \n \n \n female \n 64.0000 \n 64.00000 \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n 0 \n 2 \n PC 17756 \n 83.1583 \n E45 \n C \n \n \n female \n 55.0000 \n 55.00000 \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n 2 \n 0 \n 11770 \n 25.7000 \n C101 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Crafton, Mr. John Bertram \n 0 \n 0 \n 113791 \n 26.5500 \n NA \n S \n \n \n male \n 70.0000 \n 70.00000 \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n 1 \n 1 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Crosby, Miss. Harriet R \n 0 \n 2 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n female \n 64.0000 \n 64.00000 \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n 1 \n 1 \n 112901 \n 26.5500 \n B26 \n S \n \n \n male \n 39.0000 \n 39.00000 \n 1 \n 0 \n Cumings, Mr. John Bradley \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n female \n 38.0000 \n 38.00000 \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n male \n 51.0000 \n 51.00000 \n 1 \n 1 \n Daly, Mr. Peter Denis \n 0 \n 0 \n 113055 \n 26.5500 \n E17 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 1 \n Daniel, Mr. Robert Williams \n 0 \n 0 \n 113804 \n 30.5000 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Daniels, Miss. Sarah \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n Davidson, Mr. Thornton \n 1 \n 0 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n female \n 27.0000 \n 27.00000 \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n 1 \n 2 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n Dick, Mr. Albert Adrian \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n female \n 17.0000 \n 17.00000 \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n male \n 53.0000 \n 53.00000 \n 1 \n 1 \n Dodge, Dr. Washington \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n male \n 4.0000 \n 4.00000 \n 1 \n 1 \n Dodge, Master. Washington \n 0 \n 2 \n 33638 \n 81.8583 \n A34 \n S \n \n \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Douglas, Mr. Walter Donald \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n female \n 27.0000 \n 27.00000 \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n 1 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n 1 \n 0 \n 11755 \n 39.6000 \n A16 \n C \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n 1 \n 0 \n PC 17485 \n 56.9292 \n A20 \n C \n \n \n male \n 39.0000 \n 39.00000 \n 1 \n 0 \n Dulles, Mr. William Crothers \n 0 \n 0 \n PC 17580 \n 29.7000 \n A18 \n C \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n 0 \n 1 \n 11767 \n 83.1583 \n C54 \n C \n \n \n female \n 38.0000 \n 38.00000 \n 1 \n 1 \n Endres, Miss. Caroline Louise \n 0 \n 0 \n PC 17757 \n 227.5250 \n C45 \n C \n \n \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 0 \n Evans, Miss. Edith Corse \n 0 \n 0 \n PC 17531 \n 31.6792 \n A29 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Farthing, Mr. John \n 0 \n 0 \n PC 17483 \n 221.7792 \n C95 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n 0 \n 0 \n PC 17598 \n 31.6833 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Fleming, Miss. Margaret \n 0 \n 0 \n 17421 \n 110.8833 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n 0 \n 0 \n PC 17474 \n 26.3875 \n E25 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n 0 \n 0 \n 113051 \n 27.7500 \n C111 \n C \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 28.0000 \n 28.00000 \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n male \n 19.0000 \n 19.00000 \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n Fortune, Mr. Mark \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 60.0000 \n 60.00000 \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n 0 \n 0 \n PC 17485 \n 56.9292 \n E36 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n 0 \n 0 \n 113778 \n 26.5500 \n D34 \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 1 \n Frauenthal, Dr. Henry William \n 2 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n 1 \n 0 \n 17765 \n 27.7208 \n D40 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n 1 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n 0 \n 2 \n 13568 \n 49.5000 \n B39 \n C \n \n \n male \n 60.0000 \n 60.00000 \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Fry, Mr. Richard \n 0 \n 0 \n 112058 \n 0.0000 \n B102 \n S \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Gee, Mr. Arthur H \n 0 \n 0 \n 111320 \n 38.5000 \n E63 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Geiger, Miss. Amalie \n 0 \n 0 \n 113503 \n 211.5000 \n C130 \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n Giglio, Mr. Victor \n 0 \n 0 \n PC 17593 \n 79.2000 \n B86 \n C \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n male \n 71.0000 \n 71.00000 \n 1 \n 0 \n Goldschmidt, Mr. George B \n 0 \n 0 \n PC 17754 \n 34.6542 \n A5 \n C \n \n \n male \n 53.0000 \n 53.00000 \n 1 \n 1 \n Gracie, Col. Archibald IV \n 0 \n 0 \n 113780 \n 28.5000 \n C51 \n C \n \n \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n Graham, Miss. Margaret Edith \n 0 \n 0 \n 112053 \n 30.0000 \n B42 \n S \n \n \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n Graham, Mr. George Edward \n 0 \n 1 \n PC 17582 \n 153.4625 \n C91 \n S \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n 0 \n 1 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n male \n 23.0000 \n 23.00000 \n 1 \n 1 \n Greenfield, Mr. William Bertram \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n 0 \n 0 \n PC 17593 \n 79.2000 \n B82 B84 \n C \n \n \n male \n 25.0000 \n 25.00000 \n 1 \n 1 \n Harder, Mr. George Achilles \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n female \n 25.0000 \n 25.00000 \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n female \n 49.0000 \n 49.00000 \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Harrington, Mr. Charles H \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n male \n 40.0000 \n 40.00000 \n 1 \n 0 \n Harrison, Mr. William \n 0 \n 0 \n 112059 \n 0.0000 \n B94 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 1 \n Hassab, Mr. Hammad \n 0 \n 0 \n PC 17572 \n 76.7292 \n D49 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Hawksford, Mr. Walter James \n 0 \n 0 \n 16988 \n 30.0000 \n D45 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n 0 \n 0 \n 11767 \n 83.1583 \n C54 \n C \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Hays, Mr. Charles Melville \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n female \n 52.0000 \n 52.00000 \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Head, Mr. Christopher \n 0 \n 0 \n 113038 \n 42.5000 \n B11 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Hipkins, Mr. William Edward \n 0 \n 0 \n 680 \n 50.0000 \n C39 \n S \n \n \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n female \n 44.0000 \n 44.00000 \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n female \n 51.0000 \n 51.00000 \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n 1 \n 0 \n 13502 \n 77.9583 \n D11 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n 0 \n 0 \n 111426 \n 26.5500 \n NA \n C \n \n \n male \n 38.0000 \n 38.00000 \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Hoyt, Mr. William Fisher \n 0 \n 0 \n PC 17600 \n 30.6958 \n NA \n C \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n female \n 38.0000 \n 38.00000 \n 1 \n 1 \n Icard, Miss. Amelie \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n female \n 50.0000 \n 50.00000 \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n 0 \n 0 \n PC 17595 \n 28.7125 \n C49 \n C \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n 0 \n 0 \n 112058 \n 0.0000 \n B52 B54 B56 \n S \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Jones, Mr. Charles Cresson \n 0 \n 0 \n 694 \n 26.0000 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Julian, Mr. Henry Forbes \n 0 \n 0 \n 113044 \n 26.0000 \n E60 \n S \n \n \n male \n 32.5000 \n 32.50000 \n 1 \n 0 \n Keeping, Mr. Edwin \n 0 \n 0 \n 113503 \n 211.5000 \n C132 \n C \n \n \n male \n 58.0000 \n 58.00000 \n 1 \n 0 \n Kent, Mr. Edward Austin \n 0 \n 0 \n 11771 \n 29.7000 \n B37 \n C \n \n \n male \n 41.0000 \n 41.00000 \n 1 \n 0 \n Kenyon, Mr. Frederick R \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Klaber, Mr. Herman \n 0 \n 0 \n 113028 \n 26.5500 \n C124 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Kreuchen, Miss. Emilie \n 0 \n 0 \n 24160 \n 211.3375 \n NA \n S \n \n \n female \n 49.0000 \n 49.00000 \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n 0 \n 0 \n 17465 \n 25.9292 \n D17 \n S \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n LeRoy, Miss. Bertha \n 0 \n 0 \n PC 17761 \n 106.4250 \n NA \n C \n \n \n male \n 35.0000 \n 35.00000 \n 1 \n 1 \n Lesurer, Mr. Gustave J \n 0 \n 0 \n PC 17755 \n 512.3292 \n B101 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Lewy, Mr. Ervin G \n 0 \n 0 \n PC 17612 \n 27.7208 \n NA \n C \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n 0 \n 0 \n 17475 \n 26.5500 \n NA \n S \n \n \n female \n 55.0000 \n 55.00000 \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n 0 \n 0 \n 112377 \n 27.7208 \n NA \n C \n \n \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n Lines, Miss. Mary Conover \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n female \n 51.0000 \n 51.00000 \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n Long, Mr. Milton Clyde \n 0 \n 0 \n 113501 \n 30.0000 \n D6 \n S \n \n \n female \n 21.0000 \n 21.00000 \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n 0 \n 0 \n 13502 \n 77.9583 \n D9 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Loring, Mr. Joseph Holland \n 0 \n 0 \n 113801 \n 45.5000 \n NA \n S \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Lurette, Miss. Elise \n 0 \n 0 \n PC 17569 \n 146.5208 \n B80 \n C \n \n \n female \n 15.0000 \n 15.00000 \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n 0 \n 1 \n 24160 \n 211.3375 \n B5 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Maguire, Mr. John Edward \n 0 \n 0 \n 110469 \n 26.0000 \n C106 \n S \n \n \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n Maioni, Miss. Roberta \n 0 \n 0 \n 110152 \n 86.5000 \n B79 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Marechal, Mr. Pierre \n 0 \n 0 \n 11774 \n 29.7000 \n C47 \n C \n \n \n male \n 19.0000 \n 19.00000 \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n 0 \n 0 \n PC 17482 \n 49.5042 \n C90 \n C \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n McCarthy, Mr. Timothy J \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n McGough, Mr. James Robert \n 0 \n 0 \n PC 17473 \n 26.2875 \n E25 \n S \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n male \n 65.0000 \n 65.00000 \n 1 \n 0 \n Millet, Mr. Francis Davis \n 0 \n 0 \n 13509 \n 26.5500 \n E38 \n S \n \n \n male \n 44.0000 \n 44.00000 \n 1 \n 0 \n Minahan, Dr. William Edward \n 2 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Minahan, Miss. Daisy E \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n female \n 37.0000 \n 37.00000 \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n 1 \n 0 \n 13236 \n 57.7500 \n C78 \n C \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Molson, Mr. Harry Markland \n 0 \n 0 \n 113787 \n 30.5000 \n C30 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n Natsch, Mr. Charles H \n 0 \n 1 \n PC 17596 \n 29.7000 \n C118 \n C \n \n \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n Newell, Miss. Madeleine \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Newell, Miss. Marjorie \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n male \n 58.0000 \n 58.00000 \n 1 \n 0 \n Newell, Mr. Arthur Webster \n 0 \n 2 \n 35273 \n 113.2750 \n D48 \n C \n \n \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n 0 \n 2 \n 11752 \n 26.2833 \n D47 \n S \n \n \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n 0 \n 0 \n 693 \n 26.0000 \n NA \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n 0 \n 0 \n PC 17758 \n 108.9000 \n C105 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n 0 \n 0 \n F.C. 12998 \n 25.7417 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n 0 \n 1 \n 113509 \n 61.9792 \n B36 \n C \n \n \n male \n 65.0000 \n 65.00000 \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n 0 \n 1 \n 113509 \n 61.9792 \n B30 \n C \n \n \n male \n 28.5000 \n 28.50000 \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n 0 \n 0 \n PC 17562 \n 27.7208 \n D43 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n 0 \n 0 \n 112052 \n 0.0000 \n NA \n S \n \n \n male \n 45.5000 \n 45.50000 \n 1 \n 0 \n Partner, Mr. Austen \n 0 \n 0 \n 113043 \n 28.5000 \n C124 \n S \n \n \n male \n 23.0000 \n 23.00000 \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n 0 \n 0 \n 12749 \n 93.5000 \n B24 \n S \n \n \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n female \n 17.0000 \n 17.00000 \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Perreault, Miss. Anne \n 0 \n 0 \n 12749 \n 93.5000 \n B73 \n S \n \n \n male \n 52.0000 \n 52.00000 \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n 0 \n 0 \n 113786 \n 30.5000 \n C104 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n 0 \n 0 \n 110465 \n 52.0000 \n C110 \n S \n \n \n female \n 56.0000 \n 56.00000 \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n 0 \n 1 \n 11767 \n 83.1583 \n C50 \n C \n \n \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n 0 \n 0 \n 19972 \n 0.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n 0 \n 0 \n PC 17607 \n 39.6000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 1 \n 0 \n Ringhini, Mr. Sante \n 0 \n 0 \n PC 17760 \n 135.6333 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Robbins, Mr. Victor \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n female \n 43.0000 \n 43.00000 \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n 0 \n 1 \n 24160 \n 211.3375 \n B3 \n S \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n 0 \n 0 \n PC 17590 \n 50.4958 \n A24 \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n 0 \n 0 \n 111428 \n 26.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n 0 \n 0 \n 113767 \n 50.0000 \n A32 \n S \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n 0 \n 0 \n PC 17613 \n 27.7208 \n A11 \n C \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n Ross, Mr. John Hugo \n 0 \n 0 \n 13049 \n 40.1250 \n A10 \n C \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Rothschild, Mr. Martin \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n male \n 33.0000 \n 33.00000 \n 1 \n 0 \n Rowe, Mr. Alfred G \n 0 \n 0 \n 113790 \n 26.5500 \n NA \n S \n \n \n male \n 13.0000 \n 13.00000 \n 1 \n 1 \n Ryerson, Master. John Borie \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n female \n 21.0000 \n 21.00000 \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n male \n 61.0000 \n 61.00000 \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n 0 \n 0 \n 19988 \n 30.5000 \n C106 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Sagesser, Mlle. Emma \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Salomon, Mr. Abraham L \n 0 \n 0 \n 111163 \n 26.0000 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n 1 \n 0 \n 13236 \n 57.7500 \n C28 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Serepeca, Miss. Augusta \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n C \n \n \n male \n 34.0000 \n 34.00000 \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n 0 \n 0 \n 113794 \n 26.5500 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n 0 \n 0 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n male \n 35.0000 \n 35.00000 \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n 0 \n 0 \n PC 17475 \n 26.2875 \n E24 \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Silvey, Mr. William Baird \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n male \n 56.0000 \n 56.00000 \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n 0 \n 0 \n 13213 \n 35.5000 \n A26 \n C \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 1 \n Sloper, Mr. William Thompson \n 0 \n 0 \n 113788 \n 35.5000 \n A6 \n S \n \n \n male \n 56.0000 \n 56.00000 \n 1 \n 0 \n Smart, Mr. John Montgomery \n 0 \n 0 \n 113792 \n 26.5500 \n NA \n S \n \n \n male \n 56.0000 \n 56.00000 \n 1 \n 0 \n Smith, Mr. James Clinch \n 0 \n 0 \n 17764 \n 30.6958 \n A7 \n C \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n Smith, Mr. Lucien Philip \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Smith, Mr. Richard William \n 0 \n 0 \n 113056 \n 26.0000 \n A19 \n S \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n male \n 6.0000 \n 6.00000 \n 1 \n 1 \n Spedden, Master. Robert Douglas \n 0 \n 2 \n 16966 \n 134.5000 \n E34 \n C \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n male \n 57.0000 \n 57.00000 \n 1 \n 0 \n Spencer, Mr. William Augustus \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n male \n 32.0000 \n 32.00000 \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n 0 \n 0 \n 13214 \n 30.5000 \n B50 \n C \n \n \n male \n 62.0000 \n 62.00000 \n 1 \n 0 \n Stead, Mr. William Thomas \n 0 \n 0 \n 113514 \n 26.5500 \n C87 \n S \n \n \n male \n 54.0000 \n 54.00000 \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n female \n 43.0000 \n 43.00000 \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n female \n 52.0000 \n 52.00000 \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Stewart, Mr. Albert A \n 0 \n 0 \n PC 17605 \n 27.7208 \n NA \n C \n \n \n female \n 62.0000 \n 62.00000 \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n male \n 67.0000 \n 67.00000 \n 1 \n 0 \n Straus, Mr. Isidor \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n female \n 63.0000 \n 63.00000 \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n male \n 61.0000 \n 61.00000 \n 1 \n 0 \n Sutton, Mr. Frederick \n 0 \n 0 \n 36963 \n 32.3208 \n D50 \n S \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n 0 \n 0 \n 17466 \n 25.9292 \n D17 \n S \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Taussig, Miss. Ruth \n 0 \n 2 \n 110413 \n 79.6500 \n E68 \n S \n \n \n male \n 52.0000 \n 52.00000 \n 1 \n 0 \n Taussig, Mr. Emil \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n Thayer, Mr. John Borland \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n male \n 17.0000 \n 17.00000 \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n 0 \n 2 \n 17421 \n 110.8833 \n C70 \n C \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n 0 \n 0 \n 2543 \n 28.5375 \n C53 \n C \n \n \n male \n 40.0000 \n 40.00000 \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n 0 \n 0 \n PC 17601 \n 27.7208 \n NA \n C \n \n \n male \n 61.0000 \n 61.00000 \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n 0 \n 0 \n 111240 \n 33.5000 \n B19 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Walker, Mr. William Anderson \n 0 \n 0 \n 36967 \n 34.0208 \n D46 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Ward, Miss. Anna \n 0 \n 0 \n PC 17755 \n 512.3292 \n NA \n C \n \n \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n Warren, Mr. Frank Manley \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n female \n 60.0000 \n 60.00000 \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n male \n 60.0000 \n 60.00000 \n 1 \n 0 \n Weir, Col. John \n 0 \n 0 \n 113800 \n 26.5500 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n White, Mr. Percival Wayland \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n White, Mr. Richard Frasar \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n female \n 55.0000 \n 55.00000 \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n Wick, Miss. Mary Natalie \n 0 \n 2 \n 36928 \n 164.8667 \n C7 \n S \n \n \n male \n 57.0000 \n 57.00000 \n 1 \n 0 \n Wick, Mr. George Dennick \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Widener, Mr. George Dunton \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n Widener, Mr. Harry Elkins \n 0 \n 2 \n 113503 \n 211.5000 \n C82 \n C \n \n \n female \n 50.0000 \n 50.00000 \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n female \n 21.0000 \n 21.00000 \n 1 \n 1 \n Willard, Miss. Constance \n 0 \n 0 \n 113795 \n 26.5500 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 1 \n 0 \n Williams, Mr. Charles Duane \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n male \n 21.0000 \n 21.00000 \n 1 \n 1 \n Williams, Mr. Richard Norris II \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n 0 \n 0 \n 113510 \n 35.0000 \n C128 \n S \n \n \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n Wilson, Miss. Helen Alice \n 0 \n 0 \n 16966 \n 134.5000 \n E39 E41 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Woolner, Mr. Hugh \n 0 \n 0 \n 19947 \n 35.5000 \n C52 \n S \n \n \n male \n 62.0000 \n 62.00000 \n 1 \n 0 \n Wright, Mr. George \n 0 \n 0 \n 113807 \n 26.5500 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Young, Miss. Marie Grice \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Abelson, Mr. Samuel \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n 0 \n 0 \n 248744 \n 13.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n 0 \n 0 \n 231945 \n 11.5000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n 0 \n 0 \n C.A. 34050 \n 10.5000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Angle, Mr. William A \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n male \n 57.0000 \n 57.00000 \n 2 \n 0 \n Ashby, Mr. John \n 0 \n 0 \n 244346 \n 13.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n 0 \n 0 \n 29108 \n 11.5000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n 0 \n 0 \n C.A. 31030 \n 10.5000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n 0 \n 0 \n 28551 \n 13.0000 \n D \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Banfield, Mr. Frederick James \n 0 \n 0 \n C.A./SOTON 34068 \n 10.5000 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 2 \n 0 \n Bateman, Rev. Robert James \n 0 \n 0 \n S.O.P. 1166 \n 12.5250 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 1 \n Beane, Mr. Edward \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Beauchamp, Mr. Henry James \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 2 \n 1 \n Becker, Master. Richard F \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n female \n 4.0000 \n 4.00000 \n 2 \n 1 \n Becker, Miss. Marion Louise \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n female \n 12.0000 \n 12.00000 \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n 0 \n 3 \n 230136 \n 39.0000 \n F4 \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 1 \n Beesley, Mr. Lawrence \n 0 \n 0 \n 248698 \n 13.0000 \n D56 \n S \n \n \n female \n 19.0000 \n 19.00000 \n 2 \n 1 \n Bentham, Miss. Lilian W \n 0 \n 0 \n 28404 \n 13.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Berriman, Mr. William John \n 0 \n 0 \n 28425 \n 13.0000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Botsford, Mr. William Hull \n 0 \n 0 \n 237670 \n 13.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Bowenur, Mr. Solomon \n 0 \n 0 \n 211535 \n 13.0000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Bracken, Mr. James H \n 0 \n 0 \n 220367 \n 13.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n 0 \n 0 \n 248733 \n 13.0000 \n F33 \n S \n \n \n female \n 15.0000 \n 15.00000 \n 2 \n 1 \n Brown, Miss. Edith Eileen \n 0 \n 2 \n 29750 \n 39.0000 \n NA \n S \n \n \n male \n 60.0000 \n 60.00000 \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Buss, Miss. Kate \n 0 \n 0 \n 27849 \n 13.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n 0 \n 0 \n 234686 \n 13.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n 0 \n 0 \n 244310 \n 13.0000 \n NA \n S \n \n \n female \n 42.0000 \n 42.00000 \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n 0 \n 0 \n 236852 \n 13.0000 \n NA \n S \n \n \n male \n 0.8333 \n 0.83330 \n 2 \n 1 \n Caldwell, Master. Alden Gates \n 0 \n 2 \n 248738 \n 29.0000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 2 \n 1 \n Cameron, Miss. Clear Annie \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Campbell, Mr. William \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Carbines, Mr. William \n 0 \n 0 \n 28424 \n 13.0000 \n NA \n S \n \n \n female \n 44.0000 \n 44.00000 \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n male \n 52.0000 \n 52.00000 \n 2 \n 0 \n Chapman, Mr. Charles Henry \n 0 \n 0 \n 248731 \n 13.5000 \n NA \n S \n \n \n male \n 37.0000 \n 37.00000 \n 2 \n 0 \n Chapman, Mr. John Henry \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 2 \n 1 \n Christy, Miss. Julie Rachel \n 1 \n 1 \n 237789 \n 30.0000 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n 0 \n 2 \n 237789 \n 30.0000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n 0 \n 0 \n W./C. 14263 \n 10.5000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n 0 \n 0 \n 248740 \n 13.0000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n 0 \n 0 \n 28034 \n 10.5000 \n NA \n S \n \n \n female \n 8.0000 \n 8.00000 \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n 0 \n 2 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 0 \n Collyer, Mr. Harvey \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n 0 \n 0 \n W./C. 14266 \n 10.5000 \n F33 \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n 0 \n 0 \n 237249 \n 13.0000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n 0 \n 0 \n 29107 \n 11.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n male \n 8.0000 \n 8.00000 \n 2 \n 1 \n Davies, Master. John Morgan Jr \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Davies, Mr. Charles Henry \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n female \n 48.0000 \n 48.00000 \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n 0 \n 2 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Davis, Miss. Mary \n 0 \n 0 \n 237668 \n 13.0000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n 0 \n 0 \n 244360 \n 13.0000 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 2 \n 0 \n Deacon, Mr. Percy William \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Denbury, Mr. Herbert \n 0 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Dibden, Mr. William \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 2 \n 1 \n Doling, Miss. Elsie \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 2 \n 0 \n Downton, Mr. William James \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n male \n 8.0000 \n 8.00000 \n 2 \n 1 \n Drew, Master. Marshall Brines \n 0 \n 2 \n 28220 \n 32.5000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Drew, Mr. James Vivian \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 2 \n 1 \n Duran y More, Miss. Asuncion \n 1 \n 0 \n SC/PARIS 2149 \n 13.8583 \n NA \n C \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Duran y More, Miss. Florentina \n 1 \n 0 \n SC/PARIS 2148 \n 13.8583 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n 0 \n 0 \n 29751 \n 13.0000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Enander, Mr. Ingvar \n 0 \n 0 \n 236854 \n 13.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n 0 \n 0 \n 236171 \n 13.0000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 2 \n 0 \n Faunthorpe, Mr. Harry \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n 0 \n 0 \n C.A. 15185 \n 10.5000 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n 0 \n 0 \n 229236 \n 13.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n 0 \n 0 \n 239854 \n 0.0000 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n 0 \n 0 \n 237671 \n 13.0000 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 2 \n 0 \n Fynney, Mr. Joseph J \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 2 \n 0 \n Gale, Mr. Harry \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Gale, Mr. Shadrach \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Garside, Miss. Ethel \n 0 \n 0 \n 243880 \n 13.0000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 2 \n 0 \n Gaskell, Mr. Alfred \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Gavey, Mr. Lawrence \n 0 \n 0 \n 31028 \n 10.5000 \n NA \n S \n \n \n male \n 47.0000 \n 47.00000 \n 2 \n 0 \n Gilbert, Mr. William \n 0 \n 0 \n C.A. 30769 \n 10.5000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Giles, Mr. Edgar \n 1 \n 0 \n 28133 \n 11.5000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Giles, Mr. Frederick Edward \n 1 \n 0 \n 28134 \n 11.5000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Giles, Mr. Ralph \n 0 \n 0 \n 248726 \n 13.5000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Gill, Mr. John William \n 0 \n 0 \n 233866 \n 13.0000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Gillespie, Mr. William Henry \n 0 \n 0 \n 12233 \n 13.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n 0 \n 0 \n 250646 \n 13.0000 \n NA \n S \n \n \n male \n 52.0000 \n 52.00000 \n 2 \n 0 \n Greenberg, Mr. Samuel \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Hale, Mr. Reginald \n 0 \n 0 \n 250653 \n 13.0000 \n NA \n S \n \n \n male \n 0.6667 \n 0.66670 \n 2 \n 1 \n Hamalainen, Master. Viljo \n 1 \n 1 \n 250649 \n 14.5000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n 0 \n 2 \n 250649 \n 14.5000 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 2 \n 0 \n Harbeck, Mr. William H \n 0 \n 0 \n 248746 \n 13.0000 \n NA \n S \n \n \n female \n 6.0000 \n 6.00000 \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Harper, Rev. John \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n male \n 62.0000 \n 62.00000 \n 2 \n 1 \n Harris, Mr. George \n 0 \n 0 \n S.W./PP 752 \n 10.5000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Harris, Mr. Walter \n 0 \n 0 \n W/C 14208 \n 10.5000 \n NA \n S \n \n \n female \n 7.0000 \n 7.00000 \n 2 \n 1 \n Hart, Miss. Eva Miriam \n 0 \n 2 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 2 \n 0 \n Hart, Mr. Benjamin \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Herman, Miss. Alice \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Herman, Miss. Kate \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n male \n 49.0000 \n 49.00000 \n 2 \n 0 \n Herman, Mr. Samuel \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 48.0000 \n 48.00000 \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 55.0000 \n 55.00000 \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n 0 \n 0 \n 248706 \n 16.0000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n Hickman, Mr. Lewis \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Hickman, Mr. Stanley George \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 2 \n 0 \n Hiltunen, Miss. Marta \n 1 \n 1 \n 250650 \n 13.0000 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n 2 \n 1 \n 29105 \n 23.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Hocking, Mr. Richard George \n 2 \n 1 \n 29104 \n 11.5000 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n 0 \n 0 \n 242963 \n 13.0000 \n NA \n S \n \n \n female \n 54.0000 \n 54.00000 \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n 1 \n 3 \n 29105 \n 23.0000 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 2 \n 0 \n Hodges, Mr. Henry Price \n 0 \n 0 \n 250643 \n 13.0000 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 2 \n 0 \n Hold, Mr. Stephen \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 1 \n Hosono, Mr. Masabumi \n 0 \n 0 \n 237798 \n 13.0000 \n NA \n S \n \n \n male \n 63.0000 \n 63.00000 \n 2 \n 0 \n Howard, Mr. Benjamin \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n female \n 60.0000 \n 60.00000 \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 2 \n 0 \n Hunt, Mr. George Henry \n 0 \n 0 \n SCO/W 1585 \n 12.2750 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 2 \n 1 \n Ilett, Miss. Bertha \n 0 \n 0 \n SO/C 14885 \n 10.5000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n 1 \n 0 \n 243847 \n 27.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n 2 \n 1 \n 243847 \n 27.0000 \n NA \n S \n \n \n male \n 47.0000 \n 47.00000 \n 2 \n 0 \n Jarvis, Mr. John Denzil \n 0 \n 0 \n 237565 \n 15.0000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n 0 \n 0 \n C.A. 33111 \n 10.5000 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n 0 \n 0 \n SC/AH Basle 541 \n 13.7917 \n D \n C \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Kantor, Mr. Sinai \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 2 \n 1 \n Keane, Miss. Nora A \n 0 \n 0 \n 226593 \n 12.3500 \n E101 \n Q \n \n \n male \n 35.0000 \n 35.00000 \n 2 \n 0 \n Keane, Mr. Daniel \n 0 \n 0 \n 233734 \n 12.3500 \n NA \n Q \n \n \n female \n 45.0000 \n 45.00000 \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n 0 \n 0 \n 223596 \n 13.5000 \n NA \n S \n \n \n male \n 57.0000 \n 57.00000 \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n 0 \n 0 \n 219533 \n 12.3500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Knight, Mr. Robert J \n 0 \n 0 \n 239855 \n 0.0000 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n 0 \n 0 \n C.A. 18723 \n 10.5000 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Lahtinen, Rev. William \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Lamb, Mr. John Joseph \n 0 \n 0 \n 240261 \n 10.7083 \n NA \n Q \n \n \n female \n 1.0000 \n 1.00000 \n 2 \n 1 \n Laroche, Miss. Louise \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n female \n 3.0000 \n 3.00000 \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n female \n 17.0000 \n 17.00000 \n 2 \n 1 \n Lehmann, Miss. Bertha \n 0 \n 0 \n SC 1748 \n 12.0000 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n 0 \n 0 \n 248727 \n 33.0000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n 0 \n 0 \n C.A. 34260 \n 10.5000 \n F33 \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Levy, Mr. Rene Jacques \n 0 \n 0 \n SC/Paris 2163 \n 12.8750 \n D \n C \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n 0 \n 0 \n C.A. 29566 \n 10.5000 \n NA \n S \n \n \n male \n 61.0000 \n 61.00000 \n 2 \n 0 \n Lingane, Mr. John \n 0 \n 0 \n 235509 \n 12.3500 \n NA \n Q \n \n \n male \n 50.0000 \n 50.00000 \n 2 \n 0 \n Louch, Mr. Charles Alexander \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n female \n 42.0000 \n 42.00000 \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n female \n 57.0000 \n 57.00000 \n 2 \n 0 \n Mack, Mrs. (Mary) \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n E77 \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Malachard, Mr. Noel \n 0 \n 0 \n 237735 \n 15.0458 \n D \n C \n \n \n male \n 1.0000 \n 1.00000 \n 2 \n 1 \n Mallet, Master. Andre \n 0 \n 2 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 0 \n Mallet, Mr. Albert \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n 0 \n 0 \n SC/A.3 2861 \n 15.5792 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Matthews, Mr. William John \n 0 \n 0 \n 28228 \n 13.0000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n 0 \n 0 \n 239059 \n 16.0000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n 0 \n 0 \n 237216 \n 13.5000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n McCrie, Mr. James Matthew \n 0 \n 0 \n 233478 \n 13.0000 \n NA \n S \n \n \n male \n 46.0000 \n 46.00000 \n 2 \n 0 \n McKane, Mr. Peter David \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n female \n 13.0000 \n 13.00000 \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n female \n 41.0000 \n 41.00000 \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 1 \n Mellors, Mr. William John \n 0 \n 0 \n SW/PP 751 \n 10.5000 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 2 \n 0 \n Meyer, Mr. August \n 0 \n 0 \n 248723 \n 13.0000 \n NA \n S \n \n \n male \n 48.0000 \n 48.00000 \n 2 \n 0 \n Milling, Mr. Jacob Christian \n 0 \n 0 \n 234360 \n 13.0000 \n NA \n S \n \n \n male \n 70.0000 \n 70.00000 \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n 0 \n 0 \n C.A. 24580 \n 10.5000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Montvila, Rev. Juozas \n 0 \n 0 \n 211536 \n 13.0000 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 2 \n 0 \n Moraweck, Dr. Ernest \n 0 \n 0 \n 29011 \n 14.0000 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n NA \n S \n \n \n male \n 62.0000 \n 62.00000 \n 2 \n 0 \n Myles, Mr. Thomas Francis \n 0 \n 0 \n 240276 \n 9.6875 \n NA \n Q \n \n \n male \n 32.5000 \n 32.50000 \n 2 \n 0 \n Nasser, Mr. Nicholas \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n female \n 14.0000 \n 14.00000 \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n male \n 2.0000 \n 2.00000 \n 2 \n 1 \n Navratil, Master. Edmond Roger \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n male \n 3.0000 \n 3.00000 \n 2 \n 1 \n Navratil, Master. Michel M \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n male \n 36.5000 \n 36.50000 \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n 0 \n 2 \n 230080 \n 26.0000 \n F2 \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Nesson, Mr. Israel \n 0 \n 0 \n 244368 \n 13.0000 \n F2 \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Norman, Mr. Robert Douglas \n 0 \n 0 \n 218629 \n 13.5000 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n 0 \n 0 \n SC/PARIS 2166 \n 13.8625 \n D38 \n C \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n 0 \n 0 \n C.A. 29395 \n 10.5000 \n F33 \n S \n \n \n male \n 39.0000 \n 39.00000 \n 2 \n 0 \n Otter, Mr. Richard \n 0 \n 0 \n 28213 \n 13.0000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n 0 \n 0 \n W./C. 14260 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 1 \n Padro y Manent, Mr. Julian \n 0 \n 0 \n SC/PARIS 2146 \n 13.8625 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Pain, Dr. Alfred \n 0 \n 0 \n 244278 \n 10.5000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n 0 \n 0 \n SC/PARIS 2147 \n 13.8583 \n NA \n C \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Parker, Mr. Clifford Richard \n 0 \n 0 \n SC 14888 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n female \n 50.0000 \n 50.00000 \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Pengelly, Mr. Frederick William \n 0 \n 0 \n 28665 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Pernot, Mr. Rene \n 0 \n 0 \n SC/PARIS 2131 \n 15.0500 \n NA \n C \n \n \n male \n 41.0000 \n 41.00000 \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n 0 \n 0 \n 237393 \n 13.0000 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 2 \n 0 \n Phillips, Mr. Escott Robert \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n female \n 32.0000 \n 32.00000 \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n 0 \n 0 \n 234604 \n 13.0000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Ponesell, Mr. Martin \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n 0 \n 0 \n C.A. 34644 \n 12.7375 \n NA \n C \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Pulbaum, Mr. Franz \n 0 \n 0 \n SC/PARIS 2168 \n 15.0333 \n NA \n C \n \n \n female \n 2.0000 \n 2.00000 \n 2 \n 1 \n Quick, Miss. Phyllis May \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n female \n 8.0000 \n 8.00000 \n 2 \n 1 \n Quick, Miss. Winifred Vera \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n 0 \n 2 \n 26360 \n 26.0000 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Reeves, Mr. David \n 0 \n 0 \n C.A. 17248 \n 10.5000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Renouf, Mr. Peter Henry \n 1 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n 3 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n 0 \n 0 \n 230434 \n 13.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Richard, Mr. Emile \n 0 \n 0 \n SC/PARIS 2133 \n 15.0458 \n NA \n C \n \n \n male \n 0.8333 \n 0.83330 \n 2 \n 1 \n Richards, Master. George Sibley \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n male \n 3.0000 \n 3.00000 \n 2 \n 1 \n Richards, Master. William Rowe \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n 2 \n 3 \n 29106 \n 18.7500 \n NA \n S \n \n \n female \n 50.0000 \n 50.00000 \n 2 \n 1 \n Ridsdale, Miss. Lucy \n 0 \n 0 \n W./C. 14258 \n 10.5000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n 0 \n 0 \n 28004 \n 10.5000 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 2 \n 1 \n Rugg, Miss. Emily \n 0 \n 0 \n C.A. 31026 \n 10.5000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Schmidt, Mr. August \n 0 \n 0 \n 248659 \n 13.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n 0 \n 0 \n 244361 \n 13.0000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Sharp, Mr. Percival James R \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n 0 \n 2 \n 250652 \n 13.0000 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n Sincock, Miss. Maude \n 0 \n 0 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Sinkkonen, Miss. Anna \n 0 \n 0 \n 250648 \n 13.0000 \n NA \n S \n \n \n male \n 59.0000 \n 59.00000 \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n 0 \n 0 \n 237442 \n 13.5000 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n 0 \n 0 \n 234818 \n 12.3500 \n NA \n Q \n \n \n male \n 35.0000 \n 35.00000 \n 2 \n 0 \n Slemen, Mr. Richard James \n 0 \n 0 \n 28206 \n 10.5000 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 2 \n 1 \n Smith, Miss. Marion Elsie \n 0 \n 0 \n 31418 \n 13.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n 0 \n 0 \n C.A. 29178 \n 13.0000 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n 0 \n 0 \n 237734 \n 15.0458 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n 0 \n 0 \n F.C.C. 13540 \n 10.5000 \n NA \n S \n \n \n male \n 18.5000 \n 18.50000 \n 2 \n 0 \n Swane, Mr. George \n 0 \n 0 \n 248734 \n 13.0000 \n F \n S \n \n \n male \n 14.0000 \n 14.00000 \n 2 \n 0 \n Sweet, Mr. George Frederick \n 0 \n 0 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 50.0000 \n 50.00000 \n 2 \n 1 \n Toomey, Miss. Ellen \n 0 \n 0 \n F.C.C. 13531 \n 10.5000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n 0 \n 0 \n 233639 \n 13.0000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n 0 \n 0 \n 240929 \n 12.6500 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n 0 \n 0 \n 34218 \n 10.5000 \n E101 \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n Turpin, Mr. William John Robert \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 2 \n 0 \n Veal, Mr. James \n 0 \n 0 \n 28221 \n 13.0000 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 2 \n 1 \n Walcroft, Miss. Nellie \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Ware, Mr. John James \n 1 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Ware, Mr. William Jeffery \n 1 \n 0 \n 28666 \n 10.5000 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n 0 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n 0 \n 0 \n 239856 \n 0.0000 \n NA \n S \n \n \n female \n 12.0000 \n 12.00000 \n 2 \n 1 \n Watt, Miss. Bertha J \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n female \n 32.5000 \n 32.50000 \n 2 \n 1 \n Webber, Miss. Susan \n 0 \n 0 \n 27267 \n 13.0000 \n E101 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Weisz, Mr. Leopold \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n male \n 2.0000 \n 2.00000 \n 2 \n 1 \n Wells, Master. Ralph Lester \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n female \n 4.0000 \n 4.00000 \n 2 \n 1 \n Wells, Miss. Joan \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n 0 \n 2 \n 29103 \n 23.0000 \n NA \n S \n \n \n female \n 0.9167 \n 0.91670 \n 2 \n 1 \n West, Miss. Barbara J \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n female \n 5.0000 \n 5.00000 \n 2 \n 1 \n West, Miss. Constance Mirium \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n West, Mr. Edwy Arthur \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n male \n 66.0000 \n 66.00000 \n 2 \n 0 \n Wheadon, Mr. Edward H \n 0 \n 0 \n C.A. 24579 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n 0 \n 0 \n SC/PARIS 2159 \n 12.8750 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 1 \n Wilhelms, Mr. Charles \n 0 \n 0 \n 244270 \n 13.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 1 \n Williams, Mr. Charles Eugene \n 0 \n 0 \n 244373 \n 13.0000 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 2 \n 1 \n Wright, Miss. Marion \n 0 \n 0 \n 220844 \n 13.5000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n 0 \n 0 \n 248747 \n 13.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Abbing, Mr. Anthony \n 0 \n 0 \n C.A. 5547 \n 7.5500 \n NA \n S \n \n \n male \n 13.0000 \n 13.00000 \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n 0 \n 2 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n 0 \n 0 \n 348125 \n 7.6500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n 0 \n 0 \n 348122 \n 7.6500 \n F G63 \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n 0 \n 0 \n SOTON/O2 3101284 \n 7.9250 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n 0 \n 0 \n 2657 \n 7.2292 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n 0 \n 0 \n C 7076 \n 7.2500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Adams, Mr. John \n 0 \n 0 \n 341826 \n 8.0500 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n 1 \n 0 \n 7546 \n 9.4750 \n NA \n S \n \n \n male \n 0.8333 \n 0.83330 \n 3 \n 1 \n Aks, Master. Philip Frank \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Alexander, Mr. William \n 0 \n 0 \n 3474 \n 7.8875 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n 0 \n 0 \n SOTON/O2 3101287 \n 7.9250 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Ali, Mr. Ahmed \n 0 \n 0 \n SOTON/O.Q. 3101311 \n 7.0500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Ali, Mr. William \n 0 \n 0 \n SOTON/O.Q. 3101312 \n 7.0500 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Allen, Mr. William Henry \n 0 \n 0 \n 373450 \n 8.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Allum, Mr. Owen George \n 0 \n 0 \n 2223 \n 8.3000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n 1 \n 0 \n 350046 \n 7.8542 \n NA \n S \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 6.0000 \n 6.00000 \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n 4 \n 2 \n 3101281 \n 7.9250 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n 4 \n 2 \n 347091 \n 7.7750 \n NA \n S \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 11.0000 \n 11.00000 \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Andersson, Mr. Anders Johan \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n 0 \n 0 \n 350043 \n 7.7958 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n 0 \n 0 \n 347075 \n 7.7750 \n NA \n S \n \n \n female \n 39.0000 \n 39.00000 \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n 0 \n 0 \n 347466 \n 7.8542 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Angheloff, Mr. Minko \n 0 \n 0 \n 349202 \n 7.8958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n 0 \n 0 \n 349911 \n 7.7750 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Asim, Mr. Adola \n 0 \n 0 \n SOTON/O.Q. 3101310 \n 7.0500 \n NA \n S \n \n \n male \n 5.0000 \n 5.00000 \n 3 \n 0 \n Asplund, Master. Carl Edgar \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 3.0000 \n 3.00000 \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 13.0000 \n 13.00000 \n 3 \n 0 \n Asplund, Master. Filip Oscar \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n female \n 5.0000 \n 5.00000 \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 1 \n Asplund, Mr. Johan Charles \n 0 \n 0 \n 350054 \n 7.7958 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n 0 \n 0 \n 2696 \n 7.2250 \n NA \n C \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Assaf, Mr. Gerios \n 0 \n 0 \n 2692 \n 7.2250 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Assam, Mr. Ali \n 0 \n 0 \n SOTON/O.Q. 3101309 \n 7.0500 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 0 \n Attalah, Miss. Malake \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Attalah, Mr. Sleiman \n 0 \n 0 \n 2694 \n 7.2250 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Augustsson, Mr. Albert \n 0 \n 0 \n 347468 \n 7.8542 \n NA \n S \n \n \n female \n 13.0000 \n 13.00000 \n 3 \n 1 \n Ayoub, Miss. Banoura \n 0 \n 0 \n 2687 \n 7.2292 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Baccos, Mr. Raffull \n 0 \n 0 \n 2679 \n 7.2250 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n 1 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n 3 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n female \n 0.7500 \n 0.75000 \n 3 \n 1 \n Baclini, Miss. Eugenie \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 0.7500 \n 0.75000 \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 5.0000 \n 5.00000 \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n 0 \n 3 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Badman, Miss. Emily Louisa \n 0 \n 0 \n A/4 31416 \n 8.0500 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Badt, Mr. Mohamed \n 0 \n 0 \n 2623 \n 7.2250 \n NA \n C \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Balkic, Mr. Cerin \n 0 \n 0 \n 349248 \n 7.8958 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Barah, Mr. Hanna Assi \n 0 \n 0 \n 2663 \n 7.2292 \n NA \n C \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Barbara, Miss. Saiide \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 0 \n Barry, Miss. Julia \n 0 \n 0 \n 330844 \n 7.8792 \n NA \n Q \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Barton, Mr. David John \n 0 \n 0 \n 324669 \n 8.0500 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Beavan, Mr. William Thomas \n 0 \n 0 \n 323951 \n 8.0500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n 0 \n 0 \n 347068 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n 0 \n 0 \n PP 4348 \n 9.3500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Betros, Master. Seman \n 0 \n 0 \n 2622 \n 7.2292 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Betros, Mr. Tannous \n 0 \n 0 \n 2648 \n 4.0125 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Bing, Mr. Lee \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n 0 \n 0 \n 312992 \n 7.7750 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n 0 \n 0 \n 347090 \n 7.7500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n 0 \n 0 \n 349224 \n 7.8958 \n NA \n S \n \n \n male \n 6.0000 \n 6.00000 \n 3 \n 0 \n Boulos, Master. Akar \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Boulos, Miss. Nourelain \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Boulos, Mr. Hanna \n 0 \n 0 \n 2664 \n 7.2250 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n 0 \n 2 \n 2678 \n 15.2458 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Bourke, Miss. Mary \n 0 \n 2 \n 364848 \n 7.7500 \n NA \n Q \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Bourke, Mr. John \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n female \n 32.0000 \n 32.00000 \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n 0 \n 0 \n 334914 \n 7.7250 \n NA \n Q \n \n \n female \n 20.0000 \n 20.00000 \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n 0 \n 0 \n 347471 \n 7.8542 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Braund, Mr. Lewis Richard \n 1 \n 0 \n 3460 \n 7.0458 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Braund, Mr. Owen Harris \n 1 \n 0 \n A/5 21171 \n 7.2500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n 0 \n 0 \n 350045 \n 7.7958 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n 0 \n 0 \n 364512 \n 8.0500 \n NA \n S \n \n \n female \n 18.5000 \n 18.50000 \n 3 \n 0 \n Buckley, Miss. Katherine \n 0 \n 0 \n 329944 \n 7.2833 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Buckley, Mr. Daniel \n 0 \n 0 \n 330920 \n 7.8208 \n NA \n Q \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Burke, Mr. Jeremiah \n 0 \n 0 \n 365222 \n 6.7500 \n NA \n Q \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Burns, Miss. Mary Delia \n 0 \n 0 \n 330963 \n 7.8792 \n NA \n Q \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Cacic, Miss. Manda \n 0 \n 0 \n 315087 \n 8.6625 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Cacic, Miss. Marija \n 0 \n 0 \n 315084 \n 8.6625 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Cacic, Mr. Jego Grga \n 0 \n 0 \n 315091 \n 8.6625 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 3 \n 0 \n Cacic, Mr. Luka \n 0 \n 0 \n 315089 \n 8.6625 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Calic, Mr. Jovo \n 0 \n 0 \n 315093 \n 8.6625 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Calic, Mr. Petar \n 0 \n 0 \n 315086 \n 8.6625 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Canavan, Miss. Mary \n 0 \n 0 \n 364846 \n 7.7500 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Canavan, Mr. Patrick \n 0 \n 0 \n 364858 \n 7.7500 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Cann, Mr. Ernest Charles \n 0 \n 0 \n A./5. 2152 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Caram, Mr. Joseph \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n 0 \n 0 \n 350042 \n 7.7958 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n 0 \n 0 \n 350409 \n 7.8542 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n 0 \n 0 \n 367231 \n 7.7500 \n NA \n Q \n \n \n female \n 37.0000 \n 37.00000 \n 3 \n 0 \n Carr, Miss. Jeannie \n 0 \n 0 \n 368364 \n 7.7500 \n NA \n Q \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Carver, Mr. Alfred John \n 0 \n 0 \n 392095 \n 7.2500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Celotti, Mr. Francesco \n 0 \n 0 \n 343275 \n 8.0500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Charters, Mr. David \n 0 \n 0 \n A/5. 13032 \n 7.7333 \n NA \n Q \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Chip, Mr. Chang \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Christmann, Mr. Emil \n 0 \n 0 \n 343276 \n 8.0500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n 0 \n 0 \n SOTON/O.Q. 3101307 \n 7.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n 0 \n 0 \n A/5 3540 \n 8.0500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Colbert, Mr. Patrick \n 0 \n 0 \n 371109 \n 7.2500 \n NA \n Q \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Coleff, Mr. Peju \n 0 \n 0 \n 349210 \n 7.4958 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Coleff, Mr. Satio \n 0 \n 0 \n 349209 \n 7.4958 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n 0 \n 0 \n 21332 \n 7.7333 \n NA \n Q \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Connaghton, Mr. Michael \n 0 \n 0 \n 335097 \n 7.7500 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Connolly, Miss. Kate \n 0 \n 0 \n 370373 \n 7.7500 \n NA \n Q \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Connolly, Miss. Kate \n 0 \n 0 \n 330972 \n 7.6292 \n NA \n Q \n \n \n male \n 70.5000 \n 70.50000 \n 3 \n 0 \n Connors, Mr. Patrick \n 0 \n 0 \n 370369 \n 7.7500 \n NA \n Q \n \n \n male \n 43.0000 \n 43.00000 \n 3 \n 0 \n Cook, Mr. Jacob \n 0 \n 0 \n A/5 3536 \n 8.0500 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Cor, Mr. Bartol \n 0 \n 0 \n 349230 \n 7.8958 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Cor, Mr. Ivan \n 0 \n 0 \n 349229 \n 7.8958 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Cor, Mr. Liudevit \n 0 \n 0 \n 349231 \n 7.8958 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Corn, Mr. Harry \n 0 \n 0 \n SOTON/OQ 392090 \n 8.0500 \n NA \n S \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n male \n 3.0000 \n 3.00000 \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n 0 \n 2 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n male \n 59.0000 \n 59.00000 \n 3 \n 0 \n Coxon, Mr. Daniel \n 0 \n 0 \n 364500 \n 7.2500 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Crease, Mr. Ernest James \n 0 \n 0 \n S.P. 3464 \n 8.1583 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 1 \n Cribb, Miss. Laura Alice \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 0 \n Cribb, Mr. John Hatfield \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Culumovic, Mr. Jeso \n 0 \n 0 \n 315090 \n 8.6625 \n NA \n S \n \n \n male \n 22.5000 \n 22.50000 \n 3 \n 0 \n Daher, Mr. Shedid \n 0 \n 0 \n 2698 \n 7.2250 \n NA \n C \n \n \n male \n 45.0000 \n 45.00000 \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n 0 \n 0 \n 7598 \n 8.0500 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n 0 \n 0 \n 7552 \n 10.5167 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Dakic, Mr. Branko \n 0 \n 0 \n 349228 \n 10.1708 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n 0 \n 0 \n 382650 \n 6.9500 \n NA \n Q \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n 0 \n 0 \n 382651 \n 7.7500 \n NA \n Q \n \n \n male \n 0.3333 \n 0.33330 \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n 0 \n 2 \n 347080 \n 14.4000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Danoff, Mr. Yoto \n 0 \n 0 \n 349219 \n 7.8958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n 0 \n 0 \n 349203 \n 7.8958 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Davies, Mr. Alfred J \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Davies, Mr. Evan \n 0 \n 0 \n SC/A4 23568 \n 8.0500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Davies, Mr. John Samuel \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Davies, Mr. Joseph \n 2 \n 0 \n A/4 48873 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Davison, Mr. Thomas Henry \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n male \n 36.5000 \n 36.50000 \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 1 \n de Mulder, Mr. Theodore \n 0 \n 0 \n 345774 \n 9.5000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n 0 \n 0 \n 345778 \n 9.5000 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 3 \n 1 \n Dean, Master. Bertram Vere \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n female \n 0.1667 \n 0.16670 \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Dean, Mr. Bertram Frank \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Delalic, Mr. Redjo \n 0 \n 0 \n 349250 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Demetri, Mr. Marinko \n 0 \n 0 \n 349238 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Denkoff, Mr. Mitto \n 0 \n 0 \n 349225 \n 7.8958 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Dennis, Mr. Samuel \n 0 \n 0 \n A/5 21172 \n 7.2500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Dennis, Mr. William \n 0 \n 0 \n A/5 21175 \n 7.2500 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n 0 \n 0 \n 330958 \n 7.8792 \n NA \n Q \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Dika, Mr. Mirko \n 0 \n 0 \n 349232 \n 7.8958 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Dimic, Mr. Jovan \n 0 \n 0 \n 315088 \n 8.6625 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n 0 \n 0 \n 349226 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Doharr, Mr. Tannous \n 0 \n 0 \n 2686 \n 7.2292 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Dooley, Mr. Patrick \n 0 \n 0 \n 370376 \n 7.7500 \n NA \n Q \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n 0 \n 0 \n A/5. 10482 \n 8.0500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 0 \n Doyle, Miss. Elizabeth \n 0 \n 0 \n 368702 \n 7.7500 \n NA \n Q \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 1 \n Drapkin, Miss. Jennie \n 0 \n 0 \n SOTON/OQ 392083 \n 8.0500 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Drazenoic, Mr. Jozef \n 0 \n 0 \n 349241 \n 7.8958 \n NA \n C \n \n \n male \n 65.0000 \n 65.00000 \n 3 \n 0 \n Duane, Mr. Frank \n 0 \n 0 \n 336439 \n 7.7500 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 1 \n Duquemin, Mr. Joseph \n 0 \n 0 \n S.O./P.P. 752 \n 7.5500 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n 0 \n 0 \n 349912 \n 7.7750 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Eklund, Mr. Hans Linus \n 0 \n 0 \n 347074 \n 7.7750 \n NA \n S \n \n \n male \n 45.0000 \n 45.00000 \n 3 \n 0 \n Ekstrom, Mr. Johan \n 0 \n 0 \n 347061 \n 6.9750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Elias, Mr. Dibo \n 0 \n 0 \n 2674 \n 7.2250 \n NA \n C \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Elias, Mr. Joseph \n 0 \n 2 \n 2675 \n 7.2292 \n NA \n C \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Elias, Mr. Joseph Jr \n 1 \n 1 \n 2690 \n 7.2292 \n NA \n C \n \n \n male \n 15.0000 \n 15.00000 \n 3 \n 0 \n Elias, Mr. Tannous \n 1 \n 1 \n 2695 \n 7.2292 \n NA \n C \n \n \n male \n 47.0000 \n 47.00000 \n 3 \n 0 \n Elsbury, Mr. William James \n 0 \n 0 \n A/5 3902 \n 7.2500 \n NA \n S \n \n \n female \n 5.0000 \n 5.00000 \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Emir, Mr. Farred Chehab \n 0 \n 0 \n 2631 \n 7.2250 \n NA \n C \n \n \n male \n 40.5000 \n 40.50000 \n 3 \n 0 \n Everett, Mr. Thomas James \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n male \n 40.5000 \n 40.50000 \n 3 \n 0 \n Farrell, Mr. James \n 0 \n 0 \n 367232 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Finoli, Mr. Luigi \n 0 \n 0 \n SOTON/O.Q. 3101308 \n 7.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n 0 \n 0 \n 350036 \n 7.7958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Fleming, Miss. Honora \n 0 \n 0 \n 364859 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Flynn, Mr. James \n 0 \n 0 \n 364851 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Flynn, Mr. John \n 0 \n 0 \n 368323 \n 6.9500 \n NA \n Q \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Foley, Mr. Joseph \n 0 \n 0 \n 330910 \n 7.8792 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Foley, Mr. William \n 0 \n 0 \n 365235 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Foo, Mr. Choong \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ford, Mr. Arthur \n 0 \n 0 \n A/5 1478 \n 8.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Ford, Mr. Edward Watson \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Ford, Mr. William Neal \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n female \n 48.0000 \n 48.00000 \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Fox, Mr. Patrick \n 0 \n 0 \n 368573 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n 0 \n 0 \n SOTON/O.Q. 3101314 \n 7.2500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Gallagher, Mr. Martin \n 0 \n 0 \n 36864 \n 7.7417 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Garfirth, Mr. John \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n 0 \n 0 \n 349254 \n 7.8958 \n NA \n C \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Gilinski, Mr. Eliezer \n 0 \n 0 \n 14973 \n 8.0500 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n 0 \n 0 \n 35851 \n 7.7333 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n 0 \n 0 \n 335677 \n 7.7500 \n NA \n Q \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n 0 \n 2 \n 363291 \n 20.5250 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Goldsmith, Mr. Frank John \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 3 \n 0 \n Goldsmith, Mr. Nathan \n 0 \n 0 \n SOTON/O.Q. 3101263 \n 7.8500 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n 0 \n 0 \n SOTON/O.Q. 3101306 \n 7.0500 \n NA \n S \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 0 \n Goodwin, Master. Harold Victor \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 11.0000 \n 11.00000 \n 3 \n 0 \n Goodwin, Master. William Frederick \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n female \n 10.0000 \n 10.00000 \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 14.0000 \n 14.00000 \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n female \n 43.0000 \n 43.00000 \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 3 \n 0 \n Green, Mr. George Henry \n 0 \n 0 \n 21440 \n 8.0500 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n 0 \n 0 \n 8471 \n 8.3625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Guest, Mr. Robert \n 0 \n 0 \n 376563 \n 8.0500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n 0 \n 0 \n 7534 \n 9.8458 \n NA \n S \n \n \n male \n 37.0000 \n 37.00000 \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n 2 \n 0 \n 3101276 \n 7.9250 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n 2 \n 0 \n 3101277 \n 7.9250 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n 0 \n 0 \n 347069 \n 7.7750 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 0 \n Haas, Miss. Aloisia \n 0 \n 0 \n 349236 \n 8.8500 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 0 \n Hagardon, Miss. Kate \n 0 \n 0 \n AQ/3. 30631 \n 7.7333 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n 1 \n 0 \n 65303 \n 19.9667 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n 1 \n 0 \n 65304 \n 19.9667 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Hampe, Mr. Leon \n 0 \n 0 \n 345769 \n 9.5000 \n NA \n S \n \n \n male \n 23.5000 \n 23.50000 \n 3 \n 0 \n Hanna, Mr. Mansour \n 0 \n 0 \n 2693 \n 7.2292 \n NA \n C \n \n \n male \n 41.0000 \n 41.00000 \n 3 \n 0 \n Hansen, Mr. Claus Peter \n 2 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n 1 \n 0 \n 350025 \n 7.8542 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n 0 \n 0 \n 350029 \n 7.8542 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n 1 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n 0 \n 0 \n W./C. 6609 \n 7.5500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n 0 \n 0 \n 374887 \n 7.2500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Hart, Mr. Henry \n 0 \n 0 \n 394140 \n 6.8583 \n NA \n Q \n \n \n male \n 11.0000 \n 11.00000 \n 3 \n 0 \n Hassan, Mr. Houssein G N \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n 0 \n 0 \n 370375 \n 7.7500 \n NA \n Q \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n 0 \n 0 \n 347089 \n 6.9750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Hee, Mr. Ling \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n 0 \n 0 \n 365226 \n 6.7500 \n NA \n Q \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 1 \n Heikkinen, Miss. Laina \n 0 \n 0 \n STON/O2. 3101282 \n 7.9250 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n 0 \n 0 \n STON/O2. 3101290 \n 7.9250 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n 0 \n 0 \n 7548 \n 8.9625 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n 0 \n 0 \n 349243 \n 7.8958 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n 0 \n 0 \n 347086 \n 7.7750 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Henry, Miss. Delia \n 0 \n 0 \n 382649 \n 7.7500 \n NA \n Q \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n 0 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n 1 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n 0 \n 0 \n C 7075 \n 6.4500 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Holthen, Mr. Johan Martin \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 1 \n Honkanen, Miss. Eliina \n 0 \n 0 \n STON/O2. 3101283 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Horgan, Mr. John \n 0 \n 0 \n 370377 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Howard, Miss. May Elizabeth \n 0 \n 0 \n A. 2. 39186 \n 8.0500 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n 0 \n 0 \n 348121 \n 7.6500 \n F G63 \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Hyman, Mr. Abraham \n 0 \n 0 \n 3470 \n 7.8875 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n 0 \n 0 \n 2685 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ilieff, Mr. Ylio \n 0 \n 0 \n 349220 \n 7.8958 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n 1 \n 0 \n STON/O2. 3101270 \n 7.9250 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n 1 \n 0 \n STON/O2. 3101271 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ivanoff, Mr. Kanio \n 0 \n 0 \n 349201 \n 7.8958 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Jalsevac, Mr. Ivan \n 0 \n 0 \n 349240 \n 7.8958 \n NA \n C \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Jansson, Mr. Carl Olof \n 0 \n 0 \n 350034 \n 7.7958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Jardin, Mr. Jose Neto \n 0 \n 0 \n SOTON/O.Q. 3101305 \n 7.0500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Jensen, Mr. Hans Peder \n 0 \n 0 \n 350050 \n 7.8542 \n NA \n S \n \n \n male \n 48.0000 \n 48.00000 \n 3 \n 0 \n Jensen, Mr. Niels Peder \n 0 \n 0 \n 350047 \n 7.8542 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n 1 \n 0 \n 350048 \n 7.0542 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Jermyn, Miss. Annie \n 0 \n 0 \n 14313 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n 0 \n 0 \n 65306 \n 8.1125 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n 0 \n 0 \n 3101264 \n 6.4958 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n 0 \n 0 \n 347070 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Johansson, Mr. Erik \n 0 \n 0 \n 350052 \n 7.7958 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n 0 \n 0 \n 7540 \n 8.6542 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Johansson, Mr. Karl Johan \n 0 \n 0 \n 347063 \n 7.7750 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Johansson, Mr. Nils \n 0 \n 0 \n 347467 \n 7.8542 \n NA \n S \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 1 \n Johnson, Master. Harold Theodor \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n male \n 49.0000 \n 49.00000 \n 3 \n 0 \n Johnson, Mr. Alfred \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n 0 \n 0 \n 347062 \n 7.7750 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n 0 \n 2 \n 347742 \n 11.1333 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Johnston, Mr. Andrew G \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Jonkoff, Mr. Lalio \n 0 \n 0 \n 349204 \n 7.8958 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Jonsson, Mr. Carl \n 0 \n 0 \n 350417 \n 7.8542 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n 0 \n 0 \n 350408 \n 7.8542 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 3 \n 0 \n Jussila, Miss. Katriina \n 1 \n 0 \n 4136 \n 9.8250 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Jussila, Miss. Mari Aina \n 1 \n 0 \n 4137 \n 9.8250 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Jussila, Mr. Eiriik \n 0 \n 0 \n STON/O 2. 3101286 \n 7.9250 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n 0 \n 0 \n STON/O 2. 3101274 \n 7.1250 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n 0 \n 0 \n 8475 \n 8.4333 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Karaic, Mr. Milan \n 0 \n 0 \n 349246 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n 0 \n 0 \n 350053 \n 7.7958 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n 0 \n 0 \n 347465 \n 7.8542 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Karlsson, Mr. Nils August \n 0 \n 0 \n 350060 \n 7.5208 \n NA \n S \n \n \n female \n 4.0000 \n 4.00000 \n 3 \n 1 \n Karun, Miss. Manca \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 1 \n Karun, Mr. Franz \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kassem, Mr. Fared \n 0 \n 0 \n 2700 \n 7.2292 \n NA \n C \n \n \n male \n 18.5000 \n 18.50000 \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n 0 \n 0 \n 2682 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n 0 \n 0 \n 12460 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Keefe, Mr. Arthur \n 0 \n 0 \n 323592 \n 7.2500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n 0 \n 0 \n 9234 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Kelly, Miss. Mary \n 0 \n 0 \n 14312 \n 7.7500 \n NA \n Q \n \n \n male \n 34.5000 \n 34.50000 \n 3 \n 0 \n Kelly, Mr. James \n 0 \n 0 \n 330911 \n 7.8292 \n NA \n Q \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 0 \n Kelly, Mr. James \n 0 \n 0 \n 363592 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Kennedy, Mr. John \n 0 \n 0 \n 368783 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Khalil, Mr. Betros \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kiernan, Mr. John \n 1 \n 0 \n 367227 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kiernan, Mr. Philip \n 1 \n 0 \n 367229 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n 0 \n 0 \n 36865 \n 7.7375 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Kink, Miss. Maria \n 2 \n 0 \n 315152 \n 8.6625 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Kink, Mr. Vincenz \n 2 \n 0 \n 315151 \n 8.6625 \n NA \n S \n \n \n female \n 4.0000 \n 4.00000 \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n 0 \n 2 \n 315153 \n 22.0250 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n 3 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n 1 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n 1 \n 1 \n 350405 \n 12.1833 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Klasen, Mr. Klas Albin \n 1 \n 1 \n 350404 \n 7.8542 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n 0 \n 2 \n 350405 \n 12.1833 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kraeff, Mr. Theodor \n 0 \n 0 \n 349253 \n 7.8958 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Krekorian, Mr. Neshan \n 0 \n 0 \n 2654 \n 7.2292 \n F E57 \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lahoud, Mr. Sarkis \n 0 \n 0 \n 2624 \n 7.2250 \n NA \n C \n \n \n female \n 37.0000 \n 37.00000 \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n 0 \n 0 \n 4135 \n 9.5875 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Laleff, Mr. Kristo \n 0 \n 0 \n 349217 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Lam, Mr. Ali \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lam, Mr. Len \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n 0 \n 0 \n C 7077 \n 7.2500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lane, Mr. Patrick \n 0 \n 0 \n 7935 \n 7.7500 \n NA \n Q \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 1 \n Lang, Mr. Fang \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Larsson, Mr. August Viktor \n 0 \n 0 \n 7545 \n 9.4833 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n 0 \n 0 \n 347067 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n 0 \n 0 \n 347065 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n 0 \n 0 \n 2620 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Miss. Ida \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Miss. Jeannie \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Miss. Mathilde \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n 0 \n 4 \n 4133 \n 25.4667 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n 0 \n 0 \n STON/O 2. 3101292 \n 7.9250 \n NA \n S \n \n \n male \n 34.5000 \n 34.50000 \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n 0 \n 0 \n 2683 \n 6.4375 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lennon, Miss. Mary \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lennon, Mr. Denis \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Leonard, Mr. Lionel \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Lester, Mr. James \n 0 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Lievens, Mr. Rene Aime \n 0 \n 0 \n 345781 \n 9.5000 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n 0 \n 0 \n 347071 \n 7.7750 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n 0 \n 0 \n 347073 \n 7.7500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Lindqvist, Mr. Eino William \n 1 \n 0 \n STON/O 2. 3101285 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Linehan, Mr. Michael \n 0 \n 0 \n 330971 \n 7.8792 \n NA \n Q \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Ling, Mr. Lee \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lithman, Mr. Simon \n 0 \n 0 \n S.O./P.P. 251 \n 7.5500 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Lobb, Mr. William Arthur \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lockyer, Mr. Edward \n 0 \n 0 \n 1222 \n 7.8792 \n NA \n S \n \n \n male \n 20.5000 \n 20.50000 \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n 0 \n 0 \n A/5 21173 \n 7.2500 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 1 \n Lulic, Mr. Nikola \n 0 \n 0 \n 315098 \n 8.6625 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n 0 \n 0 \n 347743 \n 7.0542 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 1 \n Lundin, Miss. Olga Elida \n 0 \n 0 \n 347469 \n 7.8542 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n 0 \n 0 \n 350403 \n 7.5792 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n 0 \n 0 \n 349235 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n MacKay, Mr. George William \n 0 \n 0 \n C.A. 42795 \n 7.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n 0 \n 0 \n 370370 \n 7.7500 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n 0 \n 0 \n C 17369 \n 7.1417 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n 0 \n 0 \n STON/O 2. 3101275 \n 7.1250 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n 0 \n 0 \n 330924 \n 7.8792 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mahon, Mr. John \n 0 \n 0 \n AQ/4 3130 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Maisner, Mr. Simon \n 0 \n 0 \n A/S 2816 \n 8.0500 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n 0 \n 0 \n STON/O 2. 3101268 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Mamee, Mr. Hanna \n 0 \n 0 \n 2677 \n 7.2292 \n NA \n C \n \n \n female \n 30.5000 \n 30.50000 \n 3 \n 0 \n Mangan, Miss. Mary \n 0 \n 0 \n 364850 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Mannion, Miss. Margareth \n 0 \n 0 \n 36866 \n 7.7375 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n 0 \n 0 \n 2655 \n 7.2292 \n F E46 \n C \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Markoff, Mr. Marin \n 0 \n 0 \n 349213 \n 7.8958 \n NA \n C \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Markun, Mr. Johann \n 0 \n 0 \n 349257 \n 7.8958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Masselmani, Mrs. Fatima \n 0 \n 0 \n 2649 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Matinoff, Mr. Nicola \n 0 \n 0 \n 349255 \n 7.8958 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n 0 \n 0 \n 383123 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n 0 \n 0 \n 367228 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McCoy, Miss. Agnes \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McCoy, Miss. Alicia \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n McCoy, Mr. Bernard \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n 0 \n 0 \n 330932 \n 7.7875 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n McEvoy, Mr. Michael \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McGovern, Miss. Mary \n 0 \n 0 \n 330931 \n 7.8792 \n NA \n Q \n \n \n female \n 15.0000 \n 15.00000 \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n 0 \n 0 \n 330923 \n 8.0292 \n NA \n Q \n \n \n female \n 35.0000 \n 35.00000 \n 3 \n 0 \n McGowan, Miss. Katherine \n 0 \n 0 \n 9232 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n McMahon, Mr. Martin \n 0 \n 0 \n 370372 \n 7.7500 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n McNamee, Mr. Neal \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n McNeill, Miss. Bridget \n 0 \n 0 \n 370368 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n 0 \n 0 \n SOTON/O.Q. 392087 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n 0 \n 0 \n 343095 \n 8.0500 \n NA \n S \n \n \n male \n 55.5000 \n 55.50000 \n 3 \n 0 \n Meo, Mr. Alfonzo \n 0 \n 0 \n A.5. 11206 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mernagh, Mr. Robert \n 0 \n 0 \n 368703 \n 7.7500 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n 0 \n 0 \n 345501 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Miles, Mr. Frank \n 0 \n 0 \n 359306 \n 8.0500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Mineff, Mr. Ivan \n 0 \n 0 \n 349233 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Minkoff, Mr. Lazar \n 0 \n 0 \n 349211 \n 7.8958 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n 0 \n 0 \n 349207 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mitkoff, Mr. Mito \n 0 \n 0 \n 349221 \n 7.8958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n 0 \n 0 \n 330980 \n 7.8792 \n NA \n Q \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n 0 \n 0 \n 348123 \n 7.6500 \n F G73 \n S \n \n \n male \n 6.0000 \n 6.00000 \n 3 \n 1 \n Moor, Master. Meier \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 1 \n Moor, Mrs. (Beila) \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moore, Mr. Leonard Charles \n 0 \n 0 \n A4. 54510 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Moran, Miss. Bertha \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moran, Mr. Daniel J \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moran, Mr. James \n 0 \n 0 \n 330877 \n 8.4583 \n NA \n Q \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Morley, Mr. William \n 0 \n 0 \n 364506 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n 0 \n 0 \n 372622 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Moss, Mr. Albert Johan \n 0 \n 0 \n 312991 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Moubarek, Master. Gerios \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n 0 \n 2 \n 2661 \n 15.2458 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n 0 \n 0 \n 2626 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n 0 \n 0 \n 374746 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n 0 \n 0 \n 35852 \n 7.7333 \n NA \n Q \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n 0 \n 0 \n 382653 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Murdlin, Mr. Joseph \n 0 \n 0 \n A./5. 3235 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Murphy, Miss. Nora \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n 0 \n 0 \n 347078 \n 7.7500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Naidenoff, Mr. Penko \n 0 \n 0 \n 349206 \n 7.8958 \n NA \n S \n \n \n female \n 15.0000 \n 15.00000 \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n 0 \n 0 \n 2667 \n 7.2250 \n NA \n C \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n 0 \n 2 \n 2653 \n 15.7417 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Nakid, Mr. Sahid \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Nancarrow, Mr. William Henry \n 0 \n 0 \n A./5. 3338 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Nankoff, Mr. Minko \n 0 \n 0 \n 349218 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Nasr, Mr. Mustafa \n 0 \n 0 \n 2652 \n 7.2292 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Naughton, Miss. Hannah \n 0 \n 0 \n 365237 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Nenkoff, Mr. Christo \n 0 \n 0 \n 349234 \n 7.8958 \n NA \n S \n \n \n male \n 12.0000 \n 12.00000 \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n female \n 14.0000 \n 14.00000 \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n 0 \n 0 \n 3101297 \n 7.9250 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Niklasson, Mr. Samuel \n 0 \n 0 \n 363611 \n 8.0500 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n 0 \n 0 \n 347066 \n 7.7750 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n 0 \n 0 \n 347470 \n 7.8542 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n 0 \n 0 \n 350410 \n 7.8542 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n 0 \n 0 \n SOTON/O2 3101272 \n 7.1250 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 1 \n Niskanen, Mr. Juha \n 0 \n 0 \n STON/O 2. 3101289 \n 7.9250 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n 0 \n 0 \n A/4. 39886 \n 7.8000 \n NA \n S \n \n \n male \n 28.5000 \n 28.50000 \n 3 \n 0 \n Novel, Mr. Mansouer \n 0 \n 0 \n 2697 \n 7.2292 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n 0 \n 0 \n 347081 \n 7.7500 \n NA \n S \n \n \n male \n 61.0000 \n 61.00000 \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n 0 \n 0 \n 345364 \n 6.2375 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Brien, Mr. Thomas \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Brien, Mr. Timothy \n 0 \n 0 \n 330979 \n 7.8292 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Connell, Mr. Patrick D \n 0 \n 0 \n 334912 \n 7.7333 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Connor, Mr. Maurice \n 0 \n 0 \n 371060 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Connor, Mr. Patrick \n 0 \n 0 \n 366713 \n 7.7500 \n NA \n Q \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Odahl, Mr. Nils Martin \n 0 \n 0 \n 7267 \n 9.2250 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n 0 \n 0 \n 364856 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n 0 \n 0 \n 14311 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n 0 \n 0 \n 330959 \n 7.8792 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Ohman, Miss. Velin \n 0 \n 0 \n 347085 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n O'Keefe, Mr. Patrick \n 0 \n 0 \n 368402 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n 0 \n 0 \n 330919 \n 7.8292 \n NA \n Q \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 1 \n Olsen, Master. Artur Karl \n 0 \n 1 \n C 17368 \n 3.1708 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Olsen, Mr. Henry Margido \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n 0 \n 1 \n 4579 \n 8.4042 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Olsen, Mr. Ole Martin \n 0 \n 0 \n Fa 265302 \n 7.3125 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 0 \n Olsson, Miss. Elina \n 0 \n 0 \n 350407 \n 7.8542 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n 0 \n 0 \n 347464 \n 7.8542 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n 0 \n 0 \n 347079 \n 7.7750 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n 0 \n 0 \n 6563 \n 9.2250 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 0 \n Oreskovic, Miss. Jelka \n 0 \n 0 \n 315085 \n 8.6625 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 3 \n 0 \n Oreskovic, Miss. Marija \n 0 \n 0 \n 315096 \n 8.6625 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Oreskovic, Mr. Luka \n 0 \n 0 \n 315094 \n 8.6625 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Osen, Mr. Olaf Elon \n 0 \n 0 \n 7534 \n 9.2167 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 1 \n Osman, Mrs. Mara \n 0 \n 0 \n 349244 \n 8.6833 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n 0 \n 0 \n 330909 \n 7.6292 \n NA \n Q \n \n \n male \n 2.0000 \n 2.00000 \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n male \n 6.0000 \n 6.00000 \n 3 \n 0 \n Palsson, Master. Paul Folke \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n female \n 3.0000 \n 3.00000 \n 3 \n 0 \n Palsson, Miss. Stina Viola \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n female \n 8.0000 \n 8.00000 \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n 0 \n 4 \n 349909 \n 21.0750 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 3 \n 0 \n Panula, Master. Eino Viljami \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 7.0000 \n 7.00000 \n 3 \n 0 \n Panula, Master. Juha Niilo \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 2.0000 \n 2.00000 \n 3 \n 0 \n Panula, Master. Urho Abraham \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 14.0000 \n 14.00000 \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n female \n 41.0000 \n 41.00000 \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n 0 \n 5 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Pasic, Mr. Jakob \n 0 \n 0 \n 315097 \n 8.6625 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Patchett, Mr. George \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Paulner, Mr. Uscher \n 0 \n 0 \n 3411 \n 8.7125 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Pavlovic, Mr. Stefo \n 0 \n 0 \n 349242 \n 7.8958 \n NA \n S \n \n \n male \n 0.7500 \n 0.75000 \n 3 \n 0 \n Peacock, Master. Alfred Edward \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n female \n 3.0000 \n 3.00000 \n 3 \n 0 \n Peacock, Miss. Treasteall \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n 0 \n 2 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Pearce, Mr. Ernest \n 0 \n 0 \n 343271 \n 7.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Pedersen, Mr. Olaf \n 0 \n 0 \n 345498 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Peduzzi, Mr. Joseph \n 0 \n 0 \n A/5 2817 \n 8.0500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n 0 \n 0 \n STON/O 2. 3101294 \n 7.9250 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n 0 \n 0 \n STON/O 2. 3101291 \n 7.9250 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Perkin, Mr. John Henry \n 0 \n 0 \n A/5 21174 \n 7.2500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n 1 \n 0 \n 347083 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Peter, Master. Michael J \n 1 \n 1 \n 2668 \n 22.3583 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Peter, Miss. Anna \n 1 \n 1 \n 2668 \n 22.3583 \n F E69 \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n 0 \n 2 \n 2668 \n 22.3583 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Peters, Miss. Katie \n 0 \n 0 \n 330935 \n 8.1375 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Petersen, Mr. Marius \n 0 \n 0 \n 342441 \n 8.0500 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 3 \n 0 \n Petranec, Miss. Matilda \n 0 \n 0 \n 349245 \n 7.8958 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Petroff, Mr. Nedelio \n 0 \n 0 \n 349212 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n 0 \n 0 \n 349215 \n 7.8958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Petterson, Mr. Johan Emil \n 1 \n 0 \n 347076 \n 7.7750 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n 0 \n 0 \n 347087 \n 7.7750 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n 0 \n 0 \n SOTON/O.Q. 392078 \n 8.0500 \n E10 \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n 0 \n 0 \n 349227 \n 7.8958 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Pokrnic, Mr. Mate \n 0 \n 0 \n 315095 \n 8.6625 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Pokrnic, Mr. Tome \n 0 \n 0 \n 315092 \n 8.6625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Radeff, Mr. Alexander \n 0 \n 0 \n 349223 \n 7.8958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n 0 \n 0 \n 65305 \n 8.1125 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Razi, Mr. Raihed \n 0 \n 0 \n 2629 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Reed, Mr. James George \n 0 \n 0 \n 362316 \n 7.2500 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 3 \n 0 \n Rekic, Mr. Tido \n 0 \n 0 \n 349249 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Reynolds, Mr. Harold J \n 0 \n 0 \n 342684 \n 8.0500 \n NA \n S \n \n \n male \n 10.0000 \n 10.00000 \n 3 \n 0 \n Rice, Master. Albert \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 0 \n Rice, Master. Arthur \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 7.0000 \n 7.00000 \n 3 \n 0 \n Rice, Master. Eric \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 2.0000 \n 2.00000 \n 3 \n 0 \n Rice, Master. Eugene \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 8.0000 \n 8.00000 \n 3 \n 0 \n Rice, Master. George Hugh \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n female \n 39.0000 \n 39.00000 \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n 0 \n 5 \n 382652 \n 29.1250 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n 0 \n 0 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Rintamaki, Mr. Matti \n 0 \n 0 \n STON/O 2. 3101273 \n 7.1250 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n 0 \n 0 \n 334915 \n 7.7208 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Risien, Mr. Samuel Beard \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 3 \n 0 \n Robins, Mr. Alexander A \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n female \n 47.0000 \n 47.00000 \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Rogers, Mr. William John \n 0 \n 0 \n S.C./A.4. 23567 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n 0 \n 0 \n 312993 \n 7.7750 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n female \n 41.0000 \n 41.00000 \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n 0 \n 2 \n 370129 \n 20.2125 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Roth, Miss. Sarah A \n 0 \n 0 \n 342712 \n 8.0500 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 3 \n 0 \n Rouse, Mr. Richard Henry \n 0 \n 0 \n A/5 3594 \n 8.0500 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Rush, Mr. Alfred George John \n 0 \n 0 \n A/4. 20589 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Ryan, Mr. Edward \n 0 \n 0 \n 383162 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ryan, Mr. Patrick \n 0 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Saad, Mr. Amin \n 0 \n 0 \n 2671 \n 7.2292 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Saad, Mr. Khalil \n 0 \n 0 \n 2672 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Saade, Mr. Jean Nassr \n 0 \n 0 \n 2676 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sadlier, Mr. Matthew \n 0 \n 0 \n 367655 \n 7.7292 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sadowitz, Mr. Harry \n 0 \n 0 \n LP 1588 \n 7.5750 \n NA \n S \n \n \n male \n 38.5000 \n 38.50000 \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n 0 \n 0 \n SOTON/O.Q. 3101262 \n 7.2500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Master. Thomas Henry \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n 14.5000 \n 14.50000 \n 3 \n 0 \n Sage, Master. William Henry \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Ada \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Constance Gladys \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Stella Anna \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. Frederick \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. George John Jr \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. John George \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Salander, Mr. Karl Johan \n 0 \n 0 \n 7266 \n 9.3250 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n 0 \n 0 \n 343120 \n 7.6500 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Salonen, Mr. Johan Werner \n 0 \n 0 \n 3101296 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Samaan, Mr. Elias \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Samaan, Mr. Hanna \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Samaan, Mr. Youssef \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n 0 \n 2 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n female \n 4.0000 \n 4.00000 \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Sap, Mr. Julius \n 0 \n 0 \n 345768 \n 9.5000 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Saundercock, Mr. William Henry \n 0 \n 0 \n A/5. 2151 \n 8.0500 \n NA \n S \n \n \n male \n 24.5000 \n 24.50000 \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n 0 \n 0 \n 342826 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Scanlan, Mr. James \n 0 \n 0 \n 36209 \n 7.7250 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sdycoff, Mr. Todor \n 0 \n 0 \n 349222 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n 0 \n 0 \n 370374 \n 7.7500 \n NA \n Q \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n 0 \n 0 \n 345779 \n 9.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Shellard, Mr. Frederick William \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n 0 \n 0 \n 330968 \n 7.7792 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n 0 \n 0 \n 374910 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Simmons, Mr. John \n 0 \n 0 \n SOTON/OQ 392082 \n 8.0500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Sirayanian, Mr. Orsen \n 0 \n 0 \n 2669 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sirota, Mr. Maurice \n 0 \n 0 \n 392092 \n 8.0500 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Sivic, Mr. Husein \n 0 \n 0 \n 349251 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n 0 \n 0 \n STON/O 2. 3101280 \n 7.9250 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n 0 \n 0 \n 3101265 \n 7.4958 \n NA \n S \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 0 \n Skoog, Master. Harald \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n male \n 10.0000 \n 10.00000 \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Skoog, Miss. Mabel \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Skoog, Mr. Wilhelm \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Slabenoff, Mr. Petco \n 0 \n 0 \n 349214 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n 0 \n 0 \n SOTON/OQ 392086 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Smiljanic, Mr. Mile \n 0 \n 0 \n 315037 \n 8.6625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Smith, Mr. Thomas \n 0 \n 0 \n 384461 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Smyth, Miss. Julia \n 0 \n 0 \n 335432 \n 7.7333 \n NA \n Q \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n 0 \n 0 \n 348124 \n 7.6500 \n F G73 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Somerton, Mr. Francis William \n 0 \n 0 \n A.5. 18509 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Spector, Mr. Woolf \n 0 \n 0 \n A.5. 3236 \n 8.0500 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Spinner, Mr. Henry John \n 0 \n 0 \n STON/OQ. 369943 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Staneff, Mr. Ivan \n 0 \n 0 \n 349208 \n 7.8958 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Stankovic, Mr. Ivan \n 0 \n 0 \n 349239 \n 8.6625 \n NA \n C \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n 0 \n 0 \n CA. 2314 \n 7.5500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Stanley, Mr. Edward Roland \n 0 \n 0 \n A/4 45380 \n 8.0500 \n NA \n S \n \n \n male \n 60.5000 \n 60.50000 \n 3 \n 0 \n Storey, Mr. Thomas \n 0 \n 0 \n 3701 \n NA \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n 0 \n 0 \n 349205 \n 7.8958 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n 0 \n 0 \n 7553 \n 9.8375 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 1 \n Stranden, Mr. Juho \n 0 \n 0 \n STON/O 2. 3101288 \n 7.9250 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Strilic, Mr. Ivan \n 0 \n 0 \n 315083 \n 8.6625 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Strom, Miss. Telma Matilda \n 0 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n 1 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n 0 \n 0 \n SOTON/OQ 392089 \n 8.0500 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 1 \n Sundman, Mr. Johan Julian \n 0 \n 0 \n STON/O 2. 3101269 \n 7.9250 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n 0 \n 0 \n SOTON/OQ 392076 \n 7.0500 \n NA \n S \n \n \n male \n 74.0000 \n 74.00000 \n 3 \n 0 \n Svensson, Mr. Johan \n 0 \n 0 \n 347060 \n 7.7750 \n NA \n S \n \n \n male \n 14.0000 \n 14.00000 \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n 0 \n 0 \n 7538 \n 9.2250 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Svensson, Mr. Olof \n 0 \n 0 \n 350035 \n 7.7958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n 0 \n 0 \n 350033 \n 7.7958 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n 0 \n 0 \n 363294 \n 8.0500 \n NA \n S \n \n \n male \n 0.4167 \n 0.41670 \n 3 \n 1 \n Thomas, Master. Assad Alexander \n 0 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomas, Mr. Charles P \n 1 \n 0 \n 2621 \n 6.4375 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomas, Mr. John \n 0 \n 0 \n 2681 \n 6.4375 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomas, Mr. Tannous \n 0 \n 0 \n 2684 \n 7.2250 \n NA \n C \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n 1 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n 0 \n 0 \n 32302 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thorneycroft, Mr. Percival \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Tikkanen, Mr. Juho \n 0 \n 0 \n STON/O 2. 3101293 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Tobin, Mr. Roger \n 0 \n 0 \n 383121 \n 7.7500 \n F38 \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Todoroff, Mr. Lalio \n 0 \n 0 \n 349216 \n 7.8958 \n NA \n S \n \n \n male \n 30.5000 \n 30.50000 \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n 0 \n 0 \n 364499 \n 8.0500 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 0 \n Torber, Mr. Ernst William \n 0 \n 0 \n 364511 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Torfa, Mr. Assad \n 0 \n 0 \n 2673 \n 7.2292 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Tornquist, Mr. William Henry \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Toufik, Mr. Nakli \n 0 \n 0 \n 2641 \n 7.2292 \n NA \n C \n \n \n male \n 7.0000 \n 7.00000 \n 3 \n 1 \n Touma, Master. Georges Youssef \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 1 \n Touma, Miss. Maria Youssef \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n 0 \n 2 \n 2650 \n 15.2458 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Turcin, Mr. Stjepan \n 0 \n 0 \n 349247 \n 7.8958 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Turja, Miss. Anna Sofia \n 0 \n 0 \n 4138 \n 9.8417 \n NA \n S \n \n \n female \n 63.0000 \n 63.00000 \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n 0 \n 0 \n 4134 \n 9.5875 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n van Billiard, Master. James William \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n male \n 11.5000 \n 11.50000 \n 3 \n 0 \n van Billiard, Master. Walter John \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n male \n 40.5000 \n 40.50000 \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n 0 \n 2 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n female \n 10.0000 \n 10.00000 \n 3 \n 0 \n Van Impe, Miss. Catharina \n 0 \n 2 \n 345773 \n 24.1500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n 0 \n 0 \n 345777 \n 9.5000 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n 0 \n 0 \n 345780 \n 9.5000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n 0 \n 0 \n 345770 \n 9.5000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n 0 \n 0 \n 345783 \n 9.5000 \n NA \n S \n \n \n male \n 47.0000 \n 47.00000 \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n 0 \n 0 \n 345765 \n 9.0000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Vander Planke, Mr. Julius \n 3 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n 1 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 1 \n Vartanian, Mr. David \n 0 \n 0 \n 2658 \n 7.2250 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n 0 \n 0 \n 350416 \n 7.8542 \n NA \n S \n \n \n female \n 14.0000 \n 14.00000 \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n 0 \n 0 \n 350406 \n 7.8542 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Vovk, Mr. Janko \n 0 \n 0 \n 349252 \n 7.8958 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Waelens, Mr. Achille \n 0 \n 0 \n 345767 \n 9.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ware, Mr. Frederick \n 0 \n 0 \n 359309 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Warren, Mr. Charles William \n 0 \n 0 \n C.A. 49867 \n 7.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Webber, Mr. James \n 0 \n 0 \n SOTON/OQ 3101316 \n 8.0500 \n NA \n S \n \n \n male \n 32.5000 \n 32.50000 \n 3 \n 0 \n Wenzel, Mr. Linhart \n 0 \n 0 \n 345775 \n 9.5000 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n 0 \n 0 \n 2688 \n 7.2292 \n NA \n C \n \n \n male \n 51.0000 \n 51.00000 \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n 0 \n 0 \n 347064 \n 7.7500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n 1 \n 0 \n 3101267 \n 6.4958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n 1 \n 0 \n 3101266 \n 6.4958 \n NA \n S \n \n \n female \n 47.0000 \n 47.00000 \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n 1 \n 0 \n 363272 \n 7.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n 0 \n 0 \n 3410 \n 8.7125 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Willey, Mr. Edward \n 0 \n 0 \n S.O./P.P. 751 \n 7.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n 0 \n 0 \n A/5 2466 \n 8.0500 \n NA \n S \n \n \n male \n 28.5000 \n 28.50000 \n 3 \n 0 \n Williams, Mr. Leslie \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Windelov, Mr. Einar \n 0 \n 0 \n SOTON/OQ 3101317 \n 7.2500 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Wirz, Mr. Albert \n 0 \n 0 \n 315154 \n 8.6625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Wiseman, Mr. Phillippe \n 0 \n 0 \n A/4. 34244 \n 7.2500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Wittevrongel, Mr. Camille \n 0 \n 0 \n 345771 \n 9.5000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Yasbeck, Mr. Antoni \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n female \n 15.0000 \n 15.00000 \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n male \n 45.5000 \n 45.50000 \n 3 \n 0 \n Youseff, Mr. Gerious \n 0 \n 0 \n 2628 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Yousif, Mr. Wazli \n 0 \n 0 \n 2647 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Yousseff, Mr. Gerious \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n female \n 14.5000 \n 14.50000 \n 3 \n 0 \n Zabour, Miss. Hileni \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Zabour, Miss. Thamine \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n male \n 26.5000 \n 26.50000 \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n 0 \n 0 \n 2656 \n 7.2250 \n NA \n C \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Zakarian, Mr. Ortin \n 0 \n 0 \n 2670 \n 7.2250 \n NA \n C \n \n \n\n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Zimmerman, Mr. Leo \n 0 \n 0 \n 315082 \n 7.8750 \n NA \n S \n
\n\nWe can see these these are columns,\n\n* **Pclass**: Passenger’s class, 1 = 1st (Upper), 2 = 2nd(Middle), 3 = 3rd(Lower)\n* **Survived**: Survived (1) or died (0), 0 = No, 1 = Yes\n* **Name**: Passenger’s name\n* **Sex**: Passenger’s sex\n* **Age**: Passenger’s age\n* **SibSp**: Number of siblings/spouses aboard\n* **Parch**: Number of parents/children aboard\n* **Ticket**: Ticket number\n* **Fare**: Fare\n* **Cabin**: Cabin number\n* **Embarked**: Port of embarkation, C = Cherbourg, Q = Queenstown, S = Southampton\n\n\nWe can see more details on the [Data Dictionary](https://www.kaggle.com/c/titanic/data)\n\n# Loops\n\nLoops are a fundamental concept in traditional programming languages. \n\nA loop is a way to repeat a number of commands until a given condition is met.\n\nThis repetition of code is called **iteration**.\n\nA repetitive action could be \"create several similar plots\".\n\nWithin a loop, any other code can be run to produce anything we want such as plots, models, reports, and datasets.\n\nSince R is a vectorised language, loops are not as prominently used in R as in Python or other programming languages. Despite this, they are a key part of programming in general and can save you a large amount of time and typing in certain cases.\n\nThey allow you to automate parts of your code that are in need of repetition.\n\nSimilar to how functions help make our code more abstract and general, loops perform a similar purpose. We are essentially simplifying a specific case of code to a more general case.\n\nWe are going to look at `for` loops first. \n\n## For Loops\n\nThese are the most common type of loop the other type is a `while` loop which can do the same things, but in a slightly different way.\n\nFor loops follow the basic structure below.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Basic Structure of a loop\n\n# Creating the loop\nfor (each_item in my_iterable) { \n \n output <- commands\n }\n```\n:::\n\n\n\n\n* We start the loop with the word `for`,\n\n* Followed by `()` brackets where we first specify an index variable, `i` is commonly used but it can be anything that you want. Remember, we want to use clear and descriptive variable names. This is a place holder and corresponds to each different element as we move through the loop,\n\n* Then the word `in`.\n\n* Then specify an iterable. This could be a `vector`, a `list`, a `dataframe` etc. An iterable is any object that can be iterated through, one element at a time. \n\n* Followed by the `{}` curly brackets, which will have our commands within, these could be multiple lines of code.\n\n### Example\n\nLet's look at an example.\n\nWe start by creating an iterable, I have created a vector with the numbers **0 through 5**.\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector\n\nexample_vector <- c(0, 1, 2, 3, 4, 5)\n```\n:::\n\n\n\n\nWe can then create our loop which doubles every value and prints it out.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating the loop\n\nfor (each_number in example_vector) {\n \n # Print the value at each step\n print(each_number * 2)\n \n }\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 0\n[1] 2\n[1] 4\n[1] 6\n[1] 8\n[1] 10\n```\n\n\n:::\n:::\n\n\n\n\n\n\\\n\n\n\n\nIn the above example we simply printed our results in the console, if we wanted to store our result, we can simply create a data structure of our choice and use the append function, as shown below.\n\n\nThe keyword `for` is followed by a variable that refers to each item in my iterable. I’ve called this variable **`each_number`**. It is good to be clear and explicit when naming variables, so they explain what the variable is. \n\nThe keyword `in` is followed by the iterable I want to loop over - `example_vector`.\n\nThe output of my command is appended to `result`. The command here is to multiply each number in `example_vector` by 2. The **`append()`** function simply adds an element to the end of a vector. We first specify the vector we want to add to which is `result` and then specify the values that we want to add to it. Within the function this is set to the parameter `values`.\n\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Create an empty output\n# Which we will fill when the loop runs\n\nresult <- c()\n\n# Creating the loop\n\nfor (each_number in example_vector) {\n \n # Print the value at each step\n print(each_number * 2)\n \n result <- append(result, values = each_number * 2)\n \n}\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 0\n[1] 2\n[1] 4\n[1] 6\n[1] 8\n[1] 10\n```\n\n\n:::\n\n```{.r .cell-code}\n# To display the data\n\nresult\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 0 2 4 6 8 10\n```\n\n\n:::\n:::\n\n\n\n\n\n\n
\n\n\nAlthough it is useful to know how to use loops in R, it is often faster to accomplish the same thing using vectorised operations in R. \n\nWe already saw examples in the Vector Arithmetic section. A vectorised function is a function that will apply the same operation on each element of the vectors.\n\nFor example:\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Creating a vector\n\nexample_vector <- 1:5\n\n# Using a sqrt() function on our vector\n\nsqrt(example_vector)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 1.000000 1.414214 1.732051 2.000000 2.236068\n```\n\n\n:::\n:::\n\n\n\n\n
\n\nTo make this calculation, there is no need for a loop. However, not all functions work this way. \n\nWhile there are many functions out there that vectorise particular calculations, there are still some tasks that cannot be vectorised. This is where iteration becomes useful. While we should always be looking to vectorise calculations, we can take comfort knowing that we have a back up tool to use just in case it fails us.\n\nWe also have while loops, which are used to loop until a specific condition is met. \n\nYou can a find a tutorial on them here: [While Loop](https://www.datamentor.io/r-programming/while-loop/).\n\n\n\n### Exercise 1\n\n::: {.panel-tabset}\n\n#### Exercise\n\n1. You are given a vector of measurements that are grams (g). \n\n For this exercise, we want to convert all of these measurements to kilograms (kg). \n\n **For reference, 1kg is equal to 1000 grams.**\n\n Using a for loop, create and append to a new vector called **kilograms** that contains the values converted to kilograms.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Vector \n\ngrams <- c(100000, 7899900, 967312, 49185, 6100)\n```\n:::\n\n\n\n\n\n#### Hint\n\nPlease note below is pseudocode, that is the 'recipie' for getting the answer.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Starting vector\n\ngrams <- c(100000, 7899900, 967312, 49185, 6100)\n\n# Empty vector for result storage\n\nkilograms <- c()\n\n# For loop\n\nfor (each_number in vector) {\n \n convert to kilograms\n \n append result to kilograms\n}\n\n\n# To display the data\n\nkilograms\n```\n:::\n\n\n\n\n#### Answer\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Starting vector\n\ngrams <- c(100000, 7899900, 967312, 49185, 6100)\n\n# Empty vector for result storage\n\nkilograms <- c()\n\n# For loop\n\nfor (measurement in grams) {\n # Converting grams to kg\n converted_kilogram <- measurement / 1000 \n \n # Appending to kilo_grams result vector\n kilograms <- append(kilograms, values = converted_kilogram) \n \n}\n\n# To display the data\n\nkilograms\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n[1] 100.000 7899.900 967.312 49.185 6.100\n```\n\n\n:::\n:::\n\n\n\n\n:::\n\n\n\n### Extension Exercise\n\nIf you would like to go deeper into for loops before moving on, try the extension exercise below.\n\n::: {.panel-tabset}\n\n#### Exercise\n\n1. Complete the code below, Use a for loop to load all the files in the data folder. Some steps have been given to you already.\n\n* We have loaded the packages tidyverse and fs\n\n* We then use the function `fs::dir_ls()` which will give a list of all the file paths in the data folder, we have assgined this to `file paths`.\n\n* We have created an empty list called `my_datasets` which we fill with out datasets after the loop runs.\n\n* Your task is to create a for loop to loop through the `file_paths` and store each dataset as an element in the list `my_datasets`\n\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Loading packages\n\nlibrary(tidyverse) # For loading data and manipulation of data\nlibrary(fs) # File system\n\n\n# Get a list of the file paths\nfile_paths <- fs::dir_ls(\"Data\") \n\n# Display the file paths\nfile_paths\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nData/bikes_data_set.csv Data/imdb_scores.csv Data/netflix_data.csv \nData/police_data.xlsx Data/revenue_data_set.csv Data/titanic.csv \nData/titanic_clean.csv \n```\n\n\n:::\n\n```{.r .cell-code}\n# Create a list to store all the dataframes\nmy_datasets <- list()\n```\n:::\n\n\n\n\n#### Hint\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Loading packages\n\nlibrary(tidyverse) # For loading data and manipulation of data\nlibrary(fs) # File system\n\n\n# Get a list of the file paths\nfile_paths <- fs::dir_ls(\"Data\") \n\n# Display the file paths\nfile_paths\n\n# Create a list to store all the dataframes\nmy_datasets <- list()\n\n\n# Loop through file paths and store in the list\n\nfor (each_file_path in file_paths){\n \n # adding a new element in the my datasets list\n my_datasets <- command \n }\n```\n:::\n\n\n\n\n#### Show Answer\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(tidyverse) # For loading data and manipulation of data\nlibrary(fs) # File system\n\n\n# Get a list of the file paths\nfile_paths <- fs::dir_ls(\"Data\") \n\n# Display the file paths\nfile_paths\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nData/bikes_data_set.csv Data/imdb_scores.csv Data/netflix_data.csv \nData/police_data.xlsx Data/revenue_data_set.csv Data/titanic.csv \nData/titanic_clean.csv \n```\n\n\n:::\n\n```{.r .cell-code}\n# Create a list to store all the dataframes\nmy_datasets <- list()\n\n# Loop through file paths and store in the list\n\nfor (each_file_path in file_paths){\n \n # adding a new element in the my datasets list\n my_datasets[[each_file_path]] <- readr::read_csv(file = file_paths[[each_file_path]])\n}\n\n# To display the list of dataframes\ndplyr::glimpse(my_datasets)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nList of 7\n $ Data/bikes_data_set.csv : spc_tbl_ [737 × 12] (S3: spec_tbl_df/tbl_df/tbl/data.frame)\n ..$ Date : chr [1:737] \"04/01/2015\" \"05/01/2015\" \"04/01/2015\" \"05/01/2015\" ...\n ..$ real Temperature : num [1:737] 2.75 9 2.75 9 NA NA 8 9 9 9 ...\n ..$ empty column : logi [1:737] NA NA NA NA NA NA ...\n ..$ Feel Temperature : num [1:737] 0 7.25 0 7.25 NA NA 5.75 5.5 6.75 6.75 ...\n ..$ Humidity : num [1:737] 93 81.5 93 81.5 NA ...\n ..$ Wind Speed : num [1:737] 7.5 8.85 7.5 8.85 NA ...\n ..$ weather code : chr [1:737] \"broken_clouds\" \"broken_clouds\" \"broken_clouds\" \"broken_clouds\" ...\n ..$ DO NOT TOUCH THIS COLUMN: logi [1:737] NA NA NA NA NA NA ...\n ..$ is holiday : logi [1:737] FALSE FALSE FALSE FALSE NA NA ...\n ..$ is weekend : logi [1:737] TRUE FALSE TRUE FALSE NA NA ...\n ..$ season : chr [1:737] \"winter\" \"winter\" \"winter\" \"winter\" ...\n ..$ count : num [1:737] 9234 20372 9234 20372 NA ...\n ..- attr(*, \"spec\")=\n .. .. cols(\n .. .. Date = col_character(),\n .. .. `real Temperature` = col_double(),\n .. .. `empty column` = col_logical(),\n .. .. `Feel Temperature` = col_double(),\n .. .. Humidity = col_double(),\n .. .. `Wind Speed` = col_double(),\n .. .. `weather code` = col_character(),\n .. .. `DO NOT TOUCH THIS COLUMN` = col_logical(),\n .. .. `is holiday` = col_logical(),\n .. .. `is weekend` = col_logical(),\n .. .. season = col_character(),\n .. .. count = col_double()\n .. .. )\n ..- attr(*, \"problems\")=\n \n
\n \n \n\n pclass \n survived \n name_of_passenger \n sex_of_passenger \n age_of_passenger \n imputed_age_of_passenger \n sibsp \n parch \n ticket \n fare \n cabin \n embarked \n \n \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n 24160 \n 211.3375 \n B5 \n S \n \n \n 1 \n 1 \n Allison, Master. Hudson Trevor \n male \n 0.9167 \n 0.91670 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 0 \n Allison, Miss. Helen Loraine \n female \n 2.0000 \n 2.00000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n male \n 30.0000 \n 30.00000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n female \n 25.0000 \n 25.00000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n 1 \n 1 \n Anderson, Mr. Harry \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n 19952 \n 26.5500 \n E12 \n S \n \n \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n female \n 63.0000 \n 63.00000 \n 1 \n 0 \n 13502 \n 77.9583 \n D7 \n S \n \n \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n male \n NA \n 29.79431 \n 0 \n 0 \n 112050 \n 0.0000 \n A36 \n S \n \n \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n female \n NA \n 29.79431 \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17609 \n 49.5042 \n NA \n C \n \n \n 1 \n 0 \n Astor, Col. John Jacob \n male \n NA \n 29.79431 \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n 19877 \n 78.8500 \n NA \n S \n \n \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n male \n 80.0000 \n 80.00000 \n 0 \n 0 \n 27042 \n 30.0000 \n A23 \n S \n \n \n 1 \n 0 \n Baumann, Mr. John D \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17318 \n 25.9250 \n NA \n S \n \n \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n male \n 24.0000 \n 24.00000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n female \n 50.0000 \n 50.00000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n 1 \n 1 \n Bazzani, Miss. Albina \n female \n 32.0000 \n 32.00000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n 1 \n 0 \n Beattie, Mr. Thomson \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n male \n 37.0000 \n 37.00000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n female \n 47.0000 \n 47.00000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n 1 \n 1 \n Behr, Mr. Karl Howell \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 111369 \n 30.0000 \n C148 \n C \n \n \n 1 \n 1 \n Bidois, Miss. Rosalie \n female \n 42.0000 \n 42.00000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n 1 \n 1 \n Bird, Miss. Ellen \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n PC 17483 \n 221.7792 \n C97 \n S \n \n \n 1 \n 0 \n Birnbaum, Mr. Jakob \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 13905 \n 26.0000 \n NA \n C \n \n \n 1 \n 1 \n Bishop, Mr. Dickinson H \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n 1 \n 1 \n Bissette, Miss. Amelia \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C99 \n S \n \n \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 110564 \n 26.5500 \n C52 \n S \n \n \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 113784 \n 35.5000 \n T \n S \n \n \n 1 \n 1 \n Blank, Mr. Henry \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 112277 \n 31.0000 \n A31 \n C \n \n \n 1 \n 1 \n Bonnell, Miss. Caroline \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 36928 \n 164.8667 \n C7 \n S \n \n \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n female \n 58.0000 \n 58.00000 \n 0 \n 0 \n 113783 \n 26.5500 \n C103 \n S \n \n \n 1 \n 0 \n Borebank, Mr. John James \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 110489 \n 26.5500 \n D22 \n S \n \n \n 1 \n 1 \n Bowen, Miss. Grace Scott \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n NA \n C \n \n \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n female \n 22.0000 \n 22.00000 \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n male \n NA \n 29.79431 \n 0 \n 0 \n 111427 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Brady, Mr. John Bertram \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n 113054 \n 30.5000 \n A21 \n S \n \n \n 1 \n 0 \n Brandeis, Mr. Emil \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n PC 17591 \n 50.4958 \n B10 \n C \n \n \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n male \n NA \n 29.79431 \n 0 \n 0 \n 112379 \n 39.6000 \n NA \n C \n \n \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n female \n 44.0000 \n 44.00000 \n 0 \n 0 \n PC 17610 \n 27.7208 \n B4 \n C \n \n \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n female \n 59.0000 \n 59.00000 \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n female \n 60.0000 \n 60.00000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n female \n 41.0000 \n 41.00000 \n 0 \n 0 \n 16966 \n 134.5000 \n E40 \n C \n \n \n 1 \n 0 \n Butt, Major. Archibald Willingham \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 113050 \n 26.5500 \n B38 \n S \n \n \n 1 \n 0 \n Cairns, Mr. Alexander \n male \n NA \n 29.79431 \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n S \n \n \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n PC 17476 \n 26.2875 \n E24 \n S \n \n \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n female \n 53.0000 \n 53.00000 \n 0 \n 0 \n PC 17606 \n 27.4458 \n NA \n C \n \n \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n male \n 36.0000 \n 36.00000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n female \n 58.0000 \n 58.00000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 695 \n 5.0000 \n B51 B53 B55 \n S \n \n \n 1 \n 0 \n Carrau, Mr. Francisco M \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n 1 \n 1 \n Carter, Master. William Thornton II \n male \n 11.0000 \n 11.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 1 \n Carter, Miss. Lucile Polk \n female \n 14.0000 \n 14.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 1 \n Carter, Mr. William Ernest \n male \n 36.0000 \n 36.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n female \n 36.0000 \n 36.00000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n 1 \n 0 \n Case, Mr. Howard Brown \n male \n 49.0000 \n 49.00000 \n 0 \n 0 \n 19924 \n 26.0000 \n NA \n S \n \n \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n female \n NA \n 29.79431 \n 0 \n 0 \n 17770 \n 27.7208 \n NA \n C \n \n \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n female \n 76.0000 \n 76.00000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n female \n 47.0000 \n 47.00000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n female \n 33.0000 \n 33.00000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n 1 \n 1 \n Chaudanson, Miss. Victorine \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n B61 \n C \n \n \n 1 \n 1 \n Cherry, Miss. Gladys \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n PC 17594 \n 29.7000 \n A9 \n C \n \n \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n female \n NA \n 29.79431 \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n male \n NA \n 29.79431 \n 0 \n 0 \n 112051 \n 0.0000 \n NA \n S \n \n \n 1 \n 0 \n Clark, Mr. Walter Miller \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n female \n 26.0000 \n 26.00000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n 1 \n 1 \n Cleaver, Miss. Alice \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n 1 \n 0 \n Clifford, Mr. George Quincy \n male \n NA \n 29.79431 \n 0 \n 0 \n 110465 \n 52.0000 \n A14 \n S \n \n \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 5727 \n 25.5875 \n E58 \n S \n \n \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E49 \n C \n \n \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n male \n 37.0000 \n 37.00000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E52 \n C \n \n \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n female \n 64.0000 \n 64.00000 \n 0 \n 2 \n PC 17756 \n 83.1583 \n E45 \n C \n \n \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n female \n 55.0000 \n 55.00000 \n 2 \n 0 \n 11770 \n 25.7000 \n C101 \n S \n \n \n 1 \n 0 \n Crafton, Mr. John Bertram \n male \n NA \n 29.79431 \n 0 \n 0 \n 113791 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n male \n 70.0000 \n 70.00000 \n 1 \n 1 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n 1 \n 1 \n Crosby, Miss. Harriet R \n female \n 36.0000 \n 36.00000 \n 0 \n 2 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n female \n 64.0000 \n 64.00000 \n 1 \n 1 \n 112901 \n 26.5500 \n B26 \n S \n \n \n 1 \n 0 \n Cumings, Mr. John Bradley \n male \n 39.0000 \n 39.00000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n female \n 38.0000 \n 38.00000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n 1 \n 1 \n Daly, Mr. Peter Denis \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 113055 \n 26.5500 \n E17 \n S \n \n \n 1 \n 1 \n Daniel, Mr. Robert Williams \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 113804 \n 30.5000 \n NA \n S \n \n \n 1 \n 1 \n Daniels, Miss. Sarah \n female \n 33.0000 \n 33.00000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n 1 \n 0 \n Davidson, Mr. Thornton \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n female \n 27.0000 \n 27.00000 \n 1 \n 2 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n 1 \n 1 \n Dick, Mr. Albert Adrian \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n female \n 17.0000 \n 17.00000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n 1 \n 1 \n Dodge, Dr. Washington \n male \n 53.0000 \n 53.00000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n 1 \n 1 \n Dodge, Master. Washington \n male \n 4.0000 \n 4.00000 \n 0 \n 2 \n 33638 \n 81.8583 \n A34 \n S \n \n \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n 1 \n 0 \n Douglas, Mr. Walter Donald \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n female \n 27.0000 \n 27.00000 \n 1 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n female \n 48.0000 \n 48.00000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n female \n 48.0000 \n 48.00000 \n 1 \n 0 \n 11755 \n 39.6000 \n A16 \n C \n \n \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n PC 17485 \n 56.9292 \n A20 \n C \n \n \n 1 \n 0 \n Dulles, Mr. William Crothers \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n PC 17580 \n 29.7000 \n A18 \n C \n \n \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n female \n 23.0000 \n 23.00000 \n 0 \n 1 \n 11767 \n 83.1583 \n C54 \n C \n \n \n 1 \n 1 \n Endres, Miss. Caroline Louise \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n C45 \n C \n \n \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n female \n 54.0000 \n 54.00000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n 1 \n 0 \n Evans, Miss. Edith Corse \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17531 \n 31.6792 \n A29 \n C \n \n \n 1 \n 0 \n Farthing, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17483 \n 221.7792 \n C95 \n S \n \n \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n female \n NA \n 29.79431 \n 0 \n 0 \n PC 17598 \n 31.6833 \n NA \n S \n \n \n 1 \n 1 \n Fleming, Miss. Margaret \n female \n NA \n 29.79431 \n 0 \n 0 \n 17421 \n 110.8833 \n NA \n C \n \n \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17474 \n 26.3875 \n E25 \n S \n \n \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 113051 \n 27.7500 \n C111 \n C \n \n \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n female \n 24.0000 \n 24.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n female \n 28.0000 \n 28.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n female \n 23.0000 \n 23.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n male \n 19.0000 \n 19.00000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 0 \n Fortune, Mr. Mark \n male \n 64.0000 \n 64.00000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n female \n 60.0000 \n 60.00000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n PC 17485 \n 56.9292 \n E36 \n C \n \n \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n male \n NA \n 29.79431 \n 0 \n 0 \n 113778 \n 26.5500 \n D34 \n S \n \n \n 1 \n 1 \n Frauenthal, Dr. Henry William \n male \n 50.0000 \n 50.00000 \n 2 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n male \n 43.0000 \n 43.00000 \n 1 \n 0 \n 17765 \n 27.7208 \n D40 \n C \n \n \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n female \n NA \n 29.79431 \n 1 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n female \n 22.0000 \n 22.00000 \n 0 \n 2 \n 13568 \n 49.5000 \n B39 \n C \n \n \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n male \n 60.0000 \n 60.00000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n 1 \n 0 \n Fry, Mr. Richard \n male \n NA \n 29.79431 \n 0 \n 0 \n 112058 \n 0.0000 \n B102 \n S \n \n \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n 1 \n 0 \n Gee, Mr. Arthur H \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 111320 \n 38.5000 \n E63 \n S \n \n \n 1 \n 1 \n Geiger, Miss. Amalie \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n 113503 \n 211.5000 \n C130 \n C \n \n \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n female \n 22.0000 \n 22.00000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n female \n 45.0000 \n 45.00000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n 1 \n 0 \n Giglio, Mr. Victor \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B86 \n C \n \n \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n female \n NA \n 29.79431 \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n 1 \n 0 \n Goldschmidt, Mr. George B \n male \n 71.0000 \n 71.00000 \n 0 \n 0 \n PC 17754 \n 34.6542 \n A5 \n C \n \n \n 1 \n 1 \n Gracie, Col. Archibald IV \n male \n 53.0000 \n 53.00000 \n 0 \n 0 \n 113780 \n 28.5000 \n C51 \n C \n \n \n 1 \n 1 \n Graham, Miss. Margaret Edith \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 112053 \n 30.0000 \n B42 \n S \n \n \n 1 \n 0 \n Graham, Mr. George Edward \n male \n 38.0000 \n 38.00000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C91 \n S \n \n \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n female \n 58.0000 \n 58.00000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n 1 \n 1 \n Greenfield, Mr. William Bertram \n male \n 23.0000 \n 23.00000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n female \n 45.0000 \n 45.00000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B82 B84 \n C \n \n \n 1 \n 1 \n Harder, Mr. George Achilles \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n female \n 25.0000 \n 25.00000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n male \n 48.0000 \n 48.00000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n female \n 49.0000 \n 49.00000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n 1 \n 0 \n Harrington, Mr. Charles H \n male \n NA \n 29.79431 \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n 1 \n 0 \n Harrison, Mr. William \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 112059 \n 0.0000 \n B94 \n S \n \n \n 1 \n 1 \n Hassab, Mr. Hammad \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n PC 17572 \n 76.7292 \n D49 \n C \n \n \n 1 \n 1 \n Hawksford, Mr. Walter James \n male \n NA \n 29.79431 \n 0 \n 0 \n 16988 \n 30.0000 \n D45 \n S \n \n \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 11767 \n 83.1583 \n C54 \n C \n \n \n 1 \n 0 \n Hays, Mr. Charles Melville \n male \n 55.0000 \n 55.00000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n female \n 52.0000 \n 52.00000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n 1 \n 0 \n Head, Mr. Christopher \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 113038 \n 42.5000 \n B11 \n S \n \n \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n male \n NA \n 29.79431 \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n 1 \n 0 \n Hipkins, Mr. William Edward \n male \n 55.0000 \n 55.00000 \n 0 \n 0 \n 680 \n 50.0000 \n C39 \n S \n \n \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n female \n 16.0000 \n 16.00000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n female \n 44.0000 \n 44.00000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n female \n 51.0000 \n 51.00000 \n 1 \n 0 \n 13502 \n 77.9583 \n D11 \n S \n \n \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 111426 \n 26.5500 \n NA \n C \n \n \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n 1 \n 0 \n Hoyt, Mr. William Fisher \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17600 \n 30.6958 \n NA \n C \n \n \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n 1 \n 1 \n Icard, Miss. Amelie \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n female \n 50.0000 \n 50.00000 \n 0 \n 0 \n PC 17595 \n 28.7125 \n C49 \n C \n \n \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n male \n 49.0000 \n 49.00000 \n 0 \n 0 \n 112058 \n 0.0000 \n B52 B54 B56 \n S \n \n \n 1 \n 0 \n Jones, Mr. Charles Cresson \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n 694 \n 26.0000 \n NA \n S \n \n \n 1 \n 0 \n Julian, Mr. Henry Forbes \n male \n 50.0000 \n 50.00000 \n 0 \n 0 \n 113044 \n 26.0000 \n E60 \n S \n \n \n 1 \n 0 \n Keeping, Mr. Edwin \n male \n 32.5000 \n 32.50000 \n 0 \n 0 \n 113503 \n 211.5000 \n C132 \n C \n \n \n 1 \n 0 \n Kent, Mr. Edward Austin \n male \n 58.0000 \n 58.00000 \n 0 \n 0 \n 11771 \n 29.7000 \n B37 \n C \n \n \n 1 \n 0 \n Kenyon, Mr. Frederick R \n male \n 41.0000 \n 41.00000 \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n female \n NA \n 29.79431 \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n female \n 45.0000 \n 45.00000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n 1 \n 0 \n Klaber, Mr. Herman \n male \n NA \n 29.79431 \n 0 \n 0 \n 113028 \n 26.5500 \n C124 \n S \n \n \n 1 \n 1 \n Kreuchen, Miss. Emilie \n female \n 39.0000 \n 39.00000 \n 0 \n 0 \n 24160 \n 211.3375 \n NA \n S \n \n \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n female \n 49.0000 \n 49.00000 \n 0 \n 0 \n 17465 \n 25.9292 \n D17 \n S \n \n \n 1 \n 1 \n LeRoy, Miss. Bertha \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n PC 17761 \n 106.4250 \n NA \n C \n \n \n 1 \n 1 \n Lesurer, Mr. Gustave J \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n B101 \n C \n \n \n 1 \n 0 \n Lewy, Mr. Ervin G \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17612 \n 27.7208 \n NA \n C \n \n \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 17475 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n female \n 55.0000 \n 55.00000 \n 0 \n 0 \n 112377 \n 27.7208 \n NA \n C \n \n \n 1 \n 1 \n Lines, Miss. Mary Conover \n female \n 16.0000 \n 16.00000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n female \n 51.0000 \n 51.00000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n 1 \n 0 \n Long, Mr. Milton Clyde \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 113501 \n 30.0000 \n D6 \n S \n \n \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 13502 \n 77.9583 \n D9 \n S \n \n \n 1 \n 0 \n Loring, Mr. Joseph Holland \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 113801 \n 45.5000 \n NA \n S \n \n \n 1 \n 1 \n Lurette, Miss. Elise \n female \n 58.0000 \n 58.00000 \n 0 \n 0 \n PC 17569 \n 146.5208 \n B80 \n C \n \n \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n female \n 15.0000 \n 15.00000 \n 0 \n 1 \n 24160 \n 211.3375 \n B5 \n S \n \n \n 1 \n 0 \n Maguire, Mr. John Edward \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 110469 \n 26.0000 \n C106 \n S \n \n \n 1 \n 1 \n Maioni, Miss. Roberta \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 110152 \n 86.5000 \n B79 \n S \n \n \n 1 \n 1 \n Marechal, Mr. Pierre \n male \n NA \n 29.79431 \n 0 \n 0 \n 11774 \n 29.7000 \n C47 \n C \n \n \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n male \n 19.0000 \n 19.00000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17482 \n 49.5042 \n C90 \n C \n \n \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n 1 \n 0 \n McCarthy, Mr. Timothy J \n male \n 54.0000 \n 54.00000 \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n 1 \n 1 \n McGough, Mr. James Robert \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17473 \n 26.2875 \n E25 \n S \n \n \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n female \n NA \n 29.79431 \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n 1 \n 0 \n Millet, Mr. Francis Davis \n male \n 65.0000 \n 65.00000 \n 0 \n 0 \n 13509 \n 26.5500 \n E38 \n S \n \n \n 1 \n 0 \n Minahan, Dr. William Edward \n male \n 44.0000 \n 44.00000 \n 2 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n 1 \n 1 \n Minahan, Miss. Daisy E \n female \n 33.0000 \n 33.00000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n female \n 37.0000 \n 37.00000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n 13236 \n 57.7500 \n C78 \n C \n \n \n 1 \n 0 \n Molson, Mr. Harry Markland \n male \n 55.0000 \n 55.00000 \n 0 \n 0 \n 113787 \n 30.5000 \n C30 \n S \n \n \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n 1 \n 0 \n Natsch, Mr. Charles H \n male \n 37.0000 \n 37.00000 \n 0 \n 1 \n PC 17596 \n 29.7000 \n C118 \n C \n \n \n 1 \n 1 \n Newell, Miss. Madeleine \n female \n 31.0000 \n 31.00000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n 1 \n 1 \n Newell, Miss. Marjorie \n female \n 23.0000 \n 23.00000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n 1 \n 0 \n Newell, Mr. Arthur Webster \n male \n 58.0000 \n 58.00000 \n 0 \n 2 \n 35273 \n 113.2750 \n D48 \n C \n \n \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n female \n 19.0000 \n 19.00000 \n 0 \n 2 \n 11752 \n 26.2833 \n D47 \n S \n \n \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n male \n 64.0000 \n 64.00000 \n 0 \n 0 \n 693 \n 26.0000 \n NA \n S \n \n \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n female \n 39.0000 \n 39.00000 \n 0 \n 0 \n PC 17758 \n 108.9000 \n C105 \n C \n \n \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n male \n NA \n 29.79431 \n 0 \n 0 \n F.C. 12998 \n 25.7417 \n NA \n C \n \n \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n female \n 22.0000 \n 22.00000 \n 0 \n 1 \n 113509 \n 61.9792 \n B36 \n C \n \n \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n male \n 65.0000 \n 65.00000 \n 0 \n 1 \n 113509 \n 61.9792 \n B30 \n C \n \n \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n male \n 28.5000 \n 28.50000 \n 0 \n 0 \n PC 17562 \n 27.7208 \n D43 \n C \n \n \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n male \n NA \n 29.79431 \n 0 \n 0 \n 112052 \n 0.0000 \n NA \n S \n \n \n 1 \n 0 \n Partner, Mr. Austen \n male \n 45.5000 \n 45.50000 \n 0 \n 0 \n 113043 \n 28.5000 \n C124 \n S \n \n \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 12749 \n 93.5000 \n B24 \n S \n \n \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n female \n 22.0000 \n 22.00000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n female \n 17.0000 \n 17.00000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n 1 \n 1 \n Perreault, Miss. Anne \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 12749 \n 93.5000 \n B73 \n S \n \n \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n male \n 52.0000 \n 52.00000 \n 0 \n 0 \n 113786 \n 30.5000 \n C104 \n S \n \n \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 110465 \n 52.0000 \n C110 \n S \n \n \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n female \n 56.0000 \n 56.00000 \n 0 \n 1 \n 11767 \n 83.1583 \n C50 \n C \n \n \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n 19972 \n 0.0000 \n NA \n S \n \n \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17607 \n 39.6000 \n NA \n S \n \n \n 1 \n 0 \n Ringhini, Mr. Sante \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n NA \n C \n \n \n 1 \n 0 \n Robbins, Mr. Victor \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n female \n 43.0000 \n 43.00000 \n 0 \n 1 \n 24160 \n 211.3375 \n B3 \n S \n \n \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n PC 17590 \n 50.4958 \n A24 \n S \n \n \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 111428 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n male \n NA \n 29.79431 \n 0 \n 0 \n 113767 \n 50.0000 \n A32 \n S \n \n \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n female \n 33.0000 \n 33.00000 \n 0 \n 0 \n PC 17613 \n 27.7208 \n A11 \n C \n \n \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n 1 \n 0 \n Ross, Mr. John Hugo \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 13049 \n 40.1250 \n A10 \n C \n \n \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n female \n 33.0000 \n 33.00000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n 1 \n 0 \n Rothschild, Mr. Martin \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n female \n 54.0000 \n 54.00000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n 1 \n 0 \n Rowe, Mr. Alfred G \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 113790 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Ryerson, Master. John Borie \n male \n 13.0000 \n 13.00000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n female \n 18.0000 \n 18.00000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n female \n 21.0000 \n 21.00000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n male \n 61.0000 \n 61.00000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n female \n 48.0000 \n 48.00000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n male \n NA \n 29.79431 \n 0 \n 0 \n 19988 \n 30.5000 \n C106 \n S \n \n \n 1 \n 1 \n Sagesser, Mlle. Emma \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n 1 \n 1 \n Salomon, Mr. Abraham L \n male \n NA \n 29.79431 \n 0 \n 0 \n 111163 \n 26.0000 \n NA \n S \n \n \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n female \n 35.0000 \n 35.00000 \n 1 \n 0 \n 13236 \n 57.7500 \n C28 \n C \n \n \n 1 \n 1 \n Serepeca, Miss. Augusta \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n C \n \n \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 113794 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n female \n 40.0000 \n 40.00000 \n 0 \n 0 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17475 \n 26.2875 \n E24 \n S \n \n \n 1 \n 0 \n Silvey, Mr. William Baird \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n female \n 39.0000 \n 39.00000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n male \n 56.0000 \n 56.00000 \n 0 \n 0 \n 13213 \n 35.5000 \n A26 \n C \n \n \n 1 \n 1 \n Sloper, Mr. William Thompson \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 113788 \n 35.5000 \n A6 \n S \n \n \n 1 \n 0 \n Smart, Mr. John Montgomery \n male \n 56.0000 \n 56.00000 \n 0 \n 0 \n 113792 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Smith, Mr. James Clinch \n male \n 56.0000 \n 56.00000 \n 0 \n 0 \n 17764 \n 30.6958 \n A7 \n C \n \n \n 1 \n 0 \n Smith, Mr. Lucien Philip \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n 1 \n 0 \n Smith, Mr. Richard William \n male \n NA \n 29.79431 \n 0 \n 0 \n 113056 \n 26.0000 \n A19 \n S \n \n \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n female \n 23.0000 \n 23.00000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n 1 \n 1 \n Spedden, Master. Robert Douglas \n male \n 6.0000 \n 6.00000 \n 0 \n 2 \n 16966 \n 134.5000 \n E34 \n C \n \n \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n 1 \n 0 \n Spencer, Mr. William Augustus \n male \n 57.0000 \n 57.00000 \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n female \n NA \n 29.79431 \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 13214 \n 30.5000 \n B50 \n C \n \n \n 1 \n 0 \n Stead, Mr. William Thomas \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n 113514 \n 26.5500 \n C87 \n S \n \n \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n female \n 43.0000 \n 43.00000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n female \n 52.0000 \n 52.00000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n 1 \n 0 \n Stewart, Mr. Albert A \n male \n NA \n 29.79431 \n 0 \n 0 \n PC 17605 \n 27.7208 \n NA \n C \n \n \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n female \n 62.0000 \n 62.00000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n 1 \n 0 \n Straus, Mr. Isidor \n male \n 67.0000 \n 67.00000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n female \n 63.0000 \n 63.00000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n 1 \n 0 \n Sutton, Mr. Frederick \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 36963 \n 32.3208 \n D50 \n S \n \n \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n female \n 48.0000 \n 48.00000 \n 0 \n 0 \n 17466 \n 25.9292 \n D17 \n S \n \n \n 1 \n 1 \n Taussig, Miss. Ruth \n female \n 18.0000 \n 18.00000 \n 0 \n 2 \n 110413 \n 79.6500 \n E68 \n S \n \n \n 1 \n 0 \n Taussig, Mr. Emil \n male \n 52.0000 \n 52.00000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n male \n 48.0000 \n 48.00000 \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n female \n NA \n 29.79431 \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n 1 \n 0 \n Thayer, Mr. John Borland \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n male \n 17.0000 \n 17.00000 \n 0 \n 2 \n 17421 \n 110.8833 \n C70 \n C \n \n \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n female \n NA \n 29.79431 \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 2543 \n 28.5375 \n C53 \n C \n \n \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n PC 17601 \n 27.7208 \n NA \n C \n \n \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 111240 \n 33.5000 \n B19 \n S \n \n \n 1 \n 0 \n Walker, Mr. William Anderson \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 36967 \n 34.0208 \n D46 \n S \n \n \n 1 \n 1 \n Ward, Miss. Anna \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n NA \n C \n \n \n 1 \n 0 \n Warren, Mr. Frank Manley \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n female \n 60.0000 \n 60.00000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n 1 \n 0 \n Weir, Col. John \n male \n 60.0000 \n 60.00000 \n 0 \n 0 \n 113800 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n White, Mr. Percival Wayland \n male \n 54.0000 \n 54.00000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n 1 \n 0 \n White, Mr. Richard Frasar \n male \n 21.0000 \n 21.00000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n female \n 55.0000 \n 55.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n 1 \n 1 \n Wick, Miss. Mary Natalie \n female \n 31.0000 \n 31.00000 \n 0 \n 2 \n 36928 \n 164.8667 \n C7 \n S \n \n \n 1 \n 0 \n Wick, Mr. George Dennick \n male \n 57.0000 \n 57.00000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n 1 \n 0 \n Widener, Mr. George Dunton \n male \n 50.0000 \n 50.00000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n 1 \n 0 \n Widener, Mr. Harry Elkins \n male \n 27.0000 \n 27.00000 \n 0 \n 2 \n 113503 \n 211.5000 \n C82 \n C \n \n \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n female \n 50.0000 \n 50.00000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n 1 \n 1 \n Willard, Miss. Constance \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 113795 \n 26.5500 \n NA \n S \n \n \n 1 \n 0 \n Williams, Mr. Charles Duane \n male \n 51.0000 \n 51.00000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n 1 \n 1 \n Williams, Mr. Richard Norris II \n male \n 21.0000 \n 21.00000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n male \n NA \n 29.79431 \n 0 \n 0 \n 113510 \n 35.0000 \n C128 \n S \n \n \n 1 \n 1 \n Wilson, Miss. Helen Alice \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n 16966 \n 134.5000 \n E39 E41 \n C \n \n \n 1 \n 1 \n Woolner, Mr. Hugh \n male \n NA \n 29.79431 \n 0 \n 0 \n 19947 \n 35.5000 \n C52 \n S \n \n \n 1 \n 0 \n Wright, Mr. George \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n 113807 \n 26.5500 \n NA \n S \n \n \n 1 \n 1 \n Young, Miss. Marie Grice \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n 2 \n 0 \n Abelson, Mr. Samuel \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n female \n 28.0000 \n 28.00000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 248744 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 231945 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n C.A. 34050 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Angle, Mr. William A \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n female \n 36.0000 \n 36.00000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Ashby, Mr. John \n male \n 57.0000 \n 57.00000 \n 0 \n 0 \n 244346 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 29108 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n C.A. 31030 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n 28551 \n 13.0000 \n D \n S \n \n \n 2 \n 0 \n Banfield, Mr. Frederick James \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n C.A./SOTON 34068 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Bateman, Rev. Robert James \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n S.O.P. 1166 \n 12.5250 \n NA \n S \n \n \n 2 \n 1 \n Beane, Mr. Edward \n male \n 32.0000 \n 32.00000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Beauchamp, Mr. Henry James \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Becker, Master. Richard F \n male \n 1.0000 \n 1.00000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Becker, Miss. Marion Louise \n female \n 4.0000 \n 4.00000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n female \n 12.0000 \n 12.00000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n female \n 36.0000 \n 36.00000 \n 0 \n 3 \n 230136 \n 39.0000 \n F4 \n S \n \n \n 2 \n 1 \n Beesley, Mr. Lawrence \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 248698 \n 13.0000 \n D56 \n S \n \n \n 2 \n 1 \n Bentham, Miss. Lilian W \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28404 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Berriman, Mr. William John \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 28425 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Botsford, Mr. William Hull \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 237670 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Bowenur, Mr. Solomon \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 211535 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Bracken, Mr. James H \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 220367 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 248733 \n 13.0000 \n F33 \n S \n \n \n 2 \n 1 \n Brown, Miss. Edith Eileen \n female \n 15.0000 \n 15.00000 \n 0 \n 2 \n 29750 \n 39.0000 \n NA \n S \n \n \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n male \n 60.0000 \n 60.00000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n female \n 20.0000 \n 20.00000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Buss, Miss. Kate \n female \n 36.0000 \n 36.00000 \n 0 \n 0 \n 27849 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 234686 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 244310 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n female \n 42.0000 \n 42.00000 \n 0 \n 0 \n 236852 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Caldwell, Master. Alden Gates \n male \n 0.8333 \n 0.83330 \n 0 \n 2 \n 248738 \n 29.0000 \n NA \n S \n \n \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n male \n 26.0000 \n 26.00000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n 2 \n 1 \n Cameron, Miss. Clear Annie \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Campbell, Mr. William \n male \n NA \n 29.79431 \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n 2 \n 0 \n Carbines, Mr. William \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28424 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n female \n 44.0000 \n 44.00000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Chapman, Mr. Charles Henry \n male \n 52.0000 \n 52.00000 \n 0 \n 0 \n 248731 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Chapman, Mr. John Henry \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Christy, Miss. Julie Rachel \n female \n 25.0000 \n 25.00000 \n 1 \n 1 \n 237789 \n 30.0000 \n NA \n S \n \n \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n female \n 45.0000 \n 45.00000 \n 0 \n 2 \n 237789 \n 30.0000 \n NA \n S \n \n \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n female \n 28.0000 \n 28.00000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n W./C. 14263 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 248740 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 28034 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n female \n 8.0000 \n 8.00000 \n 0 \n 2 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n 2 \n 0 \n Collyer, Mr. Harvey \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n W./C. 14266 \n 10.5000 \n F33 \n S \n \n \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 237249 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n female \n NA \n 29.79431 \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 29107 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n male \n NA \n 29.79431 \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n 2 \n 1 \n Davies, Master. John Morgan Jr \n male \n 8.0000 \n 8.00000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 0 \n Davies, Mr. Charles Henry \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n female \n 48.0000 \n 48.00000 \n 0 \n 2 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 1 \n Davis, Miss. Mary \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 237668 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 244360 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Deacon, Mr. Percy William \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n female \n 24.0000 \n 24.00000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n 2 \n 0 \n Denbury, Mr. Herbert \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n 2 \n 0 \n Dibden, Mr. William \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 1 \n Doling, Miss. Elsie \n female \n 18.0000 \n 18.00000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n female \n 34.0000 \n 34.00000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n 2 \n 0 \n Downton, Mr. William James \n male \n 54.0000 \n 54.00000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Drew, Master. Marshall Brines \n male \n 8.0000 \n 8.00000 \n 0 \n 2 \n 28220 \n 32.5000 \n NA \n S \n \n \n 2 \n 0 \n Drew, Mr. James Vivian \n male \n 42.0000 \n 42.00000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n female \n 34.0000 \n 34.00000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n 2 \n 1 \n Duran y More, Miss. Asuncion \n female \n 27.0000 \n 27.00000 \n 1 \n 0 \n SC/PARIS 2149 \n 13.8583 \n NA \n C \n \n \n 2 \n 1 \n Duran y More, Miss. Florentina \n female \n 30.0000 \n 30.00000 \n 1 \n 0 \n SC/PARIS 2148 \n 13.8583 \n NA \n C \n \n \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 29751 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Enander, Mr. Ingvar \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 236854 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 236171 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Faunthorpe, Mr. Harry \n male \n 40.0000 \n 40.00000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n C.A. 15185 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 229236 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n male \n NA \n 29.79431 \n 0 \n 0 \n 239854 \n 0.0000 \n NA \n S \n \n \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n 237671 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Fynney, Mr. Joseph J \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Gale, Mr. Harry \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Gale, Mr. Shadrach \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Garside, Miss. Ethel \n female \n 34.0000 \n 34.00000 \n 0 \n 0 \n 243880 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Gaskell, Mr. Alfred \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Gavey, Mr. Lawrence \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 31028 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Gilbert, Mr. William \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n C.A. 30769 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Giles, Mr. Edgar \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n 28133 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Giles, Mr. Frederick Edward \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n 28134 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Giles, Mr. Ralph \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 248726 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Gill, Mr. John William \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 233866 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Gillespie, Mr. William Henry \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 12233 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 250646 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Greenberg, Mr. Samuel \n male \n 52.0000 \n 52.00000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Hale, Mr. Reginald \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 250653 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Hamalainen, Master. Viljo \n male \n 0.6667 \n 0.66670 \n 1 \n 1 \n 250649 \n 14.5000 \n NA \n S \n \n \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n female \n 24.0000 \n 24.00000 \n 0 \n 2 \n 250649 \n 14.5000 \n NA \n S \n \n \n 2 \n 0 \n Harbeck, Mr. William H \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n 248746 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n female \n 6.0000 \n 6.00000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n 2 \n 0 \n Harper, Rev. John \n male \n 28.0000 \n 28.00000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n 2 \n 1 \n Harris, Mr. George \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n S.W./PP 752 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Harris, Mr. Walter \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n W/C 14208 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Hart, Miss. Eva Miriam \n female \n 7.0000 \n 7.00000 \n 0 \n 2 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n 2 \n 0 \n Hart, Mr. Benjamin \n male \n 43.0000 \n 43.00000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n 2 \n 1 \n Herman, Miss. Alice \n female \n 24.0000 \n 24.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Herman, Miss. Kate \n female \n 24.0000 \n 24.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 0 \n Herman, Mr. Samuel \n male \n 49.0000 \n 49.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n female \n 48.0000 \n 48.00000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n female \n 55.0000 \n 55.00000 \n 0 \n 0 \n 248706 \n 16.0000 \n NA \n S \n \n \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n Hickman, Mr. Lewis \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n Hickman, Mr. Stanley George \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 0 \n Hiltunen, Miss. Marta \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n 250650 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n 29105 \n 23.0000 \n NA \n S \n \n \n 2 \n 0 \n Hocking, Mr. Richard George \n male \n 23.0000 \n 23.00000 \n 2 \n 1 \n 29104 \n 11.5000 \n NA \n S \n \n \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 242963 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n female \n 54.0000 \n 54.00000 \n 1 \n 3 \n 29105 \n 23.0000 \n NA \n S \n \n \n 2 \n 0 \n Hodges, Mr. Henry Price \n male \n 50.0000 \n 50.00000 \n 0 \n 0 \n 250643 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Hold, Mr. Stephen \n male \n 44.0000 \n 44.00000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n 2 \n 1 \n Hosono, Mr. Masabumi \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 237798 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Howard, Mr. Benjamin \n male \n 63.0000 \n 63.00000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n female \n 60.0000 \n 60.00000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Hunt, Mr. George Henry \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n SCO/W 1585 \n 12.2750 \n NA \n S \n \n \n 2 \n 1 \n Ilett, Miss. Bertha \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n SO/C 14885 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n 243847 \n 27.0000 \n NA \n S \n \n \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n 243847 \n 27.0000 \n NA \n S \n \n \n 2 \n 0 \n Jarvis, Mr. John Denzil \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 237565 \n 15.0000 \n NA \n S \n \n \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n male \n 22.0000 \n 22.00000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n C.A. 33111 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n SC/AH Basle 541 \n 13.7917 \n D \n C \n \n \n 2 \n 0 \n Kantor, Mr. Sinai \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n female \n 24.0000 \n 24.00000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Keane, Miss. Nora A \n female \n NA \n 29.79431 \n 0 \n 0 \n 226593 \n 12.3500 \n E101 \n Q \n \n \n 2 \n 0 \n Keane, Mr. Daniel \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 233734 \n 12.3500 \n NA \n Q \n \n \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n 223596 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n male \n 57.0000 \n 57.00000 \n 0 \n 0 \n 219533 \n 12.3500 \n NA \n Q \n \n \n 2 \n 0 \n Knight, Mr. Robert J \n male \n NA \n 29.79431 \n 0 \n 0 \n 239855 \n 0.0000 \n NA \n S \n \n \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n C.A. 18723 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Lahtinen, Rev. William \n male \n 30.0000 \n 30.00000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Lamb, Mr. John Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n 240261 \n 10.7083 \n NA \n Q \n \n \n 2 \n 1 \n Laroche, Miss. Louise \n female \n 1.0000 \n 1.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n female \n 3.0000 \n 3.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n male \n 25.0000 \n 25.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n female \n 22.0000 \n 22.00000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n 2 \n 1 \n Lehmann, Miss. Bertha \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n SC 1748 \n 12.0000 \n NA \n C \n \n \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n female \n NA \n 29.79431 \n 0 \n 0 \n 248727 \n 33.0000 \n NA \n S \n \n \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n female \n 34.0000 \n 34.00000 \n 0 \n 0 \n C.A. 34260 \n 10.5000 \n F33 \n S \n \n \n 2 \n 0 \n Levy, Mr. Rene Jacques \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n SC/Paris 2163 \n 12.8750 \n D \n C \n \n \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n C.A. 29566 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Lingane, Mr. John \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 235509 \n 12.3500 \n NA \n Q \n \n \n 2 \n 0 \n Louch, Mr. Charles Alexander \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n female \n 42.0000 \n 42.00000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Mack, Mrs. (Mary) \n female \n 57.0000 \n 57.00000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n E77 \n S \n \n \n 2 \n 0 \n Malachard, Mr. Noel \n male \n NA \n 29.79431 \n 0 \n 0 \n 237735 \n 15.0458 \n D \n C \n \n \n 2 \n 1 \n Mallet, Master. Andre \n male \n 1.0000 \n 1.00000 \n 0 \n 2 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n 2 \n 0 \n Mallet, Mr. Albert \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/A.3 2861 \n 15.5792 \n NA \n C \n \n \n 2 \n 0 \n Matthews, Mr. William John \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 28228 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 239059 \n 16.0000 \n NA \n S \n \n \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 237216 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n McCrie, Mr. James Matthew \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 233478 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n McKane, Mr. Peter David \n male \n 46.0000 \n 46.00000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n female \n 13.0000 \n 13.00000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n female \n 41.0000 \n 41.00000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n 2 \n 1 \n Mellors, Mr. William John \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n SW/PP 751 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Meyer, Mr. August \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 248723 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Milling, Mr. Jacob Christian \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n 234360 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n male \n 70.0000 \n 70.00000 \n 0 \n 0 \n C.A. 24580 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Montvila, Rev. Juozas \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 211536 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Moraweck, Dr. Ernest \n male \n 54.0000 \n 54.00000 \n 0 \n 0 \n 29011 \n 14.0000 \n NA \n S \n \n \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Myles, Mr. Thomas Francis \n male \n 62.0000 \n 62.00000 \n 0 \n 0 \n 240276 \n 9.6875 \n NA \n Q \n \n \n 2 \n 0 \n Nasser, Mr. Nicholas \n male \n 32.5000 \n 32.50000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n female \n 14.0000 \n 14.00000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n 2 \n 1 \n Navratil, Master. Edmond Roger \n male \n 2.0000 \n 2.00000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n 2 \n 1 \n Navratil, Master. Michel M \n male \n 3.0000 \n 3.00000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n male \n 36.5000 \n 36.50000 \n 0 \n 2 \n 230080 \n 26.0000 \n F2 \n S \n \n \n 2 \n 0 \n Nesson, Mr. Israel \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 244368 \n 13.0000 \n F2 \n S \n \n \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n male \n 19.0000 \n 19.00000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 0 \n Norman, Mr. Robert Douglas \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 218629 \n 13.5000 \n NA \n S \n \n \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SC/PARIS 2166 \n 13.8625 \n D38 \n C \n \n \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n C.A. 29395 \n 10.5000 \n F33 \n S \n \n \n 2 \n 0 \n Otter, Mr. Richard \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 28213 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n W./C. 14260 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Padro y Manent, Mr. Julian \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/PARIS 2146 \n 13.8625 \n NA \n C \n \n \n 2 \n 0 \n Pain, Dr. Alfred \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 244278 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n SC/PARIS 2147 \n 13.8583 \n NA \n C \n \n \n 2 \n 0 \n Parker, Mr. Clifford Richard \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n SC 14888 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n male \n NA \n 29.79431 \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n female \n 50.0000 \n 50.00000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Pengelly, Mr. Frederick William \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28665 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Pernot, Mr. Rene \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/PARIS 2131 \n 15.0500 \n NA \n C \n \n \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n 237393 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n female \n 21.0000 \n 21.00000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Phillips, Mr. Escott Robert \n male \n 43.0000 \n 43.00000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n female \n 32.0000 \n 32.00000 \n 0 \n 0 \n 234604 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Ponesell, Mr. Martin \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n C.A. 34644 \n 12.7375 \n NA \n C \n \n \n 2 \n 0 \n Pulbaum, Mr. Franz \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n SC/PARIS 2168 \n 15.0333 \n NA \n C \n \n \n 2 \n 1 \n Quick, Miss. Phyllis May \n female \n 2.0000 \n 2.00000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Quick, Miss. Winifred Vera \n female \n 8.0000 \n 8.00000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n female \n 33.0000 \n 33.00000 \n 0 \n 2 \n 26360 \n 26.0000 \n NA \n S \n \n \n 2 \n 0 \n Reeves, Mr. David \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n C.A. 17248 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Renouf, Mr. Peter Henry \n male \n 34.0000 \n 34.00000 \n 1 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 230434 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Richard, Mr. Emile \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n SC/PARIS 2133 \n 15.0458 \n NA \n C \n \n \n 2 \n 1 \n Richards, Master. George Sibley \n male \n 0.8333 \n 0.83330 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n 2 \n 1 \n Richards, Master. William Rowe \n male \n 3.0000 \n 3.00000 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n female \n 24.0000 \n 24.00000 \n 2 \n 3 \n 29106 \n 18.7500 \n NA \n S \n \n \n 2 \n 1 \n Ridsdale, Miss. Lucy \n female \n 50.0000 \n 50.00000 \n 0 \n 0 \n W./C. 14258 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 28004 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Rugg, Miss. Emily \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n C.A. 31026 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Schmidt, Mr. August \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 248659 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 244361 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sharp, Mr. Percival James R \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n female \n 25.0000 \n 25.00000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n female \n 18.0000 \n 18.00000 \n 0 \n 2 \n 250652 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Sincock, Miss. Maude \n female \n 20.0000 \n 20.00000 \n 0 \n 0 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n 2 \n 1 \n Sinkkonen, Miss. Anna \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 250648 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n male \n 59.0000 \n 59.00000 \n 0 \n 0 \n 237442 \n 13.5000 \n NA \n S \n \n \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 234818 \n 12.3500 \n NA \n Q \n \n \n 2 \n 0 \n Slemen, Mr. Richard James \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 28206 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Smith, Miss. Marion Elsie \n female \n 40.0000 \n 40.00000 \n 0 \n 0 \n 31418 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n C.A. 29178 \n 13.0000 \n NA \n S \n \n \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n 237734 \n 15.0458 \n NA \n C \n \n \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n F.C.C. 13540 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Swane, Mr. George \n male \n 18.5000 \n 18.50000 \n 0 \n 0 \n 248734 \n 13.0000 \n F \n S \n \n \n 2 \n 0 \n Sweet, Mr. George Frederick \n male \n 14.0000 \n 14.00000 \n 0 \n 0 \n 220845 \n 65.0000 \n NA \n S \n \n \n 2 \n 1 \n Toomey, Miss. Ellen \n female \n 50.0000 \n 50.00000 \n 0 \n 0 \n F.C.C. 13531 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 233639 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 240929 \n 12.6500 \n NA \n S \n \n \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n female \n 27.0000 \n 27.00000 \n 0 \n 0 \n 34218 \n 10.5000 \n E101 \n S \n \n \n 2 \n 0 \n Turpin, Mr. William John Robert \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n female \n 27.0000 \n 27.00000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Veal, Mr. James \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 28221 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Walcroft, Miss. Nellie \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Ware, Mr. John James \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Ware, Mr. William Jeffery \n male \n 23.0000 \n 23.00000 \n 1 \n 0 \n 28666 \n 10.5000 \n NA \n S \n \n \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n male \n NA \n 29.79431 \n 0 \n 0 \n 239856 \n 0.0000 \n NA \n S \n \n \n 2 \n 1 \n Watt, Miss. Bertha J \n female \n 12.0000 \n 12.00000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n female \n 40.0000 \n 40.00000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n 2 \n 1 \n Webber, Miss. Susan \n female \n 32.5000 \n 32.50000 \n 0 \n 0 \n 27267 \n 13.0000 \n E101 \n S \n \n \n 2 \n 0 \n Weisz, Mr. Leopold \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n female \n 29.0000 \n 29.00000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n 2 \n 1 \n Wells, Master. Ralph Lester \n male \n 2.0000 \n 2.00000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n Wells, Miss. Joan \n female \n 4.0000 \n 4.00000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n female \n 29.0000 \n 29.00000 \n 0 \n 2 \n 29103 \n 23.0000 \n NA \n S \n \n \n 2 \n 1 \n West, Miss. Barbara J \n female \n 0.9167 \n 0.91670 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 1 \n West, Miss. Constance Mirium \n female \n 5.0000 \n 5.00000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 0 \n West, Mr. Edwy Arthur \n male \n 36.0000 \n 36.00000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n female \n 33.0000 \n 33.00000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n 2 \n 0 \n Wheadon, Mr. Edward H \n male \n 66.0000 \n 66.00000 \n 0 \n 0 \n C.A. 24579 \n 10.5000 \n NA \n S \n \n \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n male \n NA \n 29.79431 \n 0 \n 0 \n SC/PARIS 2159 \n 12.8750 \n NA \n S \n \n \n 2 \n 1 \n Wilhelms, Mr. Charles \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 244270 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Williams, Mr. Charles Eugene \n male \n NA \n 29.79431 \n 0 \n 0 \n 244373 \n 13.0000 \n NA \n S \n \n \n 2 \n 1 \n Wright, Miss. Marion \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n 220844 \n 13.5000 \n NA \n S \n \n \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 248747 \n 13.0000 \n NA \n S \n \n \n 3 \n 0 \n Abbing, Mr. Anthony \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n C.A. 5547 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n male \n 13.0000 \n 13.00000 \n 0 \n 2 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n male \n 16.0000 \n 16.00000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 348125 \n 7.6500 \n NA \n S \n \n \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 348122 \n 7.6500 \n F G63 \n S \n \n \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SOTON/O2 3101284 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 2657 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n C 7076 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Adams, Mr. John \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 341826 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n female \n 40.0000 \n 40.00000 \n 1 \n 0 \n 7546 \n 9.4750 \n NA \n S \n \n \n 3 \n 1 \n Aks, Master. Philip Frank \n male \n 0.8333 \n 0.83330 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n female \n 18.0000 \n 18.00000 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n 3 \n 0 \n Alexander, Mr. William \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 3474 \n 7.8875 \n NA \n S \n \n \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SOTON/O2 3101287 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Ali, Mr. Ahmed \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n SOTON/O.Q. 3101311 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Ali, Mr. William \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n SOTON/O.Q. 3101312 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Allen, Mr. William Henry \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 373450 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Allum, Mr. Owen George \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 2223 \n 8.3000 \n NA \n S \n \n \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 350046 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n male \n 4.0000 \n 4.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n female \n 6.0000 \n 6.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n female \n 2.0000 \n 2.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n female \n 17.0000 \n 17.00000 \n 4 \n 2 \n 3101281 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n female \n 38.0000 \n 38.00000 \n 4 \n 2 \n 347091 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n female \n 9.0000 \n 9.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n female \n 11.0000 \n 11.00000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Mr. Anders Johan \n male \n 39.0000 \n 39.00000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 350043 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347075 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n female \n 39.0000 \n 39.00000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 347466 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Angheloff, Mr. Minko \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 349202 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n female \n 18.0000 \n 18.00000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349911 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Asim, Mr. Adola \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n SOTON/O.Q. 3101310 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Master. Carl Edgar \n male \n 5.0000 \n 5.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n male \n 9.0000 \n 9.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n male \n 3.0000 \n 3.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Master. Filip Oscar \n male \n 13.0000 \n 13.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n female \n 5.0000 \n 5.00000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n male \n 40.0000 \n 40.00000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Mr. Johan Charles \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 350054 \n 7.7958 \n NA \n S \n \n \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n female \n 38.0000 \n 38.00000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n 2696 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Assaf, Mr. Gerios \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 2692 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Assam, Mr. Ali \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n SOTON/O.Q. 3101309 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Attalah, Miss. Malake \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Attalah, Mr. Sleiman \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 2694 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Augustsson, Mr. Albert \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 347468 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Ayoub, Miss. Banoura \n female \n 13.0000 \n 13.00000 \n 0 \n 0 \n 2687 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Baccos, Mr. Raffull \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 2679 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n male \n 32.0000 \n 32.00000 \n 1 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n female \n 33.0000 \n 33.00000 \n 3 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n 3 \n 1 \n Baclini, Miss. Eugenie \n female \n 0.7500 \n 0.75000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n female \n 0.7500 \n 0.75000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n female \n 5.0000 \n 5.00000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n female \n 24.0000 \n 24.00000 \n 0 \n 3 \n 2666 \n 19.2583 \n NA \n C \n \n \n 3 \n 1 \n Badman, Miss. Emily Louisa \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n A/4 31416 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Badt, Mr. Mohamed \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 2623 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Balkic, Mr. Cerin \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 349248 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Barah, Mr. Hanna Assi \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 2663 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Barbara, Miss. Saiide \n female \n 18.0000 \n 18.00000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n female \n 45.0000 \n 45.00000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Barry, Miss. Julia \n female \n 27.0000 \n 27.00000 \n 0 \n 0 \n 330844 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Barton, Mr. David John \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 324669 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Beavan, Mr. William Thomas \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 323951 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347068 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n PP 4348 \n 9.3500 \n NA \n S \n \n \n 3 \n 0 \n Betros, Master. Seman \n male \n NA \n 29.79431 \n 0 \n 0 \n 2622 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Betros, Mr. Tannous \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 2648 \n 4.0125 \n NA \n C \n \n \n 3 \n 1 \n Bing, Mr. Lee \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 312992 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347090 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 349224 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Boulos, Master. Akar \n male \n 6.0000 \n 6.00000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Boulos, Miss. Nourelain \n female \n 9.0000 \n 9.00000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Boulos, Mr. Hanna \n male \n NA \n 29.79431 \n 0 \n 0 \n 2664 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n female \n NA \n 29.79431 \n 0 \n 2 \n 2678 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Bourke, Miss. Mary \n female \n NA \n 29.79431 \n 0 \n 2 \n 364848 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Bourke, Mr. John \n male \n 40.0000 \n 40.00000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n female \n 32.0000 \n 32.00000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 334914 \n 7.7250 \n NA \n Q \n \n \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n female \n 20.0000 \n 20.00000 \n 0 \n 0 \n 347471 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Braund, Mr. Lewis Richard \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n 3460 \n 7.0458 \n NA \n S \n \n \n 3 \n 0 \n Braund, Mr. Owen Harris \n male \n 22.0000 \n 22.00000 \n 1 \n 0 \n A/5 21171 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 350045 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 364512 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Buckley, Miss. Katherine \n female \n 18.5000 \n 18.50000 \n 0 \n 0 \n 329944 \n 7.2833 \n NA \n Q \n \n \n 3 \n 1 \n Buckley, Mr. Daniel \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 330920 \n 7.8208 \n NA \n Q \n \n \n 3 \n 0 \n Burke, Mr. Jeremiah \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 365222 \n 6.7500 \n NA \n Q \n \n \n 3 \n 0 \n Burns, Miss. Mary Delia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 330963 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Cacic, Miss. Manda \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 315087 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Cacic, Miss. Marija \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 315084 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Cacic, Mr. Jego Grga \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 315091 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Cacic, Mr. Luka \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n 315089 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Calic, Mr. Jovo \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315093 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Calic, Mr. Petar \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315086 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Canavan, Miss. Mary \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 364846 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Canavan, Mr. Patrick \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 364858 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Cann, Mr. Ernest Charles \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A./5. 2152 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Caram, Mr. Joseph \n male \n NA \n 29.79431 \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n female \n NA \n 29.79431 \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 350042 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 350409 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 367231 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Carr, Miss. Jeannie \n female \n 37.0000 \n 37.00000 \n 0 \n 0 \n 368364 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Carver, Mr. Alfred John \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 392095 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Celotti, Mr. Francesco \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 343275 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Charters, Mr. David \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A/5. 13032 \n 7.7333 \n NA \n Q \n \n \n 3 \n 1 \n Chip, Mr. Chang \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Christmann, Mr. Emil \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 343276 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n male \n 26.0000 \n 26.00000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n SOTON/O.Q. 3101307 \n 7.0500 \n NA \n S \n \n \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n A/5 3540 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Colbert, Mr. Patrick \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 371109 \n 7.2500 \n NA \n Q \n \n \n 3 \n 0 \n Coleff, Mr. Peju \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 349210 \n 7.4958 \n NA \n S \n \n \n 3 \n 0 \n Coleff, Mr. Satio \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349209 \n 7.4958 \n NA \n S \n \n \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 21332 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n Connaghton, Mr. Michael \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 335097 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Connolly, Miss. Kate \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 370373 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Connolly, Miss. Kate \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 330972 \n 7.6292 \n NA \n Q \n \n \n 3 \n 0 \n Connors, Mr. Patrick \n male \n 70.5000 \n 70.50000 \n 0 \n 0 \n 370369 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Cook, Mr. Jacob \n male \n 43.0000 \n 43.00000 \n 0 \n 0 \n A/5 3536 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Cor, Mr. Bartol \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 349230 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Cor, Mr. Ivan \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 349229 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Cor, Mr. Liudevit \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349231 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Corn, Mr. Harry \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n SOTON/OQ 392090 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n male \n 9.0000 \n 9.00000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n male \n 3.0000 \n 3.00000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n female \n 36.0000 \n 36.00000 \n 0 \n 2 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n 3 \n 0 \n Coxon, Mr. Daniel \n male \n 59.0000 \n 59.00000 \n 0 \n 0 \n 364500 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Crease, Mr. Ernest James \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n S.P. 3464 \n 8.1583 \n NA \n S \n \n \n 3 \n 1 \n Cribb, Miss. Laura Alice \n female \n 17.0000 \n 17.00000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Cribb, Mr. John Hatfield \n male \n 44.0000 \n 44.00000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Culumovic, Mr. Jeso \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315090 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Daher, Mr. Shedid \n male \n 22.5000 \n 22.50000 \n 0 \n 0 \n 2698 \n 7.2250 \n NA \n C \n \n \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 7598 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 7552 \n 10.5167 \n NA \n S \n \n \n 3 \n 0 \n Dakic, Mr. Branko \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349228 \n 10.1708 \n NA \n S \n \n \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 382650 \n 6.9500 \n NA \n Q \n \n \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 382651 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n male \n 0.3333 \n 0.33330 \n 0 \n 2 \n 347080 \n 14.4000 \n NA \n S \n \n \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n male \n 34.0000 \n 34.00000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n female \n 28.0000 \n 28.00000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n 3 \n 0 \n Danoff, Mr. Yoto \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 349219 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 349203 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. Alfred J \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. Evan \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n SC/A4 23568 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. John Samuel \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Davies, Mr. Joseph \n male \n 17.0000 \n 17.00000 \n 2 \n 0 \n A/4 48873 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Davison, Mr. Thomas Henry \n male \n NA \n 29.79431 \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n female \n NA \n 29.79431 \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n male \n 36.5000 \n 36.50000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n female \n 36.0000 \n 36.00000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n 3 \n 1 \n de Mulder, Mr. Theodore \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 345774 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 345778 \n 9.5000 \n NA \n S \n \n \n 3 \n 1 \n Dean, Master. Bertram Vere \n male \n 1.0000 \n 1.00000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n female \n 0.1667 \n 0.16670 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 0 \n Dean, Mr. Bertram Frank \n male \n 26.0000 \n 26.00000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n female \n 33.0000 \n 33.00000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n 3 \n 0 \n Delalic, Mr. Redjo \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 349250 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Demetri, Mr. Marinko \n male \n NA \n 29.79431 \n 0 \n 0 \n 349238 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Denkoff, Mr. Mitto \n male \n NA \n 29.79431 \n 0 \n 0 \n 349225 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Dennis, Mr. Samuel \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n A/5 21172 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Dennis, Mr. William \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n A/5 21175 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n female \n 19.0000 \n 19.00000 \n 0 \n 0 \n 330958 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Dika, Mr. Mirko \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 349232 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Dimic, Mr. Jovan \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 315088 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n male \n 43.0000 \n 43.00000 \n 0 \n 0 \n 349226 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Doharr, Mr. Tannous \n male \n NA \n 29.79431 \n 0 \n 0 \n 2686 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Dooley, Mr. Patrick \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 370376 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n A/5. 10482 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n female \n 30.0000 \n 30.00000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n 3 \n 0 \n Doyle, Miss. Elizabeth \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 368702 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Drapkin, Miss. Jennie \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n SOTON/OQ 392083 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Drazenoic, Mr. Jozef \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 349241 \n 7.8958 \n NA \n C \n \n \n 3 \n 0 \n Duane, Mr. Frank \n male \n 65.0000 \n 65.00000 \n 0 \n 0 \n 336439 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Duquemin, Mr. Joseph \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n S.O./P.P. 752 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n male \n 23.0000 \n 23.00000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n female \n 22.0000 \n 22.00000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 349912 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Eklund, Mr. Hans Linus \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 347074 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Ekstrom, Mr. Johan \n male \n 45.0000 \n 45.00000 \n 0 \n 0 \n 347061 \n 6.9750 \n NA \n S \n \n \n 3 \n 0 \n Elias, Mr. Dibo \n male \n NA \n 29.79431 \n 0 \n 0 \n 2674 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Elias, Mr. Joseph \n male \n 39.0000 \n 39.00000 \n 0 \n 2 \n 2675 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Elias, Mr. Joseph Jr \n male \n 17.0000 \n 17.00000 \n 1 \n 1 \n 2690 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Elias, Mr. Tannous \n male \n 15.0000 \n 15.00000 \n 1 \n 1 \n 2695 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Elsbury, Mr. William James \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n A/5 3902 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n female \n 5.0000 \n 5.00000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n 3 \n 0 \n Emir, Mr. Farred Chehab \n male \n NA \n 29.79431 \n 0 \n 0 \n 2631 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Everett, Mr. Thomas James \n male \n 40.5000 \n 40.50000 \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n 3 \n 0 \n Farrell, Mr. James \n male \n 40.5000 \n 40.50000 \n 0 \n 0 \n 367232 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Finoli, Mr. Luigi \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 3101308 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 350036 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Fleming, Miss. Honora \n female \n NA \n 29.79431 \n 0 \n 0 \n 364859 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Flynn, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n 364851 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Flynn, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 368323 \n 6.9500 \n NA \n Q \n \n \n 3 \n 0 \n Foley, Mr. Joseph \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 330910 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Foley, Mr. William \n male \n NA \n 29.79431 \n 0 \n 0 \n 365235 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Foo, Mr. Choong \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n female \n 21.0000 \n 21.00000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n female \n 9.0000 \n 9.00000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mr. Arthur \n male \n NA \n 29.79431 \n 0 \n 0 \n A/5 1478 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mr. Edward Watson \n male \n 18.0000 \n 18.00000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mr. William Neal \n male \n 16.0000 \n 16.00000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n female \n 48.0000 \n 48.00000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n 3 \n 0 \n Fox, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 368573 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 3101314 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Gallagher, Mr. Martin \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 36864 \n 7.7417 \n NA \n Q \n \n \n 3 \n 0 \n Garfirth, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349254 \n 7.8958 \n NA \n C \n \n \n 3 \n 0 \n Gilinski, Mr. Eliezer \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 14973 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n female \n 16.0000 \n 16.00000 \n 0 \n 0 \n 35851 \n 7.7333 \n NA \n Q \n \n \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n female \n NA \n 29.79431 \n 0 \n 0 \n 335677 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n male \n 9.0000 \n 9.00000 \n 0 \n 2 \n 363291 \n 20.5250 \n NA \n S \n \n \n 3 \n 0 \n Goldsmith, Mr. Frank John \n male \n 33.0000 \n 33.00000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n 3 \n 0 \n Goldsmith, Mr. Nathan \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n SOTON/O.Q. 3101263 \n 7.8500 \n NA \n S \n \n \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n SOTON/O.Q. 3101306 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Master. Harold Victor \n male \n 9.0000 \n 9.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n male \n 1.0000 \n 1.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Master. William Frederick \n male \n 11.0000 \n 11.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n female \n 10.0000 \n 10.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n female \n 16.0000 \n 16.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n male \n 14.0000 \n 14.00000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n male \n 40.0000 \n 40.00000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n female \n 43.0000 \n 43.00000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n 3 \n 0 \n Green, Mr. George Henry \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 21440 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 8471 \n 8.3625 \n NA \n S \n \n \n 3 \n 0 \n Guest, Mr. Robert \n male \n NA \n 29.79431 \n 0 \n 0 \n 376563 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 7534 \n 9.8458 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n male \n 37.0000 \n 37.00000 \n 2 \n 0 \n 3101276 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n 3101277 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 347069 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Haas, Miss. Aloisia \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349236 \n 8.8500 \n NA \n S \n \n \n 3 \n 0 \n Hagardon, Miss. Kate \n female \n 17.0000 \n 17.00000 \n 0 \n 0 \n AQ/3. 30631 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n male \n NA \n 29.79431 \n 1 \n 0 \n 65303 \n 19.9667 \n NA \n S \n \n \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n male \n NA \n 29.79431 \n 1 \n 0 \n 65304 \n 19.9667 \n NA \n S \n \n \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n female \n 24.0000 \n 24.00000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n 3 \n 0 \n Hampe, Mr. Leon \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 345769 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Hanna, Mr. Mansour \n male \n 23.5000 \n 23.50000 \n 0 \n 0 \n 2693 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Hansen, Mr. Claus Peter \n male \n 41.0000 \n 41.00000 \n 2 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n male \n 26.0000 \n 26.00000 \n 1 \n 0 \n 350025 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350029 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n female \n 45.0000 \n 45.00000 \n 1 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n female \n NA \n 29.79431 \n 0 \n 0 \n W./C. 6609 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 374887 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Hart, Mr. Henry \n male \n NA \n 29.79431 \n 0 \n 0 \n 394140 \n 6.8583 \n NA \n Q \n \n \n 3 \n 0 \n Hassan, Mr. Houssein G N \n male \n 11.0000 \n 11.00000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 370375 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 347089 \n 6.9750 \n NA \n S \n \n \n 3 \n 1 \n Hee, Mr. Ling \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 365226 \n 6.7500 \n NA \n Q \n \n \n 3 \n 1 \n Heikkinen, Miss. Laina \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n STON/O2. 3101282 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n STON/O2. 3101290 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 7548 \n 8.9625 \n NA \n S \n \n \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 349243 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 347086 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Henry, Miss. Delia \n female \n NA \n 29.79431 \n 0 \n 0 \n 382649 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n female \n 2.0000 \n 2.00000 \n 0 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n male \n 43.0000 \n 43.00000 \n 0 \n 0 \n C 7075 \n 6.4500 \n NA \n S \n \n \n 3 \n 0 \n Holthen, Mr. Johan Martin \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n 3 \n 1 \n Honkanen, Miss. Eliina \n female \n 27.0000 \n 27.00000 \n 0 \n 0 \n STON/O2. 3101283 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Horgan, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 370377 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Howard, Miss. May Elizabeth \n female \n NA \n 29.79431 \n 0 \n 0 \n A. 2. 39186 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n male \n 42.0000 \n 42.00000 \n 0 \n 0 \n 348121 \n 7.6500 \n F G63 \n S \n \n \n 3 \n 1 \n Hyman, Mr. Abraham \n male \n NA \n 29.79431 \n 0 \n 0 \n 3470 \n 7.8875 \n NA \n S \n \n \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 2685 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Ilieff, Mr. Ylio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349220 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n female \n 27.0000 \n 27.00000 \n 1 \n 0 \n STON/O2. 3101270 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n female \n 25.0000 \n 25.00000 \n 1 \n 0 \n STON/O2. 3101271 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Ivanoff, Mr. Kanio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349201 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Jalsevac, Mr. Ivan \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 349240 \n 7.8958 \n NA \n C \n \n \n 3 \n 1 \n Jansson, Mr. Carl Olof \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350034 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Jardin, Mr. Jose Neto \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 3101305 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Jensen, Mr. Hans Peder \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 350050 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jensen, Mr. Niels Peder \n male \n 48.0000 \n 48.00000 \n 0 \n 0 \n 350047 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n male \n 17.0000 \n 17.00000 \n 1 \n 0 \n 350048 \n 7.0542 \n NA \n S \n \n \n 3 \n 1 \n Jermyn, Miss. Annie \n female \n NA \n 29.79431 \n 0 \n 0 \n 14313 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n male \n NA \n 29.79431 \n 0 \n 0 \n 65306 \n 8.1125 \n NA \n S \n \n \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 3101264 \n 6.4958 \n NA \n S \n \n \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347070 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Erik \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 350052 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 7540 \n 8.6542 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Karl Johan \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n 347063 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Johansson, Mr. Nils \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 347467 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Johnson, Master. Harold Theodor \n male \n 4.0000 \n 4.00000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n female \n 1.0000 \n 1.00000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n 3 \n 0 \n Johnson, Mr. Alfred \n male \n 49.0000 \n 49.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 347062 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n female \n 27.0000 \n 27.00000 \n 0 \n 2 \n 347742 \n 11.1333 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n male \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n female \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Mr. Andrew G \n male \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n female \n NA \n 29.79431 \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n 3 \n 0 \n Jonkoff, Mr. Lalio \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 349204 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Jonsson, Mr. Carl \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 350417 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 350408 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Jussila, Miss. Katriina \n female \n 20.0000 \n 20.00000 \n 1 \n 0 \n 4136 \n 9.8250 \n NA \n S \n \n \n 3 \n 0 \n Jussila, Miss. Mari Aina \n female \n 21.0000 \n 21.00000 \n 1 \n 0 \n 4137 \n 9.8250 \n NA \n S \n \n \n 3 \n 1 \n Jussila, Mr. Eiriik \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/O 2. 3101286 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n STON/O 2. 3101274 \n 7.1250 \n NA \n S \n \n \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 8475 \n 8.4333 \n NA \n S \n \n \n 3 \n 0 \n Karaic, Mr. Milan \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n 349246 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350053 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 347465 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Karlsson, Mr. Nils August \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 350060 \n 7.5208 \n NA \n S \n \n \n 3 \n 1 \n Karun, Miss. Manca \n female \n 4.0000 \n 4.00000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n 3 \n 1 \n Karun, Mr. Franz \n male \n 39.0000 \n 39.00000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n 3 \n 0 \n Kassem, Mr. Fared \n male \n NA \n 29.79431 \n 0 \n 0 \n 2700 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n male \n 18.5000 \n 18.50000 \n 0 \n 0 \n 2682 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n male \n NA \n 29.79431 \n 0 \n 0 \n 12460 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Keefe, Mr. Arthur \n male \n NA \n 29.79431 \n 0 \n 0 \n 323592 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 9234 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Kelly, Miss. Mary \n female \n NA \n 29.79431 \n 0 \n 0 \n 14312 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Kelly, Mr. James \n male \n 34.5000 \n 34.50000 \n 0 \n 0 \n 330911 \n 7.8292 \n NA \n Q \n \n \n 3 \n 0 \n Kelly, Mr. James \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n 363592 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Kennedy, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 368783 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Khalil, Mr. Betros \n male \n NA \n 29.79431 \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n female \n NA \n 29.79431 \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Kiernan, Mr. John \n male \n NA \n 29.79431 \n 1 \n 0 \n 367227 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Kiernan, Mr. Philip \n male \n NA \n 29.79431 \n 1 \n 0 \n 367229 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n male \n NA \n 29.79431 \n 0 \n 0 \n 36865 \n 7.7375 \n NA \n Q \n \n \n 3 \n 0 \n Kink, Miss. Maria \n female \n 22.0000 \n 22.00000 \n 2 \n 0 \n 315152 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Kink, Mr. Vincenz \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n 315151 \n 8.6625 \n NA \n S \n \n \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n female \n 4.0000 \n 4.00000 \n 0 \n 2 \n 315153 \n 22.0250 \n NA \n S \n \n \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n female \n 1.0000 \n 1.00000 \n 1 \n 1 \n 350405 \n 12.1833 \n NA \n S \n \n \n 3 \n 0 \n Klasen, Mr. Klas Albin \n male \n 18.0000 \n 18.00000 \n 1 \n 1 \n 350404 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n female \n 36.0000 \n 36.00000 \n 0 \n 2 \n 350405 \n 12.1833 \n NA \n S \n \n \n 3 \n 0 \n Kraeff, Mr. Theodor \n male \n NA \n 29.79431 \n 0 \n 0 \n 349253 \n 7.8958 \n NA \n C \n \n \n 3 \n 1 \n Krekorian, Mr. Neshan \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 2654 \n 7.2292 \n F E57 \n C \n \n \n 3 \n 0 \n Lahoud, Mr. Sarkis \n male \n NA \n 29.79431 \n 0 \n 0 \n 2624 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n female \n 37.0000 \n 37.00000 \n 0 \n 0 \n 4135 \n 9.5875 \n NA \n S \n \n \n 3 \n 0 \n Laleff, Mr. Kristo \n male \n NA \n 29.79431 \n 0 \n 0 \n 349217 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Lam, Mr. Ali \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Lam, Mr. Len \n male \n NA \n 29.79431 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n C 7077 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Lane, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 7935 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Lang, Mr. Fang \n male \n 26.0000 \n 26.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Larsson, Mr. August Viktor \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 7545 \n 9.4833 \n NA \n S \n \n \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 347067 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 347065 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 2620 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n male \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Miss. Ida \n female \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Miss. Jeannie \n female \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Miss. Mathilde \n female \n NA \n 29.79431 \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n female \n NA \n 29.79431 \n 0 \n 4 \n 4133 \n 25.4667 \n NA \n S \n \n \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/O 2. 3101292 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n male \n 34.5000 \n 34.50000 \n 0 \n 0 \n 2683 \n 6.4375 \n NA \n C \n \n \n 3 \n 0 \n Lennon, Miss. Mary \n female \n NA \n 29.79431 \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Lennon, Mr. Denis \n male \n NA \n 29.79431 \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Leonard, Mr. Lionel \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 0 \n Lester, Mr. James \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Lievens, Mr. Rene Aime \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 345781 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n female \n 25.0000 \n 25.00000 \n 0 \n 0 \n 347071 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n female \n 45.0000 \n 45.00000 \n 0 \n 0 \n 347073 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n female \n 30.0000 \n 30.00000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n 3 \n 1 \n Lindqvist, Mr. Eino William \n male \n 20.0000 \n 20.00000 \n 1 \n 0 \n STON/O 2. 3101285 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Linehan, Mr. Michael \n male \n NA \n 29.79431 \n 0 \n 0 \n 330971 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Ling, Mr. Lee \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n 3 \n 0 \n Lithman, Mr. Simon \n male \n NA \n 29.79431 \n 0 \n 0 \n S.O./P.P. 251 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Lobb, Mr. William Arthur \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n female \n 26.0000 \n 26.00000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Lockyer, Mr. Edward \n male \n NA \n 29.79431 \n 0 \n 0 \n 1222 \n 7.8792 \n NA \n S \n \n \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n male \n 20.5000 \n 20.50000 \n 0 \n 0 \n A/5 21173 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Lulic, Mr. Nikola \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 315098 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 347743 \n 7.0542 \n NA \n S \n \n \n 3 \n 1 \n Lundin, Miss. Olga Elida \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n 347469 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 350403 \n 7.5792 \n NA \n S \n \n \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n male \n NA \n 29.79431 \n 0 \n 0 \n 349235 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n MacKay, Mr. George William \n male \n NA \n 29.79431 \n 0 \n 0 \n C.A. 42795 \n 7.5500 \n NA \n S \n \n \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 370370 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n C 17369 \n 7.1417 \n NA \n S \n \n \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n STON/O 2. 3101275 \n 7.1250 \n NA \n S \n \n \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n female \n NA \n 29.79431 \n 0 \n 0 \n 330924 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Mahon, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n AQ/4 3130 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Maisner, Mr. Simon \n male \n NA \n 29.79431 \n 0 \n 0 \n A/S 2816 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n STON/O 2. 3101268 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Mamee, Mr. Hanna \n male \n NA \n 29.79431 \n 0 \n 0 \n 2677 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Mangan, Miss. Mary \n female \n 30.5000 \n 30.50000 \n 0 \n 0 \n 364850 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Mannion, Miss. Margareth \n female \n NA \n 29.79431 \n 0 \n 0 \n 36866 \n 7.7375 \n NA \n Q \n \n \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n male \n NA \n 29.79431 \n 0 \n 0 \n 2655 \n 7.2292 \n F E46 \n C \n \n \n 3 \n 0 \n Markoff, Mr. Marin \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n 349213 \n 7.8958 \n NA \n C \n \n \n 3 \n 0 \n Markun, Mr. Johann \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 349257 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Masselmani, Mrs. Fatima \n female \n NA \n 29.79431 \n 0 \n 0 \n 2649 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Matinoff, Mr. Nicola \n male \n NA \n 29.79431 \n 0 \n 0 \n 349255 \n 7.8958 \n NA \n C \n \n \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 383123 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n 367228 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n McCoy, Miss. Agnes \n female \n NA \n 29.79431 \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n 3 \n 1 \n McCoy, Miss. Alicia \n female \n NA \n 29.79431 \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n 3 \n 1 \n McCoy, Mr. Bernard \n male \n NA \n 29.79431 \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n female \n NA \n 29.79431 \n 0 \n 0 \n 330932 \n 7.7875 \n NA \n Q \n \n \n 3 \n 0 \n McEvoy, Mr. Michael \n male \n NA \n 29.79431 \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n 3 \n 1 \n McGovern, Miss. Mary \n female \n NA \n 29.79431 \n 0 \n 0 \n 330931 \n 7.8792 \n NA \n Q \n \n \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n female \n 15.0000 \n 15.00000 \n 0 \n 0 \n 330923 \n 8.0292 \n NA \n Q \n \n \n 3 \n 0 \n McGowan, Miss. Katherine \n female \n 35.0000 \n 35.00000 \n 0 \n 0 \n 9232 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n McMahon, Mr. Martin \n male \n NA \n 29.79431 \n 0 \n 0 \n 370372 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n McNamee, Mr. Neal \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n female \n 19.0000 \n 19.00000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n McNeill, Miss. Bridget \n female \n NA \n 29.79431 \n 0 \n 0 \n 370368 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n female \n NA \n 29.79431 \n 0 \n 0 \n SOTON/O.Q. 392087 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n female \n NA \n 29.79431 \n 0 \n 0 \n 343095 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Meo, Mr. Alfonzo \n male \n 55.5000 \n 55.50000 \n 0 \n 0 \n A.5. 11206 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Mernagh, Mr. Robert \n male \n NA \n 29.79431 \n 0 \n 0 \n 368703 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 345501 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Miles, Mr. Frank \n male \n NA \n 29.79431 \n 0 \n 0 \n 359306 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Mineff, Mr. Ivan \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 349233 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Minkoff, Mr. Lazar \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 349211 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 349207 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Mitkoff, Mr. Mito \n male \n NA \n 29.79431 \n 0 \n 0 \n 349221 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 330980 \n 7.8792 \n NA \n Q \n \n \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 348123 \n 7.6500 \n F G73 \n S \n \n \n 3 \n 1 \n Moor, Master. Meier \n male \n 6.0000 \n 6.00000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n 3 \n 1 \n Moor, Mrs. (Beila) \n female \n 27.0000 \n 27.00000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n 3 \n 0 \n Moore, Mr. Leonard Charles \n male \n NA \n 29.79431 \n 0 \n 0 \n A4. 54510 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Moran, Miss. Bertha \n female \n NA \n 29.79431 \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n 3 \n 0 \n Moran, Mr. Daniel J \n male \n NA \n 29.79431 \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n 3 \n 0 \n Moran, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n 330877 \n 8.4583 \n NA \n Q \n \n \n 3 \n 0 \n Morley, Mr. William \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 364506 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n male \n NA \n 29.79431 \n 0 \n 0 \n 372622 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Moss, Mr. Albert Johan \n male \n NA \n 29.79431 \n 0 \n 0 \n 312991 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Moubarek, Master. Gerios \n male \n NA \n 29.79431 \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n male \n NA \n 29.79431 \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n female \n NA \n 29.79431 \n 0 \n 2 \n 2661 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n female \n NA \n 29.79431 \n 0 \n 0 \n 2626 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n male \n NA \n 29.79431 \n 0 \n 0 \n 374746 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 35852 \n 7.7333 \n NA \n Q \n \n \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n female \n 24.0000 \n 24.00000 \n 0 \n 0 \n 382653 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Murdlin, Mr. Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n A./5. 3235 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n female \n NA \n 29.79431 \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n female \n NA \n 29.79431 \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n 3 \n 1 \n Murphy, Miss. Nora \n female \n NA \n 29.79431 \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n male \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347078 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Naidenoff, Mr. Penko \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 349206 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n female \n 15.0000 \n 15.00000 \n 0 \n 0 \n 2667 \n 7.2250 \n NA \n C \n \n \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n female \n 1.0000 \n 1.00000 \n 0 \n 2 \n 2653 \n 15.7417 \n NA \n C \n \n \n 3 \n 1 \n Nakid, Mr. Sahid \n male \n 20.0000 \n 20.00000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n 3 \n 0 \n Nancarrow, Mr. William Henry \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n A./5. 3338 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Nankoff, Mr. Minko \n male \n NA \n 29.79431 \n 0 \n 0 \n 349218 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Nasr, Mr. Mustafa \n male \n NA \n 29.79431 \n 0 \n 0 \n 2652 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Naughton, Miss. Hannah \n female \n NA \n 29.79431 \n 0 \n 0 \n 365237 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Nenkoff, Mr. Christo \n male \n NA \n 29.79431 \n 0 \n 0 \n 349234 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n male \n 12.0000 \n 12.00000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n female \n 14.0000 \n 14.00000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n female \n 29.0000 \n 29.00000 \n 0 \n 0 \n 3101297 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Niklasson, Mr. Samuel \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 363611 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347066 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n female \n 26.0000 \n 26.00000 \n 0 \n 0 \n 347470 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 350410 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n male \n 41.0000 \n 41.00000 \n 0 \n 0 \n SOTON/O2 3101272 \n 7.1250 \n NA \n S \n \n \n 3 \n 1 \n Niskanen, Mr. Juha \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n STON/O 2. 3101289 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A/4. 39886 \n 7.8000 \n NA \n S \n \n \n 3 \n 0 \n Novel, Mr. Mansouer \n male \n 28.5000 \n 28.50000 \n 0 \n 0 \n 2697 \n 7.2292 \n NA \n C \n \n \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 347081 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n male \n 61.0000 \n 61.00000 \n 0 \n 0 \n 345364 \n 6.2375 \n NA \n S \n \n \n 3 \n 0 \n O'Brien, Mr. Thomas \n male \n NA \n 29.79431 \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n O'Brien, Mr. Timothy \n male \n NA \n 29.79431 \n 0 \n 0 \n 330979 \n 7.8292 \n NA \n Q \n \n \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n female \n NA \n 29.79431 \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n 3 \n 0 \n O'Connell, Mr. Patrick D \n male \n NA \n 29.79431 \n 0 \n 0 \n 334912 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n O'Connor, Mr. Maurice \n male \n NA \n 29.79431 \n 0 \n 0 \n 371060 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n O'Connor, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 366713 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Odahl, Mr. Nils Martin \n male \n 23.0000 \n 23.00000 \n 0 \n 0 \n 7267 \n 9.2250 \n NA \n S \n \n \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n female \n NA \n 29.79431 \n 0 \n 0 \n 364856 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n female \n NA \n 29.79431 \n 0 \n 0 \n 14311 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 330959 \n 7.8792 \n NA \n Q \n \n \n 3 \n 1 \n Ohman, Miss. Velin \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 347085 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n O'Keefe, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 368402 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 330919 \n 7.8292 \n NA \n Q \n \n \n 3 \n 1 \n Olsen, Master. Artur Karl \n male \n 9.0000 \n 9.00000 \n 0 \n 1 \n C 17368 \n 3.1708 \n NA \n S \n \n \n 3 \n 0 \n Olsen, Mr. Henry Margido \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n male \n 42.0000 \n 42.00000 \n 0 \n 1 \n 4579 \n 8.4042 \n NA \n S \n \n \n 3 \n 0 \n Olsen, Mr. Ole Martin \n male \n NA \n 29.79431 \n 0 \n 0 \n Fa 265302 \n 7.3125 \n NA \n S \n \n \n 3 \n 0 \n Olsson, Miss. Elina \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n 350407 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 347464 \n 7.8542 \n NA \n S \n \n \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 347079 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 6563 \n 9.2250 \n NA \n S \n \n \n 3 \n 0 \n Oreskovic, Miss. Jelka \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n 315085 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Oreskovic, Miss. Marija \n female \n 20.0000 \n 20.00000 \n 0 \n 0 \n 315096 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Oreskovic, Mr. Luka \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 315094 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Osen, Mr. Olaf Elon \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n 7534 \n 9.2167 \n NA \n S \n \n \n 3 \n 1 \n Osman, Mrs. Mara \n female \n 31.0000 \n 31.00000 \n 0 \n 0 \n 349244 \n 8.6833 \n NA \n S \n \n \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n female \n NA \n 29.79431 \n 0 \n 0 \n 330909 \n 7.6292 \n NA \n Q \n \n \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n male \n 2.0000 \n 2.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Master. Paul Folke \n male \n 6.0000 \n 6.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Miss. Stina Viola \n female \n 3.0000 \n 3.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n female \n 8.0000 \n 8.00000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n female \n 29.0000 \n 29.00000 \n 0 \n 4 \n 349909 \n 21.0750 \n NA \n S \n \n \n 3 \n 0 \n Panula, Master. Eino Viljami \n male \n 1.0000 \n 1.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Master. Juha Niilo \n male \n 7.0000 \n 7.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Master. Urho Abraham \n male \n 2.0000 \n 2.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n male \n 16.0000 \n 16.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n male \n 14.0000 \n 14.00000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n female \n 41.0000 \n 41.00000 \n 0 \n 5 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Pasic, Mr. Jakob \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 315097 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Patchett, Mr. George \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Paulner, Mr. Uscher \n male \n NA \n 29.79431 \n 0 \n 0 \n 3411 \n 8.7125 \n NA \n C \n \n \n 3 \n 0 \n Pavlovic, Mr. Stefo \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n 349242 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Peacock, Master. Alfred Edward \n male \n 0.7500 \n 0.75000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n 3 \n 0 \n Peacock, Miss. Treasteall \n female \n 3.0000 \n 3.00000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n female \n 26.0000 \n 26.00000 \n 0 \n 2 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n 3 \n 0 \n Pearce, Mr. Ernest \n male \n NA \n 29.79431 \n 0 \n 0 \n 343271 \n 7.0000 \n NA \n S \n \n \n 3 \n 0 \n Pedersen, Mr. Olaf \n male \n NA \n 29.79431 \n 0 \n 0 \n 345498 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Peduzzi, Mr. Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n A/5 2817 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n STON/O 2. 3101294 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n STON/O 2. 3101291 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Perkin, Mr. John Henry \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n A/5 21174 \n 7.2500 \n NA \n S \n \n \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 347083 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Peter, Master. Michael J \n male \n NA \n 29.79431 \n 1 \n 1 \n 2668 \n 22.3583 \n NA \n C \n \n \n 3 \n 1 \n Peter, Miss. Anna \n female \n NA \n 29.79431 \n 1 \n 1 \n 2668 \n 22.3583 \n F E69 \n C \n \n \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n female \n NA \n 29.79431 \n 0 \n 2 \n 2668 \n 22.3583 \n NA \n C \n \n \n 3 \n 0 \n Peters, Miss. Katie \n female \n NA \n 29.79431 \n 0 \n 0 \n 330935 \n 8.1375 \n NA \n Q \n \n \n 3 \n 0 \n Petersen, Mr. Marius \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 342441 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Petranec, Miss. Matilda \n female \n 28.0000 \n 28.00000 \n 0 \n 0 \n 349245 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Petroff, Mr. Nedelio \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349212 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n male \n NA \n 29.79431 \n 0 \n 0 \n 349215 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Petterson, Mr. Johan Emil \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n 347076 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 347087 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n SOTON/O.Q. 392078 \n 8.0500 \n E10 \n S \n \n \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n male \n NA \n 29.79431 \n 0 \n 0 \n 349227 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Pokrnic, Mr. Mate \n male \n 17.0000 \n 17.00000 \n 0 \n 0 \n 315095 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Pokrnic, Mr. Tome \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 315092 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Radeff, Mr. Alexander \n male \n NA \n 29.79431 \n 0 \n 0 \n 349223 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n female \n NA \n 29.79431 \n 0 \n 0 \n 65305 \n 8.1125 \n NA \n S \n \n \n 3 \n 0 \n Razi, Mr. Raihed \n male \n NA \n 29.79431 \n 0 \n 0 \n 2629 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Reed, Mr. James George \n male \n NA \n 29.79431 \n 0 \n 0 \n 362316 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Rekic, Mr. Tido \n male \n 38.0000 \n 38.00000 \n 0 \n 0 \n 349249 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Reynolds, Mr. Harold J \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n 342684 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rice, Master. Albert \n male \n 10.0000 \n 10.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. Arthur \n male \n 4.0000 \n 4.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. Eric \n male \n 7.0000 \n 7.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. Eugene \n male \n 2.0000 \n 2.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Master. George Hugh \n male \n 8.0000 \n 8.00000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n female \n 39.0000 \n 39.00000 \n 0 \n 5 \n 382652 \n 29.1250 \n NA \n Q \n \n \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 3101295 \n 39.6875 \n NA \n S \n \n \n 3 \n 0 \n Rintamaki, Mr. Matti \n male \n 35.0000 \n 35.00000 \n 0 \n 0 \n STON/O 2. 3101273 \n 7.1250 \n NA \n S \n \n \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n female \n NA \n 29.79431 \n 0 \n 0 \n 334915 \n 7.7208 \n NA \n Q \n \n \n 3 \n 0 \n Risien, Mr. Samuel Beard \n male \n NA \n 29.79431 \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n female \n NA \n 29.79431 \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Robins, Mr. Alexander A \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n female \n 47.0000 \n 47.00000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Rogers, Mr. William John \n male \n NA \n 29.79431 \n 0 \n 0 \n S.C./A.4. 23567 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n male \n NA \n 29.79431 \n 0 \n 0 \n 312993 \n 7.7750 \n NA \n S \n \n \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n female \n 2.0000 \n 2.00000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n male \n 18.0000 \n 18.00000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n female \n 41.0000 \n 41.00000 \n 0 \n 2 \n 370129 \n 20.2125 \n NA \n S \n \n \n 3 \n 1 \n Roth, Miss. Sarah A \n female \n NA \n 29.79431 \n 0 \n 0 \n 342712 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rouse, Mr. Richard Henry \n male \n 50.0000 \n 50.00000 \n 0 \n 0 \n A/5 3594 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Rush, Mr. Alfred George John \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n A/4. 20589 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Ryan, Mr. Edward \n male \n NA \n 29.79431 \n 0 \n 0 \n 383162 \n 7.7500 \n NA \n Q \n \n \n 3 \n 0 \n Ryan, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n 3 \n 0 \n Saad, Mr. Amin \n male \n NA \n 29.79431 \n 0 \n 0 \n 2671 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Saad, Mr. Khalil \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 2672 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Saade, Mr. Jean Nassr \n male \n NA \n 29.79431 \n 0 \n 0 \n 2676 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Sadlier, Mr. Matthew \n male \n NA \n 29.79431 \n 0 \n 0 \n 367655 \n 7.7292 \n NA \n Q \n \n \n 3 \n 0 \n Sadowitz, Mr. Harry \n male \n NA \n 29.79431 \n 0 \n 0 \n LP 1588 \n 7.5750 \n NA \n S \n \n \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n male \n 38.5000 \n 38.50000 \n 0 \n 0 \n SOTON/O.Q. 3101262 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Master. Thomas Henry \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Master. William Henry \n male \n 14.5000 \n 14.50000 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Ada \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Constance Gladys \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Miss. Stella Anna \n female \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. Frederick \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. George John Jr \n male \n NA \n 29.79431 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mr. John George \n male \n NA \n 29.79431 \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n female \n NA \n 29.79431 \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n 3 \n 0 \n Salander, Mr. Karl Johan \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 7266 \n 9.3250 \n NA \n S \n \n \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n female \n 21.0000 \n 21.00000 \n 0 \n 0 \n 343120 \n 7.6500 \n NA \n S \n \n \n 3 \n 0 \n Salonen, Mr. Johan Werner \n male \n 39.0000 \n 39.00000 \n 0 \n 0 \n 3101296 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Samaan, Mr. Elias \n male \n NA \n 29.79431 \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n 3 \n 0 \n Samaan, Mr. Hanna \n male \n NA \n 29.79431 \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n 3 \n 0 \n Samaan, Mr. Youssef \n male \n NA \n 29.79431 \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n female \n 1.0000 \n 1.00000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n female \n 24.0000 \n 24.00000 \n 0 \n 2 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n female \n 4.0000 \n 4.00000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n 3 \n 1 \n Sap, Mr. Julius \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 345768 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Saundercock, Mr. William Henry \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n A/5. 2151 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n male \n 24.5000 \n 24.50000 \n 0 \n 0 \n 342826 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Scanlan, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n 36209 \n 7.7250 \n NA \n Q \n \n \n 3 \n 0 \n Sdycoff, Mr. Todor \n male \n NA \n 29.79431 \n 0 \n 0 \n 349222 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n male \n NA \n 29.79431 \n 0 \n 0 \n 370374 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 345779 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Shellard, Mr. Frederick William \n male \n NA \n 29.79431 \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n female \n NA \n 29.79431 \n 0 \n 0 \n 330968 \n 7.7792 \n NA \n Q \n \n \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n male \n NA \n 29.79431 \n 0 \n 0 \n 374910 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Simmons, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/OQ 392082 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Sirayanian, Mr. Orsen \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 2669 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Sirota, Mr. Maurice \n male \n NA \n 29.79431 \n 0 \n 0 \n 392092 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Sivic, Mr. Husein \n male \n 40.0000 \n 40.00000 \n 0 \n 0 \n 349251 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n STON/O 2. 3101280 \n 7.9250 \n NA \n S \n \n \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 3101265 \n 7.4958 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Master. Harald \n male \n 4.0000 \n 4.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n male \n 10.0000 \n 10.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Miss. Mabel \n female \n 9.0000 \n 9.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n female \n 2.0000 \n 2.00000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Mr. Wilhelm \n male \n 40.0000 \n 40.00000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n female \n 45.0000 \n 45.00000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n 3 \n 0 \n Slabenoff, Mr. Petco \n male \n NA \n 29.79431 \n 0 \n 0 \n 349214 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/OQ 392086 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Smiljanic, Mr. Mile \n male \n NA \n 29.79431 \n 0 \n 0 \n 315037 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Smith, Mr. Thomas \n male \n NA \n 29.79431 \n 0 \n 0 \n 384461 \n 7.7500 \n NA \n Q \n \n \n 3 \n 1 \n Smyth, Miss. Julia \n female \n NA \n 29.79431 \n 0 \n 0 \n 335432 \n 7.7333 \n NA \n Q \n \n \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 348124 \n 7.6500 \n F G73 \n S \n \n \n 3 \n 0 \n Somerton, Mr. Francis William \n male \n 30.0000 \n 30.00000 \n 0 \n 0 \n A.5. 18509 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Spector, Mr. Woolf \n male \n NA \n 29.79431 \n 0 \n 0 \n A.5. 3236 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Spinner, Mr. Henry John \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/OQ. 369943 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Staneff, Mr. Ivan \n male \n NA \n 29.79431 \n 0 \n 0 \n 349208 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Stankovic, Mr. Ivan \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 349239 \n 8.6625 \n NA \n C \n \n \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n female \n 23.0000 \n 23.00000 \n 0 \n 0 \n CA. 2314 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Stanley, Mr. Edward Roland \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n A/4 45380 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Storey, Mr. Thomas \n male \n 60.5000 \n 60.50000 \n 0 \n 0 \n 3701 \n NA \n NA \n S \n \n \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n male \n 19.0000 \n 19.00000 \n 0 \n 0 \n 349205 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n female \n 22.0000 \n 22.00000 \n 0 \n 0 \n 7553 \n 9.8375 \n NA \n S \n \n \n 3 \n 1 \n Stranden, Mr. Juho \n male \n 31.0000 \n 31.00000 \n 0 \n 0 \n STON/O 2. 3101288 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Strilic, Mr. Ivan \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 315083 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Strom, Miss. Telma Matilda \n female \n 2.0000 \n 2.00000 \n 0 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n female \n 29.0000 \n 29.00000 \n 1 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n male \n 16.0000 \n 16.00000 \n 0 \n 0 \n SOTON/OQ 392089 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Sundman, Mr. Johan Julian \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n STON/O 2. 3101269 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n SOTON/OQ 392076 \n 7.0500 \n NA \n S \n \n \n 3 \n 0 \n Svensson, Mr. Johan \n male \n 74.0000 \n 74.00000 \n 0 \n 0 \n 347060 \n 7.7750 \n NA \n S \n \n \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n male \n 14.0000 \n 14.00000 \n 0 \n 0 \n 7538 \n 9.2250 \n NA \n S \n \n \n 3 \n 0 \n Svensson, Mr. Olof \n male \n 24.0000 \n 24.00000 \n 0 \n 0 \n 350035 \n 7.7958 \n NA \n S \n \n \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n 350033 \n 7.7958 \n NA \n S \n \n \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n male \n 34.0000 \n 34.00000 \n 0 \n 0 \n 363294 \n 8.0500 \n NA \n S \n \n \n 3 \n 1 \n Thomas, Master. Assad Alexander \n male \n 0.4167 \n 0.41670 \n 0 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n 3 \n 0 \n Thomas, Mr. Charles P \n male \n NA \n 29.79431 \n 1 \n 0 \n 2621 \n 6.4375 \n NA \n C \n \n \n 3 \n 0 \n Thomas, Mr. John \n male \n NA \n 29.79431 \n 0 \n 0 \n 2681 \n 6.4375 \n NA \n C \n \n \n 3 \n 0 \n Thomas, Mr. Tannous \n male \n NA \n 29.79431 \n 0 \n 0 \n 2684 \n 7.2250 \n NA \n C \n \n \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n male \n NA \n 29.79431 \n 0 \n 0 \n 32302 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Thorneycroft, Mr. Percival \n male \n NA \n 29.79431 \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n female \n NA \n 29.79431 \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Tikkanen, Mr. Juho \n male \n 32.0000 \n 32.00000 \n 0 \n 0 \n STON/O 2. 3101293 \n 7.9250 \n NA \n S \n \n \n 3 \n 0 \n Tobin, Mr. Roger \n male \n NA \n 29.79431 \n 0 \n 0 \n 383121 \n 7.7500 \n F38 \n Q \n \n \n 3 \n 0 \n Todoroff, Mr. Lalio \n male \n NA \n 29.79431 \n 0 \n 0 \n 349216 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n male \n 30.5000 \n 30.50000 \n 0 \n 0 \n 364499 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Torber, Mr. Ernst William \n male \n 44.0000 \n 44.00000 \n 0 \n 0 \n 364511 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Torfa, Mr. Assad \n male \n NA \n 29.79431 \n 0 \n 0 \n 2673 \n 7.2292 \n NA \n C \n \n \n 3 \n 1 \n Tornquist, Mr. William Henry \n male \n 25.0000 \n 25.00000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n 3 \n 0 \n Toufik, Mr. Nakli \n male \n NA \n 29.79431 \n 0 \n 0 \n 2641 \n 7.2292 \n NA \n C \n \n \n 3 \n 1 \n Touma, Master. Georges Youssef \n male \n 7.0000 \n 7.00000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Touma, Miss. Maria Youssef \n female \n 9.0000 \n 9.00000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n female \n 29.0000 \n 29.00000 \n 0 \n 2 \n 2650 \n 15.2458 \n NA \n C \n \n \n 3 \n 0 \n Turcin, Mr. Stjepan \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 349247 \n 7.8958 \n NA \n S \n \n \n 3 \n 1 \n Turja, Miss. Anna Sofia \n female \n 18.0000 \n 18.00000 \n 0 \n 0 \n 4138 \n 9.8417 \n NA \n S \n \n \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n female \n 63.0000 \n 63.00000 \n 0 \n 0 \n 4134 \n 9.5875 \n NA \n S \n \n \n 3 \n 0 \n van Billiard, Master. James William \n male \n NA \n 29.79431 \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n van Billiard, Master. Walter John \n male \n 11.5000 \n 11.50000 \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n male \n 40.5000 \n 40.50000 \n 0 \n 2 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n 3 \n 0 \n Van Impe, Miss. Catharina \n female \n 10.0000 \n 10.00000 \n 0 \n 2 \n 345773 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n male \n NA \n 29.79431 \n 0 \n 0 \n 345777 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n male \n 33.0000 \n 33.00000 \n 0 \n 0 \n 345780 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 345770 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n male \n 28.0000 \n 28.00000 \n 0 \n 0 \n 345783 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n male \n 47.0000 \n 47.00000 \n 0 \n 0 \n 345765 \n 9.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n female \n 18.0000 \n 18.00000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Mr. Julius \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n male \n 16.0000 \n 16.00000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n female \n 31.0000 \n 31.00000 \n 1 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n 3 \n 1 \n Vartanian, Mr. David \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 2658 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n male \n 20.0000 \n 20.00000 \n 0 \n 0 \n 350416 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n female \n 14.0000 \n 14.00000 \n 0 \n 0 \n 350406 \n 7.8542 \n NA \n S \n \n \n 3 \n 0 \n Vovk, Mr. Janko \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 349252 \n 7.8958 \n NA \n S \n \n \n 3 \n 0 \n Waelens, Mr. Achille \n male \n 22.0000 \n 22.00000 \n 0 \n 0 \n 345767 \n 9.0000 \n NA \n S \n \n \n 3 \n 0 \n Ware, Mr. Frederick \n male \n NA \n 29.79431 \n 0 \n 0 \n 359309 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Warren, Mr. Charles William \n male \n NA \n 29.79431 \n 0 \n 0 \n C.A. 49867 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Webber, Mr. James \n male \n NA \n 29.79431 \n 0 \n 0 \n SOTON/OQ 3101316 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Wenzel, Mr. Linhart \n male \n 32.5000 \n 32.50000 \n 0 \n 0 \n 345775 \n 9.5000 \n NA \n S \n \n \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n female \n 38.0000 \n 38.00000 \n 0 \n 0 \n 2688 \n 7.2292 \n NA \n C \n \n \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n male \n 51.0000 \n 51.00000 \n 0 \n 0 \n 347064 \n 7.7500 \n NA \n S \n \n \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n 3101267 \n 6.4958 \n NA \n S \n \n \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n 3101266 \n 6.4958 \n NA \n S \n \n \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n female \n 47.0000 \n 47.00000 \n 1 \n 0 \n 363272 \n 7.0000 \n NA \n S \n \n \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n male \n NA \n 29.79431 \n 0 \n 0 \n 3410 \n 8.7125 \n NA \n S \n \n \n 3 \n 0 \n Willey, Mr. Edward \n male \n NA \n 29.79431 \n 0 \n 0 \n S.O./P.P. 751 \n 7.5500 \n NA \n S \n \n \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n male \n NA \n 29.79431 \n 0 \n 0 \n A/5 2466 \n 8.0500 \n NA \n S \n \n \n 3 \n 0 \n Williams, Mr. Leslie \n male \n 28.5000 \n 28.50000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n 3 \n 0 \n Windelov, Mr. Einar \n male \n 21.0000 \n 21.00000 \n 0 \n 0 \n SOTON/OQ 3101317 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Wirz, Mr. Albert \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 315154 \n 8.6625 \n NA \n S \n \n \n 3 \n 0 \n Wiseman, Mr. Phillippe \n male \n NA \n 29.79431 \n 0 \n 0 \n A/4. 34244 \n 7.2500 \n NA \n S \n \n \n 3 \n 0 \n Wittevrongel, Mr. Camille \n male \n 36.0000 \n 36.00000 \n 0 \n 0 \n 345771 \n 9.5000 \n NA \n S \n \n \n 3 \n 0 \n Yasbeck, Mr. Antoni \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n female \n 15.0000 \n 15.00000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Youseff, Mr. Gerious \n male \n 45.5000 \n 45.50000 \n 0 \n 0 \n 2628 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Yousif, Mr. Wazli \n male \n NA \n 29.79431 \n 0 \n 0 \n 2647 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Yousseff, Mr. Gerious \n male \n NA \n 29.79431 \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n 3 \n 0 \n Zabour, Miss. Hileni \n female \n 14.5000 \n 14.50000 \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Zabour, Miss. Thamine \n female \n NA \n 29.79431 \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n male \n 26.5000 \n 26.50000 \n 0 \n 0 \n 2656 \n 7.2250 \n NA \n C \n \n \n 3 \n 0 \n Zakarian, Mr. Ortin \n male \n 27.0000 \n 27.00000 \n 0 \n 0 \n 2670 \n 7.2250 \n NA \n C \n \n \n\n 3 \n 0 \n Zimmerman, Mr. Leo \n male \n 29.0000 \n 29.00000 \n 0 \n 0 \n 315082 \n 7.8750 \n NA \n S \n \n \n
\n \n \n\n embarked \n country_embarked \n pclass \n survived \n name_of_passenger \n sex_of_passenger \n age_of_passenger \n sibsp \n parch \n ticket \n fare \n cabin \n \n \n S \n England \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n female \n 29.0000 \n 0 \n 0 \n 24160 \n 211.3375 \n B5 \n \n \n S \n England \n 1 \n 1 \n Allison, Master. Hudson Trevor \n male \n 0.9167 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 0 \n Allison, Miss. Helen Loraine \n female \n 2.0000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n male \n 30.0000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n female \n 25.0000 \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n \n \n S \n England \n 1 \n 1 \n Anderson, Mr. Harry \n male \n 48.0000 \n 0 \n 0 \n 19952 \n 26.5500 \n E12 \n \n \n S \n England \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n female \n 63.0000 \n 1 \n 0 \n 13502 \n 77.9583 \n D7 \n \n \n S \n England \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n male \n NA \n 0 \n 0 \n 112050 \n 0.0000 \n A36 \n \n \n S \n England \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n female \n NA \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n \n \n C \n France \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n male \n NA \n 0 \n 0 \n PC 17609 \n 49.5042 \n NA \n \n \n C \n France \n 1 \n 0 \n Astor, Col. John Jacob \n male \n NA \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n \n \n C \n France \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n female \n 18.0000 \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n \n \n C \n France \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n \n \n S \n England \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n female \n 26.0000 \n 0 \n 0 \n 19877 \n 78.8500 \n NA \n \n \n S \n England \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n male \n 80.0000 \n 0 \n 0 \n 27042 \n 30.0000 \n A23 \n \n \n S \n England \n 1 \n 0 \n Baumann, Mr. John D \n male \n NA \n 0 \n 0 \n PC 17318 \n 25.9250 \n NA \n \n \n C \n France \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n male \n 24.0000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n \n \n C \n France \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n female \n 50.0000 \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n \n \n C \n France \n 1 \n 1 \n Bazzani, Miss. Albina \n female \n 32.0000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n \n \n C \n France \n 1 \n 0 \n Beattie, Mr. Thomson \n male \n 36.0000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n \n \n S \n England \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n male \n 37.0000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n \n \n S \n England \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n female \n 47.0000 \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n \n \n C \n France \n 1 \n 1 \n Behr, Mr. Karl Howell \n male \n 26.0000 \n 0 \n 0 \n 111369 \n 30.0000 \n C148 \n \n \n C \n France \n 1 \n 1 \n Bidois, Miss. Rosalie \n female \n 42.0000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n \n \n S \n England \n 1 \n 1 \n Bird, Miss. Ellen \n female \n 29.0000 \n 0 \n 0 \n PC 17483 \n 221.7792 \n C97 \n \n \n C \n France \n 1 \n 0 \n Birnbaum, Mr. Jakob \n male \n 25.0000 \n 0 \n 0 \n 13905 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Bishop, Mr. Dickinson H \n male \n 25.0000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n \n \n C \n France \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n female \n 19.0000 \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n \n \n S \n England \n 1 \n 1 \n Bissette, Miss. Amelia \n female \n 35.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C99 \n \n \n S \n England \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n male \n 28.0000 \n 0 \n 0 \n 110564 \n 26.5500 \n C52 \n \n \n S \n England \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n male \n 45.0000 \n 0 \n 0 \n 113784 \n 35.5000 \n T \n \n \n C \n France \n 1 \n 1 \n Blank, Mr. Henry \n male \n 40.0000 \n 0 \n 0 \n 112277 \n 31.0000 \n A31 \n \n \n S \n England \n 1 \n 1 \n Bonnell, Miss. Caroline \n female \n 30.0000 \n 0 \n 0 \n 36928 \n 164.8667 \n C7 \n \n \n S \n England \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n female \n 58.0000 \n 0 \n 0 \n 113783 \n 26.5500 \n C103 \n \n \n S \n England \n 1 \n 0 \n Borebank, Mr. John James \n male \n 42.0000 \n 0 \n 0 \n 110489 \n 26.5500 \n D22 \n \n \n C \n France \n 1 \n 1 \n Bowen, Miss. Grace Scott \n female \n 45.0000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n NA \n \n \n S \n England \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n female \n 22.0000 \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n \n \n S \n England \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n male \n NA \n 0 \n 0 \n 111427 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Brady, Mr. John Bertram \n male \n 41.0000 \n 0 \n 0 \n 113054 \n 30.5000 \n A21 \n \n \n C \n France \n 1 \n 0 \n Brandeis, Mr. Emil \n male \n 48.0000 \n 0 \n 0 \n PC 17591 \n 50.4958 \n B10 \n \n \n C \n France \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n male \n NA \n 0 \n 0 \n 112379 \n 39.6000 \n NA \n \n \n C \n France \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n female \n 44.0000 \n 0 \n 0 \n PC 17610 \n 27.7208 \n B4 \n \n \n S \n England \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n female \n 59.0000 \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n \n \n C \n France \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n female \n 60.0000 \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n \n \n C \n France \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n female \n 41.0000 \n 0 \n 0 \n 16966 \n 134.5000 \n E40 \n \n \n S \n England \n 1 \n 0 \n Butt, Major. Archibald Willingham \n male \n 45.0000 \n 0 \n 0 \n 113050 \n 26.5500 \n B38 \n \n \n S \n England \n 1 \n 0 \n Cairns, Mr. Alexander \n male \n NA \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n male \n 42.0000 \n 0 \n 0 \n PC 17476 \n 26.2875 \n E24 \n \n \n C \n France \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n female \n 53.0000 \n 0 \n 0 \n PC 17606 \n 27.4458 \n NA \n \n \n C \n France \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n male \n 36.0000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n \n \n C \n France \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n female \n 58.0000 \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n \n \n S \n England \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n male \n 33.0000 \n 0 \n 0 \n 695 \n 5.0000 \n B51 B53 B55 \n \n \n S \n England \n 1 \n 0 \n Carrau, Mr. Francisco M \n male \n 28.0000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n \n \n S \n England \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n male \n 17.0000 \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n \n \n S \n England \n 1 \n 1 \n Carter, Master. William Thornton II \n male \n 11.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 1 \n Carter, Miss. Lucile Polk \n female \n 14.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 1 \n Carter, Mr. William Ernest \n male \n 36.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n female \n 36.0000 \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n \n \n S \n England \n 1 \n 0 \n Case, Mr. Howard Brown \n male \n 49.0000 \n 0 \n 0 \n 19924 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n female \n NA \n 0 \n 0 \n 17770 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n male \n 36.0000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n \n \n S \n England \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n female \n 76.0000 \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n \n \n S \n England \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n male \n 46.0000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n \n \n S \n England \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n female \n 47.0000 \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n \n \n S \n England \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n male \n 27.0000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n \n \n S \n England \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n female \n 33.0000 \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n \n \n C \n France \n 1 \n 1 \n Chaudanson, Miss. Victorine \n female \n 36.0000 \n 0 \n 0 \n PC 17608 \n 262.3750 \n B61 \n \n \n S \n England \n 1 \n 1 \n Cherry, Miss. Gladys \n female \n 30.0000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n \n \n C \n France \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n male \n 45.0000 \n 0 \n 0 \n PC 17594 \n 29.7000 \n A9 \n \n \n S \n England \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n female \n NA \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n \n \n S \n England \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n male \n NA \n 0 \n 0 \n 112051 \n 0.0000 \n NA \n \n \n C \n France \n 1 \n 0 \n Clark, Mr. Walter Miller \n male \n 27.0000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n \n \n C \n France \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n female \n 26.0000 \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n \n \n S \n England \n 1 \n 1 \n Cleaver, Miss. Alice \n female \n 22.0000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Clifford, Mr. George Quincy \n male \n NA \n 0 \n 0 \n 110465 \n 52.0000 \n A14 \n \n \n S \n England \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n male \n 47.0000 \n 0 \n 0 \n 5727 \n 25.5875 \n E58 \n \n \n C \n France \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n female \n 39.0000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E49 \n \n \n C \n France \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n male \n 37.0000 \n 1 \n 1 \n PC 17756 \n 83.1583 \n E52 \n \n \n C \n France \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n female \n 64.0000 \n 0 \n 2 \n PC 17756 \n 83.1583 \n E45 \n \n \n S \n England \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n female \n 55.0000 \n 2 \n 0 \n 11770 \n 25.7000 \n C101 \n \n \n S \n England \n 1 \n 0 \n Crafton, Mr. John Bertram \n male \n NA \n 0 \n 0 \n 113791 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n male \n 70.0000 \n 1 \n 1 \n WE/P 5735 \n 71.0000 \n B22 \n \n \n S \n England \n 1 \n 1 \n Crosby, Miss. Harriet R \n female \n 36.0000 \n 0 \n 2 \n WE/P 5735 \n 71.0000 \n B22 \n \n \n S \n England \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n female \n 64.0000 \n 1 \n 1 \n 112901 \n 26.5500 \n B26 \n \n \n C \n France \n 1 \n 0 \n Cumings, Mr. John Bradley \n male \n 39.0000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n \n \n C \n France \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n female \n 38.0000 \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n \n \n S \n England \n 1 \n 1 \n Daly, Mr. Peter Denis \n male \n 51.0000 \n 0 \n 0 \n 113055 \n 26.5500 \n E17 \n \n \n S \n England \n 1 \n 1 \n Daniel, Mr. Robert Williams \n male \n 27.0000 \n 0 \n 0 \n 113804 \n 30.5000 \n NA \n \n \n S \n England \n 1 \n 1 \n Daniels, Miss. Sarah \n female \n 33.0000 \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Davidson, Mr. Thornton \n male \n 31.0000 \n 1 \n 0 \n F.C. 12750 \n 52.0000 \n B71 \n \n \n S \n England \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n female \n 27.0000 \n 1 \n 2 \n F.C. 12750 \n 52.0000 \n B71 \n \n \n S \n England \n 1 \n 1 \n Dick, Mr. Albert Adrian \n male \n 31.0000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n \n \n S \n England \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n female \n 17.0000 \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n \n \n S \n England \n 1 \n 1 \n Dodge, Dr. Washington \n male \n 53.0000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n \n \n S \n England \n 1 \n 1 \n Dodge, Master. Washington \n male \n 4.0000 \n 0 \n 2 \n 33638 \n 81.8583 \n A34 \n \n \n S \n England \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n female \n 54.0000 \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n \n \n C \n France \n 1 \n 0 \n Douglas, Mr. Walter Donald \n male \n 50.0000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n \n \n C \n France \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n female \n 27.0000 \n 1 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n \n \n C \n France \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n female \n 48.0000 \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n \n \n C \n France \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n female \n 48.0000 \n 1 \n 0 \n 11755 \n 39.6000 \n A16 \n \n \n C \n France \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n male \n 49.0000 \n 1 \n 0 \n PC 17485 \n 56.9292 \n A20 \n \n \n C \n France \n 1 \n 0 \n Dulles, Mr. William Crothers \n male \n 39.0000 \n 0 \n 0 \n PC 17580 \n 29.7000 \n A18 \n \n \n C \n France \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n female \n 23.0000 \n 0 \n 1 \n 11767 \n 83.1583 \n C54 \n \n \n C \n France \n 1 \n 1 \n Endres, Miss. Caroline Louise \n female \n 38.0000 \n 0 \n 0 \n PC 17757 \n 227.5250 \n C45 \n \n \n C \n France \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n female \n 54.0000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n \n \n C \n France \n 1 \n 0 \n Evans, Miss. Edith Corse \n female \n 36.0000 \n 0 \n 0 \n PC 17531 \n 31.6792 \n A29 \n \n \n S \n England \n 1 \n 0 \n Farthing, Mr. John \n male \n NA \n 0 \n 0 \n PC 17483 \n 221.7792 \n C95 \n \n \n S \n England \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n female \n NA \n 0 \n 0 \n PC 17598 \n 31.6833 \n NA \n \n \n C \n France \n 1 \n 1 \n Fleming, Miss. Margaret \n female \n NA \n 0 \n 0 \n 17421 \n 110.8833 \n NA \n \n \n S \n England \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n male \n 36.0000 \n 0 \n 0 \n PC 17474 \n 26.3875 \n E25 \n \n \n C \n France \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n male \n 30.0000 \n 0 \n 0 \n 113051 \n 27.7500 \n C111 \n \n \n S \n England \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n female \n 24.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n female \n 28.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n female \n 23.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n male \n 19.0000 \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 0 \n Fortune, Mr. Mark \n male \n 64.0000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n S \n England \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n female \n 60.0000 \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n \n \n C \n France \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n female \n 30.0000 \n 0 \n 0 \n PC 17485 \n 56.9292 \n E36 \n \n \n S \n England \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n male \n NA \n 0 \n 0 \n 113778 \n 26.5500 \n D34 \n \n \n S \n England \n 1 \n 1 \n Frauenthal, Dr. Henry William \n male \n 50.0000 \n 2 \n 0 \n PC 17611 \n 133.6500 \n NA \n \n \n C \n France \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n male \n 43.0000 \n 1 \n 0 \n 17765 \n 27.7208 \n D40 \n \n \n S \n England \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n female \n NA \n 1 \n 0 \n PC 17611 \n 133.6500 \n NA \n \n \n C \n France \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n female \n 22.0000 \n 0 \n 2 \n 13568 \n 49.5000 \n B39 \n \n \n C \n France \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n male \n 60.0000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n \n \n C \n France \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n female \n 48.0000 \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n \n \n S \n England \n 1 \n 0 \n Fry, Mr. Richard \n male \n NA \n 0 \n 0 \n 112058 \n 0.0000 \n B102 \n \n \n S \n England \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n male \n 37.0000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n \n \n S \n England \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n female \n 35.0000 \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n \n \n S \n England \n 1 \n 0 \n Gee, Mr. Arthur H \n male \n 47.0000 \n 0 \n 0 \n 111320 \n 38.5000 \n E63 \n \n \n C \n France \n 1 \n 1 \n Geiger, Miss. Amalie \n female \n 35.0000 \n 0 \n 0 \n 113503 \n 211.5000 \n C130 \n \n \n C \n France \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n female \n 22.0000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n \n \n C \n France \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n female \n 45.0000 \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n \n \n C \n France \n 1 \n 0 \n Giglio, Mr. Victor \n male \n 24.0000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B86 \n \n \n C \n France \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n male \n 49.0000 \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n \n \n C \n France \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n female \n NA \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n \n \n C \n France \n 1 \n 0 \n Goldschmidt, Mr. George B \n male \n 71.0000 \n 0 \n 0 \n PC 17754 \n 34.6542 \n A5 \n \n \n C \n France \n 1 \n 1 \n Gracie, Col. Archibald IV \n male \n 53.0000 \n 0 \n 0 \n 113780 \n 28.5000 \n C51 \n \n \n S \n England \n 1 \n 1 \n Graham, Miss. Margaret Edith \n female \n 19.0000 \n 0 \n 0 \n 112053 \n 30.0000 \n B42 \n \n \n S \n England \n 1 \n 0 \n Graham, Mr. George Edward \n male \n 38.0000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C91 \n \n \n S \n England \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n female \n 58.0000 \n 0 \n 1 \n PC 17582 \n 153.4625 \n C125 \n \n \n C \n France \n 1 \n 1 \n Greenfield, Mr. William Bertram \n male \n 23.0000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n \n \n C \n France \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n female \n 45.0000 \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n \n \n C \n France \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n male \n 46.0000 \n 0 \n 0 \n PC 17593 \n 79.2000 \n B82 B84 \n \n \n C \n France \n 1 \n 1 \n Harder, Mr. George Achilles \n male \n 25.0000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n \n \n C \n France \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n female \n 25.0000 \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n \n \n C \n France \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n male \n 48.0000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n \n \n C \n France \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n female \n 49.0000 \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n \n \n S \n England \n 1 \n 0 \n Harrington, Mr. Charles H \n male \n NA \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n \n \n S \n England \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n male \n 45.0000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n \n \n S \n England \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n female \n 35.0000 \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n \n \n S \n England \n 1 \n 0 \n Harrison, Mr. William \n male \n 40.0000 \n 0 \n 0 \n 112059 \n 0.0000 \n B94 \n \n \n C \n France \n 1 \n 1 \n Hassab, Mr. Hammad \n male \n 27.0000 \n 0 \n 0 \n PC 17572 \n 76.7292 \n D49 \n \n \n S \n England \n 1 \n 1 \n Hawksford, Mr. Walter James \n male \n NA \n 0 \n 0 \n 16988 \n 30.0000 \n D45 \n \n \n C \n France \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n female \n 24.0000 \n 0 \n 0 \n 11767 \n 83.1583 \n C54 \n \n \n S \n England \n 1 \n 0 \n Hays, Mr. Charles Melville \n male \n 55.0000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n \n \n S \n England \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n female \n 52.0000 \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n \n \n S \n England \n 1 \n 0 \n Head, Mr. Christopher \n male \n 42.0000 \n 0 \n 0 \n 113038 \n 42.5000 \n B11 \n \n \n S \n England \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n male \n NA \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n \n \n S \n England \n 1 \n 0 \n Hipkins, Mr. William Edward \n male \n 55.0000 \n 0 \n 0 \n 680 \n 50.0000 \n C39 \n \n \n C \n France \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n female \n 16.0000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n \n \n C \n France \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n female \n 44.0000 \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n \n \n S \n England \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n female \n 51.0000 \n 1 \n 0 \n 13502 \n 77.9583 \n D11 \n \n \n S \n England \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n male \n 42.0000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n female \n 35.0000 \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n male \n 35.0000 \n 0 \n 0 \n 111426 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n male \n 38.0000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n \n \n C \n France \n 1 \n 0 \n Hoyt, Mr. William Fisher \n male \n NA \n 0 \n 0 \n PC 17600 \n 30.6958 \n NA \n \n \n S \n England \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n female \n 35.0000 \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n \n \n NA \n Unknown \n 1 \n 1 \n Icard, Miss. Amelie \n female \n 38.0000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n \n \n C \n France \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n female \n 50.0000 \n 0 \n 0 \n PC 17595 \n 28.7125 \n C49 \n \n \n S \n England \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n male \n 49.0000 \n 0 \n 0 \n 112058 \n 0.0000 \n B52 B54 B56 \n \n \n S \n England \n 1 \n 0 \n Jones, Mr. Charles Cresson \n male \n 46.0000 \n 0 \n 0 \n 694 \n 26.0000 \n NA \n \n \n S \n England \n 1 \n 0 \n Julian, Mr. Henry Forbes \n male \n 50.0000 \n 0 \n 0 \n 113044 \n 26.0000 \n E60 \n \n \n C \n France \n 1 \n 0 \n Keeping, Mr. Edwin \n male \n 32.5000 \n 0 \n 0 \n 113503 \n 211.5000 \n C132 \n \n \n C \n France \n 1 \n 0 \n Kent, Mr. Edward Austin \n male \n 58.0000 \n 0 \n 0 \n 11771 \n 29.7000 \n B37 \n \n \n S \n England \n 1 \n 0 \n Kenyon, Mr. Frederick R \n male \n 41.0000 \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n \n \n S \n England \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n female \n NA \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n \n \n S \n England \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n male \n 42.0000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n \n \n S \n England \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n female \n 45.0000 \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n \n \n S \n England \n 1 \n 0 \n Klaber, Mr. Herman \n male \n NA \n 0 \n 0 \n 113028 \n 26.5500 \n C124 \n \n \n S \n England \n 1 \n 1 \n Kreuchen, Miss. Emilie \n female \n 39.0000 \n 0 \n 0 \n 24160 \n 211.3375 \n NA \n \n \n S \n England \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n female \n 49.0000 \n 0 \n 0 \n 17465 \n 25.9292 \n D17 \n \n \n C \n France \n 1 \n 1 \n LeRoy, Miss. Bertha \n female \n 30.0000 \n 0 \n 0 \n PC 17761 \n 106.4250 \n NA \n \n \n C \n France \n 1 \n 1 \n Lesurer, Mr. Gustave J \n male \n 35.0000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n B101 \n \n \n C \n France \n 1 \n 0 \n Lewy, Mr. Ervin G \n male \n NA \n 0 \n 0 \n PC 17612 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n male \n 42.0000 \n 0 \n 0 \n 17475 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n female \n 55.0000 \n 0 \n 0 \n 112377 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 1 \n Lines, Miss. Mary Conover \n female \n 16.0000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n \n \n S \n England \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n female \n 51.0000 \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n \n \n S \n England \n 1 \n 0 \n Long, Mr. Milton Clyde \n male \n 29.0000 \n 0 \n 0 \n 113501 \n 30.0000 \n D6 \n \n \n S \n England \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n female \n 21.0000 \n 0 \n 0 \n 13502 \n 77.9583 \n D9 \n \n \n S \n England \n 1 \n 0 \n Loring, Mr. Joseph Holland \n male \n 30.0000 \n 0 \n 0 \n 113801 \n 45.5000 \n NA \n \n \n C \n France \n 1 \n 1 \n Lurette, Miss. Elise \n female \n 58.0000 \n 0 \n 0 \n PC 17569 \n 146.5208 \n B80 \n \n \n S \n England \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n female \n 15.0000 \n 0 \n 1 \n 24160 \n 211.3375 \n B5 \n \n \n S \n England \n 1 \n 0 \n Maguire, Mr. John Edward \n male \n 30.0000 \n 0 \n 0 \n 110469 \n 26.0000 \n C106 \n \n \n S \n England \n 1 \n 1 \n Maioni, Miss. Roberta \n female \n 16.0000 \n 0 \n 0 \n 110152 \n 86.5000 \n B79 \n \n \n C \n France \n 1 \n 1 \n Marechal, Mr. Pierre \n male \n NA \n 0 \n 0 \n 11774 \n 29.7000 \n C47 \n \n \n S \n England \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n male \n 19.0000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n \n \n S \n England \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n female \n 18.0000 \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n \n \n C \n France \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n female \n 24.0000 \n 0 \n 0 \n PC 17482 \n 49.5042 \n C90 \n \n \n C \n France \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n male \n 46.0000 \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n \n \n S \n England \n 1 \n 0 \n McCarthy, Mr. Timothy J \n male \n 54.0000 \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n \n \n S \n England \n 1 \n 1 \n McGough, Mr. James Robert \n male \n 36.0000 \n 0 \n 0 \n PC 17473 \n 26.2875 \n E25 \n \n \n C \n France \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n male \n 28.0000 \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n \n \n C \n France \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n female \n NA \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n \n \n S \n England \n 1 \n 0 \n Millet, Mr. Francis Davis \n male \n 65.0000 \n 0 \n 0 \n 13509 \n 26.5500 \n E38 \n \n \n Q \n Ireland \n 1 \n 0 \n Minahan, Dr. William Edward \n male \n 44.0000 \n 2 \n 0 \n 19928 \n 90.0000 \n C78 \n \n \n Q \n Ireland \n 1 \n 1 \n Minahan, Miss. Daisy E \n female \n 33.0000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n \n \n Q \n Ireland \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n female \n 37.0000 \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n \n \n C \n France \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n male \n 30.0000 \n 1 \n 0 \n 13236 \n 57.7500 \n C78 \n \n \n S \n England \n 1 \n 0 \n Molson, Mr. Harry Markland \n male \n 55.0000 \n 0 \n 0 \n 113787 \n 30.5000 \n C30 \n \n \n S \n England \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n male \n 47.0000 \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n \n \n C \n France \n 1 \n 0 \n Natsch, Mr. Charles H \n male \n 37.0000 \n 0 \n 1 \n PC 17596 \n 29.7000 \n C118 \n \n \n C \n France \n 1 \n 1 \n Newell, Miss. Madeleine \n female \n 31.0000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n \n \n C \n France \n 1 \n 1 \n Newell, Miss. Marjorie \n female \n 23.0000 \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n \n \n C \n France \n 1 \n 0 \n Newell, Mr. Arthur Webster \n male \n 58.0000 \n 0 \n 2 \n 35273 \n 113.2750 \n D48 \n \n \n S \n England \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n female \n 19.0000 \n 0 \n 2 \n 11752 \n 26.2833 \n D47 \n \n \n S \n England \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n male \n 64.0000 \n 0 \n 0 \n 693 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n female \n 39.0000 \n 0 \n 0 \n PC 17758 \n 108.9000 \n C105 \n \n \n C \n France \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n male \n NA \n 0 \n 0 \n F.C. 12998 \n 25.7417 \n NA \n \n \n C \n France \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n female \n 22.0000 \n 0 \n 1 \n 113509 \n 61.9792 \n B36 \n \n \n C \n France \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n male \n 65.0000 \n 0 \n 1 \n 113509 \n 61.9792 \n B30 \n \n \n C \n France \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n male \n 28.5000 \n 0 \n 0 \n PC 17562 \n 27.7208 \n D43 \n \n \n S \n England \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n male \n NA \n 0 \n 0 \n 112052 \n 0.0000 \n NA \n \n \n S \n England \n 1 \n 0 \n Partner, Mr. Austen \n male \n 45.5000 \n 0 \n 0 \n 113043 \n 28.5000 \n C124 \n \n \n S \n England \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n male \n 23.0000 \n 0 \n 0 \n 12749 \n 93.5000 \n B24 \n \n \n S \n England \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n male \n 29.0000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n \n \n S \n England \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n female \n 22.0000 \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n \n \n C \n France \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n male \n 18.0000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n \n \n C \n France \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n female \n 17.0000 \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n \n \n S \n England \n 1 \n 1 \n Perreault, Miss. Anne \n female \n 30.0000 \n 0 \n 0 \n 12749 \n 93.5000 \n B73 \n \n \n S \n England \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n male \n 52.0000 \n 0 \n 0 \n 113786 \n 30.5000 \n C104 \n \n \n S \n England \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n male \n 47.0000 \n 0 \n 0 \n 110465 \n 52.0000 \n C110 \n \n \n C \n France \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n female \n 56.0000 \n 0 \n 1 \n 11767 \n 83.1583 \n C50 \n \n \n S \n England \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n male \n 38.0000 \n 0 \n 0 \n 19972 \n 0.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n male \n NA \n 0 \n 0 \n PC 17607 \n 39.6000 \n NA \n \n \n C \n France \n 1 \n 0 \n Ringhini, Mr. Sante \n male \n 22.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n NA \n \n \n C \n France \n 1 \n 0 \n Robbins, Mr. Victor \n male \n NA \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n \n \n S \n England \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n female \n 43.0000 \n 0 \n 1 \n 24160 \n 211.3375 \n B3 \n \n \n S \n England \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n male \n 31.0000 \n 0 \n 0 \n PC 17590 \n 50.4958 \n A24 \n \n \n S \n England \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n male \n 45.0000 \n 0 \n 0 \n 111428 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n male \n NA \n 0 \n 0 \n 113767 \n 50.0000 \n A32 \n \n \n C \n France \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n female \n 33.0000 \n 0 \n 0 \n PC 17613 \n 27.7208 \n A11 \n \n \n C \n France \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n male \n 46.0000 \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n \n \n C \n France \n 1 \n 0 \n Ross, Mr. John Hugo \n male \n 36.0000 \n 0 \n 0 \n 13049 \n 40.1250 \n A10 \n \n \n S \n England \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n female \n 33.0000 \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n \n \n C \n France \n 1 \n 0 \n Rothschild, Mr. Martin \n male \n 55.0000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n \n \n C \n France \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n female \n 54.0000 \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n \n \n S \n England \n 1 \n 0 \n Rowe, Mr. Alfred G \n male \n 33.0000 \n 0 \n 0 \n 113790 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 1 \n Ryerson, Master. John Borie \n male \n 13.0000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n female \n 18.0000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n female \n 21.0000 \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n male \n 61.0000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n C \n France \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n female \n 48.0000 \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n \n \n S \n England \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n male \n NA \n 0 \n 0 \n 19988 \n 30.5000 \n C106 \n \n \n C \n France \n 1 \n 1 \n Sagesser, Mlle. Emma \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n \n \n S \n England \n 1 \n 1 \n Salomon, Mr. Abraham L \n male \n NA \n 0 \n 0 \n 111163 \n 26.0000 \n NA \n \n \n C \n France \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n female \n 35.0000 \n 1 \n 0 \n 13236 \n 57.7500 \n C28 \n \n \n C \n France \n 1 \n 1 \n Serepeca, Miss. Augusta \n female \n 30.0000 \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n \n \n S \n England \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n male \n 34.0000 \n 0 \n 0 \n 113794 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n female \n 40.0000 \n 0 \n 0 \n PC 17582 \n 153.4625 \n C125 \n \n \n S \n England \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n male \n 35.0000 \n 0 \n 0 \n PC 17475 \n 26.2875 \n E24 \n \n \n S \n England \n 1 \n 0 \n Silvey, Mr. William Baird \n male \n 50.0000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n \n \n S \n England \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n female \n 39.0000 \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n \n \n C \n France \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n male \n 56.0000 \n 0 \n 0 \n 13213 \n 35.5000 \n A26 \n \n \n S \n England \n 1 \n 1 \n Sloper, Mr. William Thompson \n male \n 28.0000 \n 0 \n 0 \n 113788 \n 35.5000 \n A6 \n \n \n S \n England \n 1 \n 0 \n Smart, Mr. John Montgomery \n male \n 56.0000 \n 0 \n 0 \n 113792 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 0 \n Smith, Mr. James Clinch \n male \n 56.0000 \n 0 \n 0 \n 17764 \n 30.6958 \n A7 \n \n \n S \n England \n 1 \n 0 \n Smith, Mr. Lucien Philip \n male \n 24.0000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n \n \n S \n England \n 1 \n 0 \n Smith, Mr. Richard William \n male \n NA \n 0 \n 0 \n 113056 \n 26.0000 \n A19 \n \n \n S \n England \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n female \n 18.0000 \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n \n \n S \n England \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n male \n 24.0000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n \n \n S \n England \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n female \n 23.0000 \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n \n \n C \n France \n 1 \n 1 \n Spedden, Master. Robert Douglas \n male \n 6.0000 \n 0 \n 2 \n 16966 \n 134.5000 \n E34 \n \n \n C \n France \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n male \n 45.0000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n \n \n C \n France \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n female \n 40.0000 \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n \n \n C \n France \n 1 \n 0 \n Spencer, Mr. William Augustus \n male \n 57.0000 \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n \n \n C \n France \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n female \n NA \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n \n \n C \n France \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n male \n 32.0000 \n 0 \n 0 \n 13214 \n 30.5000 \n B50 \n \n \n S \n England \n 1 \n 0 \n Stead, Mr. William Thomas \n male \n 62.0000 \n 0 \n 0 \n 113514 \n 26.5500 \n C87 \n \n \n C \n France \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n male \n 54.0000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n \n \n C \n France \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n female \n 43.0000 \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n \n \n C \n France \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n female \n 52.0000 \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n \n \n C \n France \n 1 \n 0 \n Stewart, Mr. Albert A \n male \n NA \n 0 \n 0 \n PC 17605 \n 27.7208 \n NA \n \n \n NA \n Unknown \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n female \n 62.0000 \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n \n \n S \n England \n 1 \n 0 \n Straus, Mr. Isidor \n male \n 67.0000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n \n \n S \n England \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n female \n 63.0000 \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n \n \n S \n England \n 1 \n 0 \n Sutton, Mr. Frederick \n male \n 61.0000 \n 0 \n 0 \n 36963 \n 32.3208 \n D50 \n \n \n S \n England \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n female \n 48.0000 \n 0 \n 0 \n 17466 \n 25.9292 \n D17 \n \n \n S \n England \n 1 \n 1 \n Taussig, Miss. Ruth \n female \n 18.0000 \n 0 \n 2 \n 110413 \n 79.6500 \n E68 \n \n \n S \n England \n 1 \n 0 \n Taussig, Mr. Emil \n male \n 52.0000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n \n \n S \n England \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n female \n 39.0000 \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n \n \n S \n England \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n male \n 48.0000 \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n \n \n S \n England \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n female \n NA \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n \n \n C \n France \n 1 \n 0 \n Thayer, Mr. John Borland \n male \n 49.0000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n \n \n C \n France \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n male \n 17.0000 \n 0 \n 2 \n 17421 \n 110.8833 \n C70 \n \n \n C \n France \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n female \n 39.0000 \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n \n \n C \n France \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n female \n NA \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n \n \n C \n France \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n male \n 31.0000 \n 0 \n 0 \n 2543 \n 28.5375 \n C53 \n \n \n C \n France \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n male \n 40.0000 \n 0 \n 0 \n PC 17601 \n 27.7208 \n NA \n \n \n S \n England \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n male \n 61.0000 \n 0 \n 0 \n 111240 \n 33.5000 \n B19 \n \n \n S \n England \n 1 \n 0 \n Walker, Mr. William Anderson \n male \n 47.0000 \n 0 \n 0 \n 36967 \n 34.0208 \n D46 \n \n \n C \n France \n 1 \n 1 \n Ward, Miss. Anna \n female \n 35.0000 \n 0 \n 0 \n PC 17755 \n 512.3292 \n NA \n \n \n C \n France \n 1 \n 0 \n Warren, Mr. Frank Manley \n male \n 64.0000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n \n \n C \n France \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n female \n 60.0000 \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n \n \n S \n England \n 1 \n 0 \n Weir, Col. John \n male \n 60.0000 \n 0 \n 0 \n 113800 \n 26.5500 \n NA \n \n \n S \n England \n 1 \n 0 \n White, Mr. Percival Wayland \n male \n 54.0000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n \n \n S \n England \n 1 \n 0 \n White, Mr. Richard Frasar \n male \n 21.0000 \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n \n \n C \n France \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n female \n 55.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n \n \n S \n England \n 1 \n 1 \n Wick, Miss. Mary Natalie \n female \n 31.0000 \n 0 \n 2 \n 36928 \n 164.8667 \n C7 \n \n \n S \n England \n 1 \n 0 \n Wick, Mr. George Dennick \n male \n 57.0000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n \n \n S \n England \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n female \n 45.0000 \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n \n \n C \n France \n 1 \n 0 \n Widener, Mr. George Dunton \n male \n 50.0000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n \n \n C \n France \n 1 \n 0 \n Widener, Mr. Harry Elkins \n male \n 27.0000 \n 0 \n 2 \n 113503 \n 211.5000 \n C82 \n \n \n C \n France \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n female \n 50.0000 \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n \n \n S \n England \n 1 \n 1 \n Willard, Miss. Constance \n female \n 21.0000 \n 0 \n 0 \n 113795 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 0 \n Williams, Mr. Charles Duane \n male \n 51.0000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n \n \n C \n France \n 1 \n 1 \n Williams, Mr. Richard Norris II \n male \n 21.0000 \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n \n \n S \n England \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n male \n NA \n 0 \n 0 \n 113510 \n 35.0000 \n C128 \n \n \n C \n France \n 1 \n 1 \n Wilson, Miss. Helen Alice \n female \n 31.0000 \n 0 \n 0 \n 16966 \n 134.5000 \n E39 E41 \n \n \n S \n England \n 1 \n 1 \n Woolner, Mr. Hugh \n male \n NA \n 0 \n 0 \n 19947 \n 35.5000 \n C52 \n \n \n S \n England \n 1 \n 0 \n Wright, Mr. George \n male \n 62.0000 \n 0 \n 0 \n 113807 \n 26.5500 \n NA \n \n \n C \n France \n 1 \n 1 \n Young, Miss. Marie Grice \n female \n 36.0000 \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n \n \n C \n France \n 2 \n 0 \n Abelson, Mr. Samuel \n male \n 30.0000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n \n \n C \n France \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n female \n 28.0000 \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n male \n 30.0000 \n 0 \n 0 \n 248744 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n male \n 18.0000 \n 0 \n 0 \n 231945 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n male \n 25.0000 \n 0 \n 0 \n C.A. 34050 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Angle, Mr. William A \n male \n 34.0000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n female \n 36.0000 \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ashby, Mr. John \n male \n 57.0000 \n 0 \n 0 \n 244346 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n male \n 18.0000 \n 0 \n 0 \n 29108 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n male \n 23.0000 \n 0 \n 0 \n C.A. 31030 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n female \n 36.0000 \n 0 \n 0 \n 28551 \n 13.0000 \n D \n \n \n S \n England \n 2 \n 0 \n Banfield, Mr. Frederick James \n male \n 28.0000 \n 0 \n 0 \n C.A./SOTON 34068 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bateman, Rev. Robert James \n male \n 51.0000 \n 0 \n 0 \n S.O.P. 1166 \n 12.5250 \n NA \n \n \n S \n England \n 2 \n 1 \n Beane, Mr. Edward \n male \n 32.0000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n female \n 19.0000 \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Beauchamp, Mr. Henry James \n male \n 28.0000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Becker, Master. Richard F \n male \n 1.0000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Becker, Miss. Marion Louise \n female \n 4.0000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n female \n 12.0000 \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n female \n 36.0000 \n 0 \n 3 \n 230136 \n 39.0000 \n F4 \n \n \n S \n England \n 2 \n 1 \n Beesley, Mr. Lawrence \n male \n 34.0000 \n 0 \n 0 \n 248698 \n 13.0000 \n D56 \n \n \n S \n England \n 2 \n 1 \n Bentham, Miss. Lilian W \n female \n 19.0000 \n 0 \n 0 \n 28404 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Berriman, Mr. William John \n male \n 23.0000 \n 0 \n 0 \n 28425 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Botsford, Mr. William Hull \n male \n 26.0000 \n 0 \n 0 \n 237670 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bowenur, Mr. Solomon \n male \n 42.0000 \n 0 \n 0 \n 211535 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bracken, Mr. James H \n male \n 27.0000 \n 0 \n 0 \n 220367 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n female \n 24.0000 \n 0 \n 0 \n 248733 \n 13.0000 \n F33 \n \n \n S \n England \n 2 \n 1 \n Brown, Miss. Edith Eileen \n female \n 15.0000 \n 0 \n 2 \n 29750 \n 39.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n male \n 60.0000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n female \n 40.0000 \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n female \n 20.0000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n male \n 25.0000 \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Buss, Miss. Kate \n female \n 36.0000 \n 0 \n 0 \n 27849 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n male \n 25.0000 \n 0 \n 0 \n 234686 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n male \n 42.0000 \n 0 \n 0 \n 244310 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n female \n 42.0000 \n 0 \n 0 \n 236852 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Caldwell, Master. Alden Gates \n male \n 0.8333 \n 0 \n 2 \n 248738 \n 29.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n male \n 26.0000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n female \n 22.0000 \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Cameron, Miss. Clear Annie \n female \n 35.0000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Campbell, Mr. William \n male \n NA \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Carbines, Mr. William \n male \n 19.0000 \n 0 \n 0 \n 28424 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n female \n 44.0000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n male \n 54.0000 \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Chapman, Mr. Charles Henry \n male \n 52.0000 \n 0 \n 0 \n 248731 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Chapman, Mr. John Henry \n male \n 37.0000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n female \n 29.0000 \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Christy, Miss. Julie Rachel \n female \n 25.0000 \n 1 \n 1 \n 237789 \n 30.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n female \n 45.0000 \n 0 \n 2 \n 237789 \n 30.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n male \n 29.0000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n female \n 28.0000 \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n male \n 29.0000 \n 0 \n 0 \n W./C. 14263 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n male \n 28.0000 \n 0 \n 0 \n 248740 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n male \n 24.0000 \n 0 \n 0 \n 28034 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n female \n 8.0000 \n 0 \n 2 \n C.A. 31921 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 0 \n Collyer, Mr. Harvey \n male \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n female \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n female \n 22.0000 \n 0 \n 0 \n W./C. 14266 \n 10.5000 \n F33 \n \n \n S \n England \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n female \n 30.0000 \n 0 \n 0 \n 237249 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n female \n NA \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n male \n 21.0000 \n 0 \n 0 \n 29107 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n male \n NA \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Davies, Master. John Morgan Jr \n male \n 8.0000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n Davies, Mr. Charles Henry \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n female \n 48.0000 \n 0 \n 2 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Davis, Miss. Mary \n female \n 28.0000 \n 0 \n 0 \n 237668 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n male \n 32.0000 \n 0 \n 0 \n 244360 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Deacon, Mr. Percy William \n male \n 17.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n C \n France \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n male \n 29.0000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n \n \n C \n France \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n female \n 24.0000 \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n \n \n S \n England \n 2 \n 0 \n Denbury, Mr. Herbert \n male \n 25.0000 \n 0 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Dibden, Mr. William \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Doling, Miss. Elsie \n female \n 18.0000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n female \n 34.0000 \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Downton, Mr. William James \n male \n 54.0000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Drew, Master. Marshall Brines \n male \n 8.0000 \n 0 \n 2 \n 28220 \n 32.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Drew, Mr. James Vivian \n male \n 42.0000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n female \n 34.0000 \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Duran y More, Miss. Asuncion \n female \n 27.0000 \n 1 \n 0 \n SC/PARIS 2149 \n 13.8583 \n NA \n \n \n C \n France \n 2 \n 1 \n Duran y More, Miss. Florentina \n female \n 30.0000 \n 1 \n 0 \n SC/PARIS 2148 \n 13.8583 \n NA \n \n \n S \n England \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n male \n 23.0000 \n 0 \n 0 \n 29751 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Enander, Mr. Ingvar \n male \n 21.0000 \n 0 \n 0 \n 236854 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n male \n 18.0000 \n 0 \n 0 \n 236171 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Faunthorpe, Mr. Harry \n male \n 40.0000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n female \n 29.0000 \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n male \n 18.0000 \n 0 \n 0 \n C.A. 15185 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n male \n 36.0000 \n 0 \n 0 \n 229236 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n male \n NA \n 0 \n 0 \n 239854 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n female \n 38.0000 \n 0 \n 0 \n 237671 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Fynney, Mr. Joseph J \n male \n 35.0000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gale, Mr. Harry \n male \n 38.0000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gale, Mr. Shadrach \n male \n 34.0000 \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Garside, Miss. Ethel \n female \n 34.0000 \n 0 \n 0 \n 243880 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gaskell, Mr. Alfred \n male \n 16.0000 \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gavey, Mr. Lawrence \n male \n 26.0000 \n 0 \n 0 \n 31028 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gilbert, Mr. William \n male \n 47.0000 \n 0 \n 0 \n C.A. 30769 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Giles, Mr. Edgar \n male \n 21.0000 \n 1 \n 0 \n 28133 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Giles, Mr. Frederick Edward \n male \n 21.0000 \n 1 \n 0 \n 28134 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Giles, Mr. Ralph \n male \n 24.0000 \n 0 \n 0 \n 248726 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gill, Mr. John William \n male \n 24.0000 \n 0 \n 0 \n 233866 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Gillespie, Mr. William Henry \n male \n 34.0000 \n 0 \n 0 \n 12233 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n male \n 30.0000 \n 0 \n 0 \n 250646 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Greenberg, Mr. Samuel \n male \n 52.0000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hale, Mr. Reginald \n male \n 30.0000 \n 0 \n 0 \n 250653 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hamalainen, Master. Viljo \n male \n 0.6667 \n 1 \n 1 \n 250649 \n 14.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n female \n 24.0000 \n 0 \n 2 \n 250649 \n 14.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Harbeck, Mr. William H \n male \n 44.0000 \n 0 \n 0 \n 248746 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n female \n 6.0000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Harper, Rev. John \n male \n 28.0000 \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Harris, Mr. George \n male \n 62.0000 \n 0 \n 0 \n S.W./PP 752 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Harris, Mr. Walter \n male \n 30.0000 \n 0 \n 0 \n W/C 14208 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hart, Miss. Eva Miriam \n female \n 7.0000 \n 0 \n 2 \n F.C.C. 13529 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 0 \n Hart, Mr. Benjamin \n male \n 43.0000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n female \n 45.0000 \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n \n \n S \n England \n 2 \n 1 \n Herman, Miss. Alice \n female \n 24.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Herman, Miss. Kate \n female \n 24.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Herman, Mr. Samuel \n male \n 49.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n female \n 48.0000 \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n female \n 55.0000 \n 0 \n 0 \n 248706 \n 16.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n male \n 24.0000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hickman, Mr. Lewis \n male \n 32.0000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hickman, Mr. Stanley George \n male \n 21.0000 \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hiltunen, Miss. Marta \n female \n 18.0000 \n 1 \n 1 \n 250650 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n female \n 20.0000 \n 2 \n 1 \n 29105 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hocking, Mr. Richard George \n male \n 23.0000 \n 2 \n 1 \n 29104 \n 11.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n male \n 36.0000 \n 0 \n 0 \n 242963 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n female \n 54.0000 \n 1 \n 3 \n 29105 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hodges, Mr. Henry Price \n male \n 50.0000 \n 0 \n 0 \n 250643 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hold, Mr. Stephen \n male \n 44.0000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n female \n 29.0000 \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n male \n 21.0000 \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Hosono, Mr. Masabumi \n male \n 42.0000 \n 0 \n 0 \n 237798 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Howard, Mr. Benjamin \n male \n 63.0000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n female \n 60.0000 \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Hunt, Mr. George Henry \n male \n 33.0000 \n 0 \n 0 \n SCO/W 1585 \n 12.2750 \n NA \n \n \n S \n England \n 2 \n 1 \n Ilett, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SO/C 14885 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n male \n 42.0000 \n 1 \n 0 \n 243847 \n 27.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n female \n 24.0000 \n 2 \n 1 \n 243847 \n 27.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jarvis, Mr. John Denzil \n male \n 47.0000 \n 0 \n 0 \n 237565 \n 15.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n male \n 24.0000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n male \n 22.0000 \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n male \n 32.0000 \n 0 \n 0 \n C.A. 33111 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n female \n 23.0000 \n 0 \n 0 \n SC/AH Basle 541 \n 13.7917 \n D \n \n \n S \n England \n 2 \n 0 \n Kantor, Mr. Sinai \n male \n 34.0000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n female \n 24.0000 \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n female \n 22.0000 \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n \n \n Q \n Ireland \n 2 \n 1 \n Keane, Miss. Nora A \n female \n NA \n 0 \n 0 \n 226593 \n 12.3500 \n E101 \n \n \n Q \n Ireland \n 2 \n 0 \n Keane, Mr. Daniel \n male \n 35.0000 \n 0 \n 0 \n 233734 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n female \n 45.0000 \n 0 \n 0 \n 223596 \n 13.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n male \n 57.0000 \n 0 \n 0 \n 219533 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 0 \n Knight, Mr. Robert J \n male \n NA \n 0 \n 0 \n 239855 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n male \n 31.0000 \n 0 \n 0 \n C.A. 18723 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n female \n 26.0000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Lahtinen, Rev. William \n male \n 30.0000 \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Lamb, Mr. John Joseph \n male \n NA \n 0 \n 0 \n 240261 \n 10.7083 \n NA \n \n \n C \n France \n 2 \n 1 \n Laroche, Miss. Louise \n female \n 1.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n female \n 3.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n male \n 25.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n female \n 22.0000 \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n \n \n C \n France \n 2 \n 1 \n Lehmann, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SC 1748 \n 12.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n female \n NA \n 0 \n 0 \n 248727 \n 33.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n female \n 34.0000 \n 0 \n 0 \n C.A. 34260 \n 10.5000 \n F33 \n \n \n C \n France \n 2 \n 0 \n Levy, Mr. Rene Jacques \n male \n 36.0000 \n 0 \n 0 \n SC/Paris 2163 \n 12.8750 \n D \n \n \n S \n England \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n male \n 24.0000 \n 0 \n 0 \n C.A. 29566 \n 10.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Lingane, Mr. John \n male \n 61.0000 \n 0 \n 0 \n 235509 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 0 \n Louch, Mr. Charles Alexander \n male \n 50.0000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n female \n 42.0000 \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Mack, Mrs. (Mary) \n female \n 57.0000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n E77 \n \n \n C \n France \n 2 \n 0 \n Malachard, Mr. Noel \n male \n NA \n 0 \n 0 \n 237735 \n 15.0458 \n D \n \n \n C \n France \n 2 \n 1 \n Mallet, Master. Andre \n male \n 1.0000 \n 0 \n 2 \n S.C./PARIS 2079 \n 37.0042 \n NA \n \n \n C \n France \n 2 \n 0 \n Mallet, Mr. Albert \n male \n 31.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n \n \n C \n France \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n female \n 24.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n \n \n C \n France \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n male \n NA \n 0 \n 0 \n SC/A.3 2861 \n 15.5792 \n NA \n \n \n S \n England \n 2 \n 0 \n Matthews, Mr. William John \n male \n 30.0000 \n 0 \n 0 \n 28228 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n male \n 40.0000 \n 0 \n 0 \n 239059 \n 16.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n male \n 32.0000 \n 0 \n 0 \n 237216 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n McCrie, Mr. James Matthew \n male \n 30.0000 \n 0 \n 0 \n 233478 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n McKane, Mr. Peter David \n male \n 46.0000 \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n female \n 13.0000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n female \n 41.0000 \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Mellors, Mr. William John \n male \n 19.0000 \n 0 \n 0 \n SW/PP 751 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Meyer, Mr. August \n male \n 39.0000 \n 0 \n 0 \n 248723 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Milling, Mr. Jacob Christian \n male \n 48.0000 \n 0 \n 0 \n 234360 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n male \n 70.0000 \n 0 \n 0 \n C.A. 24580 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Montvila, Rev. Juozas \n male \n 27.0000 \n 0 \n 0 \n 211536 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Moraweck, Dr. Ernest \n male \n 54.0000 \n 0 \n 0 \n 29011 \n 14.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n male \n 39.0000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n male \n 16.0000 \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 0 \n Myles, Mr. Thomas Francis \n male \n 62.0000 \n 0 \n 0 \n 240276 \n 9.6875 \n NA \n \n \n C \n France \n 2 \n 0 \n Nasser, Mr. Nicholas \n male \n 32.5000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n \n \n C \n France \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n female \n 14.0000 \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n \n \n S \n England \n 2 \n 1 \n Navratil, Master. Edmond Roger \n male \n 2.0000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n \n \n S \n England \n 2 \n 1 \n Navratil, Master. Michel M \n male \n 3.0000 \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n \n \n S \n England \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n male \n 36.5000 \n 0 \n 2 \n 230080 \n 26.0000 \n F2 \n \n \n S \n England \n 2 \n 0 \n Nesson, Mr. Israel \n male \n 26.0000 \n 0 \n 0 \n 244368 \n 13.0000 \n F2 \n \n \n S \n England \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n male \n 19.0000 \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n Norman, Mr. Robert Douglas \n male \n 28.0000 \n 0 \n 0 \n 218629 \n 13.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n male \n 20.0000 \n 0 \n 0 \n SC/PARIS 2166 \n 13.8625 \n D38 \n \n \n S \n England \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n female \n 29.0000 \n 0 \n 0 \n C.A. 29395 \n 10.5000 \n F33 \n \n \n S \n England \n 2 \n 0 \n Otter, Mr. Richard \n male \n 39.0000 \n 0 \n 0 \n 28213 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n male \n 22.0000 \n 0 \n 0 \n W./C. 14260 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Padro y Manent, Mr. Julian \n male \n NA \n 0 \n 0 \n SC/PARIS 2146 \n 13.8625 \n NA \n \n \n S \n England \n 2 \n 0 \n Pain, Dr. Alfred \n male \n 23.0000 \n 0 \n 0 \n 244278 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n male \n 29.0000 \n 0 \n 0 \n SC/PARIS 2147 \n 13.8583 \n NA \n \n \n S \n England \n 2 \n 0 \n Parker, Mr. Clifford Richard \n male \n 28.0000 \n 0 \n 0 \n SC 14888 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n male \n NA \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n female \n 50.0000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Pengelly, Mr. Frederick William \n male \n 19.0000 \n 0 \n 0 \n 28665 \n 10.5000 \n NA \n \n \n C \n France \n 2 \n 0 \n Pernot, Mr. Rene \n male \n NA \n 0 \n 0 \n SC/PARIS 2131 \n 15.0500 \n NA \n \n \n S \n England \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n male \n 41.0000 \n 0 \n 0 \n 237393 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n female \n 21.0000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n female \n 19.0000 \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Phillips, Mr. Escott Robert \n male \n 43.0000 \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n female \n 32.0000 \n 0 \n 0 \n 234604 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ponesell, Mr. Martin \n male \n 34.0000 \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n \n \n C \n France \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n male \n 30.0000 \n 0 \n 0 \n C.A. 34644 \n 12.7375 \n NA \n \n \n C \n France \n 2 \n 0 \n Pulbaum, Mr. Franz \n male \n 27.0000 \n 0 \n 0 \n SC/PARIS 2168 \n 15.0333 \n NA \n \n \n S \n England \n 2 \n 1 \n Quick, Miss. Phyllis May \n female \n 2.0000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Quick, Miss. Winifred Vera \n female \n 8.0000 \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n female \n 33.0000 \n 0 \n 2 \n 26360 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Reeves, Mr. David \n male \n 36.0000 \n 0 \n 0 \n C.A. 17248 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Renouf, Mr. Peter Henry \n male \n 34.0000 \n 1 \n 0 \n 31027 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n female \n 30.0000 \n 3 \n 0 \n 31027 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n female \n 28.0000 \n 0 \n 0 \n 230434 \n 13.0000 \n NA \n \n \n C \n France \n 2 \n 0 \n Richard, Mr. Emile \n male \n 23.0000 \n 0 \n 0 \n SC/PARIS 2133 \n 15.0458 \n NA \n \n \n S \n England \n 2 \n 1 \n Richards, Master. George Sibley \n male \n 0.8333 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Richards, Master. William Rowe \n male \n 3.0000 \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n female \n 24.0000 \n 2 \n 3 \n 29106 \n 18.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Ridsdale, Miss. Lucy \n female \n 50.0000 \n 0 \n 0 \n W./C. 14258 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n male \n 19.0000 \n 0 \n 0 \n 28004 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Rugg, Miss. Emily \n female \n 21.0000 \n 0 \n 0 \n C.A. 31026 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Schmidt, Mr. August \n male \n 26.0000 \n 0 \n 0 \n 248659 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n male \n 25.0000 \n 0 \n 0 \n 244361 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sharp, Mr. Percival James R \n male \n 27.0000 \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n female \n 25.0000 \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n female \n 18.0000 \n 0 \n 2 \n 250652 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Sincock, Miss. Maude \n female \n 20.0000 \n 0 \n 0 \n C.A. 33112 \n 36.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Sinkkonen, Miss. Anna \n female \n 30.0000 \n 0 \n 0 \n 250648 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n male \n 59.0000 \n 0 \n 0 \n 237442 \n 13.5000 \n NA \n \n \n Q \n Ireland \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n female \n 30.0000 \n 0 \n 0 \n 234818 \n 12.3500 \n NA \n \n \n S \n England \n 2 \n 0 \n Slemen, Mr. Richard James \n male \n 35.0000 \n 0 \n 0 \n 28206 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Smith, Miss. Marion Elsie \n female \n 40.0000 \n 0 \n 0 \n 31418 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n male \n 25.0000 \n 0 \n 0 \n C.A. 29178 \n 13.0000 \n NA \n \n \n C \n France \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n male \n 41.0000 \n 0 \n 0 \n 237734 \n 15.0458 \n NA \n \n \n S \n England \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n male \n 25.0000 \n 0 \n 0 \n F.C.C. 13540 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Swane, Mr. George \n male \n 18.5000 \n 0 \n 0 \n 248734 \n 13.0000 \n F \n \n \n S \n England \n 2 \n 0 \n Sweet, Mr. George Frederick \n male \n 14.0000 \n 0 \n 0 \n 220845 \n 65.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Toomey, Miss. Ellen \n female \n 50.0000 \n 0 \n 0 \n F.C.C. 13531 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n male \n 23.0000 \n 0 \n 0 \n 233639 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n female \n 28.0000 \n 0 \n 0 \n 240929 \n 12.6500 \n NA \n \n \n S \n England \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n female \n 27.0000 \n 0 \n 0 \n 34218 \n 10.5000 \n E101 \n \n \n S \n England \n 2 \n 0 \n Turpin, Mr. William John Robert \n male \n 29.0000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n female \n 27.0000 \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Veal, Mr. James \n male \n 40.0000 \n 0 \n 0 \n 28221 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Walcroft, Miss. Nellie \n female \n 31.0000 \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ware, Mr. John James \n male \n 30.0000 \n 1 \n 0 \n CA 31352 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Ware, Mr. William Jeffery \n male \n 23.0000 \n 1 \n 0 \n 28666 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n female \n 31.0000 \n 0 \n 0 \n CA 31352 \n 21.0000 \n NA \n \n \n S \n England \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n male \n NA \n 0 \n 0 \n 239856 \n 0.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Watt, Miss. Bertha J \n female \n 12.0000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n female \n 40.0000 \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n Webber, Miss. Susan \n female \n 32.5000 \n 0 \n 0 \n 27267 \n 13.0000 \n E101 \n \n \n S \n England \n 2 \n 0 \n Weisz, Mr. Leopold \n male \n 27.0000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n female \n 29.0000 \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wells, Master. Ralph Lester \n male \n 2.0000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wells, Miss. Joan \n female \n 4.0000 \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n female \n 29.0000 \n 0 \n 2 \n 29103 \n 23.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n West, Miss. Barbara J \n female \n 0.9167 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n West, Miss. Constance Mirium \n female \n 5.0000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n West, Mr. Edwy Arthur \n male \n 36.0000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n female \n 33.0000 \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n \n \n S \n England \n 2 \n 0 \n Wheadon, Mr. Edward H \n male \n 66.0000 \n 0 \n 0 \n C.A. 24579 \n 10.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n male \n NA \n 0 \n 0 \n SC/PARIS 2159 \n 12.8750 \n NA \n \n \n S \n England \n 2 \n 1 \n Wilhelms, Mr. Charles \n male \n 31.0000 \n 0 \n 0 \n 244270 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Williams, Mr. Charles Eugene \n male \n NA \n 0 \n 0 \n 244373 \n 13.0000 \n NA \n \n \n S \n England \n 2 \n 1 \n Wright, Miss. Marion \n female \n 26.0000 \n 0 \n 0 \n 220844 \n 13.5000 \n NA \n \n \n S \n England \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n female \n 24.0000 \n 0 \n 0 \n 248747 \n 13.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Abbing, Mr. Anthony \n male \n 42.0000 \n 0 \n 0 \n C.A. 5547 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n male \n 13.0000 \n 0 \n 2 \n C.A. 2673 \n 20.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n male \n 16.0000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n female \n 35.0000 \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n female \n 16.0000 \n 0 \n 0 \n 348125 \n 7.6500 \n NA \n \n \n S \n England \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n male \n 25.0000 \n 0 \n 0 \n 348122 \n 7.6500 \n F G63 \n \n \n S \n England \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101284 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n female \n 18.0000 \n 0 \n 0 \n 2657 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n male \n 30.0000 \n 0 \n 0 \n C 7076 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Adams, Mr. John \n male \n 26.0000 \n 0 \n 0 \n 341826 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n female \n 40.0000 \n 1 \n 0 \n 7546 \n 9.4750 \n NA \n \n \n S \n England \n 3 \n 1 \n Aks, Master. Philip Frank \n male \n 0.8333 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n \n \n S \n England \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n female \n 18.0000 \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n \n \n C \n France \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n male \n 26.0000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n \n \n S \n England \n 3 \n 0 \n Alexander, Mr. William \n male \n 26.0000 \n 0 \n 0 \n 3474 \n 7.8875 \n NA \n \n \n S \n England \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101287 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Ali, Mr. Ahmed \n male \n 24.0000 \n 0 \n 0 \n SOTON/O.Q. 3101311 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Ali, Mr. William \n male \n 25.0000 \n 0 \n 0 \n SOTON/O.Q. 3101312 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Allen, Mr. William Henry \n male \n 35.0000 \n 0 \n 0 \n 373450 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Allum, Mr. Owen George \n male \n 18.0000 \n 0 \n 0 \n 2223 \n 8.3000 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n male \n 32.0000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n \n \n S \n England \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n female \n 19.0000 \n 1 \n 0 \n 350046 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n male \n 4.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n female \n 6.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n female \n 2.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n female \n 17.0000 \n 4 \n 2 \n 3101281 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n female \n 38.0000 \n 4 \n 2 \n 347091 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n female \n 9.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n female \n 11.0000 \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Mr. Anders Johan \n male \n 39.0000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n male \n 27.0000 \n 0 \n 0 \n 350043 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n male \n 26.0000 \n 0 \n 0 \n 347075 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n female \n 39.0000 \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n \n \n S \n England \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n male \n 20.0000 \n 0 \n 0 \n 347466 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Angheloff, Mr. Minko \n male \n 26.0000 \n 0 \n 0 \n 349202 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n male \n 25.0000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n \n \n S \n England \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n female \n 18.0000 \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n \n \n S \n England \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n male \n 24.0000 \n 0 \n 0 \n 349911 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Asim, Mr. Adola \n male \n 35.0000 \n 0 \n 0 \n SOTON/O.Q. 3101310 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Master. Carl Edgar \n male \n 5.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n male \n 9.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n male \n 3.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Master. Filip Oscar \n male \n 13.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n female \n 5.0000 \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n male \n 40.0000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Mr. Johan Charles \n male \n 23.0000 \n 0 \n 0 \n 350054 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n female \n 38.0000 \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n \n \n C \n France \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n female \n 45.0000 \n 0 \n 0 \n 2696 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Assaf, Mr. Gerios \n male \n 21.0000 \n 0 \n 0 \n 2692 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Assam, Mr. Ali \n male \n 23.0000 \n 0 \n 0 \n SOTON/O.Q. 3101309 \n 7.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Attalah, Miss. Malake \n female \n 17.0000 \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n \n \n C \n France \n 3 \n 0 \n Attalah, Mr. Sleiman \n male \n 30.0000 \n 0 \n 0 \n 2694 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Augustsson, Mr. Albert \n male \n 23.0000 \n 0 \n 0 \n 347468 \n 7.8542 \n NA \n \n \n C \n France \n 3 \n 1 \n Ayoub, Miss. Banoura \n female \n 13.0000 \n 0 \n 0 \n 2687 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Baccos, Mr. Raffull \n male \n 20.0000 \n 0 \n 0 \n 2679 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n male \n 32.0000 \n 1 \n 0 \n 3101278 \n 15.8500 \n NA \n \n \n S \n England \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n female \n 33.0000 \n 3 \n 0 \n 3101278 \n 15.8500 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Miss. Eugenie \n female \n 0.7500 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n female \n 0.7500 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n female \n 5.0000 \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n \n \n C \n France \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n female \n 24.0000 \n 0 \n 3 \n 2666 \n 19.2583 \n NA \n \n \n S \n England \n 3 \n 1 \n Badman, Miss. Emily Louisa \n female \n 18.0000 \n 0 \n 0 \n A/4 31416 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Badt, Mr. Mohamed \n male \n 40.0000 \n 0 \n 0 \n 2623 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Balkic, Mr. Cerin \n male \n 26.0000 \n 0 \n 0 \n 349248 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Barah, Mr. Hanna Assi \n male \n 20.0000 \n 0 \n 0 \n 2663 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Barbara, Miss. Saiide \n female \n 18.0000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n female \n 45.0000 \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Barry, Miss. Julia \n female \n 27.0000 \n 0 \n 0 \n 330844 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Barton, Mr. David John \n male \n 22.0000 \n 0 \n 0 \n 324669 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Beavan, Mr. William Thomas \n male \n 19.0000 \n 0 \n 0 \n 323951 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n male \n 26.0000 \n 0 \n 0 \n 347068 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n male \n 22.0000 \n 0 \n 0 \n PP 4348 \n 9.3500 \n NA \n \n \n C \n France \n 3 \n 0 \n Betros, Master. Seman \n male \n NA \n 0 \n 0 \n 2622 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Betros, Mr. Tannous \n male \n 20.0000 \n 0 \n 0 \n 2648 \n 4.0125 \n NA \n \n \n S \n England \n 3 \n 1 \n Bing, Mr. Lee \n male \n 32.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n male \n 21.0000 \n 0 \n 0 \n 312992 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n male \n 18.0000 \n 0 \n 0 \n 347090 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n male \n 26.0000 \n 0 \n 0 \n 349224 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Master. Akar \n male \n 6.0000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Miss. Nourelain \n female \n 9.0000 \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2664 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n female \n NA \n 0 \n 2 \n 2678 \n 15.2458 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Bourke, Miss. Mary \n female \n NA \n 0 \n 2 \n 364848 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Bourke, Mr. John \n male \n 40.0000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n female \n 32.0000 \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n male \n 21.0000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n female \n 22.0000 \n 0 \n 0 \n 334914 \n 7.7250 \n NA \n \n \n S \n England \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n female \n 20.0000 \n 0 \n 0 \n 347471 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Braund, Mr. Lewis Richard \n male \n 29.0000 \n 1 \n 0 \n 3460 \n 7.0458 \n NA \n \n \n S \n England \n 3 \n 0 \n Braund, Mr. Owen Harris \n male \n 22.0000 \n 1 \n 0 \n A/5 21171 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n male \n 22.0000 \n 0 \n 0 \n 350045 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n male \n 35.0000 \n 0 \n 0 \n 364512 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Buckley, Miss. Katherine \n female \n 18.5000 \n 0 \n 0 \n 329944 \n 7.2833 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Buckley, Mr. Daniel \n male \n 21.0000 \n 0 \n 0 \n 330920 \n 7.8208 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Burke, Mr. Jeremiah \n male \n 19.0000 \n 0 \n 0 \n 365222 \n 6.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Burns, Miss. Mary Delia \n female \n 18.0000 \n 0 \n 0 \n 330963 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Miss. Manda \n female \n 21.0000 \n 0 \n 0 \n 315087 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Miss. Marija \n female \n 30.0000 \n 0 \n 0 \n 315084 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Mr. Jego Grga \n male \n 18.0000 \n 0 \n 0 \n 315091 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Cacic, Mr. Luka \n male \n 38.0000 \n 0 \n 0 \n 315089 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Calic, Mr. Jovo \n male \n 17.0000 \n 0 \n 0 \n 315093 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Calic, Mr. Petar \n male \n 17.0000 \n 0 \n 0 \n 315086 \n 8.6625 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Canavan, Miss. Mary \n female \n 21.0000 \n 0 \n 0 \n 364846 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Canavan, Mr. Patrick \n male \n 21.0000 \n 0 \n 0 \n 364858 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Cann, Mr. Ernest Charles \n male \n 21.0000 \n 0 \n 0 \n A./5. 2152 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Caram, Mr. Joseph \n male \n NA \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n \n \n C \n France \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n female \n NA \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n \n \n S \n England \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n male \n 28.0000 \n 0 \n 0 \n 350042 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n male \n 24.0000 \n 0 \n 0 \n 350409 \n 7.8542 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n female \n 16.0000 \n 0 \n 0 \n 367231 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Carr, Miss. Jeannie \n female \n 37.0000 \n 0 \n 0 \n 368364 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Carver, Mr. Alfred John \n male \n 28.0000 \n 0 \n 0 \n 392095 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Celotti, Mr. Francesco \n male \n 24.0000 \n 0 \n 0 \n 343275 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Charters, Mr. David \n male \n 21.0000 \n 0 \n 0 \n A/5. 13032 \n 7.7333 \n NA \n \n \n S \n England \n 3 \n 1 \n Chip, Mr. Chang \n male \n 32.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Christmann, Mr. Emil \n male \n 29.0000 \n 0 \n 0 \n 343276 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n male \n 26.0000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n male \n 18.0000 \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n \n \n S \n England \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n male \n 20.0000 \n 0 \n 0 \n SOTON/O.Q. 3101307 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n male \n 18.0000 \n 0 \n 0 \n A/5 3540 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Colbert, Mr. Patrick \n male \n 24.0000 \n 0 \n 0 \n 371109 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Coleff, Mr. Peju \n male \n 36.0000 \n 0 \n 0 \n 349210 \n 7.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Coleff, Mr. Satio \n male \n 24.0000 \n 0 \n 0 \n 349209 \n 7.4958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n male \n 31.0000 \n 0 \n 0 \n 21332 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Connaghton, Mr. Michael \n male \n 31.0000 \n 0 \n 0 \n 335097 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Connolly, Miss. Kate \n female \n 22.0000 \n 0 \n 0 \n 370373 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Connolly, Miss. Kate \n female \n 30.0000 \n 0 \n 0 \n 330972 \n 7.6292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Connors, Mr. Patrick \n male \n 70.5000 \n 0 \n 0 \n 370369 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Cook, Mr. Jacob \n male \n 43.0000 \n 0 \n 0 \n A/5 3536 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Cor, Mr. Bartol \n male \n 35.0000 \n 0 \n 0 \n 349230 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Cor, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 349229 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Cor, Mr. Liudevit \n male \n 19.0000 \n 0 \n 0 \n 349231 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Corn, Mr. Harry \n male \n 30.0000 \n 0 \n 0 \n SOTON/OQ 392090 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n male \n 9.0000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n \n \n S \n England \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n male \n 3.0000 \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n \n \n S \n England \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n female \n 36.0000 \n 0 \n 2 \n C.A. 37671 \n 15.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Coxon, Mr. Daniel \n male \n 59.0000 \n 0 \n 0 \n 364500 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Crease, Mr. Ernest James \n male \n 19.0000 \n 0 \n 0 \n S.P. 3464 \n 8.1583 \n NA \n \n \n S \n England \n 3 \n 1 \n Cribb, Miss. Laura Alice \n female \n 17.0000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Cribb, Mr. John Hatfield \n male \n 44.0000 \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Culumovic, Mr. Jeso \n male \n 17.0000 \n 0 \n 0 \n 315090 \n 8.6625 \n NA \n \n \n C \n France \n 3 \n 0 \n Daher, Mr. Shedid \n male \n 22.5000 \n 0 \n 0 \n 2698 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n male \n 45.0000 \n 0 \n 0 \n 7598 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n female \n 22.0000 \n 0 \n 0 \n 7552 \n 10.5167 \n NA \n \n \n S \n England \n 3 \n 0 \n Dakic, Mr. Branko \n male \n 19.0000 \n 0 \n 0 \n 349228 \n 10.1708 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n female \n 30.0000 \n 0 \n 0 \n 382650 \n 6.9500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n male \n 29.0000 \n 0 \n 0 \n 382651 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n male \n 0.3333 \n 0 \n 2 \n 347080 \n 14.4000 \n NA \n \n \n S \n England \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n male \n 34.0000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n \n \n S \n England \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n female \n 28.0000 \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n \n \n S \n England \n 3 \n 0 \n Danoff, Mr. Yoto \n male \n 27.0000 \n 0 \n 0 \n 349219 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n male \n 25.0000 \n 0 \n 0 \n 349203 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. Alfred J \n male \n 24.0000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. Evan \n male \n 22.0000 \n 0 \n 0 \n SC/A4 23568 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. John Samuel \n male \n 21.0000 \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davies, Mr. Joseph \n male \n 17.0000 \n 2 \n 0 \n A/4 48873 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Davison, Mr. Thomas Henry \n male \n NA \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n female \n NA \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n male \n 36.5000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n \n \n S \n England \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n female \n 36.0000 \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n \n \n S \n England \n 3 \n 1 \n de Mulder, Mr. Theodore \n male \n 30.0000 \n 0 \n 0 \n 345774 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n male \n 16.0000 \n 0 \n 0 \n 345778 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 1 \n Dean, Master. Bertram Vere \n male \n 1.0000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n female \n 0.1667 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 0 \n Dean, Mr. Bertram Frank \n male \n 26.0000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n female \n 33.0000 \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n \n \n S \n England \n 3 \n 0 \n Delalic, Mr. Redjo \n male \n 25.0000 \n 0 \n 0 \n 349250 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Demetri, Mr. Marinko \n male \n NA \n 0 \n 0 \n 349238 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Denkoff, Mr. Mitto \n male \n NA \n 0 \n 0 \n 349225 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Dennis, Mr. Samuel \n male \n 22.0000 \n 0 \n 0 \n A/5 21172 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Dennis, Mr. William \n male \n 36.0000 \n 0 \n 0 \n A/5 21175 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n female \n 19.0000 \n 0 \n 0 \n 330958 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Dika, Mr. Mirko \n male \n 17.0000 \n 0 \n 0 \n 349232 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Dimic, Mr. Jovan \n male \n 42.0000 \n 0 \n 0 \n 315088 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n male \n 43.0000 \n 0 \n 0 \n 349226 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Doharr, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2686 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Dooley, Mr. Patrick \n male \n 32.0000 \n 0 \n 0 \n 370376 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n male \n 19.0000 \n 0 \n 0 \n A/5. 10482 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n female \n 30.0000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Doyle, Miss. Elizabeth \n female \n 24.0000 \n 0 \n 0 \n 368702 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Drapkin, Miss. Jennie \n female \n 23.0000 \n 0 \n 0 \n SOTON/OQ 392083 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Drazenoic, Mr. Jozef \n male \n 33.0000 \n 0 \n 0 \n 349241 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Duane, Mr. Frank \n male \n 65.0000 \n 0 \n 0 \n 336439 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Duquemin, Mr. Joseph \n male \n 24.0000 \n 0 \n 0 \n S.O./P.P. 752 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n male \n 23.0000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n \n \n S \n England \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n female \n 22.0000 \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n male \n 18.0000 \n 0 \n 0 \n 349912 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Eklund, Mr. Hans Linus \n male \n 16.0000 \n 0 \n 0 \n 347074 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ekstrom, Mr. Johan \n male \n 45.0000 \n 0 \n 0 \n 347061 \n 6.9750 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Dibo \n male \n NA \n 0 \n 0 \n 2674 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Joseph \n male \n 39.0000 \n 0 \n 2 \n 2675 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Joseph Jr \n male \n 17.0000 \n 1 \n 1 \n 2690 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Elias, Mr. Tannous \n male \n 15.0000 \n 1 \n 1 \n 2695 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Elsbury, Mr. William James \n male \n 47.0000 \n 0 \n 0 \n A/5 3902 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n female \n 5.0000 \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n \n \n C \n France \n 3 \n 0 \n Emir, Mr. Farred Chehab \n male \n NA \n 0 \n 0 \n 2631 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Everett, Mr. Thomas James \n male \n 40.5000 \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Farrell, Mr. James \n male \n 40.5000 \n 0 \n 0 \n 367232 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Finoli, Mr. Luigi \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101308 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n male \n 18.0000 \n 0 \n 0 \n 350036 \n 7.7958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Fleming, Miss. Honora \n female \n NA \n 0 \n 0 \n 364859 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Flynn, Mr. James \n male \n NA \n 0 \n 0 \n 364851 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Flynn, Mr. John \n male \n NA \n 0 \n 0 \n 368323 \n 6.9500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Foley, Mr. Joseph \n male \n 26.0000 \n 0 \n 0 \n 330910 \n 7.8792 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Foley, Mr. William \n male \n NA \n 0 \n 0 \n 365235 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Foo, Mr. Choong \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n female \n 21.0000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n female \n 9.0000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mr. Arthur \n male \n NA \n 0 \n 0 \n A/5 1478 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mr. Edward Watson \n male \n 18.0000 \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mr. William Neal \n male \n 16.0000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n \n \n S \n England \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n female \n 48.0000 \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Fox, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368573 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101314 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Gallagher, Mr. Martin \n male \n 25.0000 \n 0 \n 0 \n 36864 \n 7.7417 \n NA \n \n \n S \n England \n 3 \n 0 \n Garfirth, Mr. John \n male \n NA \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n male \n NA \n 0 \n 0 \n 349254 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Gilinski, Mr. Eliezer \n male \n 22.0000 \n 0 \n 0 \n 14973 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n female \n 16.0000 \n 0 \n 0 \n 35851 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n female \n NA \n 0 \n 0 \n 335677 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n male \n 9.0000 \n 0 \n 2 \n 363291 \n 20.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Goldsmith, Mr. Frank John \n male \n 33.0000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Goldsmith, Mr. Nathan \n male \n 41.0000 \n 0 \n 0 \n SOTON/O.Q. 3101263 \n 7.8500 \n NA \n \n \n S \n England \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n female \n 31.0000 \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n male \n 38.0000 \n 0 \n 0 \n SOTON/O.Q. 3101306 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Master. Harold Victor \n male \n 9.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n male \n 1.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Master. William Frederick \n male \n 11.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n female \n 10.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n female \n 16.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n male \n 14.0000 \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n male \n 40.0000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n female \n 43.0000 \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Green, Mr. George Henry \n male \n 51.0000 \n 0 \n 0 \n 21440 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n male \n 32.0000 \n 0 \n 0 \n 8471 \n 8.3625 \n NA \n \n \n S \n England \n 3 \n 0 \n Guest, Mr. Robert \n male \n NA \n 0 \n 0 \n 376563 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n male \n 20.0000 \n 0 \n 0 \n 7534 \n 9.8458 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n male \n 37.0000 \n 2 \n 0 \n 3101276 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n male \n 28.0000 \n 2 \n 0 \n 3101277 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n male \n 19.0000 \n 0 \n 0 \n 347069 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Haas, Miss. Aloisia \n female \n 24.0000 \n 0 \n 0 \n 349236 \n 8.8500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Hagardon, Miss. Kate \n female \n 17.0000 \n 0 \n 0 \n AQ/3. 30631 \n 7.7333 \n NA \n \n \n S \n England \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n male \n NA \n 1 \n 0 \n 65303 \n 19.9667 \n NA \n \n \n S \n England \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n male \n NA \n 1 \n 0 \n 65304 \n 19.9667 \n NA \n \n \n S \n England \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n male \n 28.0000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n \n \n S \n England \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n female \n 24.0000 \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n \n \n S \n England \n 3 \n 0 \n Hampe, Mr. Leon \n male \n 20.0000 \n 0 \n 0 \n 345769 \n 9.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Hanna, Mr. Mansour \n male \n 23.5000 \n 0 \n 0 \n 2693 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Hansen, Mr. Claus Peter \n male \n 41.0000 \n 2 \n 0 \n 350026 \n 14.1083 \n NA \n \n \n S \n England \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n male \n 26.0000 \n 1 \n 0 \n 350025 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n male \n 21.0000 \n 0 \n 0 \n 350029 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n female \n 45.0000 \n 1 \n 0 \n 350026 \n 14.1083 \n NA \n \n \n S \n England \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n female \n NA \n 0 \n 0 \n W./C. 6609 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n male \n 25.0000 \n 0 \n 0 \n 374887 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Hart, Mr. Henry \n male \n NA \n 0 \n 0 \n 394140 \n 6.8583 \n NA \n \n \n C \n France \n 3 \n 0 \n Hassan, Mr. Houssein G N \n male \n 11.0000 \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n female \n NA \n 0 \n 0 \n 370375 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n male \n 27.0000 \n 0 \n 0 \n 347089 \n 6.9750 \n NA \n \n \n S \n England \n 3 \n 1 \n Hee, Mr. Ling \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n female \n 18.0000 \n 0 \n 0 \n 365226 \n 6.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Heikkinen, Miss. Laina \n female \n 26.0000 \n 0 \n 0 \n STON/O2. 3101282 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n female \n 23.0000 \n 0 \n 0 \n STON/O2. 3101290 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n female \n 22.0000 \n 0 \n 0 \n 7548 \n 8.9625 \n NA \n \n \n S \n England \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n male \n 28.0000 \n 0 \n 0 \n 349243 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n female \n 28.0000 \n 0 \n 0 \n 347086 \n 7.7750 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Henry, Miss. Delia \n female \n NA \n 0 \n 0 \n 382649 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n female \n 2.0000 \n 0 \n 1 \n 3101298 \n 12.2875 \n NA \n \n \n S \n England \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n female \n 22.0000 \n 1 \n 1 \n 3101298 \n 12.2875 \n NA \n \n \n S \n England \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n male \n 43.0000 \n 0 \n 0 \n C 7075 \n 6.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Holthen, Mr. Johan Martin \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n \n \n S \n England \n 3 \n 1 \n Honkanen, Miss. Eliina \n female \n 27.0000 \n 0 \n 0 \n STON/O2. 3101283 \n 7.9250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Horgan, Mr. John \n male \n NA \n 0 \n 0 \n 370377 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Howard, Miss. May Elizabeth \n female \n NA \n 0 \n 0 \n A. 2. 39186 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n male \n 42.0000 \n 0 \n 0 \n 348121 \n 7.6500 \n F G63 \n \n \n S \n England \n 3 \n 1 \n Hyman, Mr. Abraham \n male \n NA \n 0 \n 0 \n 3470 \n 7.8875 \n NA \n \n \n C \n France \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n male \n 30.0000 \n 0 \n 0 \n 2685 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Ilieff, Mr. Ylio \n male \n NA \n 0 \n 0 \n 349220 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n female \n 27.0000 \n 1 \n 0 \n STON/O2. 3101270 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n female \n 25.0000 \n 1 \n 0 \n STON/O2. 3101271 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Ivanoff, Mr. Kanio \n male \n NA \n 0 \n 0 \n 349201 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Jalsevac, Mr. Ivan \n male \n 29.0000 \n 0 \n 0 \n 349240 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Jansson, Mr. Carl Olof \n male \n 21.0000 \n 0 \n 0 \n 350034 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Jardin, Mr. Jose Neto \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101305 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Jensen, Mr. Hans Peder \n male \n 20.0000 \n 0 \n 0 \n 350050 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jensen, Mr. Niels Peder \n male \n 48.0000 \n 0 \n 0 \n 350047 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n male \n 17.0000 \n 1 \n 0 \n 350048 \n 7.0542 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Jermyn, Miss. Annie \n female \n NA \n 0 \n 0 \n 14313 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n male \n NA \n 0 \n 0 \n 65306 \n 8.1125 \n NA \n \n \n S \n England \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n male \n 34.0000 \n 0 \n 0 \n 3101264 \n 6.4958 \n NA \n \n \n S \n England \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n male \n 26.0000 \n 0 \n 0 \n 347070 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Erik \n male \n 22.0000 \n 0 \n 0 \n 350052 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n male \n 33.0000 \n 0 \n 0 \n 7540 \n 8.6542 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Karl Johan \n male \n 31.0000 \n 0 \n 0 \n 347063 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Johansson, Mr. Nils \n male \n 29.0000 \n 0 \n 0 \n 347467 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Johnson, Master. Harold Theodor \n male \n 4.0000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n \n \n S \n England \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n female \n 1.0000 \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnson, Mr. Alfred \n male \n 49.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n male \n 33.0000 \n 0 \n 0 \n 347062 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n male \n 19.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n S \n England \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n female \n 27.0000 \n 0 \n 2 \n 347742 \n 11.1333 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n male \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n female \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Mr. Andrew G \n male \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n female \n NA \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n \n \n S \n England \n 3 \n 0 \n Jonkoff, Mr. Lalio \n male \n 23.0000 \n 0 \n 0 \n 349204 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Jonsson, Mr. Carl \n male \n 32.0000 \n 0 \n 0 \n 350417 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n male \n 27.0000 \n 0 \n 0 \n 350408 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Jussila, Miss. Katriina \n female \n 20.0000 \n 1 \n 0 \n 4136 \n 9.8250 \n NA \n \n \n S \n England \n 3 \n 0 \n Jussila, Miss. Mari Aina \n female \n 21.0000 \n 1 \n 0 \n 4137 \n 9.8250 \n NA \n \n \n S \n England \n 3 \n 1 \n Jussila, Mr. Eiriik \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101286 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n male \n 17.0000 \n 0 \n 0 \n STON/O 2. 3101274 \n 7.1250 \n NA \n \n \n S \n England \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n male \n 21.0000 \n 0 \n 0 \n 8475 \n 8.4333 \n NA \n \n \n S \n England \n 3 \n 0 \n Karaic, Mr. Milan \n male \n 30.0000 \n 0 \n 0 \n 349246 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n male \n 21.0000 \n 0 \n 0 \n 350053 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n male \n 33.0000 \n 0 \n 0 \n 347465 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Karlsson, Mr. Nils August \n male \n 22.0000 \n 0 \n 0 \n 350060 \n 7.5208 \n NA \n \n \n C \n France \n 3 \n 1 \n Karun, Miss. Manca \n female \n 4.0000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n \n \n C \n France \n 3 \n 1 \n Karun, Mr. Franz \n male \n 39.0000 \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n \n \n C \n France \n 3 \n 0 \n Kassem, Mr. Fared \n male \n NA \n 0 \n 0 \n 2700 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n male \n 18.5000 \n 0 \n 0 \n 2682 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n male \n NA \n 0 \n 0 \n 12460 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Keefe, Mr. Arthur \n male \n NA \n 0 \n 0 \n 323592 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n female \n NA \n 0 \n 0 \n 9234 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Kelly, Miss. Mary \n female \n NA \n 0 \n 0 \n 14312 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kelly, Mr. James \n male \n 34.5000 \n 0 \n 0 \n 330911 \n 7.8292 \n NA \n \n \n S \n England \n 3 \n 0 \n Kelly, Mr. James \n male \n 44.0000 \n 0 \n 0 \n 363592 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Kennedy, Mr. John \n male \n NA \n 0 \n 0 \n 368783 \n 7.7500 \n NA \n \n \n C \n France \n 3 \n 0 \n Khalil, Mr. Betros \n male \n NA \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n female \n NA \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kiernan, Mr. John \n male \n NA \n 1 \n 0 \n 367227 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kiernan, Mr. Philip \n male \n NA \n 1 \n 0 \n 367229 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n male \n NA \n 0 \n 0 \n 36865 \n 7.7375 \n NA \n \n \n S \n England \n 3 \n 0 \n Kink, Miss. Maria \n female \n 22.0000 \n 2 \n 0 \n 315152 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Kink, Mr. Vincenz \n male \n 26.0000 \n 2 \n 0 \n 315151 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n female \n 4.0000 \n 0 \n 2 \n 315153 \n 22.0250 \n NA \n \n \n S \n England \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n male \n 29.0000 \n 3 \n 1 \n 315153 \n 22.0250 \n NA \n \n \n S \n England \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n female \n 26.0000 \n 1 \n 1 \n 315153 \n 22.0250 \n NA \n \n \n S \n England \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n female \n 1.0000 \n 1 \n 1 \n 350405 \n 12.1833 \n NA \n \n \n S \n England \n 3 \n 0 \n Klasen, Mr. Klas Albin \n male \n 18.0000 \n 1 \n 1 \n 350404 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n female \n 36.0000 \n 0 \n 2 \n 350405 \n 12.1833 \n NA \n \n \n C \n France \n 3 \n 0 \n Kraeff, Mr. Theodor \n male \n NA \n 0 \n 0 \n 349253 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Krekorian, Mr. Neshan \n male \n 25.0000 \n 0 \n 0 \n 2654 \n 7.2292 \n F E57 \n \n \n C \n France \n 3 \n 0 \n Lahoud, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2624 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n female \n 37.0000 \n 0 \n 0 \n 4135 \n 9.5875 \n NA \n \n \n S \n England \n 3 \n 0 \n Laleff, Mr. Kristo \n male \n NA \n 0 \n 0 \n 349217 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Lam, Mr. Ali \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Lam, Mr. Len \n male \n NA \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n female \n 22.0000 \n 0 \n 0 \n C 7077 \n 7.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Lane, Mr. Patrick \n male \n NA \n 0 \n 0 \n 7935 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Lang, Mr. Fang \n male \n 26.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Larsson, Mr. August Viktor \n male \n 29.0000 \n 0 \n 0 \n 7545 \n 9.4833 \n NA \n \n \n S \n England \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n male \n 29.0000 \n 0 \n 0 \n 347067 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n male \n 22.0000 \n 0 \n 0 \n 347065 \n 7.7750 \n NA \n \n \n C \n France \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n male \n 22.0000 \n 0 \n 0 \n 2620 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n male \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Miss. Ida \n female \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Miss. Jeannie \n female \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Miss. Mathilde \n female \n NA \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n female \n NA \n 0 \n 4 \n 4133 \n 25.4667 \n NA \n \n \n S \n England \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101292 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n male \n 34.5000 \n 0 \n 0 \n 2683 \n 6.4375 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Lennon, Miss. Mary \n female \n NA \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Lennon, Mr. Denis \n male \n NA \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Leonard, Mr. Lionel \n male \n 36.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lester, Mr. James \n male \n 39.0000 \n 0 \n 0 \n A/4 48871 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lievens, Mr. Rene Aime \n male \n 24.0000 \n 0 \n 0 \n 345781 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n female \n 25.0000 \n 0 \n 0 \n 347071 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n female \n 45.0000 \n 0 \n 0 \n 347073 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n male \n 36.0000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n female \n 30.0000 \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n \n \n S \n England \n 3 \n 1 \n Lindqvist, Mr. Eino William \n male \n 20.0000 \n 1 \n 0 \n STON/O 2. 3101285 \n 7.9250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Linehan, Mr. Michael \n male \n NA \n 0 \n 0 \n 330971 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Ling, Mr. Lee \n male \n 28.0000 \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Lithman, Mr. Simon \n male \n NA \n 0 \n 0 \n S.O./P.P. 251 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Lobb, Mr. William Arthur \n male \n 30.0000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n female \n 26.0000 \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Lockyer, Mr. Edward \n male \n NA \n 0 \n 0 \n 1222 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n male \n 20.5000 \n 0 \n 0 \n A/5 21173 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Lulic, Mr. Nikola \n male \n 27.0000 \n 0 \n 0 \n 315098 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n male \n 51.0000 \n 0 \n 0 \n 347743 \n 7.0542 \n NA \n \n \n S \n England \n 3 \n 1 \n Lundin, Miss. Olga Elida \n female \n 23.0000 \n 0 \n 0 \n 347469 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n male \n 32.0000 \n 0 \n 0 \n 350403 \n 7.5792 \n NA \n \n \n S \n England \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n male \n NA \n 0 \n 0 \n 349235 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n MacKay, Mr. George William \n male \n NA \n 0 \n 0 \n C.A. 42795 \n 7.5500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n female \n NA \n 0 \n 0 \n 370370 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n male \n 24.0000 \n 0 \n 0 \n C 17369 \n 7.1417 \n NA \n \n \n S \n England \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n male \n 22.0000 \n 0 \n 0 \n STON/O 2. 3101275 \n 7.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n female \n NA \n 0 \n 0 \n 330924 \n 7.8792 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mahon, Mr. John \n male \n NA \n 0 \n 0 \n AQ/4 3130 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Maisner, Mr. Simon \n male \n NA \n 0 \n 0 \n A/S 2816 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n male \n 29.0000 \n 0 \n 0 \n STON/O 2. 3101268 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 1 \n Mamee, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2677 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mangan, Miss. Mary \n female \n 30.5000 \n 0 \n 0 \n 364850 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mannion, Miss. Margareth \n female \n NA \n 0 \n 0 \n 36866 \n 7.7375 \n NA \n \n \n C \n France \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2655 \n 7.2292 \n F E46 \n \n \n C \n France \n 3 \n 0 \n Markoff, Mr. Marin \n male \n 35.0000 \n 0 \n 0 \n 349213 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Markun, Mr. Johann \n male \n 33.0000 \n 0 \n 0 \n 349257 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Masselmani, Mrs. Fatima \n female \n NA \n 0 \n 0 \n 2649 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Matinoff, Mr. Nicola \n male \n NA \n 0 \n 0 \n 349255 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n female \n NA \n 0 \n 0 \n 383123 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n male \n NA \n 0 \n 0 \n 367228 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCoy, Miss. Agnes \n female \n NA \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCoy, Miss. Alicia \n female \n NA \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McCoy, Mr. Bernard \n male \n NA \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n female \n NA \n 0 \n 0 \n 330932 \n 7.7875 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McEvoy, Mr. Michael \n male \n NA \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McGovern, Miss. Mary \n female \n NA \n 0 \n 0 \n 330931 \n 7.8792 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n female \n 15.0000 \n 0 \n 0 \n 330923 \n 8.0292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McGowan, Miss. Katherine \n female \n 35.0000 \n 0 \n 0 \n 9232 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McMahon, Mr. Martin \n male \n NA \n 0 \n 0 \n 370372 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n McNamee, Mr. Neal \n male \n 24.0000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n female \n 19.0000 \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n McNeill, Miss. Bridget \n female \n NA \n 0 \n 0 \n 370368 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n female \n NA \n 0 \n 0 \n SOTON/O.Q. 392087 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n female \n NA \n 0 \n 0 \n 343095 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Meo, Mr. Alfonzo \n male \n 55.5000 \n 0 \n 0 \n A.5. 11206 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Mernagh, Mr. Robert \n male \n NA \n 0 \n 0 \n 368703 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n male \n 21.0000 \n 0 \n 0 \n 345501 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Miles, Mr. Frank \n male \n NA \n 0 \n 0 \n 359306 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Mineff, Mr. Ivan \n male \n 24.0000 \n 0 \n 0 \n 349233 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Minkoff, Mr. Lazar \n male \n 21.0000 \n 0 \n 0 \n 349211 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n male \n 28.0000 \n 0 \n 0 \n 349207 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Mitkoff, Mr. Mito \n male \n NA \n 0 \n 0 \n 349221 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n female \n NA \n 0 \n 0 \n 330980 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n male \n 25.0000 \n 0 \n 0 \n 348123 \n 7.6500 \n F G73 \n \n \n S \n England \n 3 \n 1 \n Moor, Master. Meier \n male \n 6.0000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n \n \n S \n England \n 3 \n 1 \n Moor, Mrs. (Beila) \n female \n 27.0000 \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n \n \n S \n England \n 3 \n 0 \n Moore, Mr. Leonard Charles \n male \n NA \n 0 \n 0 \n A4. 54510 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Moran, Miss. Bertha \n female \n NA \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Moran, Mr. Daniel J \n male \n NA \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Moran, Mr. James \n male \n NA \n 0 \n 0 \n 330877 \n 8.4583 \n NA \n \n \n S \n England \n 3 \n 0 \n Morley, Mr. William \n male \n 34.0000 \n 0 \n 0 \n 364506 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n male \n NA \n 0 \n 0 \n 372622 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Moss, Mr. Albert Johan \n male \n NA \n 0 \n 0 \n 312991 \n 7.7750 \n NA \n \n \n C \n France \n 3 \n 1 \n Moubarek, Master. Gerios \n male \n NA \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n male \n NA \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n female \n NA \n 0 \n 2 \n 2661 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n female \n NA \n 0 \n 0 \n 2626 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n male \n NA \n 0 \n 0 \n 374746 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n female \n NA \n 0 \n 0 \n 35852 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n female \n 24.0000 \n 0 \n 0 \n 382653 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Murdlin, Mr. Joseph \n male \n NA \n 0 \n 0 \n A./5. 3235 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n female \n NA \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n female \n NA \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Murphy, Miss. Nora \n female \n NA \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n male \n 18.0000 \n 0 \n 0 \n 347078 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Naidenoff, Mr. Penko \n male \n 22.0000 \n 0 \n 0 \n 349206 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n female \n 15.0000 \n 0 \n 0 \n 2667 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n female \n 1.0000 \n 0 \n 2 \n 2653 \n 15.7417 \n NA \n \n \n C \n France \n 3 \n 1 \n Nakid, Mr. Sahid \n male \n 20.0000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n \n \n C \n France \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n female \n 19.0000 \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n \n \n S \n England \n 3 \n 0 \n Nancarrow, Mr. William Henry \n male \n 33.0000 \n 0 \n 0 \n A./5. 3338 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Nankoff, Mr. Minko \n male \n NA \n 0 \n 0 \n 349218 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Nasr, Mr. Mustafa \n male \n NA \n 0 \n 0 \n 2652 \n 7.2292 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Naughton, Miss. Hannah \n female \n NA \n 0 \n 0 \n 365237 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Nenkoff, Mr. Christo \n male \n NA \n 0 \n 0 \n 349234 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n male \n 12.0000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n \n \n C \n France \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n female \n 14.0000 \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n \n \n S \n England \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n female \n 29.0000 \n 0 \n 0 \n 3101297 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Niklasson, Mr. Samuel \n male \n 28.0000 \n 0 \n 0 \n 363611 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n female \n 18.0000 \n 0 \n 0 \n 347066 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n female \n 26.0000 \n 0 \n 0 \n 347470 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n male \n 21.0000 \n 0 \n 0 \n 350410 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n male \n 41.0000 \n 0 \n 0 \n SOTON/O2 3101272 \n 7.1250 \n NA \n \n \n S \n England \n 3 \n 1 \n Niskanen, Mr. Juha \n male \n 39.0000 \n 0 \n 0 \n STON/O 2. 3101289 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n male \n 21.0000 \n 0 \n 0 \n A/4. 39886 \n 7.8000 \n NA \n \n \n C \n France \n 3 \n 0 \n Novel, Mr. Mansouer \n male \n 28.5000 \n 0 \n 0 \n 2697 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n female \n 22.0000 \n 0 \n 0 \n 347081 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n male \n 61.0000 \n 0 \n 0 \n 345364 \n 6.2375 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Brien, Mr. Thomas \n male \n NA \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Brien, Mr. Timothy \n male \n NA \n 0 \n 0 \n 330979 \n 7.8292 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n female \n NA \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Connell, Mr. Patrick D \n male \n NA \n 0 \n 0 \n 334912 \n 7.7333 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Connor, Mr. Maurice \n male \n NA \n 0 \n 0 \n 371060 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Connor, Mr. Patrick \n male \n NA \n 0 \n 0 \n 366713 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Odahl, Mr. Nils Martin \n male \n 23.0000 \n 0 \n 0 \n 7267 \n 9.2250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n female \n NA \n 0 \n 0 \n 364856 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n female \n NA \n 0 \n 0 \n 14311 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n female \n NA \n 0 \n 0 \n 330959 \n 7.8792 \n NA \n \n \n S \n England \n 3 \n 1 \n Ohman, Miss. Velin \n female \n 22.0000 \n 0 \n 0 \n 347085 \n 7.7750 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Keefe, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368402 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n female \n NA \n 0 \n 0 \n 330919 \n 7.8292 \n NA \n \n \n S \n England \n 3 \n 1 \n Olsen, Master. Artur Karl \n male \n 9.0000 \n 0 \n 1 \n C 17368 \n 3.1708 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsen, Mr. Henry Margido \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n male \n 42.0000 \n 0 \n 1 \n 4579 \n 8.4042 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsen, Mr. Ole Martin \n male \n NA \n 0 \n 0 \n Fa 265302 \n 7.3125 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsson, Miss. Elina \n female \n 31.0000 \n 0 \n 0 \n 350407 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n male \n 28.0000 \n 0 \n 0 \n 347464 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n male \n 32.0000 \n 0 \n 0 \n 347079 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n male \n 20.0000 \n 0 \n 0 \n 6563 \n 9.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Oreskovic, Miss. Jelka \n female \n 23.0000 \n 0 \n 0 \n 315085 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Oreskovic, Miss. Marija \n female \n 20.0000 \n 0 \n 0 \n 315096 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Oreskovic, Mr. Luka \n male \n 20.0000 \n 0 \n 0 \n 315094 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Osen, Mr. Olaf Elon \n male \n 16.0000 \n 0 \n 0 \n 7534 \n 9.2167 \n NA \n \n \n S \n England \n 3 \n 1 \n Osman, Mrs. Mara \n female \n 31.0000 \n 0 \n 0 \n 349244 \n 8.6833 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n female \n NA \n 0 \n 0 \n 330909 \n 7.6292 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n male \n 2.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Master. Paul Folke \n male \n 6.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Miss. Stina Viola \n female \n 3.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n female \n 8.0000 \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n female \n 29.0000 \n 0 \n 4 \n 349909 \n 21.0750 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Master. Eino Viljami \n male \n 1.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Master. Juha Niilo \n male \n 7.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Master. Urho Abraham \n male \n 2.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n male \n 16.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n male \n 14.0000 \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n female \n 41.0000 \n 0 \n 5 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Pasic, Mr. Jakob \n male \n 21.0000 \n 0 \n 0 \n 315097 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Patchett, Mr. George \n male \n 19.0000 \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Paulner, Mr. Uscher \n male \n NA \n 0 \n 0 \n 3411 \n 8.7125 \n NA \n \n \n S \n England \n 3 \n 0 \n Pavlovic, Mr. Stefo \n male \n 32.0000 \n 0 \n 0 \n 349242 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Peacock, Master. Alfred Edward \n male \n 0.7500 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Peacock, Miss. Treasteall \n female \n 3.0000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n female \n 26.0000 \n 0 \n 2 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Pearce, Mr. Ernest \n male \n NA \n 0 \n 0 \n 343271 \n 7.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Pedersen, Mr. Olaf \n male \n NA \n 0 \n 0 \n 345498 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Peduzzi, Mr. Joseph \n male \n NA \n 0 \n 0 \n A/5 2817 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101294 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n male \n 25.0000 \n 0 \n 0 \n STON/O 2. 3101291 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Perkin, Mr. John Henry \n male \n 22.0000 \n 0 \n 0 \n A/5 21174 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n male \n 25.0000 \n 1 \n 0 \n 347083 \n 7.7750 \n NA \n \n \n C \n France \n 3 \n 1 \n Peter, Master. Michael J \n male \n NA \n 1 \n 1 \n 2668 \n 22.3583 \n NA \n \n \n C \n France \n 3 \n 1 \n Peter, Miss. Anna \n female \n NA \n 1 \n 1 \n 2668 \n 22.3583 \n F E69 \n \n \n C \n France \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n female \n NA \n 0 \n 2 \n 2668 \n 22.3583 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Peters, Miss. Katie \n female \n NA \n 0 \n 0 \n 330935 \n 8.1375 \n NA \n \n \n S \n England \n 3 \n 0 \n Petersen, Mr. Marius \n male \n 24.0000 \n 0 \n 0 \n 342441 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Petranec, Miss. Matilda \n female \n 28.0000 \n 0 \n 0 \n 349245 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Petroff, Mr. Nedelio \n male \n 19.0000 \n 0 \n 0 \n 349212 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n male \n NA \n 0 \n 0 \n 349215 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Petterson, Mr. Johan Emil \n male \n 25.0000 \n 1 \n 0 \n 347076 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n female \n 18.0000 \n 0 \n 0 \n 347087 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n male \n 32.0000 \n 0 \n 0 \n SOTON/O.Q. 392078 \n 8.0500 \n E10 \n \n \n S \n England \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n male \n NA \n 0 \n 0 \n 349227 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Pokrnic, Mr. Mate \n male \n 17.0000 \n 0 \n 0 \n 315095 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Pokrnic, Mr. Tome \n male \n 24.0000 \n 0 \n 0 \n 315092 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Radeff, Mr. Alexander \n male \n NA \n 0 \n 0 \n 349223 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n female \n NA \n 0 \n 0 \n 65305 \n 8.1125 \n NA \n \n \n C \n France \n 3 \n 0 \n Razi, Mr. Raihed \n male \n NA \n 0 \n 0 \n 2629 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Reed, Mr. James George \n male \n NA \n 0 \n 0 \n 362316 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rekic, Mr. Tido \n male \n 38.0000 \n 0 \n 0 \n 349249 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Reynolds, Mr. Harold J \n male \n 21.0000 \n 0 \n 0 \n 342684 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Albert \n male \n 10.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Arthur \n male \n 4.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Eric \n male \n 7.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. Eugene \n male \n 2.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Master. George Hugh \n male \n 8.0000 \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n female \n 39.0000 \n 0 \n 5 \n 382652 \n 29.1250 \n NA \n \n \n S \n England \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n female \n 22.0000 \n 0 \n 0 \n 3101295 \n 39.6875 \n NA \n \n \n S \n England \n 3 \n 0 \n Rintamaki, Mr. Matti \n male \n 35.0000 \n 0 \n 0 \n STON/O 2. 3101273 \n 7.1250 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n female \n NA \n 0 \n 0 \n 334915 \n 7.7208 \n NA \n \n \n S \n England \n 3 \n 0 \n Risien, Mr. Samuel Beard \n male \n NA \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n female \n NA \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Robins, Mr. Alexander A \n male \n 50.0000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n female \n 47.0000 \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Rogers, Mr. William John \n male \n NA \n 0 \n 0 \n S.C./A.4. 23567 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n male \n NA \n 0 \n 0 \n 312993 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n female \n 2.0000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n \n \n S \n England \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n male \n 18.0000 \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n \n \n S \n England \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n female \n 41.0000 \n 0 \n 2 \n 370129 \n 20.2125 \n NA \n \n \n S \n England \n 3 \n 1 \n Roth, Miss. Sarah A \n female \n NA \n 0 \n 0 \n 342712 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rouse, Mr. Richard Henry \n male \n 50.0000 \n 0 \n 0 \n A/5 3594 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Rush, Mr. Alfred George John \n male \n 16.0000 \n 0 \n 0 \n A/4. 20589 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Ryan, Mr. Edward \n male \n NA \n 0 \n 0 \n 383162 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Ryan, Mr. Patrick \n male \n NA \n 0 \n 0 \n 371110 \n 24.1500 \n NA \n \n \n C \n France \n 3 \n 0 \n Saad, Mr. Amin \n male \n NA \n 0 \n 0 \n 2671 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 0 \n Saad, Mr. Khalil \n male \n 25.0000 \n 0 \n 0 \n 2672 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Saade, Mr. Jean Nassr \n male \n NA \n 0 \n 0 \n 2676 \n 7.2250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Sadlier, Mr. Matthew \n male \n NA \n 0 \n 0 \n 367655 \n 7.7292 \n NA \n \n \n S \n England \n 3 \n 0 \n Sadowitz, Mr. Harry \n male \n NA \n 0 \n 0 \n LP 1588 \n 7.5750 \n NA \n \n \n S \n England \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n male \n 38.5000 \n 0 \n 0 \n SOTON/O.Q. 3101262 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Master. Thomas Henry \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Master. William Henry \n male \n 14.5000 \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Ada \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Constance Gladys \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Miss. Stella Anna \n female \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. Frederick \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. George John Jr \n male \n NA \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mr. John George \n male \n NA \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n female \n NA \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Salander, Mr. Karl Johan \n male \n 24.0000 \n 0 \n 0 \n 7266 \n 9.3250 \n NA \n \n \n S \n England \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n female \n 21.0000 \n 0 \n 0 \n 343120 \n 7.6500 \n NA \n \n \n S \n England \n 3 \n 0 \n Salonen, Mr. Johan Werner \n male \n 39.0000 \n 0 \n 0 \n 3101296 \n 7.9250 \n NA \n \n \n C \n France \n 3 \n 0 \n Samaan, Mr. Elias \n male \n NA \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n \n \n C \n France \n 3 \n 0 \n Samaan, Mr. Hanna \n male \n NA \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n \n \n C \n France \n 3 \n 0 \n Samaan, Mr. Youssef \n male \n NA \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n \n \n S \n England \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n female \n 1.0000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n female \n 24.0000 \n 0 \n 2 \n PP 9549 \n 16.7000 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n female \n 4.0000 \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sap, Mr. Julius \n male \n 25.0000 \n 0 \n 0 \n 345768 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Saundercock, Mr. William Henry \n male \n 20.0000 \n 0 \n 0 \n A/5. 2151 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n male \n 24.5000 \n 0 \n 0 \n 342826 \n 8.0500 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Scanlan, Mr. James \n male \n NA \n 0 \n 0 \n 36209 \n 7.7250 \n NA \n \n \n S \n England \n 3 \n 0 \n Sdycoff, Mr. Todor \n male \n NA \n 0 \n 0 \n 349222 \n 7.8958 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n male \n NA \n 0 \n 0 \n 370374 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n male \n 29.0000 \n 0 \n 0 \n 345779 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Shellard, Mr. Frederick William \n male \n NA \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n female \n NA \n 0 \n 0 \n 330968 \n 7.7792 \n NA \n \n \n S \n England \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n male \n NA \n 0 \n 0 \n 374910 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Simmons, Mr. John \n male \n NA \n 0 \n 0 \n SOTON/OQ 392082 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Sirayanian, Mr. Orsen \n male \n 22.0000 \n 0 \n 0 \n 2669 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Sirota, Mr. Maurice \n male \n NA \n 0 \n 0 \n 392092 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Sivic, Mr. Husein \n male \n 40.0000 \n 0 \n 0 \n 349251 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101280 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 3101265 \n 7.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Master. Harald \n male \n 4.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n male \n 10.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Miss. Mabel \n female \n 9.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n female \n 2.0000 \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Mr. Wilhelm \n male \n 40.0000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n female \n 45.0000 \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n \n \n S \n England \n 3 \n 0 \n Slabenoff, Mr. Petco \n male \n NA \n 0 \n 0 \n 349214 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n male \n NA \n 0 \n 0 \n SOTON/OQ 392086 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Smiljanic, Mr. Mile \n male \n NA \n 0 \n 0 \n 315037 \n 8.6625 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Smith, Mr. Thomas \n male \n NA \n 0 \n 0 \n 384461 \n 7.7500 \n NA \n \n \n Q \n Ireland \n 3 \n 1 \n Smyth, Miss. Julia \n female \n NA \n 0 \n 0 \n 335432 \n 7.7333 \n NA \n \n \n S \n England \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n male \n 19.0000 \n 0 \n 0 \n 348124 \n 7.6500 \n F G73 \n \n \n S \n England \n 3 \n 0 \n Somerton, Mr. Francis William \n male \n 30.0000 \n 0 \n 0 \n A.5. 18509 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Spector, Mr. Woolf \n male \n NA \n 0 \n 0 \n A.5. 3236 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Spinner, Mr. Henry John \n male \n 32.0000 \n 0 \n 0 \n STON/OQ. 369943 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Staneff, Mr. Ivan \n male \n NA \n 0 \n 0 \n 349208 \n 7.8958 \n NA \n \n \n C \n France \n 3 \n 0 \n Stankovic, Mr. Ivan \n male \n 33.0000 \n 0 \n 0 \n 349239 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n female \n 23.0000 \n 0 \n 0 \n CA. 2314 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Stanley, Mr. Edward Roland \n male \n 21.0000 \n 0 \n 0 \n A/4 45380 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Storey, Mr. Thomas \n male \n 60.5000 \n 0 \n 0 \n 3701 \n NA \n NA \n \n \n S \n England \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n male \n 19.0000 \n 0 \n 0 \n 349205 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n female \n 22.0000 \n 0 \n 0 \n 7553 \n 9.8375 \n NA \n \n \n S \n England \n 3 \n 1 \n Stranden, Mr. Juho \n male \n 31.0000 \n 0 \n 0 \n STON/O 2. 3101288 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Strilic, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 315083 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Strom, Miss. Telma Matilda \n female \n 2.0000 \n 0 \n 1 \n 347054 \n 10.4625 \n G6 \n \n \n S \n England \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n female \n 29.0000 \n 1 \n 1 \n 347054 \n 10.4625 \n G6 \n \n \n S \n England \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n male \n 16.0000 \n 0 \n 0 \n SOTON/OQ 392089 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 1 \n Sundman, Mr. Johan Julian \n male \n 44.0000 \n 0 \n 0 \n STON/O 2. 3101269 \n 7.9250 \n NA \n \n \n S \n England \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n male \n 25.0000 \n 0 \n 0 \n SOTON/OQ 392076 \n 7.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Svensson, Mr. Johan \n male \n 74.0000 \n 0 \n 0 \n 347060 \n 7.7750 \n NA \n \n \n S \n England \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n male \n 14.0000 \n 0 \n 0 \n 7538 \n 9.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Svensson, Mr. Olof \n male \n 24.0000 \n 0 \n 0 \n 350035 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n male \n 25.0000 \n 0 \n 0 \n 350033 \n 7.7958 \n NA \n \n \n S \n England \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n male \n 34.0000 \n 0 \n 0 \n 363294 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 1 \n Thomas, Master. Assad Alexander \n male \n 0.4167 \n 0 \n 1 \n 2625 \n 8.5167 \n NA \n \n \n C \n France \n 3 \n 0 \n Thomas, Mr. Charles P \n male \n NA \n 1 \n 0 \n 2621 \n 6.4375 \n NA \n \n \n C \n France \n 3 \n 0 \n Thomas, Mr. John \n male \n NA \n 0 \n 0 \n 2681 \n 6.4375 \n NA \n \n \n C \n France \n 3 \n 0 \n Thomas, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2684 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n female \n 16.0000 \n 1 \n 1 \n 2625 \n 8.5167 \n NA \n \n \n S \n England \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n male \n NA \n 0 \n 0 \n 32302 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Thorneycroft, Mr. Percival \n male \n NA \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n female \n NA \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Tikkanen, Mr. Juho \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101293 \n 7.9250 \n NA \n \n \n Q \n Ireland \n 3 \n 0 \n Tobin, Mr. Roger \n male \n NA \n 0 \n 0 \n 383121 \n 7.7500 \n F38 \n \n \n S \n England \n 3 \n 0 \n Todoroff, Mr. Lalio \n male \n NA \n 0 \n 0 \n 349216 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n male \n 30.5000 \n 0 \n 0 \n 364499 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Torber, Mr. Ernst William \n male \n 44.0000 \n 0 \n 0 \n 364511 \n 8.0500 \n NA \n \n \n C \n France \n 3 \n 0 \n Torfa, Mr. Assad \n male \n NA \n 0 \n 0 \n 2673 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 1 \n Tornquist, Mr. William Henry \n male \n 25.0000 \n 0 \n 0 \n LINE \n 0.0000 \n NA \n \n \n C \n France \n 3 \n 0 \n Toufik, Mr. Nakli \n male \n NA \n 0 \n 0 \n 2641 \n 7.2292 \n NA \n \n \n C \n France \n 3 \n 1 \n Touma, Master. Georges Youssef \n male \n 7.0000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Touma, Miss. Maria Youssef \n female \n 9.0000 \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n \n \n C \n France \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n female \n 29.0000 \n 0 \n 2 \n 2650 \n 15.2458 \n NA \n \n \n S \n England \n 3 \n 0 \n Turcin, Mr. Stjepan \n male \n 36.0000 \n 0 \n 0 \n 349247 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 1 \n Turja, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 4138 \n 9.8417 \n NA \n \n \n S \n England \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n female \n 63.0000 \n 0 \n 0 \n 4134 \n 9.5875 \n NA \n \n \n S \n England \n 3 \n 0 \n van Billiard, Master. James William \n male \n NA \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n van Billiard, Master. Walter John \n male \n 11.5000 \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n male \n 40.5000 \n 0 \n 2 \n A/5. 851 \n 14.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Van Impe, Miss. Catharina \n female \n 10.0000 \n 0 \n 2 \n 345773 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n male \n 36.0000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n female \n 30.0000 \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n \n \n S \n England \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n male \n NA \n 0 \n 0 \n 345777 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n male \n 33.0000 \n 0 \n 0 \n 345780 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n male \n 28.0000 \n 0 \n 0 \n 345770 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n male \n 28.0000 \n 0 \n 0 \n 345783 \n 9.5000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n male \n 47.0000 \n 0 \n 0 \n 345765 \n 9.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n female \n 18.0000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Mr. Julius \n male \n 31.0000 \n 3 \n 0 \n 345763 \n 18.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n male \n 16.0000 \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n female \n 31.0000 \n 1 \n 0 \n 345763 \n 18.0000 \n NA \n \n \n C \n France \n 3 \n 1 \n Vartanian, Mr. David \n male \n 22.0000 \n 0 \n 0 \n 2658 \n 7.2250 \n NA \n \n \n S \n England \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n male \n 20.0000 \n 0 \n 0 \n 350416 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n female \n 14.0000 \n 0 \n 0 \n 350406 \n 7.8542 \n NA \n \n \n S \n England \n 3 \n 0 \n Vovk, Mr. Janko \n male \n 22.0000 \n 0 \n 0 \n 349252 \n 7.8958 \n NA \n \n \n S \n England \n 3 \n 0 \n Waelens, Mr. Achille \n male \n 22.0000 \n 0 \n 0 \n 345767 \n 9.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Ware, Mr. Frederick \n male \n NA \n 0 \n 0 \n 359309 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Warren, Mr. Charles William \n male \n NA \n 0 \n 0 \n C.A. 49867 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Webber, Mr. James \n male \n NA \n 0 \n 0 \n SOTON/OQ 3101316 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wenzel, Mr. Linhart \n male \n 32.5000 \n 0 \n 0 \n 345775 \n 9.5000 \n NA \n \n \n C \n France \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n female \n 38.0000 \n 0 \n 0 \n 2688 \n 7.2292 \n NA \n \n \n S \n England \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n male \n 51.0000 \n 0 \n 0 \n 347064 \n 7.7500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n male \n 18.0000 \n 1 \n 0 \n 3101267 \n 6.4958 \n NA \n \n \n S \n England \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n male \n 21.0000 \n 1 \n 0 \n 3101266 \n 6.4958 \n NA \n \n \n S \n England \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n female \n 47.0000 \n 1 \n 0 \n 363272 \n 7.0000 \n NA \n \n \n S \n England \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n male \n NA \n 0 \n 0 \n 3410 \n 8.7125 \n NA \n \n \n S \n England \n 3 \n 0 \n Willey, Mr. Edward \n male \n NA \n 0 \n 0 \n S.O./P.P. 751 \n 7.5500 \n NA \n \n \n S \n England \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n male \n NA \n 0 \n 0 \n A/5 2466 \n 8.0500 \n NA \n \n \n S \n England \n 3 \n 0 \n Williams, Mr. Leslie \n male \n 28.5000 \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n \n \n S \n England \n 3 \n 0 \n Windelov, Mr. Einar \n male \n 21.0000 \n 0 \n 0 \n SOTON/OQ 3101317 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wirz, Mr. Albert \n male \n 27.0000 \n 0 \n 0 \n 315154 \n 8.6625 \n NA \n \n \n S \n England \n 3 \n 0 \n Wiseman, Mr. Phillippe \n male \n NA \n 0 \n 0 \n A/4. 34244 \n 7.2500 \n NA \n \n \n S \n England \n 3 \n 0 \n Wittevrongel, Mr. Camille \n male \n 36.0000 \n 0 \n 0 \n 345771 \n 9.5000 \n NA \n \n \n C \n France \n 3 \n 0 \n Yasbeck, Mr. Antoni \n male \n 27.0000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n female \n 15.0000 \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Youseff, Mr. Gerious \n male \n 45.5000 \n 0 \n 0 \n 2628 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Yousif, Mr. Wazli \n male \n NA \n 0 \n 0 \n 2647 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Yousseff, Mr. Gerious \n male \n NA \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n \n \n C \n France \n 3 \n 0 \n Zabour, Miss. Hileni \n female \n 14.5000 \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Zabour, Miss. Thamine \n female \n NA \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n \n \n C \n France \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n male \n 26.5000 \n 0 \n 0 \n 2656 \n 7.2250 \n NA \n \n \n C \n France \n 3 \n 0 \n Zakarian, Mr. Ortin \n male \n 27.0000 \n 0 \n 0 \n 2670 \n 7.2250 \n NA \n \n \n\n S \n England \n 3 \n 0 \n Zimmerman, Mr. Leo \n male \n 29.0000 \n 0 \n 0 \n 315082 \n 7.8750 \n NA \n \n \n
\n \n \n\n fare_level \n fare \n pclass \n survived \n name_of_passenger \n sex_of_passenger \n age_of_passenger \n sibsp \n parch \n ticket \n cabin \n embarked \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n female \n 29.0000 \n 0 \n 0 \n 24160 \n B5 \n S \n \n \n middling \n 151.5500 \n 1 \n 1 \n Allison, Master. Hudson Trevor \n male \n 0.9167 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n middling \n 151.5500 \n 1 \n 0 \n Allison, Miss. Helen Loraine \n female \n 2.0000 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n middling \n 151.5500 \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n male \n 30.0000 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n middling \n 151.5500 \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n female \n 25.0000 \n 1 \n 2 \n 113781 \n C22 C26 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Anderson, Mr. Harry \n male \n 48.0000 \n 0 \n 0 \n 19952 \n E12 \n S \n \n \n cheap \n 77.9583 \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n female \n 63.0000 \n 1 \n 0 \n 13502 \n D7 \n S \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n male \n NA \n 0 \n 0 \n 112050 \n A36 \n S \n \n \n cheap \n 51.4792 \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n female \n NA \n 2 \n 0 \n 11769 \n C101 \n S \n \n \n cheap \n 49.5042 \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n male \n NA \n 0 \n 0 \n PC 17609 \n NA \n C \n \n \n expensive \n 227.5250 \n 1 \n 0 \n Astor, Col. John Jacob \n male \n NA \n 1 \n 0 \n PC 17757 \n C62 C64 \n C \n \n \n expensive \n 227.5250 \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n female \n 18.0000 \n 1 \n 0 \n PC 17757 \n C62 C64 \n C \n \n \n cheap \n 69.3000 \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n B35 \n C \n \n \n cheap \n 78.8500 \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n female \n 26.0000 \n 0 \n 0 \n 19877 \n NA \n S \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n male \n 80.0000 \n 0 \n 0 \n 27042 \n A23 \n S \n \n \n cheap \n 25.9250 \n 1 \n 0 \n Baumann, Mr. John D \n male \n NA \n 0 \n 0 \n PC 17318 \n NA \n S \n \n \n expensive \n 247.5208 \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n male \n 24.0000 \n 0 \n 1 \n PC 17558 \n B58 B60 \n C \n \n \n expensive \n 247.5208 \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n female \n 50.0000 \n 0 \n 1 \n PC 17558 \n B58 B60 \n C \n \n \n cheap \n 76.2917 \n 1 \n 1 \n Bazzani, Miss. Albina \n female \n 32.0000 \n 0 \n 0 \n 11813 \n D15 \n C \n \n \n cheap \n 75.2417 \n 1 \n 0 \n Beattie, Mr. Thomson \n male \n 36.0000 \n 0 \n 0 \n 13050 \n C6 \n C \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n male \n 37.0000 \n 1 \n 1 \n 11751 \n D35 \n S \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n female \n 47.0000 \n 1 \n 1 \n 11751 \n D35 \n S \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Behr, Mr. Karl Howell \n male \n 26.0000 \n 0 \n 0 \n 111369 \n C148 \n C \n \n \n expensive \n 227.5250 \n 1 \n 1 \n Bidois, Miss. Rosalie \n female \n 42.0000 \n 0 \n 0 \n PC 17757 \n NA \n C \n \n \n expensive \n 221.7792 \n 1 \n 1 \n Bird, Miss. Ellen \n female \n 29.0000 \n 0 \n 0 \n PC 17483 \n C97 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Birnbaum, Mr. Jakob \n male \n 25.0000 \n 0 \n 0 \n 13905 \n NA \n C \n \n \n cheap \n 91.0792 \n 1 \n 1 \n Bishop, Mr. Dickinson H \n male \n 25.0000 \n 1 \n 0 \n 11967 \n B49 \n C \n \n \n cheap \n 91.0792 \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n female \n 19.0000 \n 1 \n 0 \n 11967 \n B49 \n C \n \n \n middling \n 135.6333 \n 1 \n 1 \n Bissette, Miss. Amelia \n female \n 35.0000 \n 0 \n 0 \n PC 17760 \n C99 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n male \n 28.0000 \n 0 \n 0 \n 110564 \n C52 \n S \n \n \n cheap \n 35.5000 \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n male \n 45.0000 \n 0 \n 0 \n 113784 \n T \n S \n \n \n cheap \n 31.0000 \n 1 \n 1 \n Blank, Mr. Henry \n male \n 40.0000 \n 0 \n 0 \n 112277 \n A31 \n C \n \n \n middling \n 164.8667 \n 1 \n 1 \n Bonnell, Miss. Caroline \n female \n 30.0000 \n 0 \n 0 \n 36928 \n C7 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n female \n 58.0000 \n 0 \n 0 \n 113783 \n C103 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Borebank, Mr. John James \n male \n 42.0000 \n 0 \n 0 \n 110489 \n D22 \n S \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Bowen, Miss. Grace Scott \n female \n 45.0000 \n 0 \n 0 \n PC 17608 \n NA \n C \n \n \n cheap \n 55.0000 \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n female \n 22.0000 \n 0 \n 1 \n 113505 \n E33 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n male \n NA \n 0 \n 0 \n 111427 \n NA \n S \n \n \n cheap \n 30.5000 \n 1 \n 0 \n Brady, Mr. John Bertram \n male \n 41.0000 \n 0 \n 0 \n 113054 \n A21 \n S \n \n \n cheap \n 50.4958 \n 1 \n 0 \n Brandeis, Mr. Emil \n male \n 48.0000 \n 0 \n 0 \n PC 17591 \n B10 \n C \n \n \n cheap \n 39.6000 \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n male \n NA \n 0 \n 0 \n 112379 \n NA \n C \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n female \n 44.0000 \n 0 \n 0 \n PC 17610 \n B4 \n C \n \n \n cheap \n 51.4792 \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n female \n 59.0000 \n 2 \n 0 \n 11769 \n C101 \n S \n \n \n cheap \n 76.2917 \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n female \n 60.0000 \n 0 \n 0 \n 11813 \n D15 \n C \n \n \n middling \n 134.5000 \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n female \n 41.0000 \n 0 \n 0 \n 16966 \n E40 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Butt, Major. Archibald Willingham \n male \n 45.0000 \n 0 \n 0 \n 113050 \n B38 \n S \n \n \n cheap \n 31.0000 \n 1 \n 0 \n Cairns, Mr. Alexander \n male \n NA \n 0 \n 0 \n 113798 \n NA \n S \n \n \n cheap \n 26.2875 \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n male \n 42.0000 \n 0 \n 0 \n PC 17476 \n E24 \n S \n \n \n cheap \n 27.4458 \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n female \n 53.0000 \n 0 \n 0 \n PC 17606 \n NA \n C \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n male \n 36.0000 \n 0 \n 1 \n PC 17755 \n B51 B53 B55 \n C \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n female \n 58.0000 \n 0 \n 1 \n PC 17755 \n B51 B53 B55 \n C \n \n \n cheap \n 5.0000 \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n male \n 33.0000 \n 0 \n 0 \n 695 \n B51 B53 B55 \n S \n \n \n cheap \n 47.1000 \n 1 \n 0 \n Carrau, Mr. Francisco M \n male \n 28.0000 \n 0 \n 0 \n 113059 \n NA \n S \n \n \n cheap \n 47.1000 \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n male \n 17.0000 \n 0 \n 0 \n 113059 \n NA \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Master. William Thornton II \n male \n 11.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Miss. Lucile Polk \n female \n 14.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Mr. William Ernest \n male \n 36.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n middling \n 120.0000 \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n female \n 36.0000 \n 1 \n 2 \n 113760 \n B96 B98 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Case, Mr. Howard Brown \n male \n 49.0000 \n 0 \n 0 \n 19924 \n NA \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n female \n NA \n 0 \n 0 \n 17770 \n NA \n C \n \n \n cheap \n 78.8500 \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n male \n 36.0000 \n 1 \n 0 \n 19877 \n C46 \n S \n \n \n cheap \n 78.8500 \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n female \n 76.0000 \n 1 \n 0 \n 19877 \n C46 \n S \n \n \n cheap \n 61.1750 \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n male \n 46.0000 \n 1 \n 0 \n W.E.P. 5734 \n E31 \n S \n \n \n cheap \n 61.1750 \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n female \n 47.0000 \n 1 \n 0 \n W.E.P. 5734 \n E31 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n male \n 27.0000 \n 1 \n 0 \n 113806 \n E8 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n female \n 33.0000 \n 1 \n 0 \n 113806 \n E8 \n S \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Chaudanson, Miss. Victorine \n female \n 36.0000 \n 0 \n 0 \n PC 17608 \n B61 \n C \n \n \n cheap \n 86.5000 \n 1 \n 1 \n Cherry, Miss. Gladys \n female \n 30.0000 \n 0 \n 0 \n 110152 \n B77 \n S \n \n \n cheap \n 29.7000 \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n male \n 45.0000 \n 0 \n 0 \n PC 17594 \n A9 \n C \n \n \n cheap \n 55.0000 \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n female \n NA \n 0 \n 1 \n 113505 \n E33 \n S \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n male \n NA \n 0 \n 0 \n 112051 \n NA \n S \n \n \n middling \n 136.7792 \n 1 \n 0 \n Clark, Mr. Walter Miller \n male \n 27.0000 \n 1 \n 0 \n 13508 \n C89 \n C \n \n \n middling \n 136.7792 \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n female \n 26.0000 \n 1 \n 0 \n 13508 \n C89 \n C \n \n \n middling \n 151.5500 \n 1 \n 1 \n Cleaver, Miss. Alice \n female \n 22.0000 \n 0 \n 0 \n 113781 \n NA \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Clifford, Mr. George Quincy \n male \n NA \n 0 \n 0 \n 110465 \n A14 \n S \n \n \n cheap \n 25.5875 \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n male \n 47.0000 \n 0 \n 0 \n 5727 \n E58 \n S \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n female \n 39.0000 \n 1 \n 1 \n PC 17756 \n E49 \n C \n \n \n cheap \n 83.1583 \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n male \n 37.0000 \n 1 \n 1 \n PC 17756 \n E52 \n C \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n female \n 64.0000 \n 0 \n 2 \n PC 17756 \n E45 \n C \n \n \n cheap \n 25.7000 \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n female \n 55.0000 \n 2 \n 0 \n 11770 \n C101 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Crafton, Mr. John Bertram \n male \n NA \n 0 \n 0 \n 113791 \n NA \n S \n \n \n cheap \n 71.0000 \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n male \n 70.0000 \n 1 \n 1 \n WE/P 5735 \n B22 \n S \n \n \n cheap \n 71.0000 \n 1 \n 1 \n Crosby, Miss. Harriet R \n female \n 36.0000 \n 0 \n 2 \n WE/P 5735 \n B22 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n female \n 64.0000 \n 1 \n 1 \n 112901 \n B26 \n S \n \n \n cheap \n 71.2833 \n 1 \n 0 \n Cumings, Mr. John Bradley \n male \n 39.0000 \n 1 \n 0 \n PC 17599 \n C85 \n C \n \n \n cheap \n 71.2833 \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n female \n 38.0000 \n 1 \n 0 \n PC 17599 \n C85 \n C \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Daly, Mr. Peter Denis \n male \n 51.0000 \n 0 \n 0 \n 113055 \n E17 \n S \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Daniel, Mr. Robert Williams \n male \n 27.0000 \n 0 \n 0 \n 113804 \n NA \n S \n \n \n middling \n 151.5500 \n 1 \n 1 \n Daniels, Miss. Sarah \n female \n 33.0000 \n 0 \n 0 \n 113781 \n NA \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Davidson, Mr. Thornton \n male \n 31.0000 \n 1 \n 0 \n F.C. 12750 \n B71 \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n female \n 27.0000 \n 1 \n 2 \n F.C. 12750 \n B71 \n S \n \n \n cheap \n 57.0000 \n 1 \n 1 \n Dick, Mr. Albert Adrian \n male \n 31.0000 \n 1 \n 0 \n 17474 \n B20 \n S \n \n \n cheap \n 57.0000 \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n female \n 17.0000 \n 1 \n 0 \n 17474 \n B20 \n S \n \n \n cheap \n 81.8583 \n 1 \n 1 \n Dodge, Dr. Washington \n male \n 53.0000 \n 1 \n 1 \n 33638 \n A34 \n S \n \n \n cheap \n 81.8583 \n 1 \n 1 \n Dodge, Master. Washington \n male \n 4.0000 \n 0 \n 2 \n 33638 \n A34 \n S \n \n \n cheap \n 81.8583 \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n female \n 54.0000 \n 1 \n 1 \n 33638 \n A34 \n S \n \n \n middling \n 106.4250 \n 1 \n 0 \n Douglas, Mr. Walter Donald \n male \n 50.0000 \n 1 \n 0 \n PC 17761 \n C86 \n C \n \n \n expensive \n 247.5208 \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n female \n 27.0000 \n 1 \n 1 \n PC 17558 \n B58 B60 \n C \n \n \n middling \n 106.4250 \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n female \n 48.0000 \n 1 \n 0 \n PC 17761 \n C86 \n C \n \n \n cheap \n 39.6000 \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n female \n 48.0000 \n 1 \n 0 \n 11755 \n A16 \n C \n \n \n cheap \n 56.9292 \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n male \n 49.0000 \n 1 \n 0 \n PC 17485 \n A20 \n C \n \n \n cheap \n 29.7000 \n 1 \n 0 \n Dulles, Mr. William Crothers \n male \n 39.0000 \n 0 \n 0 \n PC 17580 \n A18 \n C \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n female \n 23.0000 \n 0 \n 1 \n 11767 \n C54 \n C \n \n \n expensive \n 227.5250 \n 1 \n 1 \n Endres, Miss. Caroline Louise \n female \n 38.0000 \n 0 \n 0 \n PC 17757 \n C45 \n C \n \n \n cheap \n 78.2667 \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n female \n 54.0000 \n 1 \n 0 \n 36947 \n D20 \n C \n \n \n cheap \n 31.6792 \n 1 \n 0 \n Evans, Miss. Edith Corse \n female \n 36.0000 \n 0 \n 0 \n PC 17531 \n A29 \n C \n \n \n expensive \n 221.7792 \n 1 \n 0 \n Farthing, Mr. John \n male \n NA \n 0 \n 0 \n PC 17483 \n C95 \n S \n \n \n cheap \n 31.6833 \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n female \n NA \n 0 \n 0 \n PC 17598 \n NA \n S \n \n \n middling \n 110.8833 \n 1 \n 1 \n Fleming, Miss. Margaret \n female \n NA \n 0 \n 0 \n 17421 \n NA \n C \n \n \n cheap \n 26.3875 \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n male \n 36.0000 \n 0 \n 0 \n PC 17474 \n E25 \n S \n \n \n cheap \n 27.7500 \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n male \n 30.0000 \n 0 \n 0 \n 113051 \n C111 \n C \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n female \n 24.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n female \n 28.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n female \n 23.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n male \n 19.0000 \n 3 \n 2 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 0 \n Fortune, Mr. Mark \n male \n 64.0000 \n 1 \n 4 \n 19950 \n C23 C25 C27 \n S \n \n \n expensive \n 263.0000 \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n female \n 60.0000 \n 1 \n 4 \n 19950 \n C23 C25 C27 \n S \n \n \n cheap \n 56.9292 \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n female \n 30.0000 \n 0 \n 0 \n PC 17485 \n E36 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n male \n NA \n 0 \n 0 \n 113778 \n D34 \n S \n \n \n middling \n 133.6500 \n 1 \n 1 \n Frauenthal, Dr. Henry William \n male \n 50.0000 \n 2 \n 0 \n PC 17611 \n NA \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n male \n 43.0000 \n 1 \n 0 \n 17765 \n D40 \n C \n \n \n middling \n 133.6500 \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n female \n NA \n 1 \n 0 \n PC 17611 \n NA \n S \n \n \n cheap \n 49.5000 \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n female \n 22.0000 \n 0 \n 2 \n 13568 \n B39 \n C \n \n \n cheap \n 79.2000 \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n male \n 60.0000 \n 1 \n 1 \n 13567 \n B41 \n C \n \n \n cheap \n 79.2000 \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n female \n 48.0000 \n 1 \n 1 \n 13567 \n B41 \n C \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Fry, Mr. Richard \n male \n NA \n 0 \n 0 \n 112058 \n B102 \n S \n \n \n cheap \n 53.1000 \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n male \n 37.0000 \n 1 \n 0 \n 113803 \n C123 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n female \n 35.0000 \n 1 \n 0 \n 113803 \n C123 \n S \n \n \n cheap \n 38.5000 \n 1 \n 0 \n Gee, Mr. Arthur H \n male \n 47.0000 \n 0 \n 0 \n 111320 \n E63 \n S \n \n \n expensive \n 211.5000 \n 1 \n 1 \n Geiger, Miss. Amalie \n female \n 35.0000 \n 0 \n 0 \n 113503 \n C130 \n C \n \n \n cheap \n 59.4000 \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n female \n 22.0000 \n 0 \n 1 \n 112378 \n NA \n C \n \n \n cheap \n 59.4000 \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n female \n 45.0000 \n 0 \n 1 \n 112378 \n NA \n C \n \n \n cheap \n 79.2000 \n 1 \n 0 \n Giglio, Mr. Victor \n male \n 24.0000 \n 0 \n 0 \n PC 17593 \n B86 \n C \n \n \n cheap \n 89.1042 \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n male \n 49.0000 \n 1 \n 0 \n 17453 \n C92 \n C \n \n \n cheap \n 89.1042 \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n female \n NA \n 1 \n 0 \n 17453 \n C92 \n C \n \n \n cheap \n 34.6542 \n 1 \n 0 \n Goldschmidt, Mr. George B \n male \n 71.0000 \n 0 \n 0 \n PC 17754 \n A5 \n C \n \n \n cheap \n 28.5000 \n 1 \n 1 \n Gracie, Col. Archibald IV \n male \n 53.0000 \n 0 \n 0 \n 113780 \n C51 \n C \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Graham, Miss. Margaret Edith \n female \n 19.0000 \n 0 \n 0 \n 112053 \n B42 \n S \n \n \n middling \n 153.4625 \n 1 \n 0 \n Graham, Mr. George Edward \n male \n 38.0000 \n 0 \n 1 \n PC 17582 \n C91 \n S \n \n \n middling \n 153.4625 \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n female \n 58.0000 \n 0 \n 1 \n PC 17582 \n C125 \n S \n \n \n cheap \n 63.3583 \n 1 \n 1 \n Greenfield, Mr. William Bertram \n male \n 23.0000 \n 0 \n 1 \n PC 17759 \n D10 D12 \n C \n \n \n cheap \n 63.3583 \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n female \n 45.0000 \n 0 \n 1 \n PC 17759 \n D10 D12 \n C \n \n \n cheap \n 79.2000 \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n male \n 46.0000 \n 0 \n 0 \n PC 17593 \n B82 B84 \n C \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Harder, Mr. George Achilles \n male \n 25.0000 \n 1 \n 0 \n 11765 \n E50 \n C \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n female \n 25.0000 \n 1 \n 0 \n 11765 \n E50 \n C \n \n \n cheap \n 76.7292 \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n male \n 48.0000 \n 1 \n 0 \n PC 17572 \n D33 \n C \n \n \n cheap \n 76.7292 \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n female \n 49.0000 \n 1 \n 0 \n PC 17572 \n D33 \n C \n \n \n cheap \n 42.4000 \n 1 \n 0 \n Harrington, Mr. Charles H \n male \n NA \n 0 \n 0 \n 113796 \n NA \n S \n \n \n cheap \n 83.4750 \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n male \n 45.0000 \n 1 \n 0 \n 36973 \n C83 \n S \n \n \n cheap \n 83.4750 \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n female \n 35.0000 \n 1 \n 0 \n 36973 \n C83 \n S \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Harrison, Mr. William \n male \n 40.0000 \n 0 \n 0 \n 112059 \n B94 \n S \n \n \n cheap \n 76.7292 \n 1 \n 1 \n Hassab, Mr. Hammad \n male \n 27.0000 \n 0 \n 0 \n PC 17572 \n D49 \n C \n \n \n cheap \n 30.0000 \n 1 \n 1 \n Hawksford, Mr. Walter James \n male \n NA \n 0 \n 0 \n 16988 \n D45 \n S \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n female \n 24.0000 \n 0 \n 0 \n 11767 \n C54 \n C \n \n \n cheap \n 93.5000 \n 1 \n 0 \n Hays, Mr. Charles Melville \n male \n 55.0000 \n 1 \n 1 \n 12749 \n B69 \n S \n \n \n cheap \n 93.5000 \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n female \n 52.0000 \n 1 \n 1 \n 12749 \n B69 \n S \n \n \n cheap \n 42.5000 \n 1 \n 0 \n Head, Mr. Christopher \n male \n 42.0000 \n 0 \n 0 \n 113038 \n B11 \n S \n \n \n cheap \n 51.8625 \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n male \n NA \n 0 \n 0 \n 17463 \n E46 \n S \n \n \n cheap \n 50.0000 \n 1 \n 0 \n Hipkins, Mr. William Edward \n male \n 55.0000 \n 0 \n 0 \n 680 \n C39 \n S \n \n \n cheap \n 57.9792 \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n female \n 16.0000 \n 0 \n 1 \n 111361 \n B18 \n C \n \n \n cheap \n 57.9792 \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n female \n 44.0000 \n 0 \n 1 \n 111361 \n B18 \n C \n \n \n cheap \n 77.9583 \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n female \n 51.0000 \n 1 \n 0 \n 13502 \n D11 \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n male \n 42.0000 \n 1 \n 0 \n 113789 \n NA \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n female \n 35.0000 \n 1 \n 0 \n 113789 \n NA \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n male \n 35.0000 \n 0 \n 0 \n 111426 \n NA \n C \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n male \n 38.0000 \n 1 \n 0 \n 19943 \n C93 \n S \n \n \n cheap \n 30.6958 \n 1 \n 0 \n Hoyt, Mr. William Fisher \n male \n NA \n 0 \n 0 \n PC 17600 \n NA \n C \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n female \n 35.0000 \n 1 \n 0 \n 19943 \n C93 \n S \n \n \n cheap \n 80.0000 \n 1 \n 1 \n Icard, Miss. Amelie \n female \n 38.0000 \n 0 \n 0 \n 113572 \n B28 \n NA \n \n \n cheap \n 28.7125 \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n female \n 50.0000 \n 0 \n 0 \n PC 17595 \n C49 \n C \n \n \n cheap \n 0.0000 \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n male \n 49.0000 \n 0 \n 0 \n 112058 \n B52 B54 B56 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Jones, Mr. Charles Cresson \n male \n 46.0000 \n 0 \n 0 \n 694 \n NA \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Julian, Mr. Henry Forbes \n male \n 50.0000 \n 0 \n 0 \n 113044 \n E60 \n S \n \n \n expensive \n 211.5000 \n 1 \n 0 \n Keeping, Mr. Edwin \n male \n 32.5000 \n 0 \n 0 \n 113503 \n C132 \n C \n \n \n cheap \n 29.7000 \n 1 \n 0 \n Kent, Mr. Edward Austin \n male \n 58.0000 \n 0 \n 0 \n 11771 \n B37 \n C \n \n \n cheap \n 51.8625 \n 1 \n 0 \n Kenyon, Mr. Frederick R \n male \n 41.0000 \n 1 \n 0 \n 17464 \n D21 \n S \n \n \n cheap \n 51.8625 \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n female \n NA \n 1 \n 0 \n 17464 \n D21 \n S \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n male \n 42.0000 \n 1 \n 0 \n 11753 \n D19 \n S \n \n \n cheap \n 52.5542 \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n female \n 45.0000 \n 1 \n 0 \n 11753 \n D19 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Klaber, Mr. Herman \n male \n NA \n 0 \n 0 \n 113028 \n C124 \n S \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Kreuchen, Miss. Emilie \n female \n 39.0000 \n 0 \n 0 \n 24160 \n NA \n S \n \n \n cheap \n 25.9292 \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n female \n 49.0000 \n 0 \n 0 \n 17465 \n D17 \n S \n \n \n middling \n 106.4250 \n 1 \n 1 \n LeRoy, Miss. Bertha \n female \n 30.0000 \n 0 \n 0 \n PC 17761 \n NA \n C \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Lesurer, Mr. Gustave J \n male \n 35.0000 \n 0 \n 0 \n PC 17755 \n B101 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Lewy, Mr. Ervin G \n male \n NA \n 0 \n 0 \n PC 17612 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n male \n 42.0000 \n 0 \n 0 \n 17475 \n NA \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n female \n 55.0000 \n 0 \n 0 \n 112377 \n NA \n C \n \n \n cheap \n 39.4000 \n 1 \n 1 \n Lines, Miss. Mary Conover \n female \n 16.0000 \n 0 \n 1 \n PC 17592 \n D28 \n S \n \n \n cheap \n 39.4000 \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n female \n 51.0000 \n 0 \n 1 \n PC 17592 \n D28 \n S \n \n \n cheap \n 30.0000 \n 1 \n 0 \n Long, Mr. Milton Clyde \n male \n 29.0000 \n 0 \n 0 \n 113501 \n D6 \n S \n \n \n cheap \n 77.9583 \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n female \n 21.0000 \n 0 \n 0 \n 13502 \n D9 \n S \n \n \n cheap \n 45.5000 \n 1 \n 0 \n Loring, Mr. Joseph Holland \n male \n 30.0000 \n 0 \n 0 \n 113801 \n NA \n S \n \n \n middling \n 146.5208 \n 1 \n 1 \n Lurette, Miss. Elise \n female \n 58.0000 \n 0 \n 0 \n PC 17569 \n B80 \n C \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n female \n 15.0000 \n 0 \n 1 \n 24160 \n B5 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Maguire, Mr. John Edward \n male \n 30.0000 \n 0 \n 0 \n 110469 \n C106 \n S \n \n \n cheap \n 86.5000 \n 1 \n 1 \n Maioni, Miss. Roberta \n female \n 16.0000 \n 0 \n 0 \n 110152 \n B79 \n S \n \n \n cheap \n 29.7000 \n 1 \n 1 \n Marechal, Mr. Pierre \n male \n NA \n 0 \n 0 \n 11774 \n C47 \n C \n \n \n cheap \n 53.1000 \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n male \n 19.0000 \n 1 \n 0 \n 113773 \n D30 \n S \n \n \n cheap \n 53.1000 \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n female \n 18.0000 \n 1 \n 0 \n 113773 \n D30 \n S \n \n \n cheap \n 49.5042 \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n female \n 24.0000 \n 0 \n 0 \n PC 17482 \n C90 \n C \n \n \n cheap \n 75.2417 \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n male \n 46.0000 \n 0 \n 0 \n 13050 \n C6 \n C \n \n \n cheap \n 51.8625 \n 1 \n 0 \n McCarthy, Mr. Timothy J \n male \n 54.0000 \n 0 \n 0 \n 17463 \n E46 \n S \n \n \n cheap \n 26.2875 \n 1 \n 1 \n McGough, Mr. James Robert \n male \n 36.0000 \n 0 \n 0 \n PC 17473 \n E25 \n S \n \n \n cheap \n 82.1708 \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n male \n 28.0000 \n 1 \n 0 \n PC 17604 \n NA \n C \n \n \n cheap \n 82.1708 \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n female \n NA \n 1 \n 0 \n PC 17604 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Millet, Mr. Francis Davis \n male \n 65.0000 \n 0 \n 0 \n 13509 \n E38 \n S \n \n \n cheap \n 90.0000 \n 1 \n 0 \n Minahan, Dr. William Edward \n male \n 44.0000 \n 2 \n 0 \n 19928 \n C78 \n Q \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Minahan, Miss. Daisy E \n female \n 33.0000 \n 1 \n 0 \n 19928 \n C78 \n Q \n \n \n cheap \n 90.0000 \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n female \n 37.0000 \n 1 \n 0 \n 19928 \n C78 \n Q \n \n \n cheap \n 57.7500 \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n male \n 30.0000 \n 1 \n 0 \n 13236 \n C78 \n C \n \n \n cheap \n 30.5000 \n 1 \n 0 \n Molson, Mr. Harry Markland \n male \n 55.0000 \n 0 \n 0 \n 113787 \n C30 \n S \n \n \n cheap \n 42.4000 \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n male \n 47.0000 \n 0 \n 0 \n 113796 \n NA \n S \n \n \n cheap \n 29.7000 \n 1 \n 0 \n Natsch, Mr. Charles H \n male \n 37.0000 \n 0 \n 1 \n PC 17596 \n C118 \n C \n \n \n middling \n 113.2750 \n 1 \n 1 \n Newell, Miss. Madeleine \n female \n 31.0000 \n 1 \n 0 \n 35273 \n D36 \n C \n \n \n middling \n 113.2750 \n 1 \n 1 \n Newell, Miss. Marjorie \n female \n 23.0000 \n 1 \n 0 \n 35273 \n D36 \n C \n \n \n middling \n 113.2750 \n 1 \n 0 \n Newell, Mr. Arthur Webster \n male \n 58.0000 \n 0 \n 2 \n 35273 \n D48 \n C \n \n \n cheap \n 26.2833 \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n female \n 19.0000 \n 0 \n 2 \n 11752 \n D47 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n male \n 64.0000 \n 0 \n 0 \n 693 \n NA \n S \n \n \n middling \n 108.9000 \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n female \n 39.0000 \n 0 \n 0 \n PC 17758 \n C105 \n C \n \n \n cheap \n 25.7417 \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n male \n NA \n 0 \n 0 \n F.C. 12998 \n NA \n C \n \n \n cheap \n 61.9792 \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n female \n 22.0000 \n 0 \n 1 \n 113509 \n B36 \n C \n \n \n cheap \n 61.9792 \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n male \n 65.0000 \n 0 \n 1 \n 113509 \n B30 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n male \n 28.5000 \n 0 \n 0 \n PC 17562 \n D43 \n C \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n male \n NA \n 0 \n 0 \n 112052 \n NA \n S \n \n \n cheap \n 28.5000 \n 1 \n 0 \n Partner, Mr. Austen \n male \n 45.5000 \n 0 \n 0 \n 113043 \n C124 \n S \n \n \n cheap \n 93.5000 \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n male \n 23.0000 \n 0 \n 0 \n 12749 \n B24 \n S \n \n \n cheap \n 66.6000 \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n male \n 29.0000 \n 1 \n 0 \n 113776 \n C2 \n S \n \n \n cheap \n 66.6000 \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n female \n 22.0000 \n 1 \n 0 \n 113776 \n C2 \n S \n \n \n middling \n 108.9000 \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n male \n 18.0000 \n 1 \n 0 \n PC 17758 \n C65 \n C \n \n \n middling \n 108.9000 \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n female \n 17.0000 \n 1 \n 0 \n PC 17758 \n C65 \n C \n \n \n cheap \n 93.5000 \n 1 \n 1 \n Perreault, Miss. Anne \n female \n 30.0000 \n 0 \n 0 \n 12749 \n B73 \n S \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n male \n 52.0000 \n 0 \n 0 \n 113786 \n C104 \n S \n \n \n cheap \n 52.0000 \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n male \n 47.0000 \n 0 \n 0 \n 110465 \n C110 \n S \n \n \n cheap \n 83.1583 \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n female \n 56.0000 \n 0 \n 1 \n 11767 \n C50 \n C \n \n \n cheap \n 0.0000 \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n male \n 38.0000 \n 0 \n 0 \n 19972 \n NA \n S \n \n \n cheap \n 39.6000 \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n male \n NA \n 0 \n 0 \n PC 17607 \n NA \n S \n \n \n middling \n 135.6333 \n 1 \n 0 \n Ringhini, Mr. Sante \n male \n 22.0000 \n 0 \n 0 \n PC 17760 \n NA \n C \n \n \n expensive \n 227.5250 \n 1 \n 0 \n Robbins, Mr. Victor \n male \n NA \n 0 \n 0 \n PC 17757 \n NA \n C \n \n \n expensive \n 211.3375 \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n female \n 43.0000 \n 0 \n 1 \n 24160 \n B3 \n S \n \n \n cheap \n 50.4958 \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n male \n 31.0000 \n 0 \n 0 \n PC 17590 \n A24 \n S \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n male \n 45.0000 \n 0 \n 0 \n 111428 \n NA \n S \n \n \n cheap \n 50.0000 \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n male \n NA \n 0 \n 0 \n 113767 \n A32 \n S \n \n \n cheap \n 27.7208 \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n female \n 33.0000 \n 0 \n 0 \n PC 17613 \n A11 \n C \n \n \n cheap \n 79.2000 \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n male \n 46.0000 \n 0 \n 0 \n PC 17585 \n NA \n C \n \n \n cheap \n 40.1250 \n 1 \n 0 \n Ross, Mr. John Hugo \n male \n 36.0000 \n 0 \n 0 \n 13049 \n A10 \n C \n \n \n cheap \n 86.5000 \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n female \n 33.0000 \n 0 \n 0 \n 110152 \n B77 \n S \n \n \n cheap \n 59.4000 \n 1 \n 0 \n Rothschild, Mr. Martin \n male \n 55.0000 \n 1 \n 0 \n PC 17603 \n NA \n C \n \n \n cheap \n 59.4000 \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n female \n 54.0000 \n 1 \n 0 \n PC 17603 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Rowe, Mr. Alfred G \n male \n 33.0000 \n 0 \n 0 \n 113790 \n NA \n S \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Master. John Borie \n male \n 13.0000 \n 2 \n 2 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n female \n 18.0000 \n 2 \n 2 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n female \n 21.0000 \n 2 \n 2 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n male \n 61.0000 \n 1 \n 3 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n expensive \n 262.3750 \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n female \n 48.0000 \n 1 \n 3 \n PC 17608 \n B57 B59 B63 B66 \n C \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n male \n NA \n 0 \n 0 \n 19988 \n C106 \n S \n \n \n cheap \n 69.3000 \n 1 \n 1 \n Sagesser, Mlle. Emma \n female \n 24.0000 \n 0 \n 0 \n PC 17477 \n B35 \n C \n \n \n cheap \n 26.0000 \n 1 \n 1 \n Salomon, Mr. Abraham L \n male \n NA \n 0 \n 0 \n 111163 \n NA \n S \n \n \n cheap \n 57.7500 \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n female \n 35.0000 \n 1 \n 0 \n 13236 \n C28 \n C \n \n \n cheap \n 31.0000 \n 1 \n 1 \n Serepeca, Miss. Augusta \n female \n 30.0000 \n 0 \n 0 \n 113798 \n NA \n C \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n male \n 34.0000 \n 0 \n 0 \n 113794 \n NA \n S \n \n \n middling \n 153.4625 \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n female \n 40.0000 \n 0 \n 0 \n PC 17582 \n C125 \n S \n \n \n cheap \n 26.2875 \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n male \n 35.0000 \n 0 \n 0 \n PC 17475 \n E24 \n S \n \n \n cheap \n 55.9000 \n 1 \n 0 \n Silvey, Mr. William Baird \n male \n 50.0000 \n 1 \n 0 \n 13507 \n E44 \n S \n \n \n cheap \n 55.9000 \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n female \n 39.0000 \n 1 \n 0 \n 13507 \n E44 \n S \n \n \n cheap \n 35.5000 \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n male \n 56.0000 \n 0 \n 0 \n 13213 \n A26 \n C \n \n \n cheap \n 35.5000 \n 1 \n 1 \n Sloper, Mr. William Thompson \n male \n 28.0000 \n 0 \n 0 \n 113788 \n A6 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Smart, Mr. John Montgomery \n male \n 56.0000 \n 0 \n 0 \n 113792 \n NA \n S \n \n \n cheap \n 30.6958 \n 1 \n 0 \n Smith, Mr. James Clinch \n male \n 56.0000 \n 0 \n 0 \n 17764 \n A7 \n C \n \n \n cheap \n 60.0000 \n 1 \n 0 \n Smith, Mr. Lucien Philip \n male \n 24.0000 \n 1 \n 0 \n 13695 \n C31 \n S \n \n \n cheap \n 26.0000 \n 1 \n 0 \n Smith, Mr. Richard William \n male \n NA \n 0 \n 0 \n 113056 \n A19 \n S \n \n \n cheap \n 60.0000 \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n female \n 18.0000 \n 1 \n 0 \n 13695 \n C31 \n S \n \n \n cheap \n 82.2667 \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n male \n 24.0000 \n 1 \n 0 \n 21228 \n B45 \n S \n \n \n cheap \n 82.2667 \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n female \n 23.0000 \n 1 \n 0 \n 21228 \n B45 \n S \n \n \n middling \n 134.5000 \n 1 \n 1 \n Spedden, Master. Robert Douglas \n male \n 6.0000 \n 0 \n 2 \n 16966 \n E34 \n C \n \n \n middling \n 134.5000 \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n male \n 45.0000 \n 1 \n 1 \n 16966 \n E34 \n C \n \n \n middling \n 134.5000 \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n female \n 40.0000 \n 1 \n 1 \n 16966 \n E34 \n C \n \n \n middling \n 146.5208 \n 1 \n 0 \n Spencer, Mr. William Augustus \n male \n 57.0000 \n 1 \n 0 \n PC 17569 \n B78 \n C \n \n \n middling \n 146.5208 \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n female \n NA \n 1 \n 0 \n PC 17569 \n B78 \n C \n \n \n cheap \n 30.5000 \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n male \n 32.0000 \n 0 \n 0 \n 13214 \n B50 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Stead, Mr. William Thomas \n male \n 62.0000 \n 0 \n 0 \n 113514 \n C87 \n S \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n male \n 54.0000 \n 1 \n 0 \n 11778 \n C116 \n C \n \n \n cheap \n 55.4417 \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n female \n 43.0000 \n 1 \n 0 \n 11778 \n C116 \n C \n \n \n cheap \n 78.2667 \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n female \n 52.0000 \n 1 \n 0 \n 36947 \n D20 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Stewart, Mr. Albert A \n male \n NA \n 0 \n 0 \n PC 17605 \n NA \n C \n \n \n cheap \n 80.0000 \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n female \n 62.0000 \n 0 \n 0 \n 113572 \n B28 \n NA \n \n \n expensive \n 221.7792 \n 1 \n 0 \n Straus, Mr. Isidor \n male \n 67.0000 \n 1 \n 0 \n PC 17483 \n C55 C57 \n S \n \n \n expensive \n 221.7792 \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n female \n 63.0000 \n 1 \n 0 \n PC 17483 \n C55 C57 \n S \n \n \n cheap \n 32.3208 \n 1 \n 0 \n Sutton, Mr. Frederick \n male \n 61.0000 \n 0 \n 0 \n 36963 \n D50 \n S \n \n \n cheap \n 25.9292 \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n female \n 48.0000 \n 0 \n 0 \n 17466 \n D17 \n S \n \n \n cheap \n 79.6500 \n 1 \n 1 \n Taussig, Miss. Ruth \n female \n 18.0000 \n 0 \n 2 \n 110413 \n E68 \n S \n \n \n cheap \n 79.6500 \n 1 \n 0 \n Taussig, Mr. Emil \n male \n 52.0000 \n 1 \n 1 \n 110413 \n E67 \n S \n \n \n cheap \n 79.6500 \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n female \n 39.0000 \n 1 \n 1 \n 110413 \n E67 \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n male \n 48.0000 \n 1 \n 0 \n 19996 \n C126 \n S \n \n \n cheap \n 52.0000 \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n female \n NA \n 1 \n 0 \n 19996 \n C126 \n S \n \n \n middling \n 110.8833 \n 1 \n 0 \n Thayer, Mr. John Borland \n male \n 49.0000 \n 1 \n 1 \n 17421 \n C68 \n C \n \n \n middling \n 110.8833 \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n male \n 17.0000 \n 0 \n 2 \n 17421 \n C70 \n C \n \n \n middling \n 110.8833 \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n female \n 39.0000 \n 1 \n 1 \n 17421 \n C68 \n C \n \n \n cheap \n 79.2000 \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n female \n NA \n 0 \n 0 \n PC 17585 \n NA \n C \n \n \n cheap \n 28.5375 \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n male \n 31.0000 \n 0 \n 0 \n 2543 \n C53 \n C \n \n \n cheap \n 27.7208 \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n male \n 40.0000 \n 0 \n 0 \n PC 17601 \n NA \n C \n \n \n cheap \n 33.5000 \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n male \n 61.0000 \n 0 \n 0 \n 111240 \n B19 \n S \n \n \n cheap \n 34.0208 \n 1 \n 0 \n Walker, Mr. William Anderson \n male \n 47.0000 \n 0 \n 0 \n 36967 \n D46 \n S \n \n \n very expensive \n 512.3292 \n 1 \n 1 \n Ward, Miss. Anna \n female \n 35.0000 \n 0 \n 0 \n PC 17755 \n NA \n C \n \n \n cheap \n 75.2500 \n 1 \n 0 \n Warren, Mr. Frank Manley \n male \n 64.0000 \n 1 \n 0 \n 110813 \n D37 \n C \n \n \n cheap \n 75.2500 \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n female \n 60.0000 \n 1 \n 0 \n 110813 \n D37 \n C \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Weir, Col. John \n male \n 60.0000 \n 0 \n 0 \n 113800 \n NA \n S \n \n \n cheap \n 77.2875 \n 1 \n 0 \n White, Mr. Percival Wayland \n male \n 54.0000 \n 0 \n 1 \n 35281 \n D26 \n S \n \n \n cheap \n 77.2875 \n 1 \n 0 \n White, Mr. Richard Frasar \n male \n 21.0000 \n 0 \n 1 \n 35281 \n D26 \n S \n \n \n middling \n 135.6333 \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n female \n 55.0000 \n 0 \n 0 \n PC 17760 \n C32 \n C \n \n \n middling \n 164.8667 \n 1 \n 1 \n Wick, Miss. Mary Natalie \n female \n 31.0000 \n 0 \n 2 \n 36928 \n C7 \n S \n \n \n middling \n 164.8667 \n 1 \n 0 \n Wick, Mr. George Dennick \n male \n 57.0000 \n 1 \n 1 \n 36928 \n NA \n S \n \n \n middling \n 164.8667 \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n female \n 45.0000 \n 1 \n 1 \n 36928 \n NA \n S \n \n \n expensive \n 211.5000 \n 1 \n 0 \n Widener, Mr. George Dunton \n male \n 50.0000 \n 1 \n 1 \n 113503 \n C80 \n C \n \n \n expensive \n 211.5000 \n 1 \n 0 \n Widener, Mr. Harry Elkins \n male \n 27.0000 \n 0 \n 2 \n 113503 \n C82 \n C \n \n \n expensive \n 211.5000 \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n female \n 50.0000 \n 1 \n 1 \n 113503 \n C80 \n C \n \n \n cheap \n 26.5500 \n 1 \n 1 \n Willard, Miss. Constance \n female \n 21.0000 \n 0 \n 0 \n 113795 \n NA \n S \n \n \n cheap \n 61.3792 \n 1 \n 0 \n Williams, Mr. Charles Duane \n male \n 51.0000 \n 0 \n 1 \n PC 17597 \n NA \n C \n \n \n cheap \n 61.3792 \n 1 \n 1 \n Williams, Mr. Richard Norris II \n male \n 21.0000 \n 0 \n 1 \n PC 17597 \n NA \n C \n \n \n cheap \n 35.0000 \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n male \n NA \n 0 \n 0 \n 113510 \n C128 \n S \n \n \n middling \n 134.5000 \n 1 \n 1 \n Wilson, Miss. Helen Alice \n female \n 31.0000 \n 0 \n 0 \n 16966 \n E39 E41 \n C \n \n \n cheap \n 35.5000 \n 1 \n 1 \n Woolner, Mr. Hugh \n male \n NA \n 0 \n 0 \n 19947 \n C52 \n S \n \n \n cheap \n 26.5500 \n 1 \n 0 \n Wright, Mr. George \n male \n 62.0000 \n 0 \n 0 \n 113807 \n NA \n S \n \n \n middling \n 135.6333 \n 1 \n 1 \n Young, Miss. Marie Grice \n female \n 36.0000 \n 0 \n 0 \n PC 17760 \n C32 \n C \n \n \n cheap \n 24.0000 \n 2 \n 0 \n Abelson, Mr. Samuel \n male \n 30.0000 \n 1 \n 0 \n P/PP 3381 \n NA \n C \n \n \n cheap \n 24.0000 \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n female \n 28.0000 \n 1 \n 0 \n P/PP 3381 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n male \n 30.0000 \n 0 \n 0 \n 248744 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n male \n 18.0000 \n 0 \n 0 \n 231945 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n male \n 25.0000 \n 0 \n 0 \n C.A. 34050 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Angle, Mr. William A \n male \n 34.0000 \n 1 \n 0 \n 226875 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n female \n 36.0000 \n 1 \n 0 \n 226875 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Ashby, Mr. John \n male \n 57.0000 \n 0 \n 0 \n 244346 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n male \n 18.0000 \n 0 \n 0 \n 29108 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n male \n 23.0000 \n 0 \n 0 \n C.A. 31030 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n female \n 36.0000 \n 0 \n 0 \n 28551 \n D \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Banfield, Mr. Frederick James \n male \n 28.0000 \n 0 \n 0 \n C.A./SOTON 34068 \n NA \n S \n \n \n cheap \n 12.5250 \n 2 \n 0 \n Bateman, Rev. Robert James \n male \n 51.0000 \n 0 \n 0 \n S.O.P. 1166 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Beane, Mr. Edward \n male \n 32.0000 \n 1 \n 0 \n 2908 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n female \n 19.0000 \n 1 \n 0 \n 2908 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Beauchamp, Mr. Henry James \n male \n 28.0000 \n 0 \n 0 \n 244358 \n NA \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Master. Richard F \n male \n 1.0000 \n 2 \n 1 \n 230136 \n F4 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Miss. Marion Louise \n female \n 4.0000 \n 2 \n 1 \n 230136 \n F4 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n female \n 12.0000 \n 2 \n 1 \n 230136 \n F4 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n female \n 36.0000 \n 0 \n 3 \n 230136 \n F4 \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Beesley, Mr. Lawrence \n male \n 34.0000 \n 0 \n 0 \n 248698 \n D56 \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Bentham, Miss. Lilian W \n female \n 19.0000 \n 0 \n 0 \n 28404 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Berriman, Mr. William John \n male \n 23.0000 \n 0 \n 0 \n 28425 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Botsford, Mr. William Hull \n male \n 26.0000 \n 0 \n 0 \n 237670 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Bowenur, Mr. Solomon \n male \n 42.0000 \n 0 \n 0 \n 211535 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Bracken, Mr. James H \n male \n 27.0000 \n 0 \n 0 \n 220367 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n female \n 24.0000 \n 0 \n 0 \n 248733 \n F33 \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Brown, Miss. Edith Eileen \n female \n 15.0000 \n 0 \n 2 \n 29750 \n NA \n S \n \n \n cheap \n 39.0000 \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n male \n 60.0000 \n 1 \n 1 \n 29750 \n NA \n S \n \n \n cheap \n 39.0000 \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n female \n 40.0000 \n 1 \n 1 \n 29750 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n female \n 20.0000 \n 1 \n 0 \n 236853 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n male \n 25.0000 \n 1 \n 0 \n 236853 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Buss, Miss. Kate \n female \n 36.0000 \n 0 \n 0 \n 27849 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n male \n 25.0000 \n 0 \n 0 \n 234686 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n male \n 42.0000 \n 0 \n 0 \n 244310 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n female \n 42.0000 \n 0 \n 0 \n 236852 \n NA \n S \n \n \n cheap \n 29.0000 \n 2 \n 1 \n Caldwell, Master. Alden Gates \n male \n 0.8333 \n 0 \n 2 \n 248738 \n NA \n S \n \n \n cheap \n 29.0000 \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n male \n 26.0000 \n 1 \n 1 \n 248738 \n NA \n S \n \n \n cheap \n 29.0000 \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n female \n 22.0000 \n 1 \n 1 \n 248738 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Cameron, Miss. Clear Annie \n female \n 35.0000 \n 0 \n 0 \n F.C.C. 13528 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Campbell, Mr. William \n male \n NA \n 0 \n 0 \n 239853 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Carbines, Mr. William \n male \n 19.0000 \n 0 \n 0 \n 28424 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n female \n 44.0000 \n 1 \n 0 \n 244252 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n male \n 54.0000 \n 1 \n 0 \n 244252 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Chapman, Mr. Charles Henry \n male \n 52.0000 \n 0 \n 0 \n 248731 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Chapman, Mr. John Henry \n male \n 37.0000 \n 1 \n 0 \n SC/AH 29037 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n female \n 29.0000 \n 1 \n 0 \n SC/AH 29037 \n NA \n S \n \n \n cheap \n 30.0000 \n 2 \n 1 \n Christy, Miss. Julie Rachel \n female \n 25.0000 \n 1 \n 1 \n 237789 \n NA \n S \n \n \n cheap \n 30.0000 \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n female \n 45.0000 \n 0 \n 2 \n 237789 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n male \n 29.0000 \n 1 \n 0 \n 2003 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n female \n 28.0000 \n 1 \n 0 \n 2003 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n male \n 29.0000 \n 0 \n 0 \n W./C. 14263 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n male \n 28.0000 \n 0 \n 0 \n 248740 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n male \n 24.0000 \n 0 \n 0 \n 28034 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n female \n 8.0000 \n 0 \n 2 \n C.A. 31921 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 0 \n Collyer, Mr. Harvey \n male \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n female \n 31.0000 \n 1 \n 1 \n C.A. 31921 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n female \n 22.0000 \n 0 \n 0 \n W./C. 14266 \n F33 \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n female \n 30.0000 \n 0 \n 0 \n 237249 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n female \n NA \n 0 \n 0 \n F.C.C. 13534 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n male \n 21.0000 \n 0 \n 0 \n 29107 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n male \n NA \n 0 \n 0 \n 239853 \n NA \n S \n \n \n cheap \n 36.7500 \n 2 \n 1 \n Davies, Master. John Morgan Jr \n male \n 8.0000 \n 1 \n 1 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Davies, Mr. Charles Henry \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 36.7500 \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n female \n 48.0000 \n 0 \n 2 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Davis, Miss. Mary \n female \n 28.0000 \n 0 \n 0 \n 237668 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n male \n 32.0000 \n 0 \n 0 \n 244360 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Deacon, Mr. Percy William \n male \n 17.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 27.7208 \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n male \n 29.0000 \n 1 \n 0 \n SC/PARIS 2167 \n NA \n C \n \n \n cheap \n 27.7208 \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n female \n 24.0000 \n 1 \n 0 \n SC/PARIS 2167 \n NA \n C \n \n \n cheap \n 31.5000 \n 2 \n 0 \n Denbury, Mr. Herbert \n male \n 25.0000 \n 0 \n 0 \n C.A. 31029 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Dibden, Mr. William \n male \n 18.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Doling, Miss. Elsie \n female \n 18.0000 \n 0 \n 1 \n 231919 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n female \n 34.0000 \n 0 \n 1 \n 231919 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Downton, Mr. William James \n male \n 54.0000 \n 0 \n 0 \n 28403 \n NA \n S \n \n \n cheap \n 32.5000 \n 2 \n 1 \n Drew, Master. Marshall Brines \n male \n 8.0000 \n 0 \n 2 \n 28220 \n NA \n S \n \n \n cheap \n 32.5000 \n 2 \n 0 \n Drew, Mr. James Vivian \n male \n 42.0000 \n 1 \n 1 \n 28220 \n NA \n S \n \n \n cheap \n 32.5000 \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n female \n 34.0000 \n 1 \n 1 \n 28220 \n NA \n S \n \n \n cheap \n 13.8583 \n 2 \n 1 \n Duran y More, Miss. Asuncion \n female \n 27.0000 \n 1 \n 0 \n SC/PARIS 2149 \n NA \n C \n \n \n cheap \n 13.8583 \n 2 \n 1 \n Duran y More, Miss. Florentina \n female \n 30.0000 \n 1 \n 0 \n SC/PARIS 2148 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n male \n 23.0000 \n 0 \n 0 \n 29751 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Enander, Mr. Ingvar \n male \n 21.0000 \n 0 \n 0 \n 236854 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n male \n 18.0000 \n 0 \n 0 \n 236171 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Faunthorpe, Mr. Harry \n male \n 40.0000 \n 1 \n 0 \n 2926 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n female \n 29.0000 \n 1 \n 0 \n 2926 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n male \n 18.0000 \n 0 \n 0 \n C.A. 15185 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n male \n 36.0000 \n 0 \n 0 \n 229236 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n male \n NA \n 0 \n 0 \n 239854 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n female \n 38.0000 \n 0 \n 0 \n 237671 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Fynney, Mr. Joseph J \n male \n 35.0000 \n 0 \n 0 \n 239865 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Gale, Mr. Harry \n male \n 38.0000 \n 1 \n 0 \n 28664 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Gale, Mr. Shadrach \n male \n 34.0000 \n 1 \n 0 \n 28664 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Garside, Miss. Ethel \n female \n 34.0000 \n 0 \n 0 \n 243880 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Gaskell, Mr. Alfred \n male \n 16.0000 \n 0 \n 0 \n 239865 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Gavey, Mr. Lawrence \n male \n 26.0000 \n 0 \n 0 \n 31028 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Gilbert, Mr. William \n male \n 47.0000 \n 0 \n 0 \n C.A. 30769 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Giles, Mr. Edgar \n male \n 21.0000 \n 1 \n 0 \n 28133 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Giles, Mr. Frederick Edward \n male \n 21.0000 \n 1 \n 0 \n 28134 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Giles, Mr. Ralph \n male \n 24.0000 \n 0 \n 0 \n 248726 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Gill, Mr. John William \n male \n 24.0000 \n 0 \n 0 \n 233866 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Gillespie, Mr. William Henry \n male \n 34.0000 \n 0 \n 0 \n 12233 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n male \n 30.0000 \n 0 \n 0 \n 250646 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Greenberg, Mr. Samuel \n male \n 52.0000 \n 0 \n 0 \n 250647 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hale, Mr. Reginald \n male \n 30.0000 \n 0 \n 0 \n 250653 \n NA \n S \n \n \n cheap \n 14.5000 \n 2 \n 1 \n Hamalainen, Master. Viljo \n male \n 0.6667 \n 1 \n 1 \n 250649 \n NA \n S \n \n \n cheap \n 14.5000 \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n female \n 24.0000 \n 0 \n 2 \n 250649 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Harbeck, Mr. William H \n male \n 44.0000 \n 0 \n 0 \n 248746 \n NA \n S \n \n \n cheap \n 33.0000 \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n female \n 6.0000 \n 0 \n 1 \n 248727 \n NA \n S \n \n \n cheap \n 33.0000 \n 2 \n 0 \n Harper, Rev. John \n male \n 28.0000 \n 0 \n 1 \n 248727 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Harris, Mr. George \n male \n 62.0000 \n 0 \n 0 \n S.W./PP 752 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Harris, Mr. Walter \n male \n 30.0000 \n 0 \n 0 \n W/C 14208 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Hart, Miss. Eva Miriam \n female \n 7.0000 \n 0 \n 2 \n F.C.C. 13529 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 0 \n Hart, Mr. Benjamin \n male \n 43.0000 \n 1 \n 1 \n F.C.C. 13529 \n NA \n S \n \n \n cheap \n 26.2500 \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n female \n 45.0000 \n 1 \n 1 \n F.C.C. 13529 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 1 \n Herman, Miss. Alice \n female \n 24.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 1 \n Herman, Miss. Kate \n female \n 24.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 0 \n Herman, Mr. Samuel \n male \n 49.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 65.0000 \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n female \n 48.0000 \n 1 \n 2 \n 220845 \n NA \n S \n \n \n cheap \n 16.0000 \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n female \n 55.0000 \n 0 \n 0 \n 248706 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n male \n 24.0000 \n 2 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hickman, Mr. Lewis \n male \n 32.0000 \n 2 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hickman, Mr. Stanley George \n male \n 21.0000 \n 2 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hiltunen, Miss. Marta \n female \n 18.0000 \n 1 \n 1 \n 250650 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n female \n 20.0000 \n 2 \n 1 \n 29105 \n NA \n S \n \n \n cheap \n 11.5000 \n 2 \n 0 \n Hocking, Mr. Richard George \n male \n 23.0000 \n 2 \n 1 \n 29104 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n male \n 36.0000 \n 0 \n 0 \n 242963 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n female \n 54.0000 \n 1 \n 3 \n 29105 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Hodges, Mr. Henry Price \n male \n 50.0000 \n 0 \n 0 \n 250643 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Hold, Mr. Stephen \n male \n 44.0000 \n 1 \n 0 \n 26707 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n female \n 29.0000 \n 1 \n 0 \n 26707 \n NA \n S \n \n \n cheap \n 73.5000 \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n male \n 21.0000 \n 0 \n 0 \n S.O.C. 14879 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Hosono, Mr. Masabumi \n male \n 42.0000 \n 0 \n 0 \n 237798 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Howard, Mr. Benjamin \n male \n 63.0000 \n 1 \n 0 \n 24065 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n female \n 60.0000 \n 1 \n 0 \n 24065 \n NA \n S \n \n \n cheap \n 12.2750 \n 2 \n 0 \n Hunt, Mr. George Henry \n male \n 33.0000 \n 0 \n 0 \n SCO/W 1585 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Ilett, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SO/C 14885 \n NA \n S \n \n \n cheap \n 27.0000 \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n male \n 42.0000 \n 1 \n 0 \n 243847 \n NA \n S \n \n \n cheap \n 27.0000 \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n female \n 24.0000 \n 2 \n 1 \n 243847 \n NA \n S \n \n \n cheap \n 15.0000 \n 2 \n 0 \n Jarvis, Mr. John Denzil \n male \n 47.0000 \n 0 \n 0 \n 237565 \n NA \n S \n \n \n cheap \n 31.5000 \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n male \n 24.0000 \n 2 \n 0 \n C.A. 31029 \n NA \n S \n \n \n cheap \n 31.5000 \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n male \n 22.0000 \n 2 \n 0 \n C.A. 31029 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n male \n 32.0000 \n 0 \n 0 \n C.A. 33111 \n NA \n S \n \n \n cheap \n 13.7917 \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n female \n 23.0000 \n 0 \n 0 \n SC/AH Basle 541 \n D \n C \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Kantor, Mr. Sinai \n male \n 34.0000 \n 1 \n 0 \n 244367 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n female \n 24.0000 \n 1 \n 0 \n 244367 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n female \n 22.0000 \n 0 \n 0 \n F.C.C. 13534 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 1 \n Keane, Miss. Nora A \n female \n NA \n 0 \n 0 \n 226593 \n E101 \n Q \n \n \n cheap \n 12.3500 \n 2 \n 0 \n Keane, Mr. Daniel \n male \n 35.0000 \n 0 \n 0 \n 233734 \n NA \n Q \n \n \n cheap \n 13.5000 \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n female \n 45.0000 \n 0 \n 0 \n 223596 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n male \n 57.0000 \n 0 \n 0 \n 219533 \n NA \n Q \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Knight, Mr. Robert J \n male \n NA \n 0 \n 0 \n 239855 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n male \n 31.0000 \n 0 \n 0 \n C.A. 18723 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n female \n 26.0000 \n 1 \n 1 \n 250651 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Lahtinen, Rev. William \n male \n 30.0000 \n 1 \n 1 \n 250651 \n NA \n S \n \n \n cheap \n 10.7083 \n 2 \n 0 \n Lamb, Mr. John Joseph \n male \n NA \n 0 \n 0 \n 240261 \n NA \n Q \n \n \n cheap \n 41.5792 \n 2 \n 1 \n Laroche, Miss. Louise \n female \n 1.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 41.5792 \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n female \n 3.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 41.5792 \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n male \n 25.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 41.5792 \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n female \n 22.0000 \n 1 \n 2 \n SC/Paris 2123 \n NA \n C \n \n \n cheap \n 12.0000 \n 2 \n 1 \n Lehmann, Miss. Bertha \n female \n 17.0000 \n 0 \n 0 \n SC 1748 \n NA \n C \n \n \n cheap \n 33.0000 \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n female \n NA \n 0 \n 0 \n 248727 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n female \n 34.0000 \n 0 \n 0 \n C.A. 34260 \n F33 \n S \n \n \n cheap \n 12.8750 \n 2 \n 0 \n Levy, Mr. Rene Jacques \n male \n 36.0000 \n 0 \n 0 \n SC/Paris 2163 \n D \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n male \n 24.0000 \n 0 \n 0 \n C.A. 29566 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 0 \n Lingane, Mr. John \n male \n 61.0000 \n 0 \n 0 \n 235509 \n NA \n Q \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Louch, Mr. Charles Alexander \n male \n 50.0000 \n 1 \n 0 \n SC/AH 3085 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n female \n 42.0000 \n 1 \n 0 \n SC/AH 3085 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Mack, Mrs. (Mary) \n female \n 57.0000 \n 0 \n 0 \n S.O./P.P. 3 \n E77 \n S \n \n \n cheap \n 15.0458 \n 2 \n 0 \n Malachard, Mr. Noel \n male \n NA \n 0 \n 0 \n 237735 \n D \n C \n \n \n cheap \n 37.0042 \n 2 \n 1 \n Mallet, Master. Andre \n male \n 1.0000 \n 0 \n 2 \n S.C./PARIS 2079 \n NA \n C \n \n \n cheap \n 37.0042 \n 2 \n 0 \n Mallet, Mr. Albert \n male \n 31.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n NA \n C \n \n \n cheap \n 37.0042 \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n female \n 24.0000 \n 1 \n 1 \n S.C./PARIS 2079 \n NA \n C \n \n \n cheap \n 15.5792 \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n male \n NA \n 0 \n 0 \n SC/A.3 2861 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Matthews, Mr. William John \n male \n 30.0000 \n 0 \n 0 \n 28228 \n NA \n S \n \n \n cheap \n 16.0000 \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n male \n 40.0000 \n 0 \n 0 \n 239059 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n male \n 32.0000 \n 0 \n 0 \n 237216 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n McCrie, Mr. James Matthew \n male \n 30.0000 \n 0 \n 0 \n 233478 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n McKane, Mr. Peter David \n male \n 46.0000 \n 0 \n 0 \n 28403 \n NA \n S \n \n \n cheap \n 19.5000 \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n female \n 13.0000 \n 0 \n 1 \n 250644 \n NA \n S \n \n \n cheap \n 19.5000 \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n female \n 41.0000 \n 0 \n 1 \n 250644 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Mellors, Mr. William John \n male \n 19.0000 \n 0 \n 0 \n SW/PP 751 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Meyer, Mr. August \n male \n 39.0000 \n 0 \n 0 \n 248723 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Milling, Mr. Jacob Christian \n male \n 48.0000 \n 0 \n 0 \n 234360 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n male \n 70.0000 \n 0 \n 0 \n C.A. 24580 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Montvila, Rev. Juozas \n male \n 27.0000 \n 0 \n 0 \n 211536 \n NA \n S \n \n \n cheap \n 14.0000 \n 2 \n 0 \n Moraweck, Dr. Ernest \n male \n 54.0000 \n 0 \n 0 \n 29011 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n male \n 39.0000 \n 0 \n 0 \n 250655 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n male \n 16.0000 \n 0 \n 0 \n S.O./P.P. 3 \n NA \n S \n \n \n cheap \n 9.6875 \n 2 \n 0 \n Myles, Mr. Thomas Francis \n male \n 62.0000 \n 0 \n 0 \n 240276 \n NA \n Q \n \n \n cheap \n 30.0708 \n 2 \n 0 \n Nasser, Mr. Nicholas \n male \n 32.5000 \n 1 \n 0 \n 237736 \n NA \n C \n \n \n cheap \n 30.0708 \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n female \n 14.0000 \n 1 \n 0 \n 237736 \n NA \n C \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Navratil, Master. Edmond Roger \n male \n 2.0000 \n 1 \n 1 \n 230080 \n F2 \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Navratil, Master. Michel M \n male \n 3.0000 \n 1 \n 1 \n 230080 \n F2 \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n male \n 36.5000 \n 0 \n 2 \n 230080 \n F2 \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Nesson, Mr. Israel \n male \n 26.0000 \n 0 \n 0 \n 244368 \n F2 \n S \n \n \n cheap \n 36.7500 \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n male \n 19.0000 \n 1 \n 1 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Norman, Mr. Robert Douglas \n male \n 28.0000 \n 0 \n 0 \n 218629 \n NA \n S \n \n \n cheap \n 13.8625 \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n male \n 20.0000 \n 0 \n 0 \n SC/PARIS 2166 \n D38 \n C \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n female \n 29.0000 \n 0 \n 0 \n C.A. 29395 \n F33 \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Otter, Mr. Richard \n male \n 39.0000 \n 0 \n 0 \n 28213 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n male \n 22.0000 \n 0 \n 0 \n W./C. 14260 \n NA \n S \n \n \n cheap \n 13.8625 \n 2 \n 1 \n Padro y Manent, Mr. Julian \n male \n NA \n 0 \n 0 \n SC/PARIS 2146 \n NA \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Pain, Dr. Alfred \n male \n 23.0000 \n 0 \n 0 \n 244278 \n NA \n S \n \n \n cheap \n 13.8583 \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n male \n 29.0000 \n 0 \n 0 \n SC/PARIS 2147 \n NA \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Parker, Mr. Clifford Richard \n male \n 28.0000 \n 0 \n 0 \n SC 14888 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n male \n NA \n 0 \n 0 \n 239853 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n female \n 50.0000 \n 0 \n 1 \n 230433 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Pengelly, Mr. Frederick William \n male \n 19.0000 \n 0 \n 0 \n 28665 \n NA \n S \n \n \n cheap \n 15.0500 \n 2 \n 0 \n Pernot, Mr. Rene \n male \n NA \n 0 \n 0 \n SC/PARIS 2131 \n NA \n C \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n male \n 41.0000 \n 0 \n 0 \n 237393 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n female \n 21.0000 \n 0 \n 1 \n S.O./P.P. 2 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n female \n 19.0000 \n 0 \n 0 \n 250655 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Phillips, Mr. Escott Robert \n male \n 43.0000 \n 0 \n 1 \n S.O./P.P. 2 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n female \n 32.0000 \n 0 \n 0 \n 234604 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Ponesell, Mr. Martin \n male \n 34.0000 \n 0 \n 0 \n 250647 \n NA \n S \n \n \n cheap \n 12.7375 \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n male \n 30.0000 \n 0 \n 0 \n C.A. 34644 \n NA \n C \n \n \n cheap \n 15.0333 \n 2 \n 0 \n Pulbaum, Mr. Franz \n male \n 27.0000 \n 0 \n 0 \n SC/PARIS 2168 \n NA \n C \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Quick, Miss. Phyllis May \n female \n 2.0000 \n 1 \n 1 \n 26360 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Quick, Miss. Winifred Vera \n female \n 8.0000 \n 1 \n 1 \n 26360 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n female \n 33.0000 \n 0 \n 2 \n 26360 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Reeves, Mr. David \n male \n 36.0000 \n 0 \n 0 \n C.A. 17248 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Renouf, Mr. Peter Henry \n male \n 34.0000 \n 1 \n 0 \n 31027 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n female \n 30.0000 \n 3 \n 0 \n 31027 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n female \n 28.0000 \n 0 \n 0 \n 230434 \n NA \n S \n \n \n cheap \n 15.0458 \n 2 \n 0 \n Richard, Mr. Emile \n male \n 23.0000 \n 0 \n 0 \n SC/PARIS 2133 \n NA \n C \n \n \n cheap \n 18.7500 \n 2 \n 1 \n Richards, Master. George Sibley \n male \n 0.8333 \n 1 \n 1 \n 29106 \n NA \n S \n \n \n cheap \n 18.7500 \n 2 \n 1 \n Richards, Master. William Rowe \n male \n 3.0000 \n 1 \n 1 \n 29106 \n NA \n S \n \n \n cheap \n 18.7500 \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n female \n 24.0000 \n 2 \n 3 \n 29106 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Ridsdale, Miss. Lucy \n female \n 50.0000 \n 0 \n 0 \n W./C. 14258 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n male \n 19.0000 \n 0 \n 0 \n 28004 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Rugg, Miss. Emily \n female \n 21.0000 \n 0 \n 0 \n C.A. 31026 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Schmidt, Mr. August \n male \n 26.0000 \n 0 \n 0 \n 248659 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n male \n 25.0000 \n 0 \n 0 \n 244361 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Sharp, Mr. Percival James R \n male \n 27.0000 \n 0 \n 0 \n 244358 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n female \n 25.0000 \n 0 \n 1 \n 230433 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n female \n 18.0000 \n 0 \n 2 \n 250652 \n NA \n S \n \n \n cheap \n 36.7500 \n 2 \n 1 \n Sincock, Miss. Maude \n female \n 20.0000 \n 0 \n 0 \n C.A. 33112 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Sinkkonen, Miss. Anna \n female \n 30.0000 \n 0 \n 0 \n 250648 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n male \n 59.0000 \n 0 \n 0 \n 237442 \n NA \n S \n \n \n cheap \n 12.3500 \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n female \n 30.0000 \n 0 \n 0 \n 234818 \n NA \n Q \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Slemen, Mr. Richard James \n male \n 35.0000 \n 0 \n 0 \n 28206 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Smith, Miss. Marion Elsie \n female \n 40.0000 \n 0 \n 0 \n 31418 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n male \n 25.0000 \n 0 \n 0 \n C.A. 29178 \n NA \n S \n \n \n cheap \n 15.0458 \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n male \n 41.0000 \n 0 \n 0 \n 237734 \n NA \n C \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n male \n 25.0000 \n 0 \n 0 \n F.C.C. 13540 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Swane, Mr. George \n male \n 18.5000 \n 0 \n 0 \n 248734 \n F \n S \n \n \n cheap \n 65.0000 \n 2 \n 0 \n Sweet, Mr. George Frederick \n male \n 14.0000 \n 0 \n 0 \n 220845 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Toomey, Miss. Ellen \n female \n 50.0000 \n 0 \n 0 \n F.C.C. 13531 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n male \n 23.0000 \n 0 \n 0 \n 233639 \n NA \n S \n \n \n cheap \n 12.6500 \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n female \n 28.0000 \n 0 \n 0 \n 240929 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n female \n 27.0000 \n 0 \n 0 \n 34218 \n E101 \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Turpin, Mr. William John Robert \n male \n 29.0000 \n 1 \n 0 \n 11668 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n female \n 27.0000 \n 1 \n 0 \n 11668 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Veal, Mr. James \n male \n 40.0000 \n 0 \n 0 \n 28221 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Walcroft, Miss. Nellie \n female \n 31.0000 \n 0 \n 0 \n F.C.C. 13528 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 0 \n Ware, Mr. John James \n male \n 30.0000 \n 1 \n 0 \n CA 31352 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Ware, Mr. William Jeffery \n male \n 23.0000 \n 1 \n 0 \n 28666 \n NA \n S \n \n \n cheap \n 21.0000 \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n female \n 31.0000 \n 0 \n 0 \n CA 31352 \n NA \n S \n \n \n cheap \n 0.0000 \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n male \n NA \n 0 \n 0 \n 239856 \n NA \n S \n \n \n cheap \n 15.7500 \n 2 \n 1 \n Watt, Miss. Bertha J \n female \n 12.0000 \n 0 \n 0 \n C.A. 33595 \n NA \n S \n \n \n cheap \n 15.7500 \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n female \n 40.0000 \n 0 \n 0 \n C.A. 33595 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Webber, Miss. Susan \n female \n 32.5000 \n 0 \n 0 \n 27267 \n E101 \n S \n \n \n cheap \n 26.0000 \n 2 \n 0 \n Weisz, Mr. Leopold \n male \n 27.0000 \n 1 \n 0 \n 228414 \n NA \n S \n \n \n cheap \n 26.0000 \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n female \n 29.0000 \n 1 \n 0 \n 228414 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Wells, Master. Ralph Lester \n male \n 2.0000 \n 1 \n 1 \n 29103 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Wells, Miss. Joan \n female \n 4.0000 \n 1 \n 1 \n 29103 \n NA \n S \n \n \n cheap \n 23.0000 \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n female \n 29.0000 \n 0 \n 2 \n 29103 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 1 \n West, Miss. Barbara J \n female \n 0.9167 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 1 \n West, Miss. Constance Mirium \n female \n 5.0000 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 0 \n West, Mr. Edwy Arthur \n male \n 36.0000 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 27.7500 \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n female \n 33.0000 \n 1 \n 2 \n C.A. 34651 \n NA \n S \n \n \n cheap \n 10.5000 \n 2 \n 0 \n Wheadon, Mr. Edward H \n male \n 66.0000 \n 0 \n 0 \n C.A. 24579 \n NA \n S \n \n \n cheap \n 12.8750 \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n male \n NA \n 0 \n 0 \n SC/PARIS 2159 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Wilhelms, Mr. Charles \n male \n 31.0000 \n 0 \n 0 \n 244270 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 1 \n Williams, Mr. Charles Eugene \n male \n NA \n 0 \n 0 \n 244373 \n NA \n S \n \n \n cheap \n 13.5000 \n 2 \n 1 \n Wright, Miss. Marion \n female \n 26.0000 \n 0 \n 0 \n 220844 \n NA \n S \n \n \n cheap \n 13.0000 \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n female \n 24.0000 \n 0 \n 0 \n 248747 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Abbing, Mr. Anthony \n male \n 42.0000 \n 0 \n 0 \n C.A. 5547 \n NA \n S \n \n \n cheap \n 20.2500 \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n male \n 13.0000 \n 0 \n 2 \n C.A. 2673 \n NA \n S \n \n \n cheap \n 20.2500 \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n male \n 16.0000 \n 1 \n 1 \n C.A. 2673 \n NA \n S \n \n \n cheap \n 20.2500 \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n female \n 35.0000 \n 1 \n 1 \n C.A. 2673 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n female \n 16.0000 \n 0 \n 0 \n 348125 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n male \n 25.0000 \n 0 \n 0 \n 348122 \n F G63 \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101284 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n female \n 18.0000 \n 0 \n 0 \n 2657 \n NA \n C \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n male \n 30.0000 \n 0 \n 0 \n C 7076 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Adams, Mr. John \n male \n 26.0000 \n 0 \n 0 \n 341826 \n NA \n S \n \n \n cheap \n 9.4750 \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n female \n 40.0000 \n 1 \n 0 \n 7546 \n NA \n S \n \n \n cheap \n 9.3500 \n 3 \n 1 \n Aks, Master. Philip Frank \n male \n 0.8333 \n 0 \n 1 \n 392091 \n NA \n S \n \n \n cheap \n 9.3500 \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n female \n 18.0000 \n 0 \n 1 \n 392091 \n NA \n S \n \n \n cheap \n 18.7875 \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n male \n 26.0000 \n 0 \n 0 \n 2699 \n NA \n C \n \n \n cheap \n 7.8875 \n 3 \n 0 \n Alexander, Mr. William \n male \n 26.0000 \n 0 \n 0 \n 3474 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n male \n 20.0000 \n 0 \n 0 \n SOTON/O2 3101287 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Ali, Mr. Ahmed \n male \n 24.0000 \n 0 \n 0 \n SOTON/O.Q. 3101311 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Ali, Mr. William \n male \n 25.0000 \n 0 \n 0 \n SOTON/O.Q. 3101312 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Allen, Mr. William Henry \n male \n 35.0000 \n 0 \n 0 \n 373450 \n NA \n S \n \n \n cheap \n 8.3000 \n 3 \n 0 \n Allum, Mr. Owen George \n male \n 18.0000 \n 0 \n 0 \n 2223 \n NA \n S \n \n \n cheap \n 22.5250 \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n male \n 32.0000 \n 0 \n 0 \n C 4001 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n female \n 19.0000 \n 1 \n 0 \n 350046 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n male \n 4.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n female \n 6.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n female \n 2.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n female \n 17.0000 \n 4 \n 2 \n 3101281 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n female \n 38.0000 \n 4 \n 2 \n 347091 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n female \n 9.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n female \n 11.0000 \n 4 \n 2 \n 347082 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Mr. Anders Johan \n male \n 39.0000 \n 1 \n 5 \n 347082 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n male \n 27.0000 \n 0 \n 0 \n 350043 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n male \n 26.0000 \n 0 \n 0 \n 347075 \n NA \n S \n \n \n cheap \n 31.2750 \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n female \n 39.0000 \n 1 \n 5 \n 347082 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n male \n 20.0000 \n 0 \n 0 \n 347466 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Angheloff, Mr. Minko \n male \n 26.0000 \n 0 \n 0 \n 349202 \n NA \n S \n \n \n cheap \n 17.8000 \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n male \n 25.0000 \n 1 \n 0 \n 349237 \n NA \n S \n \n \n cheap \n 17.8000 \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n female \n 18.0000 \n 1 \n 0 \n 349237 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n male \n 24.0000 \n 0 \n 0 \n 349911 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Asim, Mr. Adola \n male \n 35.0000 \n 0 \n 0 \n SOTON/O.Q. 3101310 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Master. Carl Edgar \n male \n 5.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n male \n 9.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n male \n 3.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Master. Filip Oscar \n male \n 13.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n female \n 5.0000 \n 4 \n 2 \n 347077 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n male \n 40.0000 \n 1 \n 5 \n 347077 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Asplund, Mr. Johan Charles \n male \n 23.0000 \n 0 \n 0 \n 350054 \n NA \n S \n \n \n cheap \n 31.3875 \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n female \n 38.0000 \n 1 \n 5 \n 347077 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n female \n 45.0000 \n 0 \n 0 \n 2696 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Assaf, Mr. Gerios \n male \n 21.0000 \n 0 \n 0 \n 2692 \n NA \n C \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Assam, Mr. Ali \n male \n 23.0000 \n 0 \n 0 \n SOTON/O.Q. 3101309 \n NA \n S \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Attalah, Miss. Malake \n female \n 17.0000 \n 0 \n 0 \n 2627 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Attalah, Mr. Sleiman \n male \n 30.0000 \n 0 \n 0 \n 2694 \n NA \n C \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Augustsson, Mr. Albert \n male \n 23.0000 \n 0 \n 0 \n 347468 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Ayoub, Miss. Banoura \n female \n 13.0000 \n 0 \n 0 \n 2687 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Baccos, Mr. Raffull \n male \n 20.0000 \n 0 \n 0 \n 2679 \n NA \n C \n \n \n cheap \n 15.8500 \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n male \n 32.0000 \n 1 \n 0 \n 3101278 \n NA \n S \n \n \n cheap \n 15.8500 \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n female \n 33.0000 \n 3 \n 0 \n 3101278 \n NA \n S \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Miss. Eugenie \n female \n 0.7500 \n 2 \n 1 \n 2666 \n NA \n C \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n female \n 0.7500 \n 2 \n 1 \n 2666 \n NA \n C \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n female \n 5.0000 \n 2 \n 1 \n 2666 \n NA \n C \n \n \n cheap \n 19.2583 \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n female \n 24.0000 \n 0 \n 3 \n 2666 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Badman, Miss. Emily Louisa \n female \n 18.0000 \n 0 \n 0 \n A/4 31416 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Badt, Mr. Mohamed \n male \n 40.0000 \n 0 \n 0 \n 2623 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Balkic, Mr. Cerin \n male \n 26.0000 \n 0 \n 0 \n 349248 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Barah, Mr. Hanna Assi \n male \n 20.0000 \n 0 \n 0 \n 2663 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Barbara, Miss. Saiide \n female \n 18.0000 \n 0 \n 1 \n 2691 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n female \n 45.0000 \n 0 \n 1 \n 2691 \n NA \n C \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Barry, Miss. Julia \n female \n 27.0000 \n 0 \n 0 \n 330844 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Barton, Mr. David John \n male \n 22.0000 \n 0 \n 0 \n 324669 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Beavan, Mr. William Thomas \n male \n 19.0000 \n 0 \n 0 \n 323951 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n male \n 26.0000 \n 0 \n 0 \n 347068 \n NA \n S \n \n \n cheap \n 9.3500 \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n male \n 22.0000 \n 0 \n 0 \n PP 4348 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Betros, Master. Seman \n male \n NA \n 0 \n 0 \n 2622 \n NA \n C \n \n \n cheap \n 4.0125 \n 3 \n 0 \n Betros, Mr. Tannous \n male \n 20.0000 \n 0 \n 0 \n 2648 \n NA \n C \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Bing, Mr. Lee \n male \n 32.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n male \n 21.0000 \n 0 \n 0 \n 312992 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n male \n 18.0000 \n 0 \n 0 \n 347090 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n male \n 26.0000 \n 0 \n 0 \n 349224 \n NA \n S \n \n \n cheap \n 15.2458 \n 3 \n 0 \n Boulos, Master. Akar \n male \n 6.0000 \n 1 \n 1 \n 2678 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 0 \n Boulos, Miss. Nourelain \n female \n 9.0000 \n 1 \n 1 \n 2678 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Boulos, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2664 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n female \n NA \n 0 \n 2 \n 2678 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Bourke, Miss. Mary \n female \n NA \n 0 \n 2 \n 364848 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Bourke, Mr. John \n male \n 40.0000 \n 1 \n 1 \n 364849 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n female \n 32.0000 \n 1 \n 1 \n 364849 \n NA \n Q \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n male \n 21.0000 \n 0 \n 0 \n 54636 \n NA \n S \n \n \n cheap \n 7.7250 \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n female \n 22.0000 \n 0 \n 0 \n 334914 \n NA \n Q \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n female \n 20.0000 \n 0 \n 0 \n 347471 \n NA \n S \n \n \n cheap \n 7.0458 \n 3 \n 0 \n Braund, Mr. Lewis Richard \n male \n 29.0000 \n 1 \n 0 \n 3460 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Braund, Mr. Owen Harris \n male \n 22.0000 \n 1 \n 0 \n A/5 21171 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n male \n 22.0000 \n 0 \n 0 \n 350045 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n male \n 35.0000 \n 0 \n 0 \n 364512 \n NA \n S \n \n \n cheap \n 7.2833 \n 3 \n 0 \n Buckley, Miss. Katherine \n female \n 18.5000 \n 0 \n 0 \n 329944 \n NA \n Q \n \n \n cheap \n 7.8208 \n 3 \n 1 \n Buckley, Mr. Daniel \n male \n 21.0000 \n 0 \n 0 \n 330920 \n NA \n Q \n \n \n cheap \n 6.7500 \n 3 \n 0 \n Burke, Mr. Jeremiah \n male \n 19.0000 \n 0 \n 0 \n 365222 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Burns, Miss. Mary Delia \n female \n 18.0000 \n 0 \n 0 \n 330963 \n NA \n Q \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Miss. Manda \n female \n 21.0000 \n 0 \n 0 \n 315087 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Miss. Marija \n female \n 30.0000 \n 0 \n 0 \n 315084 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Mr. Jego Grga \n male \n 18.0000 \n 0 \n 0 \n 315091 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Cacic, Mr. Luka \n male \n 38.0000 \n 0 \n 0 \n 315089 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Calic, Mr. Jovo \n male \n 17.0000 \n 0 \n 0 \n 315093 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Calic, Mr. Petar \n male \n 17.0000 \n 0 \n 0 \n 315086 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Canavan, Miss. Mary \n female \n 21.0000 \n 0 \n 0 \n 364846 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Canavan, Mr. Patrick \n male \n 21.0000 \n 0 \n 0 \n 364858 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Cann, Mr. Ernest Charles \n male \n 21.0000 \n 0 \n 0 \n A./5. 2152 \n NA \n S \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Caram, Mr. Joseph \n male \n NA \n 1 \n 0 \n 2689 \n NA \n C \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n female \n NA \n 1 \n 0 \n 2689 \n NA \n C \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n male \n 28.0000 \n 0 \n 0 \n 350042 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n male \n 24.0000 \n 0 \n 0 \n 350409 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n female \n 16.0000 \n 0 \n 0 \n 367231 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Carr, Miss. Jeannie \n female \n 37.0000 \n 0 \n 0 \n 368364 \n NA \n Q \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Carver, Mr. Alfred John \n male \n 28.0000 \n 0 \n 0 \n 392095 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Celotti, Mr. Francesco \n male \n 24.0000 \n 0 \n 0 \n 343275 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 0 \n Charters, Mr. David \n male \n 21.0000 \n 0 \n 0 \n A/5. 13032 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Chip, Mr. Chang \n male \n 32.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Christmann, Mr. Emil \n male \n 29.0000 \n 0 \n 0 \n 343276 \n NA \n S \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n male \n 26.0000 \n 1 \n 0 \n 2680 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n male \n 18.0000 \n 1 \n 0 \n 2680 \n NA \n C \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n male \n 20.0000 \n 0 \n 0 \n SOTON/O.Q. 3101307 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n male \n 18.0000 \n 0 \n 0 \n A/5 3540 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Colbert, Mr. Patrick \n male \n 24.0000 \n 0 \n 0 \n 371109 \n NA \n Q \n \n \n cheap \n 7.4958 \n 3 \n 0 \n Coleff, Mr. Peju \n male \n 36.0000 \n 0 \n 0 \n 349210 \n NA \n S \n \n \n cheap \n 7.4958 \n 3 \n 0 \n Coleff, Mr. Satio \n male \n 24.0000 \n 0 \n 0 \n 349209 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n male \n 31.0000 \n 0 \n 0 \n 21332 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Connaghton, Mr. Michael \n male \n 31.0000 \n 0 \n 0 \n 335097 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Connolly, Miss. Kate \n female \n 22.0000 \n 0 \n 0 \n 370373 \n NA \n Q \n \n \n cheap \n 7.6292 \n 3 \n 0 \n Connolly, Miss. Kate \n female \n 30.0000 \n 0 \n 0 \n 330972 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Connors, Mr. Patrick \n male \n 70.5000 \n 0 \n 0 \n 370369 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Cook, Mr. Jacob \n male \n 43.0000 \n 0 \n 0 \n A/5 3536 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Cor, Mr. Bartol \n male \n 35.0000 \n 0 \n 0 \n 349230 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Cor, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 349229 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Cor, Mr. Liudevit \n male \n 19.0000 \n 0 \n 0 \n 349231 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Corn, Mr. Harry \n male \n 30.0000 \n 0 \n 0 \n SOTON/OQ 392090 \n NA \n S \n \n \n cheap \n 15.9000 \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n male \n 9.0000 \n 1 \n 1 \n C.A. 37671 \n NA \n S \n \n \n cheap \n 15.9000 \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n male \n 3.0000 \n 1 \n 1 \n C.A. 37671 \n NA \n S \n \n \n cheap \n 15.9000 \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n female \n 36.0000 \n 0 \n 2 \n C.A. 37671 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Coxon, Mr. Daniel \n male \n 59.0000 \n 0 \n 0 \n 364500 \n NA \n S \n \n \n cheap \n 8.1583 \n 3 \n 0 \n Crease, Mr. Ernest James \n male \n 19.0000 \n 0 \n 0 \n S.P. 3464 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 1 \n Cribb, Miss. Laura Alice \n female \n 17.0000 \n 0 \n 1 \n 371362 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Cribb, Mr. John Hatfield \n male \n 44.0000 \n 0 \n 1 \n 371362 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Culumovic, Mr. Jeso \n male \n 17.0000 \n 0 \n 0 \n 315090 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Daher, Mr. Shedid \n male \n 22.5000 \n 0 \n 0 \n 2698 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n male \n 45.0000 \n 0 \n 0 \n 7598 \n NA \n S \n \n \n cheap \n 10.5167 \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n female \n 22.0000 \n 0 \n 0 \n 7552 \n NA \n S \n \n \n cheap \n 10.1708 \n 3 \n 0 \n Dakic, Mr. Branko \n male \n 19.0000 \n 0 \n 0 \n 349228 \n NA \n S \n \n \n cheap \n 6.9500 \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n female \n 30.0000 \n 0 \n 0 \n 382650 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n male \n 29.0000 \n 0 \n 0 \n 382651 \n NA \n Q \n \n \n cheap \n 14.4000 \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n male \n 0.3333 \n 0 \n 2 \n 347080 \n NA \n S \n \n \n cheap \n 14.4000 \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n male \n 34.0000 \n 1 \n 1 \n 347080 \n NA \n S \n \n \n cheap \n 14.4000 \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n female \n 28.0000 \n 1 \n 1 \n 347080 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Danoff, Mr. Yoto \n male \n 27.0000 \n 0 \n 0 \n 349219 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n male \n 25.0000 \n 0 \n 0 \n 349203 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Davies, Mr. Alfred J \n male \n 24.0000 \n 2 \n 0 \n A/4 48871 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Davies, Mr. Evan \n male \n 22.0000 \n 0 \n 0 \n SC/A4 23568 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Davies, Mr. John Samuel \n male \n 21.0000 \n 2 \n 0 \n A/4 48871 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Davies, Mr. Joseph \n male \n 17.0000 \n 2 \n 0 \n A/4 48873 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Davison, Mr. Thomas Henry \n male \n NA \n 1 \n 0 \n 386525 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n female \n NA \n 1 \n 0 \n 386525 \n NA \n S \n \n \n cheap \n 17.4000 \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n male \n 36.5000 \n 1 \n 0 \n 345572 \n NA \n S \n \n \n cheap \n 17.4000 \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n female \n 36.0000 \n 1 \n 0 \n 345572 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 1 \n de Mulder, Mr. Theodore \n male \n 30.0000 \n 0 \n 0 \n 345774 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n male \n 16.0000 \n 0 \n 0 \n 345778 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 1 \n Dean, Master. Bertram Vere \n male \n 1.0000 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n female \n 0.1667 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 0 \n Dean, Mr. Bertram Frank \n male \n 26.0000 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 20.5750 \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n female \n 33.0000 \n 1 \n 2 \n C.A. 2315 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Delalic, Mr. Redjo \n male \n 25.0000 \n 0 \n 0 \n 349250 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Demetri, Mr. Marinko \n male \n NA \n 0 \n 0 \n 349238 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Denkoff, Mr. Mitto \n male \n NA \n 0 \n 0 \n 349225 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Dennis, Mr. Samuel \n male \n 22.0000 \n 0 \n 0 \n A/5 21172 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Dennis, Mr. William \n male \n 36.0000 \n 0 \n 0 \n A/5 21175 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n female \n 19.0000 \n 0 \n 0 \n 330958 \n NA \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Dika, Mr. Mirko \n male \n 17.0000 \n 0 \n 0 \n 349232 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Dimic, Mr. Jovan \n male \n 42.0000 \n 0 \n 0 \n 315088 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n male \n 43.0000 \n 0 \n 0 \n 349226 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Doharr, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2686 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Dooley, Mr. Patrick \n male \n 32.0000 \n 0 \n 0 \n 370376 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n male \n 19.0000 \n 0 \n 0 \n A/5. 10482 \n NA \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n female \n 30.0000 \n 0 \n 0 \n 364516 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Doyle, Miss. Elizabeth \n female \n 24.0000 \n 0 \n 0 \n 368702 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Drapkin, Miss. Jennie \n female \n 23.0000 \n 0 \n 0 \n SOTON/OQ 392083 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Drazenoic, Mr. Jozef \n male \n 33.0000 \n 0 \n 0 \n 349241 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Duane, Mr. Frank \n male \n 65.0000 \n 0 \n 0 \n 336439 \n NA \n Q \n \n \n cheap \n 7.5500 \n 3 \n 1 \n Duquemin, Mr. Joseph \n male \n 24.0000 \n 0 \n 0 \n S.O./P.P. 752 \n NA \n S \n \n \n cheap \n 13.9000 \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n male \n 23.0000 \n 1 \n 0 \n 347072 \n NA \n S \n \n \n cheap \n 13.9000 \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n female \n 22.0000 \n 1 \n 0 \n 347072 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n male \n 18.0000 \n 0 \n 0 \n 349912 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Eklund, Mr. Hans Linus \n male \n 16.0000 \n 0 \n 0 \n 347074 \n NA \n S \n \n \n cheap \n 6.9750 \n 3 \n 0 \n Ekstrom, Mr. Johan \n male \n 45.0000 \n 0 \n 0 \n 347061 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Elias, Mr. Dibo \n male \n NA \n 0 \n 0 \n 2674 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Elias, Mr. Joseph \n male \n 39.0000 \n 0 \n 2 \n 2675 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Elias, Mr. Joseph Jr \n male \n 17.0000 \n 1 \n 1 \n 2690 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Elias, Mr. Tannous \n male \n 15.0000 \n 1 \n 1 \n 2695 \n NA \n C \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Elsbury, Mr. William James \n male \n 47.0000 \n 0 \n 0 \n A/5 3902 \n NA \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n female \n 5.0000 \n 0 \n 0 \n 364516 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Emir, Mr. Farred Chehab \n male \n NA \n 0 \n 0 \n 2631 \n NA \n C \n \n \n cheap \n 15.1000 \n 3 \n 0 \n Everett, Mr. Thomas James \n male \n 40.5000 \n 0 \n 0 \n C.A. 6212 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Farrell, Mr. James \n male \n 40.5000 \n 0 \n 0 \n 367232 \n NA \n Q \n \n \n cheap \n 7.0500 \n 3 \n 1 \n Finoli, Mr. Luigi \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101308 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n male \n 18.0000 \n 0 \n 0 \n 350036 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Fleming, Miss. Honora \n female \n NA \n 0 \n 0 \n 364859 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Flynn, Mr. James \n male \n NA \n 0 \n 0 \n 364851 \n NA \n Q \n \n \n cheap \n 6.9500 \n 3 \n 0 \n Flynn, Mr. John \n male \n NA \n 0 \n 0 \n 368323 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Foley, Mr. Joseph \n male \n 26.0000 \n 0 \n 0 \n 330910 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Foley, Mr. William \n male \n NA \n 0 \n 0 \n 365235 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Foo, Mr. Choong \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n female \n 21.0000 \n 2 \n 2 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n female \n 9.0000 \n 2 \n 2 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Ford, Mr. Arthur \n male \n NA \n 0 \n 0 \n A/5 1478 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Mr. Edward Watson \n male \n 18.0000 \n 2 \n 2 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Mr. William Neal \n male \n 16.0000 \n 1 \n 3 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 34.3750 \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n female \n 48.0000 \n 1 \n 3 \n W./C. 6608 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Fox, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368573 \n NA \n Q \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101314 \n NA \n S \n \n \n cheap \n 7.7417 \n 3 \n 0 \n Gallagher, Mr. Martin \n male \n 25.0000 \n 0 \n 0 \n 36864 \n NA \n Q \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Garfirth, Mr. John \n male \n NA \n 0 \n 0 \n 358585 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n male \n NA \n 0 \n 0 \n 349254 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Gilinski, Mr. Eliezer \n male \n 22.0000 \n 0 \n 0 \n 14973 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n female \n 16.0000 \n 0 \n 0 \n 35851 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n female \n NA \n 0 \n 0 \n 335677 \n NA \n Q \n \n \n cheap \n 20.5250 \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n male \n 9.0000 \n 0 \n 2 \n 363291 \n NA \n S \n \n \n cheap \n 20.5250 \n 3 \n 0 \n Goldsmith, Mr. Frank John \n male \n 33.0000 \n 1 \n 1 \n 363291 \n NA \n S \n \n \n cheap \n 7.8500 \n 3 \n 0 \n Goldsmith, Mr. Nathan \n male \n 41.0000 \n 0 \n 0 \n SOTON/O.Q. 3101263 \n NA \n S \n \n \n cheap \n 20.5250 \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n female \n 31.0000 \n 1 \n 1 \n 363291 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n male \n 38.0000 \n 0 \n 0 \n SOTON/O.Q. 3101306 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Master. Harold Victor \n male \n 9.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n male \n 1.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Master. William Frederick \n male \n 11.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n female \n 10.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n female \n 16.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n male \n 14.0000 \n 5 \n 2 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n male \n 40.0000 \n 1 \n 6 \n CA 2144 \n NA \n S \n \n \n cheap \n 46.9000 \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n female \n 43.0000 \n 1 \n 6 \n CA 2144 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Green, Mr. George Henry \n male \n 51.0000 \n 0 \n 0 \n 21440 \n NA \n S \n \n \n cheap \n 8.3625 \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n male \n 32.0000 \n 0 \n 0 \n 8471 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Guest, Mr. Robert \n male \n NA \n 0 \n 0 \n 376563 \n NA \n S \n \n \n cheap \n 9.8458 \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n male \n 20.0000 \n 0 \n 0 \n 7534 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n male \n 37.0000 \n 2 \n 0 \n 3101276 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n male \n 28.0000 \n 2 \n 0 \n 3101277 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n male \n 19.0000 \n 0 \n 0 \n 347069 \n NA \n S \n \n \n cheap \n 8.8500 \n 3 \n 0 \n Haas, Miss. Aloisia \n female \n 24.0000 \n 0 \n 0 \n 349236 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 0 \n Hagardon, Miss. Kate \n female \n 17.0000 \n 0 \n 0 \n AQ/3. 30631 \n NA \n Q \n \n \n cheap \n 19.9667 \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n male \n NA \n 1 \n 0 \n 65303 \n NA \n S \n \n \n cheap \n 19.9667 \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n male \n NA \n 1 \n 0 \n 65304 \n NA \n S \n \n \n cheap \n 15.8500 \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n male \n 28.0000 \n 1 \n 0 \n STON/O2. 3101279 \n NA \n S \n \n \n cheap \n 15.8500 \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n female \n 24.0000 \n 1 \n 0 \n STON/O2. 3101279 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Hampe, Mr. Leon \n male \n 20.0000 \n 0 \n 0 \n 345769 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Hanna, Mr. Mansour \n male \n 23.5000 \n 0 \n 0 \n 2693 \n NA \n C \n \n \n cheap \n 14.1083 \n 3 \n 0 \n Hansen, Mr. Claus Peter \n male \n 41.0000 \n 2 \n 0 \n 350026 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n male \n 26.0000 \n 1 \n 0 \n 350025 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n male \n 21.0000 \n 0 \n 0 \n 350029 \n NA \n S \n \n \n cheap \n 14.1083 \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n female \n 45.0000 \n 1 \n 0 \n 350026 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n female \n NA \n 0 \n 0 \n W./C. 6609 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n male \n 25.0000 \n 0 \n 0 \n 374887 \n NA \n S \n \n \n cheap \n 6.8583 \n 3 \n 0 \n Hart, Mr. Henry \n male \n NA \n 0 \n 0 \n 394140 \n NA \n Q \n \n \n cheap \n 18.7875 \n 3 \n 0 \n Hassan, Mr. Houssein G N \n male \n 11.0000 \n 0 \n 0 \n 2699 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n female \n NA \n 0 \n 0 \n 370375 \n NA \n Q \n \n \n cheap \n 6.9750 \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n male \n 27.0000 \n 0 \n 0 \n 347089 \n NA \n S \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Hee, Mr. Ling \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 6.7500 \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n female \n 18.0000 \n 0 \n 0 \n 365226 \n NA \n Q \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Heikkinen, Miss. Laina \n female \n 26.0000 \n 0 \n 0 \n STON/O2. 3101282 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n female \n 23.0000 \n 0 \n 0 \n STON/O2. 3101290 \n NA \n S \n \n \n cheap \n 8.9625 \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n female \n 22.0000 \n 0 \n 0 \n 7548 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n male \n 28.0000 \n 0 \n 0 \n 349243 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n female \n 28.0000 \n 0 \n 0 \n 347086 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Henry, Miss. Delia \n female \n NA \n 0 \n 0 \n 382649 \n NA \n Q \n \n \n cheap \n 12.2875 \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n female \n 2.0000 \n 0 \n 1 \n 3101298 \n NA \n S \n \n \n cheap \n 12.2875 \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n female \n 22.0000 \n 1 \n 1 \n 3101298 \n NA \n S \n \n \n cheap \n 6.4500 \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n male \n 43.0000 \n 0 \n 0 \n C 7075 \n NA \n S \n \n \n cheap \n 22.5250 \n 3 \n 0 \n Holthen, Mr. Johan Martin \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Honkanen, Miss. Eliina \n female \n 27.0000 \n 0 \n 0 \n STON/O2. 3101283 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Horgan, Mr. John \n male \n NA \n 0 \n 0 \n 370377 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Howard, Miss. May Elizabeth \n female \n NA \n 0 \n 0 \n A. 2. 39186 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n male \n 42.0000 \n 0 \n 0 \n 348121 \n F G63 \n S \n \n \n cheap \n 7.8875 \n 3 \n 1 \n Hyman, Mr. Abraham \n male \n NA \n 0 \n 0 \n 3470 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n male \n 30.0000 \n 0 \n 0 \n 2685 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Ilieff, Mr. Ylio \n male \n NA \n 0 \n 0 \n 349220 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n female \n 27.0000 \n 1 \n 0 \n STON/O2. 3101270 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n female \n 25.0000 \n 1 \n 0 \n STON/O2. 3101271 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Ivanoff, Mr. Kanio \n male \n NA \n 0 \n 0 \n 349201 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 1 \n Jalsevac, Mr. Ivan \n male \n 29.0000 \n 0 \n 0 \n 349240 \n NA \n C \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Jansson, Mr. Carl Olof \n male \n 21.0000 \n 0 \n 0 \n 350034 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Jardin, Mr. Jose Neto \n male \n NA \n 0 \n 0 \n SOTON/O.Q. 3101305 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Jensen, Mr. Hans Peder \n male \n 20.0000 \n 0 \n 0 \n 350050 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Jensen, Mr. Niels Peder \n male \n 48.0000 \n 0 \n 0 \n 350047 \n NA \n S \n \n \n cheap \n 7.0542 \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n male \n 17.0000 \n 1 \n 0 \n 350048 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Jermyn, Miss. Annie \n female \n NA \n 0 \n 0 \n 14313 \n NA \n Q \n \n \n cheap \n 8.1125 \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n male \n NA \n 0 \n 0 \n 65306 \n NA \n S \n \n \n cheap \n 6.4958 \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n male \n 34.0000 \n 0 \n 0 \n 3101264 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n male \n 26.0000 \n 0 \n 0 \n 347070 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Johansson, Mr. Erik \n male \n 22.0000 \n 0 \n 0 \n 350052 \n NA \n S \n \n \n cheap \n 8.6542 \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n male \n 33.0000 \n 0 \n 0 \n 7540 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Johansson, Mr. Karl Johan \n male \n 31.0000 \n 0 \n 0 \n 347063 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Johansson, Mr. Nils \n male \n 29.0000 \n 0 \n 0 \n 347467 \n NA \n S \n \n \n cheap \n 11.1333 \n 3 \n 1 \n Johnson, Master. Harold Theodor \n male \n 4.0000 \n 1 \n 1 \n 347742 \n NA \n S \n \n \n cheap \n 11.1333 \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n female \n 1.0000 \n 1 \n 1 \n 347742 \n NA \n S \n \n \n cheap \n 0.0000 \n 3 \n 0 \n Johnson, Mr. Alfred \n male \n 49.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n male \n 33.0000 \n 0 \n 0 \n 347062 \n NA \n S \n \n \n cheap \n 0.0000 \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n male \n 19.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 11.1333 \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n female \n 27.0000 \n 0 \n 2 \n 347742 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n male \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n female \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Mr. Andrew G \n male \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 23.4500 \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n female \n NA \n 1 \n 2 \n W./C. 6607 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Jonkoff, Mr. Lalio \n male \n 23.0000 \n 0 \n 0 \n 349204 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Jonsson, Mr. Carl \n male \n 32.0000 \n 0 \n 0 \n 350417 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n male \n 27.0000 \n 0 \n 0 \n 350408 \n NA \n S \n \n \n cheap \n 9.8250 \n 3 \n 0 \n Jussila, Miss. Katriina \n female \n 20.0000 \n 1 \n 0 \n 4136 \n NA \n S \n \n \n cheap \n 9.8250 \n 3 \n 0 \n Jussila, Miss. Mari Aina \n female \n 21.0000 \n 1 \n 0 \n 4137 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Jussila, Mr. Eiriik \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101286 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n male \n 17.0000 \n 0 \n 0 \n STON/O 2. 3101274 \n NA \n S \n \n \n cheap \n 8.4333 \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n male \n 21.0000 \n 0 \n 0 \n 8475 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Karaic, Mr. Milan \n male \n 30.0000 \n 0 \n 0 \n 349246 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n male \n 21.0000 \n 0 \n 0 \n 350053 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n male \n 33.0000 \n 0 \n 0 \n 347465 \n NA \n S \n \n \n cheap \n 7.5208 \n 3 \n 0 \n Karlsson, Mr. Nils August \n male \n 22.0000 \n 0 \n 0 \n 350060 \n NA \n S \n \n \n cheap \n 13.4167 \n 3 \n 1 \n Karun, Miss. Manca \n female \n 4.0000 \n 0 \n 1 \n 349256 \n NA \n C \n \n \n cheap \n 13.4167 \n 3 \n 1 \n Karun, Mr. Franz \n male \n 39.0000 \n 0 \n 1 \n 349256 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Kassem, Mr. Fared \n male \n NA \n 0 \n 0 \n 2700 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n male \n 18.5000 \n 0 \n 0 \n 2682 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n male \n NA \n 0 \n 0 \n 12460 \n NA \n Q \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Keefe, Mr. Arthur \n male \n NA \n 0 \n 0 \n 323592 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n female \n NA \n 0 \n 0 \n 9234 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Kelly, Miss. Mary \n female \n NA \n 0 \n 0 \n 14312 \n NA \n Q \n \n \n cheap \n 7.8292 \n 3 \n 0 \n Kelly, Mr. James \n male \n 34.5000 \n 0 \n 0 \n 330911 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Kelly, Mr. James \n male \n 44.0000 \n 0 \n 0 \n 363592 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Kennedy, Mr. John \n male \n NA \n 0 \n 0 \n 368783 \n NA \n Q \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Khalil, Mr. Betros \n male \n NA \n 1 \n 0 \n 2660 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n female \n NA \n 1 \n 0 \n 2660 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Kiernan, Mr. John \n male \n NA \n 1 \n 0 \n 367227 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Kiernan, Mr. Philip \n male \n NA \n 1 \n 0 \n 367229 \n NA \n Q \n \n \n cheap \n 7.7375 \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n male \n NA \n 0 \n 0 \n 36865 \n NA \n Q \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Kink, Miss. Maria \n female \n 22.0000 \n 2 \n 0 \n 315152 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Kink, Mr. Vincenz \n male \n 26.0000 \n 2 \n 0 \n 315151 \n NA \n S \n \n \n cheap \n 22.0250 \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n female \n 4.0000 \n 0 \n 2 \n 315153 \n NA \n S \n \n \n cheap \n 22.0250 \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n male \n 29.0000 \n 3 \n 1 \n 315153 \n NA \n S \n \n \n cheap \n 22.0250 \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n female \n 26.0000 \n 1 \n 1 \n 315153 \n NA \n S \n \n \n cheap \n 12.1833 \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n female \n 1.0000 \n 1 \n 1 \n 350405 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Klasen, Mr. Klas Albin \n male \n 18.0000 \n 1 \n 1 \n 350404 \n NA \n S \n \n \n cheap \n 12.1833 \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n female \n 36.0000 \n 0 \n 2 \n 350405 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Kraeff, Mr. Theodor \n male \n NA \n 0 \n 0 \n 349253 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Krekorian, Mr. Neshan \n male \n 25.0000 \n 0 \n 0 \n 2654 \n F E57 \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Lahoud, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2624 \n NA \n C \n \n \n cheap \n 9.5875 \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n female \n 37.0000 \n 0 \n 0 \n 4135 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Laleff, Mr. Kristo \n male \n NA \n 0 \n 0 \n 349217 \n NA \n S \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Lam, Mr. Ali \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 56.4958 \n 3 \n 0 \n Lam, Mr. Len \n male \n NA \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n female \n 22.0000 \n 0 \n 0 \n C 7077 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Lane, Mr. Patrick \n male \n NA \n 0 \n 0 \n 7935 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 1 \n Lang, Mr. Fang \n male \n 26.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 9.4833 \n 3 \n 0 \n Larsson, Mr. August Viktor \n male \n 29.0000 \n 0 \n 0 \n 7545 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n male \n 29.0000 \n 0 \n 0 \n 347067 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n male \n 22.0000 \n 0 \n 0 \n 347065 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n male \n 22.0000 \n 0 \n 0 \n 2620 \n NA \n C \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n male \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Miss. Ida \n female \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Miss. Jeannie \n female \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Miss. Mathilde \n female \n NA \n 3 \n 1 \n 4133 \n NA \n S \n \n \n cheap \n 25.4667 \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n female \n NA \n 0 \n 4 \n 4133 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101292 \n NA \n S \n \n \n cheap \n 6.4375 \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n male \n 34.5000 \n 0 \n 0 \n 2683 \n NA \n C \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Lennon, Miss. Mary \n female \n NA \n 1 \n 0 \n 370371 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n Lennon, Mr. Denis \n male \n NA \n 1 \n 0 \n 370371 \n NA \n Q \n \n \n cheap \n 0.0000 \n 3 \n 0 \n Leonard, Mr. Lionel \n male \n 36.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Lester, Mr. James \n male \n 39.0000 \n 0 \n 0 \n A/4 48871 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Lievens, Mr. Rene Aime \n male \n 24.0000 \n 0 \n 0 \n 345781 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n female \n 25.0000 \n 0 \n 0 \n 347071 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n female \n 45.0000 \n 0 \n 0 \n 347073 \n NA \n S \n \n \n cheap \n 15.5500 \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n male \n 36.0000 \n 1 \n 0 \n 349910 \n NA \n S \n \n \n cheap \n 15.5500 \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n female \n 30.0000 \n 1 \n 0 \n 349910 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Lindqvist, Mr. Eino William \n male \n 20.0000 \n 1 \n 0 \n STON/O 2. 3101285 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Linehan, Mr. Michael \n male \n NA \n 0 \n 0 \n 330971 \n NA \n Q \n \n \n cheap \n 56.4958 \n 3 \n 0 \n Ling, Mr. Lee \n male \n 28.0000 \n 0 \n 0 \n 1601 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Lithman, Mr. Simon \n male \n NA \n 0 \n 0 \n S.O./P.P. 251 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Lobb, Mr. William Arthur \n male \n 30.0000 \n 1 \n 0 \n A/5. 3336 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n female \n 26.0000 \n 1 \n 0 \n A/5. 3336 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Lockyer, Mr. Edward \n male \n NA \n 0 \n 0 \n 1222 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n male \n 20.5000 \n 0 \n 0 \n A/5 21173 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 1 \n Lulic, Mr. Nikola \n male \n 27.0000 \n 0 \n 0 \n 315098 \n NA \n S \n \n \n cheap \n 7.0542 \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n male \n 51.0000 \n 0 \n 0 \n 347743 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Lundin, Miss. Olga Elida \n female \n 23.0000 \n 0 \n 0 \n 347469 \n NA \n S \n \n \n cheap \n 7.5792 \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n male \n 32.0000 \n 0 \n 0 \n 350403 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n male \n NA \n 0 \n 0 \n 349235 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n MacKay, Mr. George William \n male \n NA \n 0 \n 0 \n C.A. 42795 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n female \n NA \n 0 \n 0 \n 370370 \n NA \n Q \n \n \n cheap \n 7.1417 \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n male \n 24.0000 \n 0 \n 0 \n C 17369 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n male \n 22.0000 \n 0 \n 0 \n STON/O 2. 3101275 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n female \n NA \n 0 \n 0 \n 330924 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Mahon, Mr. John \n male \n NA \n 0 \n 0 \n AQ/4 3130 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Maisner, Mr. Simon \n male \n NA \n 0 \n 0 \n A/S 2816 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n male \n 29.0000 \n 0 \n 0 \n STON/O 2. 3101268 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Mamee, Mr. Hanna \n male \n NA \n 0 \n 0 \n 2677 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Mangan, Miss. Mary \n female \n 30.5000 \n 0 \n 0 \n 364850 \n NA \n Q \n \n \n cheap \n 7.7375 \n 3 \n 1 \n Mannion, Miss. Margareth \n female \n NA \n 0 \n 0 \n 36866 \n NA \n Q \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n male \n NA \n 0 \n 0 \n 2655 \n F E46 \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Markoff, Mr. Marin \n male \n 35.0000 \n 0 \n 0 \n 349213 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Markun, Mr. Johann \n male \n 33.0000 \n 0 \n 0 \n 349257 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Masselmani, Mrs. Fatima \n female \n NA \n 0 \n 0 \n 2649 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Matinoff, Mr. Nicola \n male \n NA \n 0 \n 0 \n 349255 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n female \n NA \n 0 \n 0 \n 383123 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n male \n NA \n 0 \n 0 \n 367228 \n NA \n Q \n \n \n cheap \n 23.2500 \n 3 \n 1 \n McCoy, Miss. Agnes \n female \n NA \n 2 \n 0 \n 367226 \n NA \n Q \n \n \n cheap \n 23.2500 \n 3 \n 1 \n McCoy, Miss. Alicia \n female \n NA \n 2 \n 0 \n 367226 \n NA \n Q \n \n \n cheap \n 23.2500 \n 3 \n 1 \n McCoy, Mr. Bernard \n male \n NA \n 2 \n 0 \n 367226 \n NA \n Q \n \n \n cheap \n 7.7875 \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n female \n NA \n 0 \n 0 \n 330932 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 0 \n McEvoy, Mr. Michael \n male \n NA \n 0 \n 0 \n 36568 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 1 \n McGovern, Miss. Mary \n female \n NA \n 0 \n 0 \n 330931 \n NA \n Q \n \n \n cheap \n 8.0292 \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n female \n 15.0000 \n 0 \n 0 \n 330923 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n McGowan, Miss. Katherine \n female \n 35.0000 \n 0 \n 0 \n 9232 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n McMahon, Mr. Martin \n male \n NA \n 0 \n 0 \n 370372 \n NA \n Q \n \n \n cheap \n 16.1000 \n 3 \n 0 \n McNamee, Mr. Neal \n male \n 24.0000 \n 1 \n 0 \n 376566 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n female \n 19.0000 \n 1 \n 0 \n 376566 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n McNeill, Miss. Bridget \n female \n NA \n 0 \n 0 \n 370368 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n female \n NA \n 0 \n 0 \n SOTON/O.Q. 392087 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n female \n NA \n 0 \n 0 \n 343095 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Meo, Mr. Alfonzo \n male \n 55.5000 \n 0 \n 0 \n A.5. 11206 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Mernagh, Mr. Robert \n male \n NA \n 0 \n 0 \n 368703 \n NA \n Q \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n male \n 21.0000 \n 0 \n 0 \n 345501 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Miles, Mr. Frank \n male \n NA \n 0 \n 0 \n 359306 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Mineff, Mr. Ivan \n male \n 24.0000 \n 0 \n 0 \n 349233 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Minkoff, Mr. Lazar \n male \n 21.0000 \n 0 \n 0 \n 349211 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n male \n 28.0000 \n 0 \n 0 \n 349207 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Mitkoff, Mr. Mito \n male \n NA \n 0 \n 0 \n 349221 \n NA \n S \n \n \n cheap \n 7.8792 \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n female \n NA \n 0 \n 0 \n 330980 \n NA \n Q \n \n \n cheap \n 7.6500 \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n male \n 25.0000 \n 0 \n 0 \n 348123 \n F G73 \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Moor, Master. Meier \n male \n 6.0000 \n 0 \n 1 \n 392096 \n E121 \n S \n \n \n cheap \n 12.4750 \n 3 \n 1 \n Moor, Mrs. (Beila) \n female \n 27.0000 \n 0 \n 1 \n 392096 \n E121 \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Moore, Mr. Leonard Charles \n male \n NA \n 0 \n 0 \n A4. 54510 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 1 \n Moran, Miss. Bertha \n female \n NA \n 1 \n 0 \n 371110 \n NA \n Q \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Moran, Mr. Daniel J \n male \n NA \n 1 \n 0 \n 371110 \n NA \n Q \n \n \n cheap \n 8.4583 \n 3 \n 0 \n Moran, Mr. James \n male \n NA \n 0 \n 0 \n 330877 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Morley, Mr. William \n male \n 34.0000 \n 0 \n 0 \n 364506 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n male \n NA \n 0 \n 0 \n 372622 \n NA \n Q \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Moss, Mr. Albert Johan \n male \n NA \n 0 \n 0 \n 312991 \n NA \n S \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Moubarek, Master. Gerios \n male \n NA \n 1 \n 1 \n 2661 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n male \n NA \n 1 \n 1 \n 2661 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n female \n NA \n 0 \n 2 \n 2661 \n NA \n C \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n female \n NA \n 0 \n 0 \n 2626 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n male \n NA \n 0 \n 0 \n 374746 \n NA \n S \n \n \n cheap \n 7.7333 \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n female \n NA \n 0 \n 0 \n 35852 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n female \n 24.0000 \n 0 \n 0 \n 382653 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Murdlin, Mr. Joseph \n male \n NA \n 0 \n 0 \n A./5. 3235 \n NA \n S \n \n \n cheap \n 15.5000 \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n female \n NA \n 1 \n 0 \n 367230 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n female \n NA \n 1 \n 0 \n 367230 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 1 \n Murphy, Miss. Nora \n female \n NA \n 0 \n 0 \n 36568 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n male \n 18.0000 \n 0 \n 0 \n 347078 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Naidenoff, Mr. Penko \n male \n 22.0000 \n 0 \n 0 \n 349206 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n female \n 15.0000 \n 0 \n 0 \n 2667 \n NA \n C \n \n \n cheap \n 15.7417 \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n female \n 1.0000 \n 0 \n 2 \n 2653 \n NA \n C \n \n \n cheap \n 15.7417 \n 3 \n 1 \n Nakid, Mr. Sahid \n male \n 20.0000 \n 1 \n 1 \n 2653 \n NA \n C \n \n \n cheap \n 15.7417 \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n female \n 19.0000 \n 1 \n 1 \n 2653 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Nancarrow, Mr. William Henry \n male \n 33.0000 \n 0 \n 0 \n A./5. 3338 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Nankoff, Mr. Minko \n male \n NA \n 0 \n 0 \n 349218 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Nasr, Mr. Mustafa \n male \n NA \n 0 \n 0 \n 2652 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Naughton, Miss. Hannah \n female \n NA \n 0 \n 0 \n 365237 \n NA \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Nenkoff, Mr. Christo \n male \n NA \n 0 \n 0 \n 349234 \n NA \n S \n \n \n cheap \n 11.2417 \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n male \n 12.0000 \n 1 \n 0 \n 2651 \n NA \n C \n \n \n cheap \n 11.2417 \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n female \n 14.0000 \n 1 \n 0 \n 2651 \n NA \n C \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n female \n 29.0000 \n 0 \n 0 \n 3101297 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Niklasson, Mr. Samuel \n male \n 28.0000 \n 0 \n 0 \n 363611 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n female \n 18.0000 \n 0 \n 0 \n 347066 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n female \n 26.0000 \n 0 \n 0 \n 347470 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n male \n 21.0000 \n 0 \n 0 \n 350410 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n male \n 41.0000 \n 0 \n 0 \n SOTON/O2 3101272 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Niskanen, Mr. Juha \n male \n 39.0000 \n 0 \n 0 \n STON/O 2. 3101289 \n NA \n S \n \n \n cheap \n 7.8000 \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n male \n 21.0000 \n 0 \n 0 \n A/4. 39886 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Novel, Mr. Mansouer \n male \n 28.5000 \n 0 \n 0 \n 2697 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n female \n 22.0000 \n 0 \n 0 \n 347081 \n NA \n S \n \n \n cheap \n 6.2375 \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n male \n 61.0000 \n 0 \n 0 \n 345364 \n NA \n S \n \n \n cheap \n 15.5000 \n 3 \n 0 \n O'Brien, Mr. Thomas \n male \n NA \n 1 \n 0 \n 370365 \n NA \n Q \n \n \n cheap \n 7.8292 \n 3 \n 0 \n O'Brien, Mr. Timothy \n male \n NA \n 0 \n 0 \n 330979 \n NA \n Q \n \n \n cheap \n 15.5000 \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n female \n NA \n 1 \n 0 \n 370365 \n NA \n Q \n \n \n cheap \n 7.7333 \n 3 \n 0 \n O'Connell, Mr. Patrick D \n male \n NA \n 0 \n 0 \n 334912 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n O'Connor, Mr. Maurice \n male \n NA \n 0 \n 0 \n 371060 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 0 \n O'Connor, Mr. Patrick \n male \n NA \n 0 \n 0 \n 366713 \n NA \n Q \n \n \n cheap \n 9.2250 \n 3 \n 0 \n Odahl, Mr. Nils Martin \n male \n 23.0000 \n 0 \n 0 \n 7267 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n female \n NA \n 0 \n 0 \n 364856 \n NA \n Q \n \n \n cheap \n 7.7500 \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n female \n NA \n 0 \n 0 \n 14311 \n NA \n Q \n \n \n cheap \n 7.8792 \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n female \n NA \n 0 \n 0 \n 330959 \n NA \n Q \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Ohman, Miss. Velin \n female \n 22.0000 \n 0 \n 0 \n 347085 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n O'Keefe, Mr. Patrick \n male \n NA \n 0 \n 0 \n 368402 \n NA \n Q \n \n \n cheap \n 7.8292 \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n female \n NA \n 0 \n 0 \n 330919 \n NA \n Q \n \n \n cheap \n 3.1708 \n 3 \n 1 \n Olsen, Master. Artur Karl \n male \n 9.0000 \n 0 \n 1 \n C 17368 \n NA \n S \n \n \n cheap \n 22.5250 \n 3 \n 0 \n Olsen, Mr. Henry Margido \n male \n 28.0000 \n 0 \n 0 \n C 4001 \n NA \n S \n \n \n cheap \n 8.4042 \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n male \n 42.0000 \n 0 \n 1 \n 4579 \n NA \n S \n \n \n cheap \n 7.3125 \n 3 \n 0 \n Olsen, Mr. Ole Martin \n male \n NA \n 0 \n 0 \n Fa 265302 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Olsson, Miss. Elina \n female \n 31.0000 \n 0 \n 0 \n 350407 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n male \n 28.0000 \n 0 \n 0 \n 347464 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n male \n 32.0000 \n 0 \n 0 \n 347079 \n NA \n S \n \n \n cheap \n 9.2250 \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n male \n 20.0000 \n 0 \n 0 \n 6563 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Oreskovic, Miss. Jelka \n female \n 23.0000 \n 0 \n 0 \n 315085 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Oreskovic, Miss. Marija \n female \n 20.0000 \n 0 \n 0 \n 315096 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Oreskovic, Mr. Luka \n male \n 20.0000 \n 0 \n 0 \n 315094 \n NA \n S \n \n \n cheap \n 9.2167 \n 3 \n 0 \n Osen, Mr. Olaf Elon \n male \n 16.0000 \n 0 \n 0 \n 7534 \n NA \n S \n \n \n cheap \n 8.6833 \n 3 \n 1 \n Osman, Mrs. Mara \n female \n 31.0000 \n 0 \n 0 \n 349244 \n NA \n S \n \n \n cheap \n 7.6292 \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n female \n NA \n 0 \n 0 \n 330909 \n NA \n Q \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n male \n 2.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Master. Paul Folke \n male \n 6.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Miss. Stina Viola \n female \n 3.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n female \n 8.0000 \n 3 \n 1 \n 349909 \n NA \n S \n \n \n cheap \n 21.0750 \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n female \n 29.0000 \n 0 \n 4 \n 349909 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Master. Eino Viljami \n male \n 1.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Master. Juha Niilo \n male \n 7.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Master. Urho Abraham \n male \n 2.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n male \n 16.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n male \n 14.0000 \n 4 \n 1 \n 3101295 \n NA \n S \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n female \n 41.0000 \n 0 \n 5 \n 3101295 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Pasic, Mr. Jakob \n male \n 21.0000 \n 0 \n 0 \n 315097 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Patchett, Mr. George \n male \n 19.0000 \n 0 \n 0 \n 358585 \n NA \n S \n \n \n cheap \n 8.7125 \n 3 \n 0 \n Paulner, Mr. Uscher \n male \n NA \n 0 \n 0 \n 3411 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Pavlovic, Mr. Stefo \n male \n 32.0000 \n 0 \n 0 \n 349242 \n NA \n S \n \n \n cheap \n 13.7750 \n 3 \n 0 \n Peacock, Master. Alfred Edward \n male \n 0.7500 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n NA \n S \n \n \n cheap \n 13.7750 \n 3 \n 0 \n Peacock, Miss. Treasteall \n female \n 3.0000 \n 1 \n 1 \n SOTON/O.Q. 3101315 \n NA \n S \n \n \n cheap \n 13.7750 \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n female \n 26.0000 \n 0 \n 2 \n SOTON/O.Q. 3101315 \n NA \n S \n \n \n cheap \n 7.0000 \n 3 \n 0 \n Pearce, Mr. Ernest \n male \n NA \n 0 \n 0 \n 343271 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Pedersen, Mr. Olaf \n male \n NA \n 0 \n 0 \n 345498 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Peduzzi, Mr. Joseph \n male \n NA \n 0 \n 0 \n A/5 2817 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101294 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n male \n 25.0000 \n 0 \n 0 \n STON/O 2. 3101291 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Perkin, Mr. John Henry \n male \n 22.0000 \n 0 \n 0 \n A/5 21174 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n male \n 25.0000 \n 1 \n 0 \n 347083 \n NA \n S \n \n \n cheap \n 22.3583 \n 3 \n 1 \n Peter, Master. Michael J \n male \n NA \n 1 \n 1 \n 2668 \n NA \n C \n \n \n cheap \n 22.3583 \n 3 \n 1 \n Peter, Miss. Anna \n female \n NA \n 1 \n 1 \n 2668 \n F E69 \n C \n \n \n cheap \n 22.3583 \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n female \n NA \n 0 \n 2 \n 2668 \n NA \n C \n \n \n cheap \n 8.1375 \n 3 \n 0 \n Peters, Miss. Katie \n female \n NA \n 0 \n 0 \n 330935 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Petersen, Mr. Marius \n male \n 24.0000 \n 0 \n 0 \n 342441 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Petranec, Miss. Matilda \n female \n 28.0000 \n 0 \n 0 \n 349245 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Petroff, Mr. Nedelio \n male \n 19.0000 \n 0 \n 0 \n 349212 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n male \n NA \n 0 \n 0 \n 349215 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Petterson, Mr. Johan Emil \n male \n 25.0000 \n 1 \n 0 \n 347076 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n female \n 18.0000 \n 0 \n 0 \n 347087 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n male \n 32.0000 \n 0 \n 0 \n SOTON/O.Q. 392078 \n E10 \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n male \n NA \n 0 \n 0 \n 349227 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Pokrnic, Mr. Mate \n male \n 17.0000 \n 0 \n 0 \n 315095 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Pokrnic, Mr. Tome \n male \n 24.0000 \n 0 \n 0 \n 315092 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Radeff, Mr. Alexander \n male \n NA \n 0 \n 0 \n 349223 \n NA \n S \n \n \n cheap \n 8.1125 \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n female \n NA \n 0 \n 0 \n 65305 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Razi, Mr. Raihed \n male \n NA \n 0 \n 0 \n 2629 \n NA \n C \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Reed, Mr. James George \n male \n NA \n 0 \n 0 \n 362316 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Rekic, Mr. Tido \n male \n 38.0000 \n 0 \n 0 \n 349249 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Reynolds, Mr. Harold J \n male \n 21.0000 \n 0 \n 0 \n 342684 \n NA \n S \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Albert \n male \n 10.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Arthur \n male \n 4.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Eric \n male \n 7.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. Eugene \n male \n 2.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Master. George Hugh \n male \n 8.0000 \n 4 \n 1 \n 382652 \n NA \n Q \n \n \n cheap \n 29.1250 \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n female \n 39.0000 \n 0 \n 5 \n 382652 \n NA \n Q \n \n \n cheap \n 39.6875 \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n female \n 22.0000 \n 0 \n 0 \n 3101295 \n NA \n S \n \n \n cheap \n 7.1250 \n 3 \n 0 \n Rintamaki, Mr. Matti \n male \n 35.0000 \n 0 \n 0 \n STON/O 2. 3101273 \n NA \n S \n \n \n cheap \n 7.7208 \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n female \n NA \n 0 \n 0 \n 334915 \n NA \n Q \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Risien, Mr. Samuel Beard \n male \n NA \n 0 \n 0 \n 364498 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n female \n NA \n 0 \n 0 \n 364498 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Robins, Mr. Alexander A \n male \n 50.0000 \n 1 \n 0 \n A/5. 3337 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n female \n 47.0000 \n 1 \n 0 \n A/5. 3337 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Rogers, Mr. William John \n male \n NA \n 0 \n 0 \n S.C./A.4. 23567 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n male \n NA \n 0 \n 0 \n 312993 \n NA \n S \n \n \n cheap \n 20.2125 \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n female \n 2.0000 \n 1 \n 1 \n 370129 \n NA \n S \n \n \n cheap \n 20.2125 \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n male \n 18.0000 \n 1 \n 1 \n 370129 \n NA \n S \n \n \n cheap \n 20.2125 \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n female \n 41.0000 \n 0 \n 2 \n 370129 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Roth, Miss. Sarah A \n female \n NA \n 0 \n 0 \n 342712 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Rouse, Mr. Richard Henry \n male \n 50.0000 \n 0 \n 0 \n A/5 3594 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Rush, Mr. Alfred George John \n male \n 16.0000 \n 0 \n 0 \n A/4. 20589 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 1 \n Ryan, Mr. Edward \n male \n NA \n 0 \n 0 \n 383162 \n NA \n Q \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Ryan, Mr. Patrick \n male \n NA \n 0 \n 0 \n 371110 \n NA \n Q \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Saad, Mr. Amin \n male \n NA \n 0 \n 0 \n 2671 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Saad, Mr. Khalil \n male \n 25.0000 \n 0 \n 0 \n 2672 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Saade, Mr. Jean Nassr \n male \n NA \n 0 \n 0 \n 2676 \n NA \n C \n \n \n cheap \n 7.7292 \n 3 \n 0 \n Sadlier, Mr. Matthew \n male \n NA \n 0 \n 0 \n 367655 \n NA \n Q \n \n \n cheap \n 7.5750 \n 3 \n 0 \n Sadowitz, Mr. Harry \n male \n NA \n 0 \n 0 \n LP 1588 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n male \n 38.5000 \n 0 \n 0 \n SOTON/O.Q. 3101262 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Master. Thomas Henry \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Master. William Henry \n male \n 14.5000 \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Ada \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Constance Gladys \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Miss. Stella Anna \n female \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. Frederick \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. George John Jr \n male \n NA \n 8 \n 2 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mr. John George \n male \n NA \n 1 \n 9 \n CA. 2343 \n NA \n S \n \n \n cheap \n 69.5500 \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n female \n NA \n 1 \n 9 \n CA. 2343 \n NA \n S \n \n \n cheap \n 9.3250 \n 3 \n 0 \n Salander, Mr. Karl Johan \n male \n 24.0000 \n 0 \n 0 \n 7266 \n NA \n S \n \n \n cheap \n 7.6500 \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n female \n 21.0000 \n 0 \n 0 \n 343120 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Salonen, Mr. Johan Werner \n male \n 39.0000 \n 0 \n 0 \n 3101296 \n NA \n S \n \n \n cheap \n 21.6792 \n 3 \n 0 \n Samaan, Mr. Elias \n male \n NA \n 2 \n 0 \n 2662 \n NA \n C \n \n \n cheap \n 21.6792 \n 3 \n 0 \n Samaan, Mr. Hanna \n male \n NA \n 2 \n 0 \n 2662 \n NA \n C \n \n \n cheap \n 21.6792 \n 3 \n 0 \n Samaan, Mr. Youssef \n male \n NA \n 2 \n 0 \n 2662 \n NA \n C \n \n \n cheap \n 16.7000 \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n female \n 1.0000 \n 1 \n 1 \n PP 9549 \n G6 \n S \n \n \n cheap \n 16.7000 \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n female \n 24.0000 \n 0 \n 2 \n PP 9549 \n G6 \n S \n \n \n cheap \n 16.7000 \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n female \n 4.0000 \n 1 \n 1 \n PP 9549 \n G6 \n S \n \n \n cheap \n 9.5000 \n 3 \n 1 \n Sap, Mr. Julius \n male \n 25.0000 \n 0 \n 0 \n 345768 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Saundercock, Mr. William Henry \n male \n 20.0000 \n 0 \n 0 \n A/5. 2151 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n male \n 24.5000 \n 0 \n 0 \n 342826 \n NA \n S \n \n \n cheap \n 7.7250 \n 3 \n 0 \n Scanlan, Mr. James \n male \n NA \n 0 \n 0 \n 36209 \n NA \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Sdycoff, Mr. Todor \n male \n NA \n 0 \n 0 \n 349222 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n male \n NA \n 0 \n 0 \n 370374 \n NA \n Q \n \n \n cheap \n 9.5000 \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n male \n 29.0000 \n 0 \n 0 \n 345779 \n NA \n S \n \n \n cheap \n 15.1000 \n 3 \n 0 \n Shellard, Mr. Frederick William \n male \n NA \n 0 \n 0 \n C.A. 6212 \n NA \n S \n \n \n cheap \n 7.7792 \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n female \n NA \n 0 \n 0 \n 330968 \n NA \n Q \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n male \n NA \n 0 \n 0 \n 374910 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Simmons, Mr. John \n male \n NA \n 0 \n 0 \n SOTON/OQ 392082 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Sirayanian, Mr. Orsen \n male \n 22.0000 \n 0 \n 0 \n 2669 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Sirota, Mr. Maurice \n male \n NA \n 0 \n 0 \n 392092 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Sivic, Mr. Husein \n male \n 40.0000 \n 0 \n 0 \n 349251 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n male \n 21.0000 \n 0 \n 0 \n STON/O 2. 3101280 \n NA \n S \n \n \n cheap \n 7.4958 \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 3101265 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Master. Harald \n male \n 4.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n male \n 10.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Miss. Mabel \n female \n 9.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n female \n 2.0000 \n 3 \n 2 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Mr. Wilhelm \n male \n 40.0000 \n 1 \n 4 \n 347088 \n NA \n S \n \n \n cheap \n 27.9000 \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n female \n 45.0000 \n 1 \n 4 \n 347088 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Slabenoff, Mr. Petco \n male \n NA \n 0 \n 0 \n 349214 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n male \n NA \n 0 \n 0 \n SOTON/OQ 392086 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Smiljanic, Mr. Mile \n male \n NA \n 0 \n 0 \n 315037 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Smith, Mr. Thomas \n male \n NA \n 0 \n 0 \n 384461 \n NA \n Q \n \n \n cheap \n 7.7333 \n 3 \n 1 \n Smyth, Miss. Julia \n female \n NA \n 0 \n 0 \n 335432 \n NA \n Q \n \n \n cheap \n 7.6500 \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n male \n 19.0000 \n 0 \n 0 \n 348124 \n F G73 \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Somerton, Mr. Francis William \n male \n 30.0000 \n 0 \n 0 \n A.5. 18509 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Spector, Mr. Woolf \n male \n NA \n 0 \n 0 \n A.5. 3236 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Spinner, Mr. Henry John \n male \n 32.0000 \n 0 \n 0 \n STON/OQ. 369943 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Staneff, Mr. Ivan \n male \n NA \n 0 \n 0 \n 349208 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Stankovic, Mr. Ivan \n male \n 33.0000 \n 0 \n 0 \n 349239 \n NA \n C \n \n \n cheap \n 7.5500 \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n female \n 23.0000 \n 0 \n 0 \n CA. 2314 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Stanley, Mr. Edward Roland \n male \n 21.0000 \n 0 \n 0 \n A/4 45380 \n NA \n S \n \n \n unknown \n NA \n 3 \n 0 \n Storey, Mr. Thomas \n male \n 60.5000 \n 0 \n 0 \n 3701 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n male \n 19.0000 \n 0 \n 0 \n 349205 \n NA \n S \n \n \n cheap \n 9.8375 \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n female \n 22.0000 \n 0 \n 0 \n 7553 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Stranden, Mr. Juho \n male \n 31.0000 \n 0 \n 0 \n STON/O 2. 3101288 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Strilic, Mr. Ivan \n male \n 27.0000 \n 0 \n 0 \n 315083 \n NA \n S \n \n \n cheap \n 10.4625 \n 3 \n 0 \n Strom, Miss. Telma Matilda \n female \n 2.0000 \n 0 \n 1 \n 347054 \n G6 \n S \n \n \n cheap \n 10.4625 \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n female \n 29.0000 \n 1 \n 1 \n 347054 \n G6 \n S \n \n \n cheap \n 8.0500 \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n male \n 16.0000 \n 0 \n 0 \n SOTON/OQ 392089 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 1 \n Sundman, Mr. Johan Julian \n male \n 44.0000 \n 0 \n 0 \n STON/O 2. 3101269 \n NA \n S \n \n \n cheap \n 7.0500 \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n male \n 25.0000 \n 0 \n 0 \n SOTON/OQ 392076 \n NA \n S \n \n \n cheap \n 7.7750 \n 3 \n 0 \n Svensson, Mr. Johan \n male \n 74.0000 \n 0 \n 0 \n 347060 \n NA \n S \n \n \n cheap \n 9.2250 \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n male \n 14.0000 \n 0 \n 0 \n 7538 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 0 \n Svensson, Mr. Olof \n male \n 24.0000 \n 0 \n 0 \n 350035 \n NA \n S \n \n \n cheap \n 7.7958 \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n male \n 25.0000 \n 0 \n 0 \n 350033 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n male \n 34.0000 \n 0 \n 0 \n 363294 \n NA \n S \n \n \n cheap \n 8.5167 \n 3 \n 1 \n Thomas, Master. Assad Alexander \n male \n 0.4167 \n 0 \n 1 \n 2625 \n NA \n C \n \n \n cheap \n 6.4375 \n 3 \n 0 \n Thomas, Mr. Charles P \n male \n NA \n 1 \n 0 \n 2621 \n NA \n C \n \n \n cheap \n 6.4375 \n 3 \n 0 \n Thomas, Mr. John \n male \n NA \n 0 \n 0 \n 2681 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Thomas, Mr. Tannous \n male \n NA \n 0 \n 0 \n 2684 \n NA \n C \n \n \n cheap \n 8.5167 \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n female \n 16.0000 \n 1 \n 1 \n 2625 \n NA \n C \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n male \n NA \n 0 \n 0 \n 32302 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Thorneycroft, Mr. Percival \n male \n NA \n 1 \n 0 \n 376564 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n female \n NA \n 1 \n 0 \n 376564 \n NA \n S \n \n \n cheap \n 7.9250 \n 3 \n 0 \n Tikkanen, Mr. Juho \n male \n 32.0000 \n 0 \n 0 \n STON/O 2. 3101293 \n NA \n S \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Tobin, Mr. Roger \n male \n NA \n 0 \n 0 \n 383121 \n F38 \n Q \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Todoroff, Mr. Lalio \n male \n NA \n 0 \n 0 \n 349216 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n male \n 30.5000 \n 0 \n 0 \n 364499 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Torber, Mr. Ernst William \n male \n 44.0000 \n 0 \n 0 \n 364511 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Torfa, Mr. Assad \n male \n NA \n 0 \n 0 \n 2673 \n NA \n C \n \n \n cheap \n 0.0000 \n 3 \n 1 \n Tornquist, Mr. William Henry \n male \n 25.0000 \n 0 \n 0 \n LINE \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 0 \n Toufik, Mr. Nakli \n male \n NA \n 0 \n 0 \n 2641 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Touma, Master. Georges Youssef \n male \n 7.0000 \n 1 \n 1 \n 2650 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Touma, Miss. Maria Youssef \n female \n 9.0000 \n 1 \n 1 \n 2650 \n NA \n C \n \n \n cheap \n 15.2458 \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n female \n 29.0000 \n 0 \n 2 \n 2650 \n NA \n C \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Turcin, Mr. Stjepan \n male \n 36.0000 \n 0 \n 0 \n 349247 \n NA \n S \n \n \n cheap \n 9.8417 \n 3 \n 1 \n Turja, Miss. Anna Sofia \n female \n 18.0000 \n 0 \n 0 \n 4138 \n NA \n S \n \n \n cheap \n 9.5875 \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n female \n 63.0000 \n 0 \n 0 \n 4134 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n van Billiard, Master. James William \n male \n NA \n 1 \n 1 \n A/5. 851 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n van Billiard, Master. Walter John \n male \n 11.5000 \n 1 \n 1 \n A/5. 851 \n NA \n S \n \n \n cheap \n 14.5000 \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n male \n 40.5000 \n 0 \n 2 \n A/5. 851 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Van Impe, Miss. Catharina \n female \n 10.0000 \n 0 \n 2 \n 345773 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n male \n 36.0000 \n 1 \n 1 \n 345773 \n NA \n S \n \n \n cheap \n 24.1500 \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n female \n 30.0000 \n 1 \n 1 \n 345773 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n male \n NA \n 0 \n 0 \n 345777 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n male \n 33.0000 \n 0 \n 0 \n 345780 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n male \n 28.0000 \n 0 \n 0 \n 345770 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n male \n 28.0000 \n 0 \n 0 \n 345783 \n NA \n S \n \n \n cheap \n 9.0000 \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n male \n 47.0000 \n 0 \n 0 \n 345765 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n female \n 18.0000 \n 2 \n 0 \n 345764 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Mr. Julius \n male \n 31.0000 \n 3 \n 0 \n 345763 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n male \n 16.0000 \n 2 \n 0 \n 345764 \n NA \n S \n \n \n cheap \n 18.0000 \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n female \n 31.0000 \n 1 \n 0 \n 345763 \n NA \n S \n \n \n cheap \n 7.2250 \n 3 \n 1 \n Vartanian, Mr. David \n male \n 22.0000 \n 0 \n 0 \n 2658 \n NA \n C \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n male \n 20.0000 \n 0 \n 0 \n 350416 \n NA \n S \n \n \n cheap \n 7.8542 \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n female \n 14.0000 \n 0 \n 0 \n 350406 \n NA \n S \n \n \n cheap \n 7.8958 \n 3 \n 0 \n Vovk, Mr. Janko \n male \n 22.0000 \n 0 \n 0 \n 349252 \n NA \n S \n \n \n cheap \n 9.0000 \n 3 \n 0 \n Waelens, Mr. Achille \n male \n 22.0000 \n 0 \n 0 \n 345767 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Ware, Mr. Frederick \n male \n NA \n 0 \n 0 \n 359309 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Warren, Mr. Charles William \n male \n NA \n 0 \n 0 \n C.A. 49867 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Webber, Mr. James \n male \n NA \n 0 \n 0 \n SOTON/OQ 3101316 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Wenzel, Mr. Linhart \n male \n 32.5000 \n 0 \n 0 \n 345775 \n NA \n S \n \n \n cheap \n 7.2292 \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n female \n 38.0000 \n 0 \n 0 \n 2688 \n NA \n C \n \n \n cheap \n 7.7500 \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n male \n 51.0000 \n 0 \n 0 \n 347064 \n NA \n S \n \n \n cheap \n 6.4958 \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n male \n 18.0000 \n 1 \n 0 \n 3101267 \n NA \n S \n \n \n cheap \n 6.4958 \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n male \n 21.0000 \n 1 \n 0 \n 3101266 \n NA \n S \n \n \n cheap \n 7.0000 \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n female \n 47.0000 \n 1 \n 0 \n 363272 \n NA \n S \n \n \n cheap \n 8.7125 \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n male \n NA \n 0 \n 0 \n 3410 \n NA \n S \n \n \n cheap \n 7.5500 \n 3 \n 0 \n Willey, Mr. Edward \n male \n NA \n 0 \n 0 \n S.O./P.P. 751 \n NA \n S \n \n \n cheap \n 8.0500 \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n male \n NA \n 0 \n 0 \n A/5 2466 \n NA \n S \n \n \n cheap \n 16.1000 \n 3 \n 0 \n Williams, Mr. Leslie \n male \n 28.5000 \n 0 \n 0 \n 54636 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Windelov, Mr. Einar \n male \n 21.0000 \n 0 \n 0 \n SOTON/OQ 3101317 \n NA \n S \n \n \n cheap \n 8.6625 \n 3 \n 0 \n Wirz, Mr. Albert \n male \n 27.0000 \n 0 \n 0 \n 315154 \n NA \n S \n \n \n cheap \n 7.2500 \n 3 \n 0 \n Wiseman, Mr. Phillippe \n male \n NA \n 0 \n 0 \n A/4. 34244 \n NA \n S \n \n \n cheap \n 9.5000 \n 3 \n 0 \n Wittevrongel, Mr. Camille \n male \n 36.0000 \n 0 \n 0 \n 345771 \n NA \n S \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Yasbeck, Mr. Antoni \n male \n 27.0000 \n 1 \n 0 \n 2659 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n female \n 15.0000 \n 1 \n 0 \n 2659 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Youseff, Mr. Gerious \n male \n 45.5000 \n 0 \n 0 \n 2628 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Yousif, Mr. Wazli \n male \n NA \n 0 \n 0 \n 2647 \n NA \n C \n \n \n cheap \n 14.4583 \n 3 \n 0 \n Yousseff, Mr. Gerious \n male \n NA \n 0 \n 0 \n 2627 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Zabour, Miss. Hileni \n female \n 14.5000 \n 1 \n 0 \n 2665 \n NA \n C \n \n \n cheap \n 14.4542 \n 3 \n 0 \n Zabour, Miss. Thamine \n female \n NA \n 1 \n 0 \n 2665 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n male \n 26.5000 \n 0 \n 0 \n 2656 \n NA \n C \n \n \n cheap \n 7.2250 \n 3 \n 0 \n Zakarian, Mr. Ortin \n male \n 27.0000 \n 0 \n 0 \n 2670 \n NA \n C \n \n \n\n cheap \n 7.8750 \n 3 \n 0 \n Zimmerman, Mr. Leo \n male \n 29.0000 \n 0 \n 0 \n 315082 \n NA \n S \n \n \n
\n \n \n\n sex_of_passenger \n age_of_passenger \n imputed_age_of_passenger \n pclass \n survived \n name_of_passenger \n sibsp \n parch \n ticket \n fare \n cabin \n embarked \n \n \n female \n 29.0000 \n 29.00000 \n 1 \n 1 \n Allen, Miss. Elisabeth Walton \n 0 \n 0 \n 24160 \n 211.3375 \n B5 \n S \n \n \n male \n 0.9167 \n 0.91670 \n 1 \n 1 \n Allison, Master. Hudson Trevor \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n female \n 2.0000 \n 2.00000 \n 1 \n 0 \n Allison, Miss. Helen Loraine \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Allison, Mr. Hudson Joshua Creighton \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n female \n 25.0000 \n 25.00000 \n 1 \n 0 \n Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n 1 \n 2 \n 113781 \n 151.5500 \n C22 C26 \n S \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 1 \n Anderson, Mr. Harry \n 0 \n 0 \n 19952 \n 26.5500 \n E12 \n S \n \n \n female \n 63.0000 \n 63.00000 \n 1 \n 1 \n Andrews, Miss. Kornelia Theodosia \n 1 \n 0 \n 13502 \n 77.9583 \n D7 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Andrews, Mr. Thomas Jr \n 0 \n 0 \n 112050 \n 0.0000 \n A36 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Appleton, Mrs. Edward Dale (Charlotte Lamson) \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Artagaveytia, Mr. Ramon \n 0 \n 0 \n PC 17609 \n 49.5042 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Astor, Col. John Jacob \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Astor, Mrs. John Jacob (Madeleine Talmadge Force) \n 1 \n 0 \n PC 17757 \n 227.5250 \n C62 C64 \n C \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Aubart, Mme. Leontine Pauline \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n Barber, Miss. Ellen \"Nellie\" \n 0 \n 0 \n 19877 \n 78.8500 \n NA \n S \n \n \n male \n 80.0000 \n 80.00000 \n 1 \n 1 \n Barkworth, Mr. Algernon Henry Wilson \n 0 \n 0 \n 27042 \n 30.0000 \n A23 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Baumann, Mr. John D \n 0 \n 0 \n PC 17318 \n 25.9250 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n Baxter, Mr. Quigg Edmond \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n female \n 50.0000 \n 50.00000 \n 1 \n 1 \n Baxter, Mrs. James (Helene DeLaudeniere Chaput) \n 0 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n female \n 32.0000 \n 32.00000 \n 1 \n 1 \n Bazzani, Miss. Albina \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n Beattie, Mr. Thomson \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 1 \n Beckwith, Mr. Richard Leonard \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n female \n 47.0000 \n 47.00000 \n 1 \n 1 \n Beckwith, Mrs. Richard Leonard (Sallie Monypeny) \n 1 \n 1 \n 11751 \n 52.5542 \n D35 \n S \n \n \n male \n 26.0000 \n 26.00000 \n 1 \n 1 \n Behr, Mr. Karl Howell \n 0 \n 0 \n 111369 \n 30.0000 \n C148 \n C \n \n \n female \n 42.0000 \n 42.00000 \n 1 \n 1 \n Bidois, Miss. Rosalie \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n female \n 29.0000 \n 29.00000 \n 1 \n 1 \n Bird, Miss. Ellen \n 0 \n 0 \n PC 17483 \n 221.7792 \n C97 \n S \n \n \n male \n 25.0000 \n 25.00000 \n 1 \n 0 \n Birnbaum, Mr. Jakob \n 0 \n 0 \n 13905 \n 26.0000 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 1 \n 1 \n Bishop, Mr. Dickinson H \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n Bishop, Mrs. Dickinson H (Helen Walton) \n 1 \n 0 \n 11967 \n 91.0792 \n B49 \n C \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Bissette, Miss. Amelia \n 0 \n 0 \n PC 17760 \n 135.6333 \n C99 \n S \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 1 \n Bjornstrom-Steffansson, Mr. Mauritz Hakan \n 0 \n 0 \n 110564 \n 26.5500 \n C52 \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n Blackwell, Mr. Stephen Weart \n 0 \n 0 \n 113784 \n 35.5000 \n T \n S \n \n \n male \n 40.0000 \n 40.00000 \n 1 \n 1 \n Blank, Mr. Henry \n 0 \n 0 \n 112277 \n 31.0000 \n A31 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Bonnell, Miss. Caroline \n 0 \n 0 \n 36928 \n 164.8667 \n C7 \n S \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Bonnell, Miss. Elizabeth \n 0 \n 0 \n 113783 \n 26.5500 \n C103 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Borebank, Mr. John James \n 0 \n 0 \n 110489 \n 26.5500 \n D22 \n S \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Bowen, Miss. Grace Scott \n 0 \n 0 \n PC 17608 \n 262.3750 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Bowerman, Miss. Elsie Edith \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Bradley, Mr. George (\"George Arthur Brayton\") \n 0 \n 0 \n 111427 \n 26.5500 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 1 \n 0 \n Brady, Mr. John Bertram \n 0 \n 0 \n 113054 \n 30.5000 \n A21 \n S \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 0 \n Brandeis, Mr. Emil \n 0 \n 0 \n PC 17591 \n 50.4958 \n B10 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Brewe, Dr. Arthur Jackson \n 0 \n 0 \n 112379 \n 39.6000 \n NA \n C \n \n \n female \n 44.0000 \n 44.00000 \n 1 \n 1 \n Brown, Mrs. James Joseph (Margaret Tobin) \n 0 \n 0 \n PC 17610 \n 27.7208 \n B4 \n C \n \n \n female \n 59.0000 \n 59.00000 \n 1 \n 1 \n Brown, Mrs. John Murray (Caroline Lane Lamson) \n 2 \n 0 \n 11769 \n 51.4792 \n C101 \n S \n \n \n female \n 60.0000 \n 60.00000 \n 1 \n 1 \n Bucknell, Mrs. William Robert (Emma Eliza Ward) \n 0 \n 0 \n 11813 \n 76.2917 \n D15 \n C \n \n \n female \n 41.0000 \n 41.00000 \n 1 \n 1 \n Burns, Miss. Elizabeth Margaret \n 0 \n 0 \n 16966 \n 134.5000 \n E40 \n C \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n Butt, Major. Archibald Willingham \n 0 \n 0 \n 113050 \n 26.5500 \n B38 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Cairns, Mr. Alexander \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 1 \n Calderhead, Mr. Edward Pennington \n 0 \n 0 \n PC 17476 \n 26.2875 \n E24 \n S \n \n \n female \n 53.0000 \n 53.00000 \n 1 \n 1 \n Candee, Mrs. Edward (Helen Churchill Hungerford) \n 0 \n 0 \n PC 17606 \n 27.4458 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n Cardeza, Mr. Thomas Drake Martinez \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake) \n 0 \n 1 \n PC 17755 \n 512.3292 \n B51 B53 B55 \n C \n \n \n male \n 33.0000 \n 33.00000 \n 1 \n 0 \n Carlsson, Mr. Frans Olof \n 0 \n 0 \n 695 \n 5.0000 \n B51 B53 B55 \n S \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n Carrau, Mr. Francisco M \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 1 \n 0 \n Carrau, Mr. Jose Pedro \n 0 \n 0 \n 113059 \n 47.1000 \n NA \n S \n \n \n male \n 11.0000 \n 11.00000 \n 1 \n 1 \n Carter, Master. William Thornton II \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n female \n 14.0000 \n 14.00000 \n 1 \n 1 \n Carter, Miss. Lucile Polk \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n Carter, Mr. William Ernest \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Carter, Mrs. William Ernest (Lucile Polk) \n 1 \n 2 \n 113760 \n 120.0000 \n B96 B98 \n S \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n Case, Mr. Howard Brown \n 0 \n 0 \n 19924 \n 26.0000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick) \n 0 \n 0 \n 17770 \n 27.7208 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n Cavendish, Mr. Tyrell William \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n female \n 76.0000 \n 76.00000 \n 1 \n 1 \n Cavendish, Mrs. Tyrell William (Julia Florence Siegel) \n 1 \n 0 \n 19877 \n 78.8500 \n C46 \n S \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Chaffee, Mr. Herbert Fuller \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n female \n 47.0000 \n 47.00000 \n 1 \n 1 \n Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood) \n 1 \n 0 \n W.E.P. 5734 \n 61.1750 \n E31 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 1 \n Chambers, Mr. Norman Campbell \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Chambers, Mrs. Norman Campbell (Bertha Griggs) \n 1 \n 0 \n 113806 \n 53.1000 \n E8 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Chaudanson, Miss. Victorine \n 0 \n 0 \n PC 17608 \n 262.3750 \n B61 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Cherry, Miss. Gladys \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n Chevre, Mr. Paul Romaine \n 0 \n 0 \n PC 17594 \n 29.7000 \n A9 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Chibnall, Mrs. (Edith Martha Bowerman) \n 0 \n 1 \n 113505 \n 55.0000 \n E33 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Chisholm, Mr. Roderick Robert Crispin \n 0 \n 0 \n 112051 \n 0.0000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n Clark, Mr. Walter Miller \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n female \n 26.0000 \n 26.00000 \n 1 \n 1 \n Clark, Mrs. Walter Miller (Virginia McDowell) \n 1 \n 0 \n 13508 \n 136.7792 \n C89 \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Cleaver, Miss. Alice \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Clifford, Mr. George Quincy \n 0 \n 0 \n 110465 \n 52.0000 \n A14 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Colley, Mr. Edward Pomeroy \n 0 \n 0 \n 5727 \n 25.5875 \n E58 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Compton, Miss. Sara Rebecca \n 1 \n 1 \n PC 17756 \n 83.1583 \n E49 \n C \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n Compton, Mr. Alexander Taylor Jr \n 1 \n 1 \n PC 17756 \n 83.1583 \n E52 \n C \n \n \n female \n 64.0000 \n 64.00000 \n 1 \n 1 \n Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll) \n 0 \n 2 \n PC 17756 \n 83.1583 \n E45 \n C \n \n \n female \n 55.0000 \n 55.00000 \n 1 \n 1 \n Cornell, Mrs. Robert Clifford (Malvina Helen Lamson) \n 2 \n 0 \n 11770 \n 25.7000 \n C101 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Crafton, Mr. John Bertram \n 0 \n 0 \n 113791 \n 26.5500 \n NA \n S \n \n \n male \n 70.0000 \n 70.00000 \n 1 \n 0 \n Crosby, Capt. Edward Gifford \n 1 \n 1 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Crosby, Miss. Harriet R \n 0 \n 2 \n WE/P 5735 \n 71.0000 \n B22 \n S \n \n \n female \n 64.0000 \n 64.00000 \n 1 \n 1 \n Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead) \n 1 \n 1 \n 112901 \n 26.5500 \n B26 \n S \n \n \n male \n 39.0000 \n 39.00000 \n 1 \n 0 \n Cumings, Mr. John Bradley \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n female \n 38.0000 \n 38.00000 \n 1 \n 1 \n Cumings, Mrs. John Bradley (Florence Briggs Thayer) \n 1 \n 0 \n PC 17599 \n 71.2833 \n C85 \n C \n \n \n male \n 51.0000 \n 51.00000 \n 1 \n 1 \n Daly, Mr. Peter Denis \n 0 \n 0 \n 113055 \n 26.5500 \n E17 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 1 \n Daniel, Mr. Robert Williams \n 0 \n 0 \n 113804 \n 30.5000 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Daniels, Miss. Sarah \n 0 \n 0 \n 113781 \n 151.5500 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n Davidson, Mr. Thornton \n 1 \n 0 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n female \n 27.0000 \n 27.00000 \n 1 \n 1 \n Davidson, Mrs. Thornton (Orian Hays) \n 1 \n 2 \n F.C. 12750 \n 52.0000 \n B71 \n S \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n Dick, Mr. Albert Adrian \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n female \n 17.0000 \n 17.00000 \n 1 \n 1 \n Dick, Mrs. Albert Adrian (Vera Gillespie) \n 1 \n 0 \n 17474 \n 57.0000 \n B20 \n S \n \n \n male \n 53.0000 \n 53.00000 \n 1 \n 1 \n Dodge, Dr. Washington \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n male \n 4.0000 \n 4.00000 \n 1 \n 1 \n Dodge, Master. Washington \n 0 \n 2 \n 33638 \n 81.8583 \n A34 \n S \n \n \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n Dodge, Mrs. Washington (Ruth Vidaver) \n 1 \n 1 \n 33638 \n 81.8583 \n A34 \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Douglas, Mr. Walter Donald \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n female \n 27.0000 \n 27.00000 \n 1 \n 1 \n Douglas, Mrs. Frederick Charles (Mary Helene Baxter) \n 1 \n 1 \n PC 17558 \n 247.5208 \n B58 B60 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Douglas, Mrs. Walter Donald (Mahala Dutton) \n 1 \n 0 \n PC 17761 \n 106.4250 \n C86 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\") \n 1 \n 0 \n 11755 \n 39.6000 \n A16 \n C \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\") \n 1 \n 0 \n PC 17485 \n 56.9292 \n A20 \n C \n \n \n male \n 39.0000 \n 39.00000 \n 1 \n 0 \n Dulles, Mr. William Crothers \n 0 \n 0 \n PC 17580 \n 29.7000 \n A18 \n C \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Earnshaw, Mrs. Boulton (Olive Potter) \n 0 \n 1 \n 11767 \n 83.1583 \n C54 \n C \n \n \n female \n 38.0000 \n 38.00000 \n 1 \n 1 \n Endres, Miss. Caroline Louise \n 0 \n 0 \n PC 17757 \n 227.5250 \n C45 \n C \n \n \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n Eustis, Miss. Elizabeth Mussey \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 0 \n Evans, Miss. Edith Corse \n 0 \n 0 \n PC 17531 \n 31.6792 \n A29 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Farthing, Mr. John \n 0 \n 0 \n PC 17483 \n 221.7792 \n C95 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Flegenheim, Mrs. Alfred (Antoinette) \n 0 \n 0 \n PC 17598 \n 31.6833 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Fleming, Miss. Margaret \n 0 \n 0 \n 17421 \n 110.8833 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n Flynn, Mr. John Irwin (\"Irving\") \n 0 \n 0 \n PC 17474 \n 26.3875 \n E25 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Foreman, Mr. Benjamin Laventall \n 0 \n 0 \n 113051 \n 27.7500 \n C111 \n C \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Fortune, Miss. Alice Elizabeth \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 28.0000 \n 28.00000 \n 1 \n 1 \n Fortune, Miss. Ethel Flora \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Fortune, Miss. Mabel Helen \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n male \n 19.0000 \n 19.00000 \n 1 \n 0 \n Fortune, Mr. Charles Alexander \n 3 \n 2 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n Fortune, Mr. Mark \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 60.0000 \n 60.00000 \n 1 \n 1 \n Fortune, Mrs. Mark (Mary McDougald) \n 1 \n 4 \n 19950 \n 263.0000 \n C23 C25 C27 \n S \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Francatelli, Miss. Laura Mabel \n 0 \n 0 \n PC 17485 \n 56.9292 \n E36 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Franklin, Mr. Thomas Parham \n 0 \n 0 \n 113778 \n 26.5500 \n D34 \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 1 \n Frauenthal, Dr. Henry William \n 2 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 1 \n 1 \n Frauenthal, Mr. Isaac Gerald \n 1 \n 0 \n 17765 \n 27.7208 \n D40 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Frauenthal, Mrs. Henry William (Clara Heinsheimer) \n 1 \n 0 \n PC 17611 \n 133.6500 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Frolicher, Miss. Hedwig Margaritha \n 0 \n 2 \n 13568 \n 49.5000 \n B39 \n C \n \n \n male \n 60.0000 \n 60.00000 \n 1 \n 1 \n Frolicher-Stehli, Mr. Maxmillian \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli) \n 1 \n 1 \n 13567 \n 79.2000 \n B41 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Fry, Mr. Richard \n 0 \n 0 \n 112058 \n 0.0000 \n B102 \n S \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n Futrelle, Mr. Jacques Heath \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Futrelle, Mrs. Jacques Heath (Lily May Peel) \n 1 \n 0 \n 113803 \n 53.1000 \n C123 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Gee, Mr. Arthur H \n 0 \n 0 \n 111320 \n 38.5000 \n E63 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Geiger, Miss. Amalie \n 0 \n 0 \n 113503 \n 211.5000 \n C130 \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Gibson, Miss. Dorothy Winifred \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Gibson, Mrs. Leonard (Pauline C Boeson) \n 0 \n 1 \n 112378 \n 59.4000 \n NA \n C \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n Giglio, Mr. Victor \n 0 \n 0 \n PC 17593 \n 79.2000 \n B86 \n C \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n Goldenberg, Mr. Samuel L \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Goldenberg, Mrs. Samuel L (Edwiga Grabowska) \n 1 \n 0 \n 17453 \n 89.1042 \n C92 \n C \n \n \n male \n 71.0000 \n 71.00000 \n 1 \n 0 \n Goldschmidt, Mr. George B \n 0 \n 0 \n PC 17754 \n 34.6542 \n A5 \n C \n \n \n male \n 53.0000 \n 53.00000 \n 1 \n 1 \n Gracie, Col. Archibald IV \n 0 \n 0 \n 113780 \n 28.5000 \n C51 \n C \n \n \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n Graham, Miss. Margaret Edith \n 0 \n 0 \n 112053 \n 30.0000 \n B42 \n S \n \n \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n Graham, Mr. George Edward \n 0 \n 1 \n PC 17582 \n 153.4625 \n C91 \n S \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Graham, Mrs. William Thompson (Edith Junkins) \n 0 \n 1 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n male \n 23.0000 \n 23.00000 \n 1 \n 1 \n Greenfield, Mr. William Bertram \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Greenfield, Mrs. Leo David (Blanche Strouse) \n 0 \n 1 \n PC 17759 \n 63.3583 \n D10 D12 \n C \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Guggenheim, Mr. Benjamin \n 0 \n 0 \n PC 17593 \n 79.2000 \n B82 B84 \n C \n \n \n male \n 25.0000 \n 25.00000 \n 1 \n 1 \n Harder, Mr. George Achilles \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n female \n 25.0000 \n 25.00000 \n 1 \n 1 \n Harder, Mrs. George Achilles (Dorothy Annan) \n 1 \n 0 \n 11765 \n 55.4417 \n E50 \n C \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 1 \n Harper, Mr. Henry Sleeper \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n female \n 49.0000 \n 49.00000 \n 1 \n 1 \n Harper, Mrs. Henry Sleeper (Myna Haxtun) \n 1 \n 0 \n PC 17572 \n 76.7292 \n D33 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Harrington, Mr. Charles H \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 0 \n Harris, Mr. Henry Birkhardt \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Harris, Mrs. Henry Birkhardt (Irene Wallach) \n 1 \n 0 \n 36973 \n 83.4750 \n C83 \n S \n \n \n male \n 40.0000 \n 40.00000 \n 1 \n 0 \n Harrison, Mr. William \n 0 \n 0 \n 112059 \n 0.0000 \n B94 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 1 \n Hassab, Mr. Hammad \n 0 \n 0 \n PC 17572 \n 76.7292 \n D49 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Hawksford, Mr. Walter James \n 0 \n 0 \n 16988 \n 30.0000 \n D45 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Hays, Miss. Margaret Bechstein \n 0 \n 0 \n 11767 \n 83.1583 \n C54 \n C \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Hays, Mr. Charles Melville \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n female \n 52.0000 \n 52.00000 \n 1 \n 1 \n Hays, Mrs. Charles Melville (Clara Jennings Gregg) \n 1 \n 1 \n 12749 \n 93.5000 \n B69 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Head, Mr. Christopher \n 0 \n 0 \n 113038 \n 42.5000 \n B11 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Hilliard, Mr. Herbert Henry \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Hipkins, Mr. William Edward \n 0 \n 0 \n 680 \n 50.0000 \n C39 \n S \n \n \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n Hippach, Miss. Jean Gertrude \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n female \n 44.0000 \n 44.00000 \n 1 \n 1 \n Hippach, Mrs. Louis Albert (Ida Sophia Fischer) \n 0 \n 1 \n 111361 \n 57.9792 \n B18 \n C \n \n \n female \n 51.0000 \n 51.00000 \n 1 \n 1 \n Hogeboom, Mrs. John C (Anna Andrews) \n 1 \n 0 \n 13502 \n 77.9583 \n D11 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Holverson, Mr. Alexander Oskar \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Holverson, Mrs. Alexander Oskar (Mary Aline Towner) \n 1 \n 0 \n 113789 \n 52.0000 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 1 \n 1 \n Homer, Mr. Harry (\"Mr E Haven\") \n 0 \n 0 \n 111426 \n 26.5500 \n NA \n C \n \n \n male \n 38.0000 \n 38.00000 \n 1 \n 1 \n Hoyt, Mr. Frederick Maxfield \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Hoyt, Mr. William Fisher \n 0 \n 0 \n PC 17600 \n 30.6958 \n NA \n C \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby) \n 1 \n 0 \n 19943 \n 90.0000 \n C93 \n S \n \n \n female \n 38.0000 \n 38.00000 \n 1 \n 1 \n Icard, Miss. Amelie \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n female \n 50.0000 \n 50.00000 \n 1 \n 0 \n Isham, Miss. Ann Elizabeth \n 0 \n 0 \n PC 17595 \n 28.7125 \n C49 \n C \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 1 \n Ismay, Mr. Joseph Bruce \n 0 \n 0 \n 112058 \n 0.0000 \n B52 B54 B56 \n S \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Jones, Mr. Charles Cresson \n 0 \n 0 \n 694 \n 26.0000 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Julian, Mr. Henry Forbes \n 0 \n 0 \n 113044 \n 26.0000 \n E60 \n S \n \n \n male \n 32.5000 \n 32.50000 \n 1 \n 0 \n Keeping, Mr. Edwin \n 0 \n 0 \n 113503 \n 211.5000 \n C132 \n C \n \n \n male \n 58.0000 \n 58.00000 \n 1 \n 0 \n Kent, Mr. Edward Austin \n 0 \n 0 \n 11771 \n 29.7000 \n B37 \n C \n \n \n male \n 41.0000 \n 41.00000 \n 1 \n 0 \n Kenyon, Mr. Frederick R \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Kenyon, Mrs. Frederick R (Marion) \n 1 \n 0 \n 17464 \n 51.8625 \n D21 \n S \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 1 \n Kimball, Mr. Edwin Nelson Jr \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons) \n 1 \n 0 \n 11753 \n 52.5542 \n D19 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Klaber, Mr. Herman \n 0 \n 0 \n 113028 \n 26.5500 \n C124 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Kreuchen, Miss. Emilie \n 0 \n 0 \n 24160 \n 211.3375 \n NA \n S \n \n \n female \n 49.0000 \n 49.00000 \n 1 \n 1 \n Leader, Dr. Alice (Farnham) \n 0 \n 0 \n 17465 \n 25.9292 \n D17 \n S \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n LeRoy, Miss. Bertha \n 0 \n 0 \n PC 17761 \n 106.4250 \n NA \n C \n \n \n male \n 35.0000 \n 35.00000 \n 1 \n 1 \n Lesurer, Mr. Gustave J \n 0 \n 0 \n PC 17755 \n 512.3292 \n B101 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Lewy, Mr. Ervin G \n 0 \n 0 \n PC 17612 \n 27.7208 \n NA \n C \n \n \n male \n 42.0000 \n 42.00000 \n 1 \n 0 \n Lindeberg-Lind, Mr. Erik Gustaf (\"Mr Edward Lingrey\") \n 0 \n 0 \n 17475 \n 26.5500 \n NA \n S \n \n \n female \n 55.0000 \n 55.00000 \n 1 \n 1 \n Lindstrom, Mrs. Carl Johan (Sigrid Posse) \n 0 \n 0 \n 112377 \n 27.7208 \n NA \n C \n \n \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n Lines, Miss. Mary Conover \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n female \n 51.0000 \n 51.00000 \n 1 \n 1 \n Lines, Mrs. Ernest H (Elizabeth Lindsey James) \n 0 \n 1 \n PC 17592 \n 39.4000 \n D28 \n S \n \n \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n Long, Mr. Milton Clyde \n 0 \n 0 \n 113501 \n 30.0000 \n D6 \n S \n \n \n female \n 21.0000 \n 21.00000 \n 1 \n 1 \n Longley, Miss. Gretchen Fiske \n 0 \n 0 \n 13502 \n 77.9583 \n D9 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Loring, Mr. Joseph Holland \n 0 \n 0 \n 113801 \n 45.5000 \n NA \n S \n \n \n female \n 58.0000 \n 58.00000 \n 1 \n 1 \n Lurette, Miss. Elise \n 0 \n 0 \n PC 17569 \n 146.5208 \n B80 \n C \n \n \n female \n 15.0000 \n 15.00000 \n 1 \n 1 \n Madill, Miss. Georgette Alexandra \n 0 \n 1 \n 24160 \n 211.3375 \n B5 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 0 \n Maguire, Mr. John Edward \n 0 \n 0 \n 110469 \n 26.0000 \n C106 \n S \n \n \n female \n 16.0000 \n 16.00000 \n 1 \n 1 \n Maioni, Miss. Roberta \n 0 \n 0 \n 110152 \n 86.5000 \n B79 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Marechal, Mr. Pierre \n 0 \n 0 \n 11774 \n 29.7000 \n C47 \n C \n \n \n male \n 19.0000 \n 19.00000 \n 1 \n 0 \n Marvin, Mr. Daniel Warner \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson) \n 1 \n 0 \n 113773 \n 53.1000 \n D30 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Mayne, Mlle. Berthe Antonine (\"Mrs de Villiers\") \n 0 \n 0 \n PC 17482 \n 49.5042 \n C90 \n C \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n McCaffry, Mr. Thomas Francis \n 0 \n 0 \n 13050 \n 75.2417 \n C6 \n C \n \n \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n McCarthy, Mr. Timothy J \n 0 \n 0 \n 17463 \n 51.8625 \n E46 \n S \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 1 \n McGough, Mr. James Robert \n 0 \n 0 \n PC 17473 \n 26.2875 \n E25 \n S \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 0 \n Meyer, Mr. Edgar Joseph \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Meyer, Mrs. Edgar Joseph (Leila Saks) \n 1 \n 0 \n PC 17604 \n 82.1708 \n NA \n C \n \n \n male \n 65.0000 \n 65.00000 \n 1 \n 0 \n Millet, Mr. Francis Davis \n 0 \n 0 \n 13509 \n 26.5500 \n E38 \n S \n \n \n male \n 44.0000 \n 44.00000 \n 1 \n 0 \n Minahan, Dr. William Edward \n 2 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Minahan, Miss. Daisy E \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n female \n 37.0000 \n 37.00000 \n 1 \n 1 \n Minahan, Mrs. William Edward (Lillian E Thorpe) \n 1 \n 0 \n 19928 \n 90.0000 \n C78 \n Q \n \n \n male \n 30.0000 \n 30.00000 \n 1 \n 1 \n Mock, Mr. Philipp Edmund \n 1 \n 0 \n 13236 \n 57.7500 \n C78 \n C \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Molson, Mr. Harry Markland \n 0 \n 0 \n 113787 \n 30.5000 \n C30 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Moore, Mr. Clarence Bloomfield \n 0 \n 0 \n 113796 \n 42.4000 \n NA \n S \n \n \n male \n 37.0000 \n 37.00000 \n 1 \n 0 \n Natsch, Mr. Charles H \n 0 \n 1 \n PC 17596 \n 29.7000 \n C118 \n C \n \n \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n Newell, Miss. Madeleine \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Newell, Miss. Marjorie \n 1 \n 0 \n 35273 \n 113.2750 \n D36 \n C \n \n \n male \n 58.0000 \n 58.00000 \n 1 \n 0 \n Newell, Mr. Arthur Webster \n 0 \n 2 \n 35273 \n 113.2750 \n D48 \n C \n \n \n female \n 19.0000 \n 19.00000 \n 1 \n 1 \n Newsom, Miss. Helen Monypeny \n 0 \n 2 \n 11752 \n 26.2833 \n D47 \n S \n \n \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n Nicholson, Mr. Arthur Ernest \n 0 \n 0 \n 693 \n 26.0000 \n NA \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Oliva y Ocana, Dona. Fermina \n 0 \n 0 \n PC 17758 \n 108.9000 \n C105 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Omont, Mr. Alfred Fernand \n 0 \n 0 \n F.C. 12998 \n 25.7417 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Ostby, Miss. Helene Ragnhild \n 0 \n 1 \n 113509 \n 61.9792 \n B36 \n C \n \n \n male \n 65.0000 \n 65.00000 \n 1 \n 0 \n Ostby, Mr. Engelhart Cornelius \n 0 \n 1 \n 113509 \n 61.9792 \n B30 \n C \n \n \n male \n 28.5000 \n 28.50000 \n 1 \n 0 \n Ovies y Rodriguez, Mr. Servando \n 0 \n 0 \n PC 17562 \n 27.7208 \n D43 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Parr, Mr. William Henry Marsh \n 0 \n 0 \n 112052 \n 0.0000 \n NA \n S \n \n \n male \n 45.5000 \n 45.50000 \n 1 \n 0 \n Partner, Mr. Austen \n 0 \n 0 \n 113043 \n 28.5000 \n C124 \n S \n \n \n male \n 23.0000 \n 23.00000 \n 1 \n 0 \n Payne, Mr. Vivian Ponsonby \n 0 \n 0 \n 12749 \n 93.5000 \n B24 \n S \n \n \n male \n 29.0000 \n 29.00000 \n 1 \n 0 \n Pears, Mr. Thomas Clinton \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n female \n 22.0000 \n 22.00000 \n 1 \n 1 \n Pears, Mrs. Thomas (Edith Wearne) \n 1 \n 0 \n 113776 \n 66.6000 \n C2 \n S \n \n \n male \n 18.0000 \n 18.00000 \n 1 \n 0 \n Penasco y Castellana, Mr. Victor de Satode \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n female \n 17.0000 \n 17.00000 \n 1 \n 1 \n Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo) \n 1 \n 0 \n PC 17758 \n 108.9000 \n C65 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Perreault, Miss. Anne \n 0 \n 0 \n 12749 \n 93.5000 \n B73 \n S \n \n \n male \n 52.0000 \n 52.00000 \n 1 \n 1 \n Peuchen, Major. Arthur Godfrey \n 0 \n 0 \n 113786 \n 30.5000 \n C104 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Porter, Mr. Walter Chamberlain \n 0 \n 0 \n 110465 \n 52.0000 \n C110 \n S \n \n \n female \n 56.0000 \n 56.00000 \n 1 \n 1 \n Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) \n 0 \n 1 \n 11767 \n 83.1583 \n C50 \n C \n \n \n male \n 38.0000 \n 38.00000 \n 1 \n 0 \n Reuchlin, Jonkheer. John George \n 0 \n 0 \n 19972 \n 0.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Rheims, Mr. George Alexander Lucien \n 0 \n 0 \n PC 17607 \n 39.6000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 1 \n 0 \n Ringhini, Mr. Sante \n 0 \n 0 \n PC 17760 \n 135.6333 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Robbins, Mr. Victor \n 0 \n 0 \n PC 17757 \n 227.5250 \n NA \n C \n \n \n female \n 43.0000 \n 43.00000 \n 1 \n 1 \n Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) \n 0 \n 1 \n 24160 \n 211.3375 \n B3 \n S \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 0 \n Roebling, Mr. Washington Augustus II \n 0 \n 0 \n PC 17590 \n 50.4958 \n A24 \n S \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n Romaine, Mr. Charles Hallace (\"Mr C Rolmane\") \n 0 \n 0 \n 111428 \n 26.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Rood, Mr. Hugh Roscoe \n 0 \n 0 \n 113767 \n 50.0000 \n A32 \n S \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Rosenbaum, Miss. Edith Louise \n 0 \n 0 \n PC 17613 \n 27.7208 \n A11 \n C \n \n \n male \n 46.0000 \n 46.00000 \n 1 \n 0 \n Rosenshine, Mr. George (\"Mr George Thorne\") \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 1 \n 0 \n Ross, Mr. John Hugo \n 0 \n 0 \n 13049 \n 40.1250 \n A10 \n C \n \n \n female \n 33.0000 \n 33.00000 \n 1 \n 1 \n Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) \n 0 \n 0 \n 110152 \n 86.5000 \n B77 \n S \n \n \n male \n 55.0000 \n 55.00000 \n 1 \n 0 \n Rothschild, Mr. Martin \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n female \n 54.0000 \n 54.00000 \n 1 \n 1 \n Rothschild, Mrs. Martin (Elizabeth L. Barrett) \n 1 \n 0 \n PC 17603 \n 59.4000 \n NA \n C \n \n \n male \n 33.0000 \n 33.00000 \n 1 \n 0 \n Rowe, Mr. Alfred G \n 0 \n 0 \n 113790 \n 26.5500 \n NA \n S \n \n \n male \n 13.0000 \n 13.00000 \n 1 \n 1 \n Ryerson, Master. John Borie \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Ryerson, Miss. Emily Borie \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n female \n 21.0000 \n 21.00000 \n 1 \n 1 \n Ryerson, Miss. Susan Parker \"Suzette\" \n 2 \n 2 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n male \n 61.0000 \n 61.00000 \n 1 \n 0 \n Ryerson, Mr. Arthur Larned \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Ryerson, Mrs. Arthur Larned (Emily Maria Borie) \n 1 \n 3 \n PC 17608 \n 262.3750 \n B57 B59 B63 B66 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Saalfeld, Mr. Adolphe \n 0 \n 0 \n 19988 \n 30.5000 \n C106 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 1 \n 1 \n Sagesser, Mlle. Emma \n 0 \n 0 \n PC 17477 \n 69.3000 \n B35 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Salomon, Mr. Abraham L \n 0 \n 0 \n 111163 \n 26.0000 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Schabert, Mrs. Paul (Emma Mock) \n 1 \n 0 \n 13236 \n 57.7500 \n C28 \n C \n \n \n female \n 30.0000 \n 30.00000 \n 1 \n 1 \n Serepeca, Miss. Augusta \n 0 \n 0 \n 113798 \n 31.0000 \n NA \n C \n \n \n male \n 34.0000 \n 34.00000 \n 1 \n 1 \n Seward, Mr. Frederic Kimber \n 0 \n 0 \n 113794 \n 26.5500 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n Shutes, Miss. Elizabeth W \n 0 \n 0 \n PC 17582 \n 153.4625 \n C125 \n S \n \n \n male \n 35.0000 \n 35.00000 \n 1 \n 1 \n Silverthorne, Mr. Spencer Victor \n 0 \n 0 \n PC 17475 \n 26.2875 \n E24 \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Silvey, Mr. William Baird \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Silvey, Mrs. William Baird (Alice Munger) \n 1 \n 0 \n 13507 \n 55.9000 \n E44 \n S \n \n \n male \n 56.0000 \n 56.00000 \n 1 \n 1 \n Simonius-Blumer, Col. Oberst Alfons \n 0 \n 0 \n 13213 \n 35.5000 \n A26 \n C \n \n \n male \n 28.0000 \n 28.00000 \n 1 \n 1 \n Sloper, Mr. William Thompson \n 0 \n 0 \n 113788 \n 35.5000 \n A6 \n S \n \n \n male \n 56.0000 \n 56.00000 \n 1 \n 0 \n Smart, Mr. John Montgomery \n 0 \n 0 \n 113792 \n 26.5500 \n NA \n S \n \n \n male \n 56.0000 \n 56.00000 \n 1 \n 0 \n Smith, Mr. James Clinch \n 0 \n 0 \n 17764 \n 30.6958 \n A7 \n C \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 0 \n Smith, Mr. Lucien Philip \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Smith, Mr. Richard William \n 0 \n 0 \n 113056 \n 26.0000 \n A19 \n S \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Smith, Mrs. Lucien Philip (Mary Eloise Hughes) \n 1 \n 0 \n 13695 \n 60.0000 \n C31 \n S \n \n \n male \n 24.0000 \n 24.00000 \n 1 \n 1 \n Snyder, Mr. John Pillsbury \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n female \n 23.0000 \n 23.00000 \n 1 \n 1 \n Snyder, Mrs. John Pillsbury (Nelle Stevenson) \n 1 \n 0 \n 21228 \n 82.2667 \n B45 \n S \n \n \n male \n 6.0000 \n 6.00000 \n 1 \n 1 \n Spedden, Master. Robert Douglas \n 0 \n 2 \n 16966 \n 134.5000 \n E34 \n C \n \n \n male \n 45.0000 \n 45.00000 \n 1 \n 1 \n Spedden, Mr. Frederic Oakley \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n female \n 40.0000 \n 40.00000 \n 1 \n 1 \n Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) \n 1 \n 1 \n 16966 \n 134.5000 \n E34 \n C \n \n \n male \n 57.0000 \n 57.00000 \n 1 \n 0 \n Spencer, Mr. William Augustus \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Spencer, Mrs. William Augustus (Marie Eugenie) \n 1 \n 0 \n PC 17569 \n 146.5208 \n B78 \n C \n \n \n male \n 32.0000 \n 32.00000 \n 1 \n 1 \n Stahelin-Maeglin, Dr. Max \n 0 \n 0 \n 13214 \n 30.5000 \n B50 \n C \n \n \n male \n 62.0000 \n 62.00000 \n 1 \n 0 \n Stead, Mr. William Thomas \n 0 \n 0 \n 113514 \n 26.5500 \n C87 \n S \n \n \n male \n 54.0000 \n 54.00000 \n 1 \n 1 \n Stengel, Mr. Charles Emil Henry \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n female \n 43.0000 \n 43.00000 \n 1 \n 1 \n Stengel, Mrs. Charles Emil Henry (Annie May Morris) \n 1 \n 0 \n 11778 \n 55.4417 \n C116 \n C \n \n \n female \n 52.0000 \n 52.00000 \n 1 \n 1 \n Stephenson, Mrs. Walter Bertram (Martha Eustis) \n 1 \n 0 \n 36947 \n 78.2667 \n D20 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Stewart, Mr. Albert A \n 0 \n 0 \n PC 17605 \n 27.7208 \n NA \n C \n \n \n female \n 62.0000 \n 62.00000 \n 1 \n 1 \n Stone, Mrs. George Nelson (Martha Evelyn) \n 0 \n 0 \n 113572 \n 80.0000 \n B28 \n NA \n \n \n male \n 67.0000 \n 67.00000 \n 1 \n 0 \n Straus, Mr. Isidor \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n female \n 63.0000 \n 63.00000 \n 1 \n 0 \n Straus, Mrs. Isidor (Rosalie Ida Blun) \n 1 \n 0 \n PC 17483 \n 221.7792 \n C55 C57 \n S \n \n \n male \n 61.0000 \n 61.00000 \n 1 \n 0 \n Sutton, Mr. Frederick \n 0 \n 0 \n 36963 \n 32.3208 \n D50 \n S \n \n \n female \n 48.0000 \n 48.00000 \n 1 \n 1 \n Swift, Mrs. Frederick Joel (Margaret Welles Barron) \n 0 \n 0 \n 17466 \n 25.9292 \n D17 \n S \n \n \n female \n 18.0000 \n 18.00000 \n 1 \n 1 \n Taussig, Miss. Ruth \n 0 \n 2 \n 110413 \n 79.6500 \n E68 \n S \n \n \n male \n 52.0000 \n 52.00000 \n 1 \n 0 \n Taussig, Mr. Emil \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Taussig, Mrs. Emil (Tillie Mandelbaum) \n 1 \n 1 \n 110413 \n 79.6500 \n E67 \n S \n \n \n male \n 48.0000 \n 48.00000 \n 1 \n 1 \n Taylor, Mr. Elmer Zebley \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright) \n 1 \n 0 \n 19996 \n 52.0000 \n C126 \n S \n \n \n male \n 49.0000 \n 49.00000 \n 1 \n 0 \n Thayer, Mr. John Borland \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n male \n 17.0000 \n 17.00000 \n 1 \n 1 \n Thayer, Mr. John Borland Jr \n 0 \n 2 \n 17421 \n 110.8833 \n C70 \n C \n \n \n female \n 39.0000 \n 39.00000 \n 1 \n 1 \n Thayer, Mrs. John Borland (Marian Longstreth Morris) \n 1 \n 1 \n 17421 \n 110.8833 \n C68 \n C \n \n \n female \n NA \n 28.62425 \n 1 \n 1 \n Thorne, Mrs. Gertrude Maybelle \n 0 \n 0 \n PC 17585 \n 79.2000 \n NA \n C \n \n \n male \n 31.0000 \n 31.00000 \n 1 \n 1 \n Tucker, Mr. Gilbert Milligan Jr \n 0 \n 0 \n 2543 \n 28.5375 \n C53 \n C \n \n \n male \n 40.0000 \n 40.00000 \n 1 \n 0 \n Uruchurtu, Don. Manuel E \n 0 \n 0 \n PC 17601 \n 27.7208 \n NA \n C \n \n \n male \n 61.0000 \n 61.00000 \n 1 \n 0 \n Van der hoef, Mr. Wyckoff \n 0 \n 0 \n 111240 \n 33.5000 \n B19 \n S \n \n \n male \n 47.0000 \n 47.00000 \n 1 \n 0 \n Walker, Mr. William Anderson \n 0 \n 0 \n 36967 \n 34.0208 \n D46 \n S \n \n \n female \n 35.0000 \n 35.00000 \n 1 \n 1 \n Ward, Miss. Anna \n 0 \n 0 \n PC 17755 \n 512.3292 \n NA \n C \n \n \n male \n 64.0000 \n 64.00000 \n 1 \n 0 \n Warren, Mr. Frank Manley \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n female \n 60.0000 \n 60.00000 \n 1 \n 1 \n Warren, Mrs. Frank Manley (Anna Sophia Atkinson) \n 1 \n 0 \n 110813 \n 75.2500 \n D37 \n C \n \n \n male \n 60.0000 \n 60.00000 \n 1 \n 0 \n Weir, Col. John \n 0 \n 0 \n 113800 \n 26.5500 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 1 \n 0 \n White, Mr. Percival Wayland \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n male \n 21.0000 \n 21.00000 \n 1 \n 0 \n White, Mr. Richard Frasar \n 0 \n 1 \n 35281 \n 77.2875 \n D26 \n S \n \n \n female \n 55.0000 \n 55.00000 \n 1 \n 1 \n White, Mrs. John Stuart (Ella Holmes) \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n Wick, Miss. Mary Natalie \n 0 \n 2 \n 36928 \n 164.8667 \n C7 \n S \n \n \n male \n 57.0000 \n 57.00000 \n 1 \n 0 \n Wick, Mr. George Dennick \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 1 \n 1 \n Wick, Mrs. George Dennick (Mary Hitchcock) \n 1 \n 1 \n 36928 \n 164.8667 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 1 \n 0 \n Widener, Mr. George Dunton \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n male \n 27.0000 \n 27.00000 \n 1 \n 0 \n Widener, Mr. Harry Elkins \n 0 \n 2 \n 113503 \n 211.5000 \n C82 \n C \n \n \n female \n 50.0000 \n 50.00000 \n 1 \n 1 \n Widener, Mrs. George Dunton (Eleanor Elkins) \n 1 \n 1 \n 113503 \n 211.5000 \n C80 \n C \n \n \n female \n 21.0000 \n 21.00000 \n 1 \n 1 \n Willard, Miss. Constance \n 0 \n 0 \n 113795 \n 26.5500 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 1 \n 0 \n Williams, Mr. Charles Duane \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n male \n 21.0000 \n 21.00000 \n 1 \n 1 \n Williams, Mr. Richard Norris II \n 0 \n 1 \n PC 17597 \n 61.3792 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 0 \n Williams-Lambert, Mr. Fletcher Fellows \n 0 \n 0 \n 113510 \n 35.0000 \n C128 \n S \n \n \n female \n 31.0000 \n 31.00000 \n 1 \n 1 \n Wilson, Miss. Helen Alice \n 0 \n 0 \n 16966 \n 134.5000 \n E39 E41 \n C \n \n \n male \n NA \n 30.48562 \n 1 \n 1 \n Woolner, Mr. Hugh \n 0 \n 0 \n 19947 \n 35.5000 \n C52 \n S \n \n \n male \n 62.0000 \n 62.00000 \n 1 \n 0 \n Wright, Mr. George \n 0 \n 0 \n 113807 \n 26.5500 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 1 \n 1 \n Young, Miss. Marie Grice \n 0 \n 0 \n PC 17760 \n 135.6333 \n C32 \n C \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Abelson, Mr. Samuel \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Abelson, Mrs. Samuel (Hannah Wizosky) \n 1 \n 0 \n P/PP 3381 \n 24.0000 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Aldworth, Mr. Charles Augustus \n 0 \n 0 \n 248744 \n 13.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Andrew, Mr. Edgardo Samuel \n 0 \n 0 \n 231945 \n 11.5000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Andrew, Mr. Frank Thomas \n 0 \n 0 \n C.A. 34050 \n 10.5000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Angle, Mr. William A \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes) \n 1 \n 0 \n 226875 \n 26.0000 \n NA \n S \n \n \n male \n 57.0000 \n 57.00000 \n 2 \n 0 \n Ashby, Mr. John \n 0 \n 0 \n 244346 \n 13.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Bailey, Mr. Percy Andrew \n 0 \n 0 \n 29108 \n 11.5000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Baimbrigge, Mr. Charles Robert \n 0 \n 0 \n C.A. 31030 \n 10.5000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Ball, Mrs. (Ada E Hall) \n 0 \n 0 \n 28551 \n 13.0000 \n D \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Banfield, Mr. Frederick James \n 0 \n 0 \n C.A./SOTON 34068 \n 10.5000 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 2 \n 0 \n Bateman, Rev. Robert James \n 0 \n 0 \n S.O.P. 1166 \n 12.5250 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 1 \n Beane, Mr. Edward \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 2 \n 1 \n Beane, Mrs. Edward (Ethel Clarke) \n 1 \n 0 \n 2908 \n 26.0000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Beauchamp, Mr. Henry James \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 2 \n 1 \n Becker, Master. Richard F \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n female \n 4.0000 \n 4.00000 \n 2 \n 1 \n Becker, Miss. Marion Louise \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n female \n 12.0000 \n 12.00000 \n 2 \n 1 \n Becker, Miss. Ruth Elizabeth \n 2 \n 1 \n 230136 \n 39.0000 \n F4 \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Becker, Mrs. Allen Oliver (Nellie E Baumgardner) \n 0 \n 3 \n 230136 \n 39.0000 \n F4 \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 1 \n Beesley, Mr. Lawrence \n 0 \n 0 \n 248698 \n 13.0000 \n D56 \n S \n \n \n female \n 19.0000 \n 19.00000 \n 2 \n 1 \n Bentham, Miss. Lilian W \n 0 \n 0 \n 28404 \n 13.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Berriman, Mr. William John \n 0 \n 0 \n 28425 \n 13.0000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Botsford, Mr. William Hull \n 0 \n 0 \n 237670 \n 13.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Bowenur, Mr. Solomon \n 0 \n 0 \n 211535 \n 13.0000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Bracken, Mr. James H \n 0 \n 0 \n 220367 \n 13.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Brown, Miss. Amelia \"Mildred\" \n 0 \n 0 \n 248733 \n 13.0000 \n F33 \n S \n \n \n female \n 15.0000 \n 15.00000 \n 2 \n 1 \n Brown, Miss. Edith Eileen \n 0 \n 2 \n 29750 \n 39.0000 \n NA \n S \n \n \n male \n 60.0000 \n 60.00000 \n 2 \n 0 \n Brown, Mr. Thomas William Solomon \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 2 \n 1 \n Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford) \n 1 \n 1 \n 29750 \n 39.0000 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n Bryhl, Miss. Dagmar Jenny Ingeborg \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Bryhl, Mr. Kurt Arnold Gottfrid \n 1 \n 0 \n 236853 \n 26.0000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 2 \n 1 \n Buss, Miss. Kate \n 0 \n 0 \n 27849 \n 13.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Butler, Mr. Reginald Fenton \n 0 \n 0 \n 234686 \n 13.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Byles, Rev. Thomas Roussel Davids \n 0 \n 0 \n 244310 \n 13.0000 \n NA \n S \n \n \n female \n 42.0000 \n 42.00000 \n 2 \n 1 \n Bystrom, Mrs. (Karolina) \n 0 \n 0 \n 236852 \n 13.0000 \n NA \n S \n \n \n male \n 0.8333 \n 0.83330 \n 2 \n 1 \n Caldwell, Master. Alden Gates \n 0 \n 2 \n 248738 \n 29.0000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 1 \n Caldwell, Mr. Albert Francis \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 1 \n Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh) \n 1 \n 1 \n 248738 \n 29.0000 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 2 \n 1 \n Cameron, Miss. Clear Annie \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Campbell, Mr. William \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Carbines, Mr. William \n 0 \n 0 \n 28424 \n 13.0000 \n NA \n S \n \n \n female \n 44.0000 \n 44.00000 \n 2 \n 0 \n Carter, Mrs. Ernest Courtenay (Lilian Hughes) \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 2 \n 0 \n Carter, Rev. Ernest Courtenay \n 1 \n 0 \n 244252 \n 26.0000 \n NA \n S \n \n \n male \n 52.0000 \n 52.00000 \n 2 \n 0 \n Chapman, Mr. Charles Henry \n 0 \n 0 \n 248731 \n 13.5000 \n NA \n S \n \n \n male \n 37.0000 \n 37.00000 \n 2 \n 0 \n Chapman, Mr. John Henry \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 0 \n Chapman, Mrs. John Henry (Sara Elizabeth Lawry) \n 1 \n 0 \n SC/AH 29037 \n 26.0000 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 2 \n 1 \n Christy, Miss. Julie Rachel \n 1 \n 1 \n 237789 \n 30.0000 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 2 \n 1 \n Christy, Mrs. (Alice Frances) \n 0 \n 2 \n 237789 \n 30.0000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n Clarke, Mr. Charles Valentine \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Clarke, Mrs. Charles V (Ada Maria Winfield) \n 1 \n 0 \n 2003 \n 26.0000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n Coleridge, Mr. Reginald Charles \n 0 \n 0 \n W./C. 14263 \n 10.5000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Collander, Mr. Erik Gustaf \n 0 \n 0 \n 248740 \n 13.0000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 1 \n Collett, Mr. Sidney C Stuart \n 0 \n 0 \n 28034 \n 10.5000 \n NA \n S \n \n \n female \n 8.0000 \n 8.00000 \n 2 \n 1 \n Collyer, Miss. Marjorie \"Lottie\" \n 0 \n 2 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 0 \n Collyer, Mr. Harvey \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 2 \n 1 \n Collyer, Mrs. Harvey (Charlotte Annie Tate) \n 1 \n 1 \n C.A. 31921 \n 26.2500 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 1 \n Cook, Mrs. (Selena Rogers) \n 0 \n 0 \n W./C. 14266 \n 10.5000 \n F33 \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 0 \n Corbett, Mrs. Walter H (Irene Colvin) \n 0 \n 0 \n 237249 \n 13.0000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 2 \n 0 \n Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller) \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Cotterill, Mr. Henry \"Harry\" \n 0 \n 0 \n 29107 \n 11.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Cunningham, Mr. Alfred Fleming \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n male \n 8.0000 \n 8.00000 \n 2 \n 1 \n Davies, Master. John Morgan Jr \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Davies, Mr. Charles Henry \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n female \n 48.0000 \n 48.00000 \n 2 \n 1 \n Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) \n 0 \n 2 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Davis, Miss. Mary \n 0 \n 0 \n 237668 \n 13.0000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n de Brito, Mr. Jose Joaquim \n 0 \n 0 \n 244360 \n 13.0000 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 2 \n 0 \n Deacon, Mr. Percy William \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n del Carlo, Mr. Sebastiano \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n del Carlo, Mrs. Sebastiano (Argenia Genovesi) \n 1 \n 0 \n SC/PARIS 2167 \n 27.7208 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Denbury, Mr. Herbert \n 0 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Dibden, Mr. William \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 2 \n 1 \n Doling, Miss. Elsie \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Doling, Mrs. John T (Ada Julia Bone) \n 0 \n 1 \n 231919 \n 23.0000 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 2 \n 0 \n Downton, Mr. William James \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n male \n 8.0000 \n 8.00000 \n 2 \n 1 \n Drew, Master. Marshall Brines \n 0 \n 2 \n 28220 \n 32.5000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Drew, Mr. James Vivian \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Drew, Mrs. James Vivian (Lulu Thorne Christian) \n 1 \n 1 \n 28220 \n 32.5000 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 2 \n 1 \n Duran y More, Miss. Asuncion \n 1 \n 0 \n SC/PARIS 2149 \n 13.8583 \n NA \n C \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Duran y More, Miss. Florentina \n 1 \n 0 \n SC/PARIS 2148 \n 13.8583 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Eitemiller, Mr. George Floyd \n 0 \n 0 \n 29751 \n 13.0000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Enander, Mr. Ingvar \n 0 \n 0 \n 236854 \n 13.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Fahlstrom, Mr. Arne Jonas \n 0 \n 0 \n 236171 \n 13.0000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 2 \n 0 \n Faunthorpe, Mr. Harry \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson) \n 1 \n 0 \n 2926 \n 26.0000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 2 \n 0 \n Fillbrook, Mr. Joseph Charles \n 0 \n 0 \n C.A. 15185 \n 10.5000 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Fox, Mr. Stanley Hubert \n 0 \n 0 \n 229236 \n 13.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Frost, Mr. Anthony Wood \"Archie\" \n 0 \n 0 \n 239854 \n 0.0000 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 2 \n 0 \n Funk, Miss. Annie Clemmer \n 0 \n 0 \n 237671 \n 13.0000 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 2 \n 0 \n Fynney, Mr. Joseph J \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 2 \n 0 \n Gale, Mr. Harry \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Gale, Mr. Shadrach \n 1 \n 0 \n 28664 \n 21.0000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Garside, Miss. Ethel \n 0 \n 0 \n 243880 \n 13.0000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 2 \n 0 \n Gaskell, Mr. Alfred \n 0 \n 0 \n 239865 \n 26.0000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Gavey, Mr. Lawrence \n 0 \n 0 \n 31028 \n 10.5000 \n NA \n S \n \n \n male \n 47.0000 \n 47.00000 \n 2 \n 0 \n Gilbert, Mr. William \n 0 \n 0 \n C.A. 30769 \n 10.5000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Giles, Mr. Edgar \n 1 \n 0 \n 28133 \n 11.5000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Giles, Mr. Frederick Edward \n 1 \n 0 \n 28134 \n 11.5000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Giles, Mr. Ralph \n 0 \n 0 \n 248726 \n 13.5000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Gill, Mr. John William \n 0 \n 0 \n 233866 \n 13.0000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Gillespie, Mr. William Henry \n 0 \n 0 \n 12233 \n 13.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Givard, Mr. Hans Kristensen \n 0 \n 0 \n 250646 \n 13.0000 \n NA \n S \n \n \n male \n 52.0000 \n 52.00000 \n 2 \n 0 \n Greenberg, Mr. Samuel \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Hale, Mr. Reginald \n 0 \n 0 \n 250653 \n 13.0000 \n NA \n S \n \n \n male \n 0.6667 \n 0.66670 \n 2 \n 1 \n Hamalainen, Master. Viljo \n 1 \n 1 \n 250649 \n 14.5000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Hamalainen, Mrs. William (Anna) \n 0 \n 2 \n 250649 \n 14.5000 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 2 \n 0 \n Harbeck, Mr. William H \n 0 \n 0 \n 248746 \n 13.0000 \n NA \n S \n \n \n female \n 6.0000 \n 6.00000 \n 2 \n 1 \n Harper, Miss. Annie Jessie \"Nina\" \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Harper, Rev. John \n 0 \n 1 \n 248727 \n 33.0000 \n NA \n S \n \n \n male \n 62.0000 \n 62.00000 \n 2 \n 1 \n Harris, Mr. George \n 0 \n 0 \n S.W./PP 752 \n 10.5000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Harris, Mr. Walter \n 0 \n 0 \n W/C 14208 \n 10.5000 \n NA \n S \n \n \n female \n 7.0000 \n 7.00000 \n 2 \n 1 \n Hart, Miss. Eva Miriam \n 0 \n 2 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 2 \n 0 \n Hart, Mr. Benjamin \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 2 \n 1 \n Hart, Mrs. Benjamin (Esther Ada Bloomfield) \n 1 \n 1 \n F.C.C. 13529 \n 26.2500 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Herman, Miss. Alice \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Herman, Miss. Kate \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n male \n 49.0000 \n 49.00000 \n 2 \n 0 \n Herman, Mr. Samuel \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 48.0000 \n 48.00000 \n 2 \n 1 \n Herman, Mrs. Samuel (Jane Laver) \n 1 \n 2 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 55.0000 \n 55.00000 \n 2 \n 1 \n Hewlett, Mrs. (Mary D Kingcome) \n 0 \n 0 \n 248706 \n 16.0000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Hickman, Mr. Leonard Mark \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n Hickman, Mr. Lewis \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Hickman, Mr. Stanley George \n 2 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 2 \n 0 \n Hiltunen, Miss. Marta \n 1 \n 1 \n 250650 \n 13.0000 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n Hocking, Miss. Ellen \"Nellie\" \n 2 \n 1 \n 29105 \n 23.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Hocking, Mr. Richard George \n 2 \n 1 \n 29104 \n 11.5000 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Hocking, Mr. Samuel James Metcalfe \n 0 \n 0 \n 242963 \n 13.0000 \n NA \n S \n \n \n female \n 54.0000 \n 54.00000 \n 2 \n 1 \n Hocking, Mrs. Elizabeth (Eliza Needs) \n 1 \n 3 \n 29105 \n 23.0000 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 2 \n 0 \n Hodges, Mr. Henry Price \n 0 \n 0 \n 250643 \n 13.0000 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 2 \n 0 \n Hold, Mr. Stephen \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Hold, Mrs. Stephen (Annie Margaret Hill) \n 1 \n 0 \n 26707 \n 26.0000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 2 \n 0 \n Hood, Mr. Ambrose Jr \n 0 \n 0 \n S.O.C. 14879 \n 73.5000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 1 \n Hosono, Mr. Masabumi \n 0 \n 0 \n 237798 \n 13.0000 \n NA \n S \n \n \n male \n 63.0000 \n 63.00000 \n 2 \n 0 \n Howard, Mr. Benjamin \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n female \n 60.0000 \n 60.00000 \n 2 \n 0 \n Howard, Mrs. Benjamin (Ellen Truelove Arman) \n 1 \n 0 \n 24065 \n 26.0000 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 2 \n 0 \n Hunt, Mr. George Henry \n 0 \n 0 \n SCO/W 1585 \n 12.2750 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 2 \n 1 \n Ilett, Miss. Bertha \n 0 \n 0 \n SO/C 14885 \n 10.5000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 2 \n 0 \n Jacobsohn, Mr. Sidney Samuel \n 1 \n 0 \n 243847 \n 27.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy) \n 2 \n 1 \n 243847 \n 27.0000 \n NA \n S \n \n \n male \n 47.0000 \n 47.00000 \n 2 \n 0 \n Jarvis, Mr. John Denzil \n 0 \n 0 \n 237565 \n 15.0000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Jefferys, Mr. Clifford Thomas \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 2 \n 0 \n Jefferys, Mr. Ernest Wilfred \n 2 \n 0 \n C.A. 31029 \n 31.5000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n Jenkin, Mr. Stephen Curnow \n 0 \n 0 \n C.A. 33111 \n 10.5000 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 2 \n 1 \n Jerwan, Mrs. Amin S (Marie Marthe Thuillard) \n 0 \n 0 \n SC/AH Basle 541 \n 13.7917 \n D \n C \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Kantor, Mr. Sinai \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Kantor, Mrs. Sinai (Miriam Sternin) \n 1 \n 0 \n 244367 \n 26.0000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 0 \n Karnes, Mrs. J Frank (Claire Bennett) \n 0 \n 0 \n F.C.C. 13534 \n 21.0000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 2 \n 1 \n Keane, Miss. Nora A \n 0 \n 0 \n 226593 \n 12.3500 \n E101 \n Q \n \n \n male \n 35.0000 \n 35.00000 \n 2 \n 0 \n Keane, Mr. Daniel \n 0 \n 0 \n 233734 \n 12.3500 \n NA \n Q \n \n \n female \n 45.0000 \n 45.00000 \n 2 \n 1 \n Kelly, Mrs. Florence \"Fannie\" \n 0 \n 0 \n 223596 \n 13.5000 \n NA \n S \n \n \n male \n 57.0000 \n 57.00000 \n 2 \n 0 \n Kirkland, Rev. Charles Leonard \n 0 \n 0 \n 219533 \n 12.3500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Knight, Mr. Robert J \n 0 \n 0 \n 239855 \n 0.0000 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 0 \n Kvillner, Mr. Johan Henrik Johannesson \n 0 \n 0 \n C.A. 18723 \n 10.5000 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 2 \n 0 \n Lahtinen, Mrs. William (Anna Sylfven) \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Lahtinen, Rev. William \n 1 \n 1 \n 250651 \n 26.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Lamb, Mr. John Joseph \n 0 \n 0 \n 240261 \n 10.7083 \n NA \n Q \n \n \n female \n 1.0000 \n 1.00000 \n 2 \n 1 \n Laroche, Miss. Louise \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n female \n 3.0000 \n 3.00000 \n 2 \n 1 \n Laroche, Miss. Simonne Marie Anne Andree \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Laroche, Mr. Joseph Philippe Lemercier \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 2 \n 1 \n Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue) \n 1 \n 2 \n SC/Paris 2123 \n 41.5792 \n NA \n C \n \n \n female \n 17.0000 \n 17.00000 \n 2 \n 1 \n Lehmann, Miss. Bertha \n 0 \n 0 \n SC 1748 \n 12.0000 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 2 \n 1 \n Leitch, Miss. Jessie Wills \n 0 \n 0 \n 248727 \n 33.0000 \n NA \n S \n \n \n female \n 34.0000 \n 34.00000 \n 2 \n 1 \n Lemore, Mrs. (Amelia Milley) \n 0 \n 0 \n C.A. 34260 \n 10.5000 \n F33 \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Levy, Mr. Rene Jacques \n 0 \n 0 \n SC/Paris 2163 \n 12.8750 \n D \n C \n \n \n male \n 24.0000 \n 24.00000 \n 2 \n 0 \n Leyson, Mr. Robert William Norman \n 0 \n 0 \n C.A. 29566 \n 10.5000 \n NA \n S \n \n \n male \n 61.0000 \n 61.00000 \n 2 \n 0 \n Lingane, Mr. John \n 0 \n 0 \n 235509 \n 12.3500 \n NA \n Q \n \n \n male \n 50.0000 \n 50.00000 \n 2 \n 0 \n Louch, Mr. Charles Alexander \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n female \n 42.0000 \n 42.00000 \n 2 \n 1 \n Louch, Mrs. Charles Alexander (Alice Adelaide Slow) \n 1 \n 0 \n SC/AH 3085 \n 26.0000 \n NA \n S \n \n \n female \n 57.0000 \n 57.00000 \n 2 \n 0 \n Mack, Mrs. (Mary) \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n E77 \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Malachard, Mr. Noel \n 0 \n 0 \n 237735 \n 15.0458 \n D \n C \n \n \n male \n 1.0000 \n 1.00000 \n 2 \n 1 \n Mallet, Master. Andre \n 0 \n 2 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 0 \n Mallet, Mr. Albert \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Mallet, Mrs. Albert (Antoinette Magnin) \n 1 \n 1 \n S.C./PARIS 2079 \n 37.0042 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Mangiavacchi, Mr. Serafino Emilio \n 0 \n 0 \n SC/A.3 2861 \n 15.5792 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Matthews, Mr. William John \n 0 \n 0 \n 28228 \n 13.0000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 2 \n 0 \n Maybery, Mr. Frank Hubert \n 0 \n 0 \n 239059 \n 16.0000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 2 \n 0 \n McCrae, Mr. Arthur Gordon \n 0 \n 0 \n 237216 \n 13.5000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n McCrie, Mr. James Matthew \n 0 \n 0 \n 233478 \n 13.0000 \n NA \n S \n \n \n male \n 46.0000 \n 46.00000 \n 2 \n 0 \n McKane, Mr. Peter David \n 0 \n 0 \n 28403 \n 26.0000 \n NA \n S \n \n \n female \n 13.0000 \n 13.00000 \n 2 \n 1 \n Mellinger, Miss. Madeleine Violet \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n female \n 41.0000 \n 41.00000 \n 2 \n 1 \n Mellinger, Mrs. (Elizabeth Anne Maidment) \n 0 \n 1 \n 250644 \n 19.5000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 1 \n Mellors, Mr. William John \n 0 \n 0 \n SW/PP 751 \n 10.5000 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 2 \n 0 \n Meyer, Mr. August \n 0 \n 0 \n 248723 \n 13.0000 \n NA \n S \n \n \n male \n 48.0000 \n 48.00000 \n 2 \n 0 \n Milling, Mr. Jacob Christian \n 0 \n 0 \n 234360 \n 13.0000 \n NA \n S \n \n \n male \n 70.0000 \n 70.00000 \n 2 \n 0 \n Mitchell, Mr. Henry Michael \n 0 \n 0 \n C.A. 24580 \n 10.5000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Montvila, Rev. Juozas \n 0 \n 0 \n 211536 \n 13.0000 \n NA \n S \n \n \n male \n 54.0000 \n 54.00000 \n 2 \n 0 \n Moraweck, Dr. Ernest \n 0 \n 0 \n 29011 \n 14.0000 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 2 \n 0 \n Morley, Mr. Henry Samuel (\"Mr Henry Marshall\") \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 2 \n 0 \n Mudd, Mr. Thomas Charles \n 0 \n 0 \n S.O./P.P. 3 \n 10.5000 \n NA \n S \n \n \n male \n 62.0000 \n 62.00000 \n 2 \n 0 \n Myles, Mr. Thomas Francis \n 0 \n 0 \n 240276 \n 9.6875 \n NA \n Q \n \n \n male \n 32.5000 \n 32.50000 \n 2 \n 0 \n Nasser, Mr. Nicholas \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n female \n 14.0000 \n 14.00000 \n 2 \n 1 \n Nasser, Mrs. Nicholas (Adele Achem) \n 1 \n 0 \n 237736 \n 30.0708 \n NA \n C \n \n \n male \n 2.0000 \n 2.00000 \n 2 \n 1 \n Navratil, Master. Edmond Roger \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n male \n 3.0000 \n 3.00000 \n 2 \n 1 \n Navratil, Master. Michel M \n 1 \n 1 \n 230080 \n 26.0000 \n F2 \n S \n \n \n male \n 36.5000 \n 36.50000 \n 2 \n 0 \n Navratil, Mr. Michel (\"Louis M Hoffman\") \n 0 \n 2 \n 230080 \n 26.0000 \n F2 \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Nesson, Mr. Israel \n 0 \n 0 \n 244368 \n 13.0000 \n F2 \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Nicholls, Mr. Joseph Charles \n 1 \n 1 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Norman, Mr. Robert Douglas \n 0 \n 0 \n 218629 \n 13.5000 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 2 \n 1 \n Nourney, Mr. Alfred (\"Baron von Drachstedt\") \n 0 \n 0 \n SC/PARIS 2166 \n 13.8625 \n D38 \n C \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Nye, Mrs. (Elizabeth Ramell) \n 0 \n 0 \n C.A. 29395 \n 10.5000 \n F33 \n S \n \n \n male \n 39.0000 \n 39.00000 \n 2 \n 0 \n Otter, Mr. Richard \n 0 \n 0 \n 28213 \n 13.0000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 2 \n 1 \n Oxenham, Mr. Percy Thomas \n 0 \n 0 \n W./C. 14260 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 1 \n Padro y Manent, Mr. Julian \n 0 \n 0 \n SC/PARIS 2146 \n 13.8625 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Pain, Dr. Alfred \n 0 \n 0 \n 244278 \n 10.5000 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 1 \n Pallas y Castello, Mr. Emilio \n 0 \n 0 \n SC/PARIS 2147 \n 13.8583 \n NA \n C \n \n \n male \n 28.0000 \n 28.00000 \n 2 \n 0 \n Parker, Mr. Clifford Richard \n 0 \n 0 \n SC 14888 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Parkes, Mr. Francis \"Frank\" \n 0 \n 0 \n 239853 \n 0.0000 \n NA \n S \n \n \n female \n 50.0000 \n 50.00000 \n 2 \n 1 \n Parrish, Mrs. (Lutie Davis) \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Pengelly, Mr. Frederick William \n 0 \n 0 \n 28665 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Pernot, Mr. Rene \n 0 \n 0 \n SC/PARIS 2131 \n 15.0500 \n NA \n C \n \n \n male \n 41.0000 \n 41.00000 \n 2 \n 0 \n Peruschitz, Rev. Joseph Maria \n 0 \n 0 \n 237393 \n 13.0000 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 2 \n 1 \n Phillips, Miss. Alice Frances Louisa \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 2 \n 1 \n Phillips, Miss. Kate Florence (\"Mrs Kate Louise Phillips Marshall\") \n 0 \n 0 \n 250655 \n 26.0000 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 2 \n 0 \n Phillips, Mr. Escott Robert \n 0 \n 1 \n S.O./P.P. 2 \n 21.0000 \n NA \n S \n \n \n female \n 32.0000 \n 32.00000 \n 2 \n 1 \n Pinsky, Mrs. (Rosa) \n 0 \n 0 \n 234604 \n 13.0000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Ponesell, Mr. Martin \n 0 \n 0 \n 250647 \n 13.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 1 \n Portaluppi, Mr. Emilio Ilario Giuseppe \n 0 \n 0 \n C.A. 34644 \n 12.7375 \n NA \n C \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Pulbaum, Mr. Franz \n 0 \n 0 \n SC/PARIS 2168 \n 15.0333 \n NA \n C \n \n \n female \n 2.0000 \n 2.00000 \n 2 \n 1 \n Quick, Miss. Phyllis May \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n female \n 8.0000 \n 8.00000 \n 2 \n 1 \n Quick, Miss. Winifred Vera \n 1 \n 1 \n 26360 \n 26.0000 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 2 \n 1 \n Quick, Mrs. Frederick Charles (Jane Richards) \n 0 \n 2 \n 26360 \n 26.0000 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n Reeves, Mr. David \n 0 \n 0 \n C.A. 17248 \n 10.5000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 2 \n 0 \n Renouf, Mr. Peter Henry \n 1 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Renouf, Mrs. Peter Henry (Lillian Jefferys) \n 3 \n 0 \n 31027 \n 21.0000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Reynaldo, Ms. Encarnacion \n 0 \n 0 \n 230434 \n 13.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Richard, Mr. Emile \n 0 \n 0 \n SC/PARIS 2133 \n 15.0458 \n NA \n C \n \n \n male \n 0.8333 \n 0.83330 \n 2 \n 1 \n Richards, Master. George Sibley \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n male \n 3.0000 \n 3.00000 \n 2 \n 1 \n Richards, Master. William Rowe \n 1 \n 1 \n 29106 \n 18.7500 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 1 \n Richards, Mrs. Sidney (Emily Hocking) \n 2 \n 3 \n 29106 \n 18.7500 \n NA \n S \n \n \n female \n 50.0000 \n 50.00000 \n 2 \n 1 \n Ridsdale, Miss. Lucy \n 0 \n 0 \n W./C. 14258 \n 10.5000 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 2 \n 0 \n Rogers, Mr. Reginald Harry \n 0 \n 0 \n 28004 \n 10.5000 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 2 \n 1 \n Rugg, Miss. Emily \n 0 \n 0 \n C.A. 31026 \n 10.5000 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 2 \n 0 \n Schmidt, Mr. August \n 0 \n 0 \n 248659 \n 13.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Sedgwick, Mr. Charles Frederick Waddington \n 0 \n 0 \n 244361 \n 13.0000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Sharp, Mr. Percival James R \n 0 \n 0 \n 244358 \n 26.0000 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 2 \n 1 \n Shelley, Mrs. William (Imanita Parrish Hall) \n 0 \n 1 \n 230433 \n 26.0000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 2 \n 1 \n Silven, Miss. Lyyli Karoliina \n 0 \n 2 \n 250652 \n 13.0000 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 2 \n 1 \n Sincock, Miss. Maude \n 0 \n 0 \n C.A. 33112 \n 36.7500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Sinkkonen, Miss. Anna \n 0 \n 0 \n 250648 \n 13.0000 \n NA \n S \n \n \n male \n 59.0000 \n 59.00000 \n 2 \n 0 \n Sjostedt, Mr. Ernst Adolf \n 0 \n 0 \n 237442 \n 13.5000 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 2 \n 1 \n Slayter, Miss. Hilda Mary \n 0 \n 0 \n 234818 \n 12.3500 \n NA \n Q \n \n \n male \n 35.0000 \n 35.00000 \n 2 \n 0 \n Slemen, Mr. Richard James \n 0 \n 0 \n 28206 \n 10.5000 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 2 \n 1 \n Smith, Miss. Marion Elsie \n 0 \n 0 \n 31418 \n 13.0000 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Sobey, Mr. Samuel James Hayden \n 0 \n 0 \n C.A. 29178 \n 13.0000 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 2 \n 0 \n Stanton, Mr. Samuel Ward \n 0 \n 0 \n 237734 \n 15.0458 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 2 \n 0 \n Stokes, Mr. Philip Joseph \n 0 \n 0 \n F.C.C. 13540 \n 10.5000 \n NA \n S \n \n \n male \n 18.5000 \n 18.50000 \n 2 \n 0 \n Swane, Mr. George \n 0 \n 0 \n 248734 \n 13.0000 \n F \n S \n \n \n male \n 14.0000 \n 14.00000 \n 2 \n 0 \n Sweet, Mr. George Frederick \n 0 \n 0 \n 220845 \n 65.0000 \n NA \n S \n \n \n female \n 50.0000 \n 50.00000 \n 2 \n 1 \n Toomey, Miss. Ellen \n 0 \n 0 \n F.C.C. 13531 \n 10.5000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Troupiansky, Mr. Moses Aaron \n 0 \n 0 \n 233639 \n 13.0000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 2 \n 1 \n Trout, Mrs. William H (Jessie L) \n 0 \n 0 \n 240929 \n 12.6500 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 2 \n 1 \n Troutt, Miss. Edwina Celia \"Winnie\" \n 0 \n 0 \n 34218 \n 10.5000 \n E101 \n S \n \n \n male \n 29.0000 \n 29.00000 \n 2 \n 0 \n Turpin, Mr. William John Robert \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 2 \n 0 \n Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott) \n 1 \n 0 \n 11668 \n 21.0000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 2 \n 0 \n Veal, Mr. James \n 0 \n 0 \n 28221 \n 13.0000 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 2 \n 1 \n Walcroft, Miss. Nellie \n 0 \n 0 \n F.C.C. 13528 \n 21.0000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 2 \n 0 \n Ware, Mr. John James \n 1 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 2 \n 0 \n Ware, Mr. William Jeffery \n 1 \n 0 \n 28666 \n 10.5000 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 2 \n 1 \n Ware, Mrs. John James (Florence Louise Long) \n 0 \n 0 \n CA 31352 \n 21.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Watson, Mr. Ennis Hastings \n 0 \n 0 \n 239856 \n 0.0000 \n NA \n S \n \n \n female \n 12.0000 \n 12.00000 \n 2 \n 1 \n Watt, Miss. Bertha J \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 2 \n 1 \n Watt, Mrs. James (Elizabeth \"Bessie\" Inglis Milne) \n 0 \n 0 \n C.A. 33595 \n 15.7500 \n NA \n S \n \n \n female \n 32.5000 \n 32.50000 \n 2 \n 1 \n Webber, Miss. Susan \n 0 \n 0 \n 27267 \n 13.0000 \n E101 \n S \n \n \n male \n 27.0000 \n 27.00000 \n 2 \n 0 \n Weisz, Mr. Leopold \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Weisz, Mrs. Leopold (Mathilde Francoise Pede) \n 1 \n 0 \n 228414 \n 26.0000 \n NA \n S \n \n \n male \n 2.0000 \n 2.00000 \n 2 \n 1 \n Wells, Master. Ralph Lester \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n female \n 4.0000 \n 4.00000 \n 2 \n 1 \n Wells, Miss. Joan \n 1 \n 1 \n 29103 \n 23.0000 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 2 \n 1 \n Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis) \n 0 \n 2 \n 29103 \n 23.0000 \n NA \n S \n \n \n female \n 0.9167 \n 0.91670 \n 2 \n 1 \n West, Miss. Barbara J \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n female \n 5.0000 \n 5.00000 \n 2 \n 1 \n West, Miss. Constance Mirium \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 2 \n 0 \n West, Mr. Edwy Arthur \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 2 \n 1 \n West, Mrs. Edwy Arthur (Ada Mary Worth) \n 1 \n 2 \n C.A. 34651 \n 27.7500 \n NA \n S \n \n \n male \n 66.0000 \n 66.00000 \n 2 \n 0 \n Wheadon, Mr. Edward H \n 0 \n 0 \n C.A. 24579 \n 10.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 0 \n Wheeler, Mr. Edwin \"Frederick\" \n 0 \n 0 \n SC/PARIS 2159 \n 12.8750 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 2 \n 1 \n Wilhelms, Mr. Charles \n 0 \n 0 \n 244270 \n 13.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 2 \n 1 \n Williams, Mr. Charles Eugene \n 0 \n 0 \n 244373 \n 13.0000 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 2 \n 1 \n Wright, Miss. Marion \n 0 \n 0 \n 220844 \n 13.5000 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 2 \n 0 \n Yrois, Miss. Henriette (\"Mrs Harbeck\") \n 0 \n 0 \n 248747 \n 13.0000 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Abbing, Mr. Anthony \n 0 \n 0 \n C.A. 5547 \n 7.5500 \n NA \n S \n \n \n male \n 13.0000 \n 13.00000 \n 3 \n 0 \n Abbott, Master. Eugene Joseph \n 0 \n 2 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Abbott, Mr. Rossmore Edward \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n female \n 35.0000 \n 35.00000 \n 3 \n 1 \n Abbott, Mrs. Stanton (Rosa Hunt) \n 1 \n 1 \n C.A. 2673 \n 20.2500 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Abelseth, Miss. Karen Marie \n 0 \n 0 \n 348125 \n 7.6500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Abelseth, Mr. Olaus Jorgensen \n 0 \n 0 \n 348122 \n 7.6500 \n F G63 \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Abrahamsson, Mr. Abraham August Johannes \n 0 \n 0 \n SOTON/O2 3101284 \n 7.9250 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Abrahim, Mrs. Joseph (Sophie Halaut Easu) \n 0 \n 0 \n 2657 \n 7.2292 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Adahl, Mr. Mauritz Nils Martin \n 0 \n 0 \n C 7076 \n 7.2500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Adams, Mr. John \n 0 \n 0 \n 341826 \n 8.0500 \n NA \n S \n \n \n female \n 40.0000 \n 40.00000 \n 3 \n 0 \n Ahlin, Mrs. Johan (Johanna Persdotter Larsson) \n 1 \n 0 \n 7546 \n 9.4750 \n NA \n S \n \n \n male \n 0.8333 \n 0.83330 \n 3 \n 1 \n Aks, Master. Philip Frank \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Aks, Mrs. Sam (Leah Rosen) \n 0 \n 1 \n 392091 \n 9.3500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 1 \n Albimona, Mr. Nassef Cassem \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Alexander, Mr. William \n 0 \n 0 \n 3474 \n 7.8875 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Alhomaki, Mr. Ilmari Rudolf \n 0 \n 0 \n SOTON/O2 3101287 \n 7.9250 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Ali, Mr. Ahmed \n 0 \n 0 \n SOTON/O.Q. 3101311 \n 7.0500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Ali, Mr. William \n 0 \n 0 \n SOTON/O.Q. 3101312 \n 7.0500 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Allen, Mr. William Henry \n 0 \n 0 \n 373450 \n 8.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Allum, Mr. Owen George \n 0 \n 0 \n 2223 \n 8.3000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Andersen, Mr. Albert Karvin \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 1 \n Andersen-Jensen, Miss. Carla Christine Nielsine \n 1 \n 0 \n 350046 \n 7.8542 \n NA \n S \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 0 \n Andersson, Master. Sigvard Harald Elias \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 6.0000 \n 6.00000 \n 3 \n 0 \n Andersson, Miss. Ebba Iris Alfrida \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Andersson, Miss. Ellis Anna Maria \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 1 \n Andersson, Miss. Erna Alexandra \n 4 \n 2 \n 3101281 \n 7.9250 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 3 \n 0 \n Andersson, Miss. Ida Augusta Margareta \n 4 \n 2 \n 347091 \n 7.7750 \n NA \n S \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Andersson, Miss. Ingeborg Constanzia \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n female \n 11.0000 \n 11.00000 \n 3 \n 0 \n Andersson, Miss. Sigrid Elisabeth \n 4 \n 2 \n 347082 \n 31.2750 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Andersson, Mr. Anders Johan \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 1 \n Andersson, Mr. August Edvard (\"Wennerstrom\") \n 0 \n 0 \n 350043 \n 7.7958 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Andersson, Mr. Johan Samuel \n 0 \n 0 \n 347075 \n 7.7750 \n NA \n S \n \n \n female \n 39.0000 \n 39.00000 \n 3 \n 0 \n Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren) \n 1 \n 5 \n 347082 \n 31.2750 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Andreasson, Mr. Paul Edvin \n 0 \n 0 \n 347466 \n 7.8542 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Angheloff, Mr. Minko \n 0 \n 0 \n 349202 \n 7.8958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Arnold-Franchi, Mr. Josef \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Arnold-Franchi, Mrs. Josef (Josefine Franchi) \n 1 \n 0 \n 349237 \n 17.8000 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Aronsson, Mr. Ernst Axel Algot \n 0 \n 0 \n 349911 \n 7.7750 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Asim, Mr. Adola \n 0 \n 0 \n SOTON/O.Q. 3101310 \n 7.0500 \n NA \n S \n \n \n male \n 5.0000 \n 5.00000 \n 3 \n 0 \n Asplund, Master. Carl Edgar \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 0 \n Asplund, Master. Clarence Gustaf Hugo \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 3.0000 \n 3.00000 \n 3 \n 1 \n Asplund, Master. Edvin Rojj Felix \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 13.0000 \n 13.00000 \n 3 \n 0 \n Asplund, Master. Filip Oscar \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n female \n 5.0000 \n 5.00000 \n 3 \n 1 \n Asplund, Miss. Lillian Gertrud \n 4 \n 2 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Asplund, Mr. Carl Oscar Vilhelm Gustafsson \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 1 \n Asplund, Mr. Johan Charles \n 0 \n 0 \n 350054 \n 7.7958 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 3 \n 1 \n Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) \n 1 \n 5 \n 347077 \n 31.3875 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 1 \n Assaf Khalil, Mrs. Mariana (\"Miriam\") \n 0 \n 0 \n 2696 \n 7.2250 \n NA \n C \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Assaf, Mr. Gerios \n 0 \n 0 \n 2692 \n 7.2250 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Assam, Mr. Ali \n 0 \n 0 \n SOTON/O.Q. 3101309 \n 7.0500 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 0 \n Attalah, Miss. Malake \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Attalah, Mr. Sleiman \n 0 \n 0 \n 2694 \n 7.2250 \n NA \n C \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Augustsson, Mr. Albert \n 0 \n 0 \n 347468 \n 7.8542 \n NA \n S \n \n \n female \n 13.0000 \n 13.00000 \n 3 \n 1 \n Ayoub, Miss. Banoura \n 0 \n 0 \n 2687 \n 7.2292 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Baccos, Mr. Raffull \n 0 \n 0 \n 2679 \n 7.2250 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Backstrom, Mr. Karl Alfred \n 1 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 3 \n 1 \n Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson) \n 3 \n 0 \n 3101278 \n 15.8500 \n NA \n S \n \n \n female \n 0.7500 \n 0.75000 \n 3 \n 1 \n Baclini, Miss. Eugenie \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 0.7500 \n 0.75000 \n 3 \n 1 \n Baclini, Miss. Helene Barbara \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 5.0000 \n 5.00000 \n 3 \n 1 \n Baclini, Miss. Marie Catherine \n 2 \n 1 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Baclini, Mrs. Solomon (Latifa Qurban) \n 0 \n 3 \n 2666 \n 19.2583 \n NA \n C \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Badman, Miss. Emily Louisa \n 0 \n 0 \n A/4 31416 \n 8.0500 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Badt, Mr. Mohamed \n 0 \n 0 \n 2623 \n 7.2250 \n NA \n C \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Balkic, Mr. Cerin \n 0 \n 0 \n 349248 \n 7.8958 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Barah, Mr. Hanna Assi \n 0 \n 0 \n 2663 \n 7.2292 \n NA \n C \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Barbara, Miss. Saiide \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 0 \n Barbara, Mrs. (Catherine David) \n 0 \n 1 \n 2691 \n 14.4542 \n NA \n C \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 0 \n Barry, Miss. Julia \n 0 \n 0 \n 330844 \n 7.8792 \n NA \n Q \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Barton, Mr. David John \n 0 \n 0 \n 324669 \n 8.0500 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Beavan, Mr. William Thomas \n 0 \n 0 \n 323951 \n 8.0500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Bengtsson, Mr. John Viktor \n 0 \n 0 \n 347068 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Berglund, Mr. Karl Ivar Sven \n 0 \n 0 \n PP 4348 \n 9.3500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Betros, Master. Seman \n 0 \n 0 \n 2622 \n 7.2292 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Betros, Mr. Tannous \n 0 \n 0 \n 2648 \n 4.0125 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Bing, Mr. Lee \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Birkeland, Mr. Hans Martin Monsen \n 0 \n 0 \n 312992 \n 7.7750 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Bjorklund, Mr. Ernst Herbert \n 0 \n 0 \n 347090 \n 7.7500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Bostandyeff, Mr. Guentcho \n 0 \n 0 \n 349224 \n 7.8958 \n NA \n S \n \n \n male \n 6.0000 \n 6.00000 \n 3 \n 0 \n Boulos, Master. Akar \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Boulos, Miss. Nourelain \n 1 \n 1 \n 2678 \n 15.2458 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Boulos, Mr. Hanna \n 0 \n 0 \n 2664 \n 7.2250 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Boulos, Mrs. Joseph (Sultana) \n 0 \n 2 \n 2678 \n 15.2458 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Bourke, Miss. Mary \n 0 \n 2 \n 364848 \n 7.7500 \n NA \n Q \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Bourke, Mr. John \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n female \n 32.0000 \n 32.00000 \n 3 \n 0 \n Bourke, Mrs. John (Catherine) \n 1 \n 1 \n 364849 \n 15.5000 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Bowen, Mr. David John \"Dai\" \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Bradley, Miss. Bridget Delia \n 0 \n 0 \n 334914 \n 7.7250 \n NA \n Q \n \n \n female \n 20.0000 \n 20.00000 \n 3 \n 0 \n Braf, Miss. Elin Ester Maria \n 0 \n 0 \n 347471 \n 7.8542 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Braund, Mr. Lewis Richard \n 1 \n 0 \n 3460 \n 7.0458 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Braund, Mr. Owen Harris \n 1 \n 0 \n A/5 21171 \n 7.2500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Brobeck, Mr. Karl Rudolf \n 0 \n 0 \n 350045 \n 7.7958 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Brocklebank, Mr. William Alfred \n 0 \n 0 \n 364512 \n 8.0500 \n NA \n S \n \n \n female \n 18.5000 \n 18.50000 \n 3 \n 0 \n Buckley, Miss. Katherine \n 0 \n 0 \n 329944 \n 7.2833 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Buckley, Mr. Daniel \n 0 \n 0 \n 330920 \n 7.8208 \n NA \n Q \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Burke, Mr. Jeremiah \n 0 \n 0 \n 365222 \n 6.7500 \n NA \n Q \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Burns, Miss. Mary Delia \n 0 \n 0 \n 330963 \n 7.8792 \n NA \n Q \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Cacic, Miss. Manda \n 0 \n 0 \n 315087 \n 8.6625 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Cacic, Miss. Marija \n 0 \n 0 \n 315084 \n 8.6625 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Cacic, Mr. Jego Grga \n 0 \n 0 \n 315091 \n 8.6625 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 3 \n 0 \n Cacic, Mr. Luka \n 0 \n 0 \n 315089 \n 8.6625 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Calic, Mr. Jovo \n 0 \n 0 \n 315093 \n 8.6625 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Calic, Mr. Petar \n 0 \n 0 \n 315086 \n 8.6625 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Canavan, Miss. Mary \n 0 \n 0 \n 364846 \n 7.7500 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Canavan, Mr. Patrick \n 0 \n 0 \n 364858 \n 7.7500 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Cann, Mr. Ernest Charles \n 0 \n 0 \n A./5. 2152 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Caram, Mr. Joseph \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Caram, Mrs. Joseph (Maria Elias) \n 1 \n 0 \n 2689 \n 14.4583 \n NA \n C \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Carlsson, Mr. August Sigfrid \n 0 \n 0 \n 350042 \n 7.7958 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Carlsson, Mr. Carl Robert \n 0 \n 0 \n 350409 \n 7.8542 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Carr, Miss. Helen \"Ellen\" \n 0 \n 0 \n 367231 \n 7.7500 \n NA \n Q \n \n \n female \n 37.0000 \n 37.00000 \n 3 \n 0 \n Carr, Miss. Jeannie \n 0 \n 0 \n 368364 \n 7.7500 \n NA \n Q \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Carver, Mr. Alfred John \n 0 \n 0 \n 392095 \n 7.2500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Celotti, Mr. Francesco \n 0 \n 0 \n 343275 \n 8.0500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Charters, Mr. David \n 0 \n 0 \n A/5. 13032 \n 7.7333 \n NA \n Q \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Chip, Mr. Chang \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Christmann, Mr. Emil \n 0 \n 0 \n 343276 \n 8.0500 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Chronopoulos, Mr. Apostolos \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Chronopoulos, Mr. Demetrios \n 1 \n 0 \n 2680 \n 14.4542 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Coelho, Mr. Domingos Fernandeo \n 0 \n 0 \n SOTON/O.Q. 3101307 \n 7.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 1 \n Cohen, Mr. Gurshon \"Gus\" \n 0 \n 0 \n A/5 3540 \n 8.0500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Colbert, Mr. Patrick \n 0 \n 0 \n 371109 \n 7.2500 \n NA \n Q \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Coleff, Mr. Peju \n 0 \n 0 \n 349210 \n 7.4958 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Coleff, Mr. Satio \n 0 \n 0 \n 349209 \n 7.4958 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Conlon, Mr. Thomas Henry \n 0 \n 0 \n 21332 \n 7.7333 \n NA \n Q \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Connaghton, Mr. Michael \n 0 \n 0 \n 335097 \n 7.7500 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Connolly, Miss. Kate \n 0 \n 0 \n 370373 \n 7.7500 \n NA \n Q \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Connolly, Miss. Kate \n 0 \n 0 \n 330972 \n 7.6292 \n NA \n Q \n \n \n male \n 70.5000 \n 70.50000 \n 3 \n 0 \n Connors, Mr. Patrick \n 0 \n 0 \n 370369 \n 7.7500 \n NA \n Q \n \n \n male \n 43.0000 \n 43.00000 \n 3 \n 0 \n Cook, Mr. Jacob \n 0 \n 0 \n A/5 3536 \n 8.0500 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Cor, Mr. Bartol \n 0 \n 0 \n 349230 \n 7.8958 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Cor, Mr. Ivan \n 0 \n 0 \n 349229 \n 7.8958 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Cor, Mr. Liudevit \n 0 \n 0 \n 349231 \n 7.8958 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Corn, Mr. Harry \n 0 \n 0 \n SOTON/OQ 392090 \n 8.0500 \n NA \n S \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 1 \n Coutts, Master. Eden Leslie \"Neville\" \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n male \n 3.0000 \n 3.00000 \n 3 \n 1 \n Coutts, Master. William Loch \"William\" \n 1 \n 1 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 3 \n 1 \n Coutts, Mrs. William (Winnie \"Minnie\" Treanor) \n 0 \n 2 \n C.A. 37671 \n 15.9000 \n NA \n S \n \n \n male \n 59.0000 \n 59.00000 \n 3 \n 0 \n Coxon, Mr. Daniel \n 0 \n 0 \n 364500 \n 7.2500 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Crease, Mr. Ernest James \n 0 \n 0 \n S.P. 3464 \n 8.1583 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 1 \n Cribb, Miss. Laura Alice \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 0 \n Cribb, Mr. John Hatfield \n 0 \n 1 \n 371362 \n 16.1000 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Culumovic, Mr. Jeso \n 0 \n 0 \n 315090 \n 8.6625 \n NA \n S \n \n \n male \n 22.5000 \n 22.50000 \n 3 \n 0 \n Daher, Mr. Shedid \n 0 \n 0 \n 2698 \n 7.2250 \n NA \n C \n \n \n male \n 45.0000 \n 45.00000 \n 3 \n 1 \n Dahl, Mr. Karl Edwart \n 0 \n 0 \n 7598 \n 8.0500 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Dahlberg, Miss. Gerda Ulrika \n 0 \n 0 \n 7552 \n 10.5167 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Dakic, Mr. Branko \n 0 \n 0 \n 349228 \n 10.1708 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 1 \n Daly, Miss. Margaret Marcella \"Maggie\" \n 0 \n 0 \n 382650 \n 6.9500 \n NA \n Q \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Daly, Mr. Eugene Patrick \n 0 \n 0 \n 382651 \n 7.7500 \n NA \n Q \n \n \n male \n 0.3333 \n 0.33330 \n 3 \n 0 \n Danbom, Master. Gilbert Sigvard Emanuel \n 0 \n 2 \n 347080 \n 14.4000 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Danbom, Mr. Ernst Gilbert \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 3 \n 0 \n Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren) \n 1 \n 1 \n 347080 \n 14.4000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Danoff, Mr. Yoto \n 0 \n 0 \n 349219 \n 7.8958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Dantcheff, Mr. Ristiu \n 0 \n 0 \n 349203 \n 7.8958 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Davies, Mr. Alfred J \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Davies, Mr. Evan \n 0 \n 0 \n SC/A4 23568 \n 8.0500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Davies, Mr. John Samuel \n 2 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Davies, Mr. Joseph \n 2 \n 0 \n A/4 48873 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Davison, Mr. Thomas Henry \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Davison, Mrs. Thomas Henry (Mary E Finck) \n 1 \n 0 \n 386525 \n 16.1000 \n NA \n S \n \n \n male \n 36.5000 \n 36.50000 \n 3 \n 1 \n de Messemaeker, Mr. Guillaume Joseph \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 3 \n 1 \n de Messemaeker, Mrs. Guillaume Joseph (Emma) \n 1 \n 0 \n 345572 \n 17.4000 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 1 \n de Mulder, Mr. Theodore \n 0 \n 0 \n 345774 \n 9.5000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n de Pelsmaeker, Mr. Alfons \n 0 \n 0 \n 345778 \n 9.5000 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 3 \n 1 \n Dean, Master. Bertram Vere \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n female \n 0.1667 \n 0.16670 \n 3 \n 1 \n Dean, Miss. Elizabeth Gladys \"Millvina\" \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Dean, Mr. Bertram Frank \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n female \n 33.0000 \n 33.00000 \n 3 \n 1 \n Dean, Mrs. Bertram (Eva Georgetta Light) \n 1 \n 2 \n C.A. 2315 \n 20.5750 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Delalic, Mr. Redjo \n 0 \n 0 \n 349250 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Demetri, Mr. Marinko \n 0 \n 0 \n 349238 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Denkoff, Mr. Mitto \n 0 \n 0 \n 349225 \n 7.8958 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Dennis, Mr. Samuel \n 0 \n 0 \n A/5 21172 \n 7.2500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Dennis, Mr. William \n 0 \n 0 \n A/5 21175 \n 7.2500 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 1 \n Devaney, Miss. Margaret Delia \n 0 \n 0 \n 330958 \n 7.8792 \n NA \n Q \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Dika, Mr. Mirko \n 0 \n 0 \n 349232 \n 7.8958 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Dimic, Mr. Jovan \n 0 \n 0 \n 315088 \n 8.6625 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 3 \n 0 \n Dintcheff, Mr. Valtcho \n 0 \n 0 \n 349226 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Doharr, Mr. Tannous \n 0 \n 0 \n 2686 \n 7.2292 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Dooley, Mr. Patrick \n 0 \n 0 \n 370376 \n 7.7500 \n NA \n Q \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 1 \n Dorking, Mr. Edward Arthur \n 0 \n 0 \n A/5. 10482 \n 8.0500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 1 \n Dowdell, Miss. Elizabeth \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 0 \n Doyle, Miss. Elizabeth \n 0 \n 0 \n 368702 \n 7.7500 \n NA \n Q \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 1 \n Drapkin, Miss. Jennie \n 0 \n 0 \n SOTON/OQ 392083 \n 8.0500 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Drazenoic, Mr. Jozef \n 0 \n 0 \n 349241 \n 7.8958 \n NA \n C \n \n \n male \n 65.0000 \n 65.00000 \n 3 \n 0 \n Duane, Mr. Frank \n 0 \n 0 \n 336439 \n 7.7500 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 1 \n Duquemin, Mr. Joseph \n 0 \n 0 \n S.O./P.P. 752 \n 7.5500 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Dyker, Mr. Adolf Fredrik \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson) \n 1 \n 0 \n 347072 \n 13.9000 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Edvardsson, Mr. Gustaf Hjalmar \n 0 \n 0 \n 349912 \n 7.7750 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Eklund, Mr. Hans Linus \n 0 \n 0 \n 347074 \n 7.7750 \n NA \n S \n \n \n male \n 45.0000 \n 45.00000 \n 3 \n 0 \n Ekstrom, Mr. Johan \n 0 \n 0 \n 347061 \n 6.9750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Elias, Mr. Dibo \n 0 \n 0 \n 2674 \n 7.2250 \n NA \n C \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Elias, Mr. Joseph \n 0 \n 2 \n 2675 \n 7.2292 \n NA \n C \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Elias, Mr. Joseph Jr \n 1 \n 1 \n 2690 \n 7.2292 \n NA \n C \n \n \n male \n 15.0000 \n 15.00000 \n 3 \n 0 \n Elias, Mr. Tannous \n 1 \n 1 \n 2695 \n 7.2292 \n NA \n C \n \n \n male \n 47.0000 \n 47.00000 \n 3 \n 0 \n Elsbury, Mr. William James \n 0 \n 0 \n A/5 3902 \n 7.2500 \n NA \n S \n \n \n female \n 5.0000 \n 5.00000 \n 3 \n 1 \n Emanuel, Miss. Virginia Ethel \n 0 \n 0 \n 364516 \n 12.4750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Emir, Mr. Farred Chehab \n 0 \n 0 \n 2631 \n 7.2250 \n NA \n C \n \n \n male \n 40.5000 \n 40.50000 \n 3 \n 0 \n Everett, Mr. Thomas James \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n male \n 40.5000 \n 40.50000 \n 3 \n 0 \n Farrell, Mr. James \n 0 \n 0 \n 367232 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Finoli, Mr. Luigi \n 0 \n 0 \n SOTON/O.Q. 3101308 \n 7.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Fischer, Mr. Eberhard Thelander \n 0 \n 0 \n 350036 \n 7.7958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Fleming, Miss. Honora \n 0 \n 0 \n 364859 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Flynn, Mr. James \n 0 \n 0 \n 364851 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Flynn, Mr. John \n 0 \n 0 \n 368323 \n 6.9500 \n NA \n Q \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Foley, Mr. Joseph \n 0 \n 0 \n 330910 \n 7.8792 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Foley, Mr. William \n 0 \n 0 \n 365235 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Foo, Mr. Choong \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Ford, Miss. Doolina Margaret \"Daisy\" \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Ford, Miss. Robina Maggie \"Ruby\" \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ford, Mr. Arthur \n 0 \n 0 \n A/5 1478 \n 8.0500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Ford, Mr. Edward Watson \n 2 \n 2 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Ford, Mr. William Neal \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n female \n 48.0000 \n 48.00000 \n 3 \n 0 \n Ford, Mrs. Edward (Margaret Ann Watson) \n 1 \n 3 \n W./C. 6608 \n 34.3750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Fox, Mr. Patrick \n 0 \n 0 \n 368573 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Franklin, Mr. Charles (Charles Fardon) \n 0 \n 0 \n SOTON/O.Q. 3101314 \n 7.2500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Gallagher, Mr. Martin \n 0 \n 0 \n 36864 \n 7.7417 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Garfirth, Mr. John \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Gheorgheff, Mr. Stanio \n 0 \n 0 \n 349254 \n 7.8958 \n NA \n C \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Gilinski, Mr. Eliezer \n 0 \n 0 \n 14973 \n 8.0500 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Gilnagh, Miss. Katherine \"Katie\" \n 0 \n 0 \n 35851 \n 7.7333 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Glynn, Miss. Mary Agatha \n 0 \n 0 \n 335677 \n 7.7500 \n NA \n Q \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 1 \n Goldsmith, Master. Frank John William \"Frankie\" \n 0 \n 2 \n 363291 \n 20.5250 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Goldsmith, Mr. Frank John \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 3 \n 0 \n Goldsmith, Mr. Nathan \n 0 \n 0 \n SOTON/O.Q. 3101263 \n 7.8500 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 1 \n Goldsmith, Mrs. Frank John (Emily Alice Brown) \n 1 \n 1 \n 363291 \n 20.5250 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 3 \n 0 \n Goncalves, Mr. Manuel Estanslas \n 0 \n 0 \n SOTON/O.Q. 3101306 \n 7.0500 \n NA \n S \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 0 \n Goodwin, Master. Harold Victor \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 3 \n 0 \n Goodwin, Master. Sidney Leonard \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 11.0000 \n 11.00000 \n 3 \n 0 \n Goodwin, Master. William Frederick \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n female \n 10.0000 \n 10.00000 \n 3 \n 0 \n Goodwin, Miss. Jessie Allis \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 0 \n Goodwin, Miss. Lillian Amy \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 14.0000 \n 14.00000 \n 3 \n 0 \n Goodwin, Mr. Charles Edward \n 5 \n 2 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Goodwin, Mr. Charles Frederick \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n female \n 43.0000 \n 43.00000 \n 3 \n 0 \n Goodwin, Mrs. Frederick (Augusta Tyler) \n 1 \n 6 \n CA 2144 \n 46.9000 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 3 \n 0 \n Green, Mr. George Henry \n 0 \n 0 \n 21440 \n 8.0500 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Gronnestad, Mr. Daniel Danielsen \n 0 \n 0 \n 8471 \n 8.3625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Guest, Mr. Robert \n 0 \n 0 \n 376563 \n 8.0500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Gustafsson, Mr. Alfred Ossian \n 0 \n 0 \n 7534 \n 9.8458 \n NA \n S \n \n \n male \n 37.0000 \n 37.00000 \n 3 \n 0 \n Gustafsson, Mr. Anders Vilhelm \n 2 \n 0 \n 3101276 \n 7.9250 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Gustafsson, Mr. Johan Birger \n 2 \n 0 \n 3101277 \n 7.9250 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Gustafsson, Mr. Karl Gideon \n 0 \n 0 \n 347069 \n 7.7750 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 0 \n Haas, Miss. Aloisia \n 0 \n 0 \n 349236 \n 8.8500 \n NA \n S \n \n \n female \n 17.0000 \n 17.00000 \n 3 \n 0 \n Hagardon, Miss. Kate \n 0 \n 0 \n AQ/3. 30631 \n 7.7333 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Hagland, Mr. Ingvald Olai Olsen \n 1 \n 0 \n 65303 \n 19.9667 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Hagland, Mr. Konrad Mathias Reiersen \n 1 \n 0 \n 65304 \n 19.9667 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Hakkarainen, Mr. Pekka Pietari \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck) \n 1 \n 0 \n STON/O2. 3101279 \n 15.8500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Hampe, Mr. Leon \n 0 \n 0 \n 345769 \n 9.5000 \n NA \n S \n \n \n male \n 23.5000 \n 23.50000 \n 3 \n 0 \n Hanna, Mr. Mansour \n 0 \n 0 \n 2693 \n 7.2292 \n NA \n C \n \n \n male \n 41.0000 \n 41.00000 \n 3 \n 0 \n Hansen, Mr. Claus Peter \n 2 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Hansen, Mr. Henrik Juul \n 1 \n 0 \n 350025 \n 7.8542 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Hansen, Mr. Henry Damsgaard \n 0 \n 0 \n 350029 \n 7.8542 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 1 \n Hansen, Mrs. Claus Peter (Jennie L Howard) \n 1 \n 0 \n 350026 \n 14.1083 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Harknett, Miss. Alice Phoebe \n 0 \n 0 \n W./C. 6609 \n 7.5500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Harmer, Mr. Abraham (David Lishin) \n 0 \n 0 \n 374887 \n 7.2500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Hart, Mr. Henry \n 0 \n 0 \n 394140 \n 6.8583 \n NA \n Q \n \n \n male \n 11.0000 \n 11.00000 \n 3 \n 0 \n Hassan, Mr. Houssein G N \n 0 \n 0 \n 2699 \n 18.7875 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Healy, Miss. Hanora \"Nora\" \n 0 \n 0 \n 370375 \n 7.7500 \n NA \n Q \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 1 \n Hedman, Mr. Oskar Arvid \n 0 \n 0 \n 347089 \n 6.9750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Hee, Mr. Ling \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Hegarty, Miss. Hanora \"Nora\" \n 0 \n 0 \n 365226 \n 6.7500 \n NA \n Q \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 1 \n Heikkinen, Miss. Laina \n 0 \n 0 \n STON/O2. 3101282 \n 7.9250 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 0 \n Heininen, Miss. Wendla Maria \n 0 \n 0 \n STON/O2. 3101290 \n 7.9250 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Hellstrom, Miss. Hilda Maria \n 0 \n 0 \n 7548 \n 8.9625 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Hendekovic, Mr. Ignjac \n 0 \n 0 \n 349243 \n 7.8958 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 3 \n 0 \n Henriksson, Miss. Jenny Lovisa \n 0 \n 0 \n 347086 \n 7.7750 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Henry, Miss. Delia \n 0 \n 0 \n 382649 \n 7.7500 \n NA \n Q \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 1 \n Hirvonen, Miss. Hildur E \n 0 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Hirvonen, Mrs. Alexander (Helga E Lindqvist) \n 1 \n 1 \n 3101298 \n 12.2875 \n NA \n S \n \n \n male \n 43.0000 \n 43.00000 \n 3 \n 0 \n Holm, Mr. John Fredrik Alexander \n 0 \n 0 \n C 7075 \n 6.4500 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Holthen, Mr. Johan Martin \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 1 \n Honkanen, Miss. Eliina \n 0 \n 0 \n STON/O2. 3101283 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Horgan, Mr. John \n 0 \n 0 \n 370377 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Howard, Miss. May Elizabeth \n 0 \n 0 \n A. 2. 39186 \n 8.0500 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Humblen, Mr. Adolf Mathias Nicolai Olsen \n 0 \n 0 \n 348121 \n 7.6500 \n F G63 \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Hyman, Mr. Abraham \n 0 \n 0 \n 3470 \n 7.8875 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Ibrahim Shawah, Mr. Yousseff \n 0 \n 0 \n 2685 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ilieff, Mr. Ylio \n 0 \n 0 \n 349220 \n 7.8958 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 0 \n Ilmakangas, Miss. Ida Livija \n 1 \n 0 \n STON/O2. 3101270 \n 7.9250 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 3 \n 0 \n Ilmakangas, Miss. Pieta Sofia \n 1 \n 0 \n STON/O2. 3101271 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ivanoff, Mr. Kanio \n 0 \n 0 \n 349201 \n 7.8958 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Jalsevac, Mr. Ivan \n 0 \n 0 \n 349240 \n 7.8958 \n NA \n C \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Jansson, Mr. Carl Olof \n 0 \n 0 \n 350034 \n 7.7958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Jardin, Mr. Jose Neto \n 0 \n 0 \n SOTON/O.Q. 3101305 \n 7.0500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Jensen, Mr. Hans Peder \n 0 \n 0 \n 350050 \n 7.8542 \n NA \n S \n \n \n male \n 48.0000 \n 48.00000 \n 3 \n 0 \n Jensen, Mr. Niels Peder \n 0 \n 0 \n 350047 \n 7.8542 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Jensen, Mr. Svend Lauritz \n 1 \n 0 \n 350048 \n 7.0542 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Jermyn, Miss. Annie \n 0 \n 0 \n 14313 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Johannesen-Bratthammer, Mr. Bernt \n 0 \n 0 \n 65306 \n 8.1125 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Johanson, Mr. Jakob Alfred \n 0 \n 0 \n 3101264 \n 6.4958 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 1 \n Johansson Palmquist, Mr. Oskar Leander \n 0 \n 0 \n 347070 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Johansson, Mr. Erik \n 0 \n 0 \n 350052 \n 7.7958 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Johansson, Mr. Gustaf Joel \n 0 \n 0 \n 7540 \n 8.6542 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Johansson, Mr. Karl Johan \n 0 \n 0 \n 347063 \n 7.7750 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Johansson, Mr. Nils \n 0 \n 0 \n 347467 \n 7.8542 \n NA \n S \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 1 \n Johnson, Master. Harold Theodor \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 1 \n Johnson, Miss. Eleanor Ileen \n 1 \n 1 \n 347742 \n 11.1333 \n NA \n S \n \n \n male \n 49.0000 \n 49.00000 \n 3 \n 0 \n Johnson, Mr. Alfred \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Johnson, Mr. Malkolm Joackim \n 0 \n 0 \n 347062 \n 7.7750 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Johnson, Mr. William Cahoone Jr \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 1 \n Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) \n 0 \n 2 \n 347742 \n 11.1333 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Johnston, Master. William Arthur \"Willie\" \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Johnston, Miss. Catherine Helen \"Carrie\" \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Johnston, Mr. Andrew G \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson) \n 1 \n 2 \n W./C. 6607 \n 23.4500 \n NA \n S \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Jonkoff, Mr. Lalio \n 0 \n 0 \n 349204 \n 7.8958 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Jonsson, Mr. Carl \n 0 \n 0 \n 350417 \n 7.8542 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Jonsson, Mr. Nils Hilding \n 0 \n 0 \n 350408 \n 7.8542 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 3 \n 0 \n Jussila, Miss. Katriina \n 1 \n 0 \n 4136 \n 9.8250 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 0 \n Jussila, Miss. Mari Aina \n 1 \n 0 \n 4137 \n 9.8250 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Jussila, Mr. Eiriik \n 0 \n 0 \n STON/O 2. 3101286 \n 7.9250 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Kallio, Mr. Nikolai Erland \n 0 \n 0 \n STON/O 2. 3101274 \n 7.1250 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Kalvik, Mr. Johannes Halvorsen \n 0 \n 0 \n 8475 \n 8.4333 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Karaic, Mr. Milan \n 0 \n 0 \n 349246 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Karlsson, Mr. Einar Gervasius \n 0 \n 0 \n 350053 \n 7.7958 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Karlsson, Mr. Julius Konrad Eugen \n 0 \n 0 \n 347465 \n 7.8542 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Karlsson, Mr. Nils August \n 0 \n 0 \n 350060 \n 7.5208 \n NA \n S \n \n \n female \n 4.0000 \n 4.00000 \n 3 \n 1 \n Karun, Miss. Manca \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 1 \n Karun, Mr. Franz \n 0 \n 1 \n 349256 \n 13.4167 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kassem, Mr. Fared \n 0 \n 0 \n 2700 \n 7.2292 \n NA \n C \n \n \n male \n 18.5000 \n 18.50000 \n 3 \n 0 \n Katavelas, Mr. Vassilios (\"Catavelas Vassilios\") \n 0 \n 0 \n 2682 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Keane, Mr. Andrew \"Andy\" \n 0 \n 0 \n 12460 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Keefe, Mr. Arthur \n 0 \n 0 \n 323592 \n 7.2500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Kelly, Miss. Anna Katherine \"Annie Kate\" \n 0 \n 0 \n 9234 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Kelly, Miss. Mary \n 0 \n 0 \n 14312 \n 7.7500 \n NA \n Q \n \n \n male \n 34.5000 \n 34.50000 \n 3 \n 0 \n Kelly, Mr. James \n 0 \n 0 \n 330911 \n 7.8292 \n NA \n Q \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 0 \n Kelly, Mr. James \n 0 \n 0 \n 363592 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Kennedy, Mr. John \n 0 \n 0 \n 368783 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Khalil, Mr. Betros \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Khalil, Mrs. Betros (Zahie \"Maria\" Elias) \n 1 \n 0 \n 2660 \n 14.4542 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kiernan, Mr. John \n 1 \n 0 \n 367227 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kiernan, Mr. Philip \n 1 \n 0 \n 367229 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kilgannon, Mr. Thomas J \n 0 \n 0 \n 36865 \n 7.7375 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Kink, Miss. Maria \n 2 \n 0 \n 315152 \n 8.6625 \n NA \n S \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 0 \n Kink, Mr. Vincenz \n 2 \n 0 \n 315151 \n 8.6625 \n NA \n S \n \n \n female \n 4.0000 \n 4.00000 \n 3 \n 1 \n Kink-Heilmann, Miss. Luise Gretchen \n 0 \n 2 \n 315153 \n 22.0250 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Kink-Heilmann, Mr. Anton \n 3 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 1 \n Kink-Heilmann, Mrs. Anton (Luise Heilmann) \n 1 \n 1 \n 315153 \n 22.0250 \n NA \n S \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 0 \n Klasen, Miss. Gertrud Emilia \n 1 \n 1 \n 350405 \n 12.1833 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Klasen, Mr. Klas Albin \n 1 \n 1 \n 350404 \n 7.8542 \n NA \n S \n \n \n female \n 36.0000 \n 36.00000 \n 3 \n 0 \n Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist) \n 0 \n 2 \n 350405 \n 12.1833 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Kraeff, Mr. Theodor \n 0 \n 0 \n 349253 \n 7.8958 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Krekorian, Mr. Neshan \n 0 \n 0 \n 2654 \n 7.2292 \n F E57 \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lahoud, Mr. Sarkis \n 0 \n 0 \n 2624 \n 7.2250 \n NA \n C \n \n \n female \n 37.0000 \n 37.00000 \n 3 \n 0 \n Laitinen, Miss. Kristina Sofia \n 0 \n 0 \n 4135 \n 9.5875 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Laleff, Mr. Kristo \n 0 \n 0 \n 349217 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Lam, Mr. Ali \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lam, Mr. Len \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Landergren, Miss. Aurora Adelia \n 0 \n 0 \n C 7077 \n 7.2500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lane, Mr. Patrick \n 0 \n 0 \n 7935 \n 7.7500 \n NA \n Q \n \n \n male \n 26.0000 \n 26.00000 \n 3 \n 1 \n Lang, Mr. Fang \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Larsson, Mr. August Viktor \n 0 \n 0 \n 7545 \n 9.4833 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Larsson, Mr. Bengt Edvin \n 0 \n 0 \n 347067 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Larsson-Rondberg, Mr. Edvard A \n 0 \n 0 \n 347065 \n 7.7750 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 1 \n Leeni, Mr. Fahim (\"Philip Zenni\") \n 0 \n 0 \n 2620 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lefebre, Master. Henry Forbes \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Miss. Ida \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Miss. Jeannie \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Miss. Mathilde \n 3 \n 1 \n 4133 \n 25.4667 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lefebre, Mrs. Frank (Frances) \n 0 \n 4 \n 4133 \n 25.4667 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Leinonen, Mr. Antti Gustaf \n 0 \n 0 \n STON/O 2. 3101292 \n 7.9250 \n NA \n S \n \n \n male \n 34.5000 \n 34.50000 \n 3 \n 0 \n Lemberopolous, Mr. Peter L \n 0 \n 0 \n 2683 \n 6.4375 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Lennon, Miss. Mary \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lennon, Mr. Denis \n 1 \n 0 \n 370371 \n 15.5000 \n NA \n Q \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Leonard, Mr. Lionel \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Lester, Mr. James \n 0 \n 0 \n A/4 48871 \n 24.1500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Lievens, Mr. Rene Aime \n 0 \n 0 \n 345781 \n 9.5000 \n NA \n S \n \n \n female \n 25.0000 \n 25.00000 \n 3 \n 0 \n Lindahl, Miss. Agda Thorilda Viktoria \n 0 \n 0 \n 347071 \n 7.7750 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 0 \n Lindblom, Miss. Augusta Charlotta \n 0 \n 0 \n 347073 \n 7.7500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Lindell, Mr. Edvard Bengtsson \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson) \n 1 \n 0 \n 349910 \n 15.5500 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Lindqvist, Mr. Eino William \n 1 \n 0 \n STON/O 2. 3101285 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Linehan, Mr. Michael \n 0 \n 0 \n 330971 \n 7.8792 \n NA \n Q \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Ling, Mr. Lee \n 0 \n 0 \n 1601 \n 56.4958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lithman, Mr. Simon \n 0 \n 0 \n S.O./P.P. 251 \n 7.5500 \n NA \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Lobb, Mr. William Arthur \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 0 \n Lobb, Mrs. William Arthur (Cordelia K Stanlick) \n 1 \n 0 \n A/5. 3336 \n 16.1000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lockyer, Mr. Edward \n 0 \n 0 \n 1222 \n 7.8792 \n NA \n S \n \n \n male \n 20.5000 \n 20.50000 \n 3 \n 0 \n Lovell, Mr. John Hall (\"Henry\") \n 0 \n 0 \n A/5 21173 \n 7.2500 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 1 \n Lulic, Mr. Nikola \n 0 \n 0 \n 315098 \n 8.6625 \n NA \n S \n \n \n male \n 51.0000 \n 51.00000 \n 3 \n 0 \n Lundahl, Mr. Johan Svensson \n 0 \n 0 \n 347743 \n 7.0542 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 1 \n Lundin, Miss. Olga Elida \n 0 \n 0 \n 347469 \n 7.8542 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Lundstrom, Mr. Thure Edvin \n 0 \n 0 \n 350403 \n 7.5792 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Lyntakoff, Mr. Stanko \n 0 \n 0 \n 349235 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n MacKay, Mr. George William \n 0 \n 0 \n C.A. 42795 \n 7.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Madigan, Miss. Margaret \"Maggie\" \n 0 \n 0 \n 370370 \n 7.7500 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 1 \n Madsen, Mr. Fridtjof Arne \n 0 \n 0 \n C 17369 \n 7.1417 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Maenpaa, Mr. Matti Alexanteri \n 0 \n 0 \n STON/O 2. 3101275 \n 7.1250 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Mahon, Miss. Bridget Delia \n 0 \n 0 \n 330924 \n 7.8792 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mahon, Mr. John \n 0 \n 0 \n AQ/4 3130 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Maisner, Mr. Simon \n 0 \n 0 \n A/S 2816 \n 8.0500 \n NA \n S \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Makinen, Mr. Kalle Edvard \n 0 \n 0 \n STON/O 2. 3101268 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Mamee, Mr. Hanna \n 0 \n 0 \n 2677 \n 7.2292 \n NA \n C \n \n \n female \n 30.5000 \n 30.50000 \n 3 \n 0 \n Mangan, Miss. Mary \n 0 \n 0 \n 364850 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Mannion, Miss. Margareth \n 0 \n 0 \n 36866 \n 7.7375 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mardirosian, Mr. Sarkis \n 0 \n 0 \n 2655 \n 7.2292 \n F E46 \n C \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Markoff, Mr. Marin \n 0 \n 0 \n 349213 \n 7.8958 \n NA \n C \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Markun, Mr. Johann \n 0 \n 0 \n 349257 \n 7.8958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Masselmani, Mrs. Fatima \n 0 \n 0 \n 2649 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Matinoff, Mr. Nicola \n 0 \n 0 \n 349255 \n 7.8958 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McCarthy, Miss. Catherine \"Katie\" \n 0 \n 0 \n 383123 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n McCormack, Mr. Thomas Joseph \n 0 \n 0 \n 367228 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McCoy, Miss. Agnes \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McCoy, Miss. Alicia \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n McCoy, Mr. Bernard \n 2 \n 0 \n 367226 \n 23.2500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McDermott, Miss. Brigdet Delia \n 0 \n 0 \n 330932 \n 7.7875 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n McEvoy, Mr. Michael \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n McGovern, Miss. Mary \n 0 \n 0 \n 330931 \n 7.8792 \n NA \n Q \n \n \n female \n 15.0000 \n 15.00000 \n 3 \n 1 \n McGowan, Miss. Anna \"Annie\" \n 0 \n 0 \n 330923 \n 8.0292 \n NA \n Q \n \n \n female \n 35.0000 \n 35.00000 \n 3 \n 0 \n McGowan, Miss. Katherine \n 0 \n 0 \n 9232 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n McMahon, Mr. Martin \n 0 \n 0 \n 370372 \n 7.7500 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n McNamee, Mr. Neal \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 0 \n McNamee, Mrs. Neal (Eileen O'Leary) \n 1 \n 0 \n 376566 \n 16.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n McNeill, Miss. Bridget \n 0 \n 0 \n 370368 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Meanwell, Miss. (Marion Ogden) \n 0 \n 0 \n SOTON/O.Q. 392087 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Meek, Mrs. Thomas (Annie Louise Rowley) \n 0 \n 0 \n 343095 \n 8.0500 \n NA \n S \n \n \n male \n 55.5000 \n 55.50000 \n 3 \n 0 \n Meo, Mr. Alfonzo \n 0 \n 0 \n A.5. 11206 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mernagh, Mr. Robert \n 0 \n 0 \n 368703 \n 7.7500 \n NA \n Q \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 1 \n Midtsjo, Mr. Karl Albert \n 0 \n 0 \n 345501 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Miles, Mr. Frank \n 0 \n 0 \n 359306 \n 8.0500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Mineff, Mr. Ivan \n 0 \n 0 \n 349233 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Minkoff, Mr. Lazar \n 0 \n 0 \n 349211 \n 7.8958 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Mionoff, Mr. Stoytcho \n 0 \n 0 \n 349207 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Mitkoff, Mr. Mito \n 0 \n 0 \n 349221 \n 7.8958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Mockler, Miss. Helen Mary \"Ellie\" \n 0 \n 0 \n 330980 \n 7.8792 \n NA \n Q \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Moen, Mr. Sigurd Hansen \n 0 \n 0 \n 348123 \n 7.6500 \n F G73 \n S \n \n \n male \n 6.0000 \n 6.00000 \n 3 \n 1 \n Moor, Master. Meier \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n female \n 27.0000 \n 27.00000 \n 3 \n 1 \n Moor, Mrs. (Beila) \n 0 \n 1 \n 392096 \n 12.4750 \n E121 \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moore, Mr. Leonard Charles \n 0 \n 0 \n A4. 54510 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Moran, Miss. Bertha \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moran, Mr. Daniel J \n 1 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moran, Mr. James \n 0 \n 0 \n 330877 \n 8.4583 \n NA \n Q \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Morley, Mr. William \n 0 \n 0 \n 364506 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Morrow, Mr. Thomas Rowan \n 0 \n 0 \n 372622 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Moss, Mr. Albert Johan \n 0 \n 0 \n 312991 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Moubarek, Master. Gerios \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Moubarek, Master. Halim Gonios (\"William George\") \n 1 \n 1 \n 2661 \n 15.2458 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Moubarek, Mrs. George (Omine \"Amenia\" Alexander) \n 0 \n 2 \n 2661 \n 15.2458 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Moussa, Mrs. (Mantoura Boulos) \n 0 \n 0 \n 2626 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Moutal, Mr. Rahamin Haim \n 0 \n 0 \n 374746 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Mullens, Miss. Katherine \"Katie\" \n 0 \n 0 \n 35852 \n 7.7333 \n NA \n Q \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Mulvihill, Miss. Bertha E \n 0 \n 0 \n 382653 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Murdlin, Mr. Joseph \n 0 \n 0 \n A./5. 3235 \n 8.0500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Murphy, Miss. Katherine \"Kate\" \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Murphy, Miss. Margaret Jane \n 1 \n 0 \n 367230 \n 15.5000 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Murphy, Miss. Nora \n 0 \n 0 \n 36568 \n 15.5000 \n NA \n Q \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Myhrman, Mr. Pehr Fabian Oliver Malkolm \n 0 \n 0 \n 347078 \n 7.7500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Naidenoff, Mr. Penko \n 0 \n 0 \n 349206 \n 7.8958 \n NA \n S \n \n \n female \n 15.0000 \n 15.00000 \n 3 \n 1 \n Najib, Miss. Adele Kiamie \"Jane\" \n 0 \n 0 \n 2667 \n 7.2250 \n NA \n C \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 1 \n Nakid, Miss. Maria (\"Mary\") \n 0 \n 2 \n 2653 \n 15.7417 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 1 \n Nakid, Mr. Sahid \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n female \n 19.0000 \n 19.00000 \n 3 \n 1 \n Nakid, Mrs. Said (Waika \"Mary\" Mowad) \n 1 \n 1 \n 2653 \n 15.7417 \n NA \n C \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Nancarrow, Mr. William Henry \n 0 \n 0 \n A./5. 3338 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Nankoff, Mr. Minko \n 0 \n 0 \n 349218 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Nasr, Mr. Mustafa \n 0 \n 0 \n 2652 \n 7.2292 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Naughton, Miss. Hannah \n 0 \n 0 \n 365237 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Nenkoff, Mr. Christo \n 0 \n 0 \n 349234 \n 7.8958 \n NA \n S \n \n \n male \n 12.0000 \n 12.00000 \n 3 \n 1 \n Nicola-Yarred, Master. Elias \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n female \n 14.0000 \n 14.00000 \n 3 \n 1 \n Nicola-Yarred, Miss. Jamila \n 1 \n 0 \n 2651 \n 11.2417 \n NA \n C \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 0 \n Nieminen, Miss. Manta Josefina \n 0 \n 0 \n 3101297 \n 7.9250 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Niklasson, Mr. Samuel \n 0 \n 0 \n 363611 \n 8.0500 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Nilsson, Miss. Berta Olivia \n 0 \n 0 \n 347066 \n 7.7750 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 1 \n Nilsson, Miss. Helmina Josefina \n 0 \n 0 \n 347470 \n 7.8542 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Nilsson, Mr. August Ferdinand \n 0 \n 0 \n 350410 \n 7.8542 \n NA \n S \n \n \n male \n 41.0000 \n 41.00000 \n 3 \n 0 \n Nirva, Mr. Iisakki Antino Aijo \n 0 \n 0 \n SOTON/O2 3101272 \n 7.1250 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 1 \n Niskanen, Mr. Juha \n 0 \n 0 \n STON/O 2. 3101289 \n 7.9250 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Nosworthy, Mr. Richard Cater \n 0 \n 0 \n A/4. 39886 \n 7.8000 \n NA \n S \n \n \n male \n 28.5000 \n 28.50000 \n 3 \n 0 \n Novel, Mr. Mansouer \n 0 \n 0 \n 2697 \n 7.2292 \n NA \n C \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Nysten, Miss. Anna Sofia \n 0 \n 0 \n 347081 \n 7.7500 \n NA \n S \n \n \n male \n 61.0000 \n 61.00000 \n 3 \n 0 \n Nysveen, Mr. Johan Hansen \n 0 \n 0 \n 345364 \n 6.2375 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Brien, Mr. Thomas \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Brien, Mr. Timothy \n 0 \n 0 \n 330979 \n 7.8292 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey) \n 1 \n 0 \n 370365 \n 15.5000 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Connell, Mr. Patrick D \n 0 \n 0 \n 334912 \n 7.7333 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Connor, Mr. Maurice \n 0 \n 0 \n 371060 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n O'Connor, Mr. Patrick \n 0 \n 0 \n 366713 \n 7.7500 \n NA \n Q \n \n \n male \n 23.0000 \n 23.00000 \n 3 \n 0 \n Odahl, Mr. Nils Martin \n 0 \n 0 \n 7267 \n 9.2250 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n O'Donoghue, Ms. Bridget \n 0 \n 0 \n 364856 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Driscoll, Miss. Bridget \n 0 \n 0 \n 14311 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Dwyer, Miss. Ellen \"Nellie\" \n 0 \n 0 \n 330959 \n 7.8792 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 1 \n Ohman, Miss. Velin \n 0 \n 0 \n 347085 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n O'Keefe, Mr. Patrick \n 0 \n 0 \n 368402 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n O'Leary, Miss. Hanora \"Norah\" \n 0 \n 0 \n 330919 \n 7.8292 \n NA \n Q \n \n \n male \n 9.0000 \n 9.00000 \n 3 \n 1 \n Olsen, Master. Artur Karl \n 0 \n 1 \n C 17368 \n 3.1708 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Olsen, Mr. Henry Margido \n 0 \n 0 \n C 4001 \n 22.5250 \n NA \n S \n \n \n male \n 42.0000 \n 42.00000 \n 3 \n 0 \n Olsen, Mr. Karl Siegwart Andreas \n 0 \n 1 \n 4579 \n 8.4042 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Olsen, Mr. Ole Martin \n 0 \n 0 \n Fa 265302 \n 7.3125 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 0 \n Olsson, Miss. Elina \n 0 \n 0 \n 350407 \n 7.8542 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Olsson, Mr. Nils Johan Goransson \n 0 \n 0 \n 347464 \n 7.8542 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Olsson, Mr. Oscar Wilhelm \n 0 \n 0 \n 347079 \n 7.7750 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Olsvigen, Mr. Thor Anderson \n 0 \n 0 \n 6563 \n 9.2250 \n NA \n S \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 0 \n Oreskovic, Miss. Jelka \n 0 \n 0 \n 315085 \n 8.6625 \n NA \n S \n \n \n female \n 20.0000 \n 20.00000 \n 3 \n 0 \n Oreskovic, Miss. Marija \n 0 \n 0 \n 315096 \n 8.6625 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Oreskovic, Mr. Luka \n 0 \n 0 \n 315094 \n 8.6625 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Osen, Mr. Olaf Elon \n 0 \n 0 \n 7534 \n 9.2167 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 1 \n Osman, Mrs. Mara \n 0 \n 0 \n 349244 \n 8.6833 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n O'Sullivan, Miss. Bridget Mary \n 0 \n 0 \n 330909 \n 7.6292 \n NA \n Q \n \n \n male \n 2.0000 \n 2.00000 \n 3 \n 0 \n Palsson, Master. Gosta Leonard \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n male \n 6.0000 \n 6.00000 \n 3 \n 0 \n Palsson, Master. Paul Folke \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n female \n 3.0000 \n 3.00000 \n 3 \n 0 \n Palsson, Miss. Stina Viola \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n female \n 8.0000 \n 8.00000 \n 3 \n 0 \n Palsson, Miss. Torborg Danira \n 3 \n 1 \n 349909 \n 21.0750 \n NA \n S \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 0 \n Palsson, Mrs. Nils (Alma Cornelia Berglund) \n 0 \n 4 \n 349909 \n 21.0750 \n NA \n S \n \n \n male \n 1.0000 \n 1.00000 \n 3 \n 0 \n Panula, Master. Eino Viljami \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 7.0000 \n 7.00000 \n 3 \n 0 \n Panula, Master. Juha Niilo \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 2.0000 \n 2.00000 \n 3 \n 0 \n Panula, Master. Urho Abraham \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Panula, Mr. Ernesti Arvid \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 14.0000 \n 14.00000 \n 3 \n 0 \n Panula, Mr. Jaako Arnold \n 4 \n 1 \n 3101295 \n 39.6875 \n NA \n S \n \n \n female \n 41.0000 \n 41.00000 \n 3 \n 0 \n Panula, Mrs. Juha (Maria Emilia Ojala) \n 0 \n 5 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Pasic, Mr. Jakob \n 0 \n 0 \n 315097 \n 8.6625 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Patchett, Mr. George \n 0 \n 0 \n 358585 \n 14.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Paulner, Mr. Uscher \n 0 \n 0 \n 3411 \n 8.7125 \n NA \n C \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Pavlovic, Mr. Stefo \n 0 \n 0 \n 349242 \n 7.8958 \n NA \n S \n \n \n male \n 0.7500 \n 0.75000 \n 3 \n 0 \n Peacock, Master. Alfred Edward \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n female \n 3.0000 \n 3.00000 \n 3 \n 0 \n Peacock, Miss. Treasteall \n 1 \n 1 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n female \n 26.0000 \n 26.00000 \n 3 \n 0 \n Peacock, Mrs. Benjamin (Edith Nile) \n 0 \n 2 \n SOTON/O.Q. 3101315 \n 13.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Pearce, Mr. Ernest \n 0 \n 0 \n 343271 \n 7.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Pedersen, Mr. Olaf \n 0 \n 0 \n 345498 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Peduzzi, Mr. Joseph \n 0 \n 0 \n A/5 2817 \n 8.0500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Pekoniemi, Mr. Edvard \n 0 \n 0 \n STON/O 2. 3101294 \n 7.9250 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Peltomaki, Mr. Nikolai Johannes \n 0 \n 0 \n STON/O 2. 3101291 \n 7.9250 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Perkin, Mr. John Henry \n 0 \n 0 \n A/5 21174 \n 7.2500 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Persson, Mr. Ernst Ulrik \n 1 \n 0 \n 347083 \n 7.7750 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Peter, Master. Michael J \n 1 \n 1 \n 2668 \n 22.3583 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Peter, Miss. Anna \n 1 \n 1 \n 2668 \n 22.3583 \n F E69 \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Peter, Mrs. Catherine (Catherine Rizk) \n 0 \n 2 \n 2668 \n 22.3583 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Peters, Miss. Katie \n 0 \n 0 \n 330935 \n 8.1375 \n NA \n Q \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Petersen, Mr. Marius \n 0 \n 0 \n 342441 \n 8.0500 \n NA \n S \n \n \n female \n 28.0000 \n 28.00000 \n 3 \n 0 \n Petranec, Miss. Matilda \n 0 \n 0 \n 349245 \n 7.8958 \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Petroff, Mr. Nedelio \n 0 \n 0 \n 349212 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Petroff, Mr. Pastcho (\"Pentcho\") \n 0 \n 0 \n 349215 \n 7.8958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Petterson, Mr. Johan Emil \n 1 \n 0 \n 347076 \n 7.7750 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Pettersson, Miss. Ellen Natalia \n 0 \n 0 \n 347087 \n 7.7750 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 1 \n Pickard, Mr. Berk (Berk Trembisky) \n 0 \n 0 \n SOTON/O.Q. 392078 \n 8.0500 \n E10 \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Plotcharsky, Mr. Vasil \n 0 \n 0 \n 349227 \n 7.8958 \n NA \n S \n \n \n male \n 17.0000 \n 17.00000 \n 3 \n 0 \n Pokrnic, Mr. Mate \n 0 \n 0 \n 315095 \n 8.6625 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Pokrnic, Mr. Tome \n 0 \n 0 \n 315092 \n 8.6625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Radeff, Mr. Alexander \n 0 \n 0 \n 349223 \n 7.8958 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Rasmussen, Mrs. (Lena Jacobsen Solvang) \n 0 \n 0 \n 65305 \n 8.1125 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Razi, Mr. Raihed \n 0 \n 0 \n 2629 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Reed, Mr. James George \n 0 \n 0 \n 362316 \n 7.2500 \n NA \n S \n \n \n male \n 38.0000 \n 38.00000 \n 3 \n 0 \n Rekic, Mr. Tido \n 0 \n 0 \n 349249 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Reynolds, Mr. Harold J \n 0 \n 0 \n 342684 \n 8.0500 \n NA \n S \n \n \n male \n 10.0000 \n 10.00000 \n 3 \n 0 \n Rice, Master. Albert \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 0 \n Rice, Master. Arthur \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 7.0000 \n 7.00000 \n 3 \n 0 \n Rice, Master. Eric \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 2.0000 \n 2.00000 \n 3 \n 0 \n Rice, Master. Eugene \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n male \n 8.0000 \n 8.00000 \n 3 \n 0 \n Rice, Master. George Hugh \n 4 \n 1 \n 382652 \n 29.1250 \n NA \n Q \n \n \n female \n 39.0000 \n 39.00000 \n 3 \n 0 \n Rice, Mrs. William (Margaret Norton) \n 0 \n 5 \n 382652 \n 29.1250 \n NA \n Q \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Riihivouri, Miss. Susanna Juhantytar \"Sanni\" \n 0 \n 0 \n 3101295 \n 39.6875 \n NA \n S \n \n \n male \n 35.0000 \n 35.00000 \n 3 \n 0 \n Rintamaki, Mr. Matti \n 0 \n 0 \n STON/O 2. 3101273 \n 7.1250 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Riordan, Miss. Johanna \"Hannah\" \n 0 \n 0 \n 334915 \n 7.7208 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Risien, Mr. Samuel Beard \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Risien, Mrs. Samuel (Emma) \n 0 \n 0 \n 364498 \n 14.5000 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 3 \n 0 \n Robins, Mr. Alexander A \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n female \n 47.0000 \n 47.00000 \n 3 \n 0 \n Robins, Mrs. Alexander A (Grace Charity Laury) \n 1 \n 0 \n A/5. 3337 \n 14.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Rogers, Mr. William John \n 0 \n 0 \n S.C./A.4. 23567 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Rommetvedt, Mr. Knud Paust \n 0 \n 0 \n 312993 \n 7.7750 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Rosblom, Miss. Salli Helena \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Rosblom, Mr. Viktor Richard \n 1 \n 1 \n 370129 \n 20.2125 \n NA \n S \n \n \n female \n 41.0000 \n 41.00000 \n 3 \n 0 \n Rosblom, Mrs. Viktor (Helena Wilhelmina) \n 0 \n 2 \n 370129 \n 20.2125 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Roth, Miss. Sarah A \n 0 \n 0 \n 342712 \n 8.0500 \n NA \n S \n \n \n male \n 50.0000 \n 50.00000 \n 3 \n 0 \n Rouse, Mr. Richard Henry \n 0 \n 0 \n A/5 3594 \n 8.0500 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Rush, Mr. Alfred George John \n 0 \n 0 \n A/4. 20589 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 1 \n Ryan, Mr. Edward \n 0 \n 0 \n 383162 \n 7.7500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ryan, Mr. Patrick \n 0 \n 0 \n 371110 \n 24.1500 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Saad, Mr. Amin \n 0 \n 0 \n 2671 \n 7.2292 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Saad, Mr. Khalil \n 0 \n 0 \n 2672 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Saade, Mr. Jean Nassr \n 0 \n 0 \n 2676 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sadlier, Mr. Matthew \n 0 \n 0 \n 367655 \n 7.7292 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sadowitz, Mr. Harry \n 0 \n 0 \n LP 1588 \n 7.5750 \n NA \n S \n \n \n male \n 38.5000 \n 38.50000 \n 3 \n 0 \n Saether, Mr. Simon Sivertsen \n 0 \n 0 \n SOTON/O.Q. 3101262 \n 7.2500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Master. Thomas Henry \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n 14.5000 \n 14.50000 \n 3 \n 0 \n Sage, Master. William Henry \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Ada \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Constance Gladys \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Dorothy Edith \"Dolly\" \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Miss. Stella Anna \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. Douglas Bullen \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. Frederick \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. George John Jr \n 8 \n 2 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sage, Mr. John George \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Sage, Mrs. John (Annie Bullen) \n 1 \n 9 \n CA. 2343 \n 69.5500 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Salander, Mr. Karl Johan \n 0 \n 0 \n 7266 \n 9.3250 \n NA \n S \n \n \n female \n 21.0000 \n 21.00000 \n 3 \n 1 \n Salkjelsvik, Miss. Anna Kristine \n 0 \n 0 \n 343120 \n 7.6500 \n NA \n S \n \n \n male \n 39.0000 \n 39.00000 \n 3 \n 0 \n Salonen, Mr. Johan Werner \n 0 \n 0 \n 3101296 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Samaan, Mr. Elias \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Samaan, Mr. Hanna \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Samaan, Mr. Youssef \n 2 \n 0 \n 2662 \n 21.6792 \n NA \n C \n \n \n female \n 1.0000 \n 1.00000 \n 3 \n 1 \n Sandstrom, Miss. Beatrice Irene \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n female \n 24.0000 \n 24.00000 \n 3 \n 1 \n Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson) \n 0 \n 2 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n female \n 4.0000 \n 4.00000 \n 3 \n 1 \n Sandstrom, Miss. Marguerite Rut \n 1 \n 1 \n PP 9549 \n 16.7000 \n G6 \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Sap, Mr. Julius \n 0 \n 0 \n 345768 \n 9.5000 \n NA \n S \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Saundercock, Mr. William Henry \n 0 \n 0 \n A/5. 2151 \n 8.0500 \n NA \n S \n \n \n male \n 24.5000 \n 24.50000 \n 3 \n 0 \n Sawyer, Mr. Frederick Charles \n 0 \n 0 \n 342826 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Scanlan, Mr. James \n 0 \n 0 \n 36209 \n 7.7250 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sdycoff, Mr. Todor \n 0 \n 0 \n 349222 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Shaughnessy, Mr. Patrick \n 0 \n 0 \n 370374 \n 7.7500 \n NA \n Q \n \n \n male \n 29.0000 \n 29.00000 \n 3 \n 1 \n Sheerlinck, Mr. Jan Baptist \n 0 \n 0 \n 345779 \n 9.5000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Shellard, Mr. Frederick William \n 0 \n 0 \n C.A. 6212 \n 15.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Shine, Miss. Ellen Natalia \n 0 \n 0 \n 330968 \n 7.7792 \n NA \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Shorney, Mr. Charles Joseph \n 0 \n 0 \n 374910 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Simmons, Mr. John \n 0 \n 0 \n SOTON/OQ 392082 \n 8.0500 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Sirayanian, Mr. Orsen \n 0 \n 0 \n 2669 \n 7.2292 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Sirota, Mr. Maurice \n 0 \n 0 \n 392092 \n 8.0500 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Sivic, Mr. Husein \n 0 \n 0 \n 349251 \n 7.8958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Sivola, Mr. Antti Wilhelm \n 0 \n 0 \n STON/O 2. 3101280 \n 7.9250 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Sjoblom, Miss. Anna Sofia \n 0 \n 0 \n 3101265 \n 7.4958 \n NA \n S \n \n \n male \n 4.0000 \n 4.00000 \n 3 \n 0 \n Skoog, Master. Harald \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n male \n 10.0000 \n 10.00000 \n 3 \n 0 \n Skoog, Master. Karl Thorsten \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 0 \n Skoog, Miss. Mabel \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Skoog, Miss. Margit Elizabeth \n 3 \n 2 \n 347088 \n 27.9000 \n NA \n S \n \n \n male \n 40.0000 \n 40.00000 \n 3 \n 0 \n Skoog, Mr. Wilhelm \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n female \n 45.0000 \n 45.00000 \n 3 \n 0 \n Skoog, Mrs. William (Anna Bernhardina Karlsson) \n 1 \n 4 \n 347088 \n 27.9000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Slabenoff, Mr. Petco \n 0 \n 0 \n 349214 \n 7.8958 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Slocovski, Mr. Selman Francis \n 0 \n 0 \n SOTON/OQ 392086 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Smiljanic, Mr. Mile \n 0 \n 0 \n 315037 \n 8.6625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Smith, Mr. Thomas \n 0 \n 0 \n 384461 \n 7.7500 \n NA \n Q \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Smyth, Miss. Julia \n 0 \n 0 \n 335432 \n 7.7333 \n NA \n Q \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Soholt, Mr. Peter Andreas Lauritz Andersen \n 0 \n 0 \n 348124 \n 7.6500 \n F G73 \n S \n \n \n male \n 30.0000 \n 30.00000 \n 3 \n 0 \n Somerton, Mr. Francis William \n 0 \n 0 \n A.5. 18509 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Spector, Mr. Woolf \n 0 \n 0 \n A.5. 3236 \n 8.0500 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Spinner, Mr. Henry John \n 0 \n 0 \n STON/OQ. 369943 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Staneff, Mr. Ivan \n 0 \n 0 \n 349208 \n 7.8958 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Stankovic, Mr. Ivan \n 0 \n 0 \n 349239 \n 8.6625 \n NA \n C \n \n \n female \n 23.0000 \n 23.00000 \n 3 \n 1 \n Stanley, Miss. Amy Zillah Elsie \n 0 \n 0 \n CA. 2314 \n 7.5500 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Stanley, Mr. Edward Roland \n 0 \n 0 \n A/4 45380 \n 8.0500 \n NA \n S \n \n \n male \n 60.5000 \n 60.50000 \n 3 \n 0 \n Storey, Mr. Thomas \n 0 \n 0 \n 3701 \n NA \n NA \n S \n \n \n male \n 19.0000 \n 19.00000 \n 3 \n 0 \n Stoytcheff, Mr. Ilia \n 0 \n 0 \n 349205 \n 7.8958 \n NA \n S \n \n \n female \n 22.0000 \n 22.00000 \n 3 \n 0 \n Strandberg, Miss. Ida Sofia \n 0 \n 0 \n 7553 \n 9.8375 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 1 \n Stranden, Mr. Juho \n 0 \n 0 \n STON/O 2. 3101288 \n 7.9250 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Strilic, Mr. Ivan \n 0 \n 0 \n 315083 \n 8.6625 \n NA \n S \n \n \n female \n 2.0000 \n 2.00000 \n 3 \n 0 \n Strom, Miss. Telma Matilda \n 0 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 0 \n Strom, Mrs. Wilhelm (Elna Matilda Persson) \n 1 \n 1 \n 347054 \n 10.4625 \n G6 \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 1 \n Sunderland, Mr. Victor Francis \n 0 \n 0 \n SOTON/OQ 392089 \n 8.0500 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 1 \n Sundman, Mr. Johan Julian \n 0 \n 0 \n STON/O 2. 3101269 \n 7.9250 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 0 \n Sutehall, Mr. Henry Jr \n 0 \n 0 \n SOTON/OQ 392076 \n 7.0500 \n NA \n S \n \n \n male \n 74.0000 \n 74.00000 \n 3 \n 0 \n Svensson, Mr. Johan \n 0 \n 0 \n 347060 \n 7.7750 \n NA \n S \n \n \n male \n 14.0000 \n 14.00000 \n 3 \n 1 \n Svensson, Mr. Johan Cervin \n 0 \n 0 \n 7538 \n 9.2250 \n NA \n S \n \n \n male \n 24.0000 \n 24.00000 \n 3 \n 0 \n Svensson, Mr. Olof \n 0 \n 0 \n 350035 \n 7.7958 \n NA \n S \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Tenglin, Mr. Gunnar Isidor \n 0 \n 0 \n 350033 \n 7.7958 \n NA \n S \n \n \n male \n 34.0000 \n 34.00000 \n 3 \n 0 \n Theobald, Mr. Thomas Leonard \n 0 \n 0 \n 363294 \n 8.0500 \n NA \n S \n \n \n male \n 0.4167 \n 0.41670 \n 3 \n 1 \n Thomas, Master. Assad Alexander \n 0 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomas, Mr. Charles P \n 1 \n 0 \n 2621 \n 6.4375 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomas, Mr. John \n 0 \n 0 \n 2681 \n 6.4375 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomas, Mr. Tannous \n 0 \n 0 \n 2684 \n 7.2250 \n NA \n C \n \n \n female \n 16.0000 \n 16.00000 \n 3 \n 1 \n Thomas, Mrs. Alexander (Thamine \"Thelma\") \n 1 \n 1 \n 2625 \n 8.5167 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thomson, Mr. Alexander Morrison \n 0 \n 0 \n 32302 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Thorneycroft, Mr. Percival \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n female \n NA \n 28.62425 \n 3 \n 1 \n Thorneycroft, Mrs. Percival (Florence Kate White) \n 1 \n 0 \n 376564 \n 16.1000 \n NA \n S \n \n \n male \n 32.0000 \n 32.00000 \n 3 \n 0 \n Tikkanen, Mr. Juho \n 0 \n 0 \n STON/O 2. 3101293 \n 7.9250 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Tobin, Mr. Roger \n 0 \n 0 \n 383121 \n 7.7500 \n F38 \n Q \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Todoroff, Mr. Lalio \n 0 \n 0 \n 349216 \n 7.8958 \n NA \n S \n \n \n male \n 30.5000 \n 30.50000 \n 3 \n 0 \n Tomlin, Mr. Ernest Portage \n 0 \n 0 \n 364499 \n 8.0500 \n NA \n S \n \n \n male \n 44.0000 \n 44.00000 \n 3 \n 0 \n Torber, Mr. Ernst William \n 0 \n 0 \n 364511 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Torfa, Mr. Assad \n 0 \n 0 \n 2673 \n 7.2292 \n NA \n C \n \n \n male \n 25.0000 \n 25.00000 \n 3 \n 1 \n Tornquist, Mr. William Henry \n 0 \n 0 \n LINE \n 0.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Toufik, Mr. Nakli \n 0 \n 0 \n 2641 \n 7.2292 \n NA \n C \n \n \n male \n 7.0000 \n 7.00000 \n 3 \n 1 \n Touma, Master. Georges Youssef \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n female \n 9.0000 \n 9.00000 \n 3 \n 1 \n Touma, Miss. Maria Youssef \n 1 \n 1 \n 2650 \n 15.2458 \n NA \n C \n \n \n female \n 29.0000 \n 29.00000 \n 3 \n 1 \n Touma, Mrs. Darwis (Hanne Youssef Razi) \n 0 \n 2 \n 2650 \n 15.2458 \n NA \n C \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Turcin, Mr. Stjepan \n 0 \n 0 \n 349247 \n 7.8958 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 1 \n Turja, Miss. Anna Sofia \n 0 \n 0 \n 4138 \n 9.8417 \n NA \n S \n \n \n female \n 63.0000 \n 63.00000 \n 3 \n 1 \n Turkula, Mrs. (Hedwig) \n 0 \n 0 \n 4134 \n 9.5875 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n van Billiard, Master. James William \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n male \n 11.5000 \n 11.50000 \n 3 \n 0 \n van Billiard, Master. Walter John \n 1 \n 1 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n male \n 40.5000 \n 40.50000 \n 3 \n 0 \n van Billiard, Mr. Austin Blyler \n 0 \n 2 \n A/5. 851 \n 14.5000 \n NA \n S \n \n \n female \n 10.0000 \n 10.00000 \n 3 \n 0 \n Van Impe, Miss. Catharina \n 0 \n 2 \n 345773 \n 24.1500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Van Impe, Mr. Jean Baptiste \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n female \n 30.0000 \n 30.00000 \n 3 \n 0 \n Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert) \n 1 \n 1 \n 345773 \n 24.1500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n van Melkebeke, Mr. Philemon \n 0 \n 0 \n 345777 \n 9.5000 \n NA \n S \n \n \n male \n 33.0000 \n 33.00000 \n 3 \n 0 \n Vande Velde, Mr. Johannes Joseph \n 0 \n 0 \n 345780 \n 9.5000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Vande Walle, Mr. Nestor Cyriel \n 0 \n 0 \n 345770 \n 9.5000 \n NA \n S \n \n \n male \n 28.0000 \n 28.00000 \n 3 \n 0 \n Vanden Steen, Mr. Leo Peter \n 0 \n 0 \n 345783 \n 9.5000 \n NA \n S \n \n \n male \n 47.0000 \n 47.00000 \n 3 \n 0 \n Vander Cruyssen, Mr. Victor \n 0 \n 0 \n 345765 \n 9.0000 \n NA \n S \n \n \n female \n 18.0000 \n 18.00000 \n 3 \n 0 \n Vander Planke, Miss. Augusta Maria \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n male \n 31.0000 \n 31.00000 \n 3 \n 0 \n Vander Planke, Mr. Julius \n 3 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n male \n 16.0000 \n 16.00000 \n 3 \n 0 \n Vander Planke, Mr. Leo Edmondus \n 2 \n 0 \n 345764 \n 18.0000 \n NA \n S \n \n \n female \n 31.0000 \n 31.00000 \n 3 \n 0 \n Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) \n 1 \n 0 \n 345763 \n 18.0000 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 1 \n Vartanian, Mr. David \n 0 \n 0 \n 2658 \n 7.2250 \n NA \n C \n \n \n male \n 20.0000 \n 20.00000 \n 3 \n 0 \n Vendel, Mr. Olof Edvin \n 0 \n 0 \n 350416 \n 7.8542 \n NA \n S \n \n \n female \n 14.0000 \n 14.00000 \n 3 \n 0 \n Vestrom, Miss. Hulda Amanda Adolfina \n 0 \n 0 \n 350406 \n 7.8542 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Vovk, Mr. Janko \n 0 \n 0 \n 349252 \n 7.8958 \n NA \n S \n \n \n male \n 22.0000 \n 22.00000 \n 3 \n 0 \n Waelens, Mr. Achille \n 0 \n 0 \n 345767 \n 9.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Ware, Mr. Frederick \n 0 \n 0 \n 359309 \n 8.0500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Warren, Mr. Charles William \n 0 \n 0 \n C.A. 49867 \n 7.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Webber, Mr. James \n 0 \n 0 \n SOTON/OQ 3101316 \n 8.0500 \n NA \n S \n \n \n male \n 32.5000 \n 32.50000 \n 3 \n 0 \n Wenzel, Mr. Linhart \n 0 \n 0 \n 345775 \n 9.5000 \n NA \n S \n \n \n female \n 38.0000 \n 38.00000 \n 3 \n 1 \n Whabee, Mrs. George Joseph (Shawneene Abi-Saab) \n 0 \n 0 \n 2688 \n 7.2292 \n NA \n C \n \n \n male \n 51.0000 \n 51.00000 \n 3 \n 0 \n Widegren, Mr. Carl/Charles Peter \n 0 \n 0 \n 347064 \n 7.7500 \n NA \n S \n \n \n male \n 18.0000 \n 18.00000 \n 3 \n 0 \n Wiklund, Mr. Jakob Alfred \n 1 \n 0 \n 3101267 \n 6.4958 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Wiklund, Mr. Karl Johan \n 1 \n 0 \n 3101266 \n 6.4958 \n NA \n S \n \n \n female \n 47.0000 \n 47.00000 \n 3 \n 1 \n Wilkes, Mrs. James (Ellen Needs) \n 1 \n 0 \n 363272 \n 7.0000 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Willer, Mr. Aaron (\"Abi Weller\") \n 0 \n 0 \n 3410 \n 8.7125 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Willey, Mr. Edward \n 0 \n 0 \n S.O./P.P. 751 \n 7.5500 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Williams, Mr. Howard Hugh \"Harry\" \n 0 \n 0 \n A/5 2466 \n 8.0500 \n NA \n S \n \n \n male \n 28.5000 \n 28.50000 \n 3 \n 0 \n Williams, Mr. Leslie \n 0 \n 0 \n 54636 \n 16.1000 \n NA \n S \n \n \n male \n 21.0000 \n 21.00000 \n 3 \n 0 \n Windelov, Mr. Einar \n 0 \n 0 \n SOTON/OQ 3101317 \n 7.2500 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Wirz, Mr. Albert \n 0 \n 0 \n 315154 \n 8.6625 \n NA \n S \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Wiseman, Mr. Phillippe \n 0 \n 0 \n A/4. 34244 \n 7.2500 \n NA \n S \n \n \n male \n 36.0000 \n 36.00000 \n 3 \n 0 \n Wittevrongel, Mr. Camille \n 0 \n 0 \n 345771 \n 9.5000 \n NA \n S \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Yasbeck, Mr. Antoni \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n female \n 15.0000 \n 15.00000 \n 3 \n 1 \n Yasbeck, Mrs. Antoni (Selini Alexander) \n 1 \n 0 \n 2659 \n 14.4542 \n NA \n C \n \n \n male \n 45.5000 \n 45.50000 \n 3 \n 0 \n Youseff, Mr. Gerious \n 0 \n 0 \n 2628 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Yousif, Mr. Wazli \n 0 \n 0 \n 2647 \n 7.2250 \n NA \n C \n \n \n male \n NA \n 30.48562 \n 3 \n 0 \n Yousseff, Mr. Gerious \n 0 \n 0 \n 2627 \n 14.4583 \n NA \n C \n \n \n female \n 14.5000 \n 14.50000 \n 3 \n 0 \n Zabour, Miss. Hileni \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n female \n NA \n 28.62425 \n 3 \n 0 \n Zabour, Miss. Thamine \n 1 \n 0 \n 2665 \n 14.4542 \n NA \n C \n \n \n male \n 26.5000 \n 26.50000 \n 3 \n 0 \n Zakarian, Mr. Mapriededer \n 0 \n 0 \n 2656 \n 7.2250 \n NA \n C \n \n \n male \n 27.0000 \n 27.00000 \n 3 \n 0 \n Zakarian, Mr. Ortin \n 0 \n 0 \n 2670 \n 7.2250 \n NA \n C \n \n \n\n male \n 29.0000 \n 29.00000 \n 3 \n 0 \n Zimmerman, Mr. Leo \n 0 \n 0 \n 315082 \n 7.8750 \n NA \n S \n
\n \n2. **Chapter Two - Data Structures**\n\n * Be familiar with data structures in R.\n \n * Understand how vectors operate.\n \n * Be familiar with lists.\n \n * Be familiar with data frames and tibbles.\n\n\n\n
\n \n \n3. **Chapter Three - Importing and Exporting Data**\n\n * Organise our work\n \n * Have an understanding of what packages are.\n \n * Be able to load and install a package.\n \n * Be able to check package versions and R version.\n \n * Be able to import data from multiple formats.\n \n * Be able to inspect loaded data and select elements within the data frame.\n \n * Be able to export data.\n \n * Be able to explore data.\n\n\n\n
\n\n4. **Chapter Four - Tibbles and Dplyr**\n\n\n* Understand the importance of clean variable names.\n\n* Be able to clean column names using the janitor package.\n\n* Understand the use of the pipe operator.\n\n* Be able to sort data with dplyr’s arrange verb.\n\n* Be able to select data with dplyr’s select verb.\n\n* Be able to filter data with dplyr’s filter verb.\n\n* Be able to transform data with dplyr’s mutate verb.\n\n* Be able to join datasets together.\n\n\n\n
\n \n5. **Chapter Five - Summary Statistics and Aggregation**\n\n * Describe numeric and categorical data\n\n * Aggregate and data\n \n\n6. **Chapter Six - Case Study**\n",
- "supporting": [],
+ "engine": "knitr",
+ "markdown": "---\ntitle: \"Course Information\"\nauthor: \"Government Analysis Function and ONS Data Science Campus\"\nengine: knitr\nexecute:\n echo: true\n eval: false\n freeze: auto # re-render only when source changes\nformat:\n html: \n highlight: null\n theme: \n light: flatly\n dark: darkly\n toc: true\n toc-title: Contents\n toc-location: right\n toc-depth: 3\n number-sections: true\n link-external-newwindow: true\n embed-resources: true\n \n---\n\n\n\n{fig-alt=\"Data Science Campus and Analysis Function logos.\"}\n\n> To switch between light and dark modes, use the toggle in the top left\n\n# Introduction\n\nThis course will cover basic concepts and give you the confidence to work independently in the R programming language. No prior coding or statistical knowledge is assumed, however you should be confident using basic computer software.\n\nThe course is split into chapters; each chapter will build upon the previous one. It will emphasise the application of skills, building confidence and resilience in programming.\n\nIt is essential that you have frequent opportunities to practice what you have learnt from the course.\n\n# Course Materials\n\nThe course materials come in several formats:\n\n* HTML pages such as the one you are reading now\n\n* Data [](datasets.qmd) we will use during the course. **It's highly recommended you create a project with a 'data' folder and download all the required datasets before starting the course**\n\nYou can also navigate to the course Github Repository and clone or fork the website structure for yourself. If you are new to programming and version control, we recommend you remain on the website to gain the best experience.\n\n\n# Software Requirements\n\n* R programming language \n* R studio (recommended but not essential)\n* Web browser (Internet connection not necessary)\n*\tExcel or other spreadsheet software for viewing csv and xlsx documents\n \n\n# Packages\n\nPackages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data. The following will be used in this course:\n\n* tidyverse\n* readxl\n* janitor\n\n# Pre-Course Check-list:\n\n* Install R and RStudio on your laptop as per your department's guidance.\n\n* Check your department's guidelines for installing packages.\n\n* Save the data from the ZIP file to your hard drive in your working directory.\n\n\n# Course Overview\n\nThe course is divided into 6 chapters, over the 2 days we will cover,\n\n1. **Chapter One - Getting Started with R**\n\n * Be familiar with R Studio.\n \n * RStudio environment, layout, and customization.\n \n * Understand the Key Benefits of using R.\n \n * How to run code in R.\n \n * Know where to get help.\n \n * Discover R’s data types.\n \n * Be able to create Variables.\n\n\n \n
\n \n2. **Chapter Two - Data Structures**\n\n * Be familiar with data structures in R.\n \n * Understand how vectors operate.\n \n * Be familiar with lists.\n \n * Be familiar with data frames and tibbles.\n\n\n\n
\n \n \n3. **Chapter Three - Importing and Exporting Data**\n\n * Organise our work\n \n * Have an understanding of what packages are.\n \n * Be able to load and install a package.\n \n * Be able to check package versions and R version.\n \n * Be able to import data from multiple formats.\n \n * Be able to inspect loaded data and select elements within the data frame.\n \n * Be able to export data.\n \n * Be able to explore data.\n\n\n\n
\n\n4. **Chapter Four - Tibbles and Dplyr**\n\n\n* Understand the importance of clean variable names.\n\n* Be able to clean column names using the janitor package.\n\n* Understand the use of the pipe operator.\n\n* Be able to sort data with dplyr’s arrange verb.\n\n* Be able to select data with dplyr’s select verb.\n\n* Be able to filter data with dplyr’s filter verb.\n\n* Be able to transform data with dplyr’s mutate verb.\n\n* Be able to join datasets together.\n\n\n\n
\n \n5. **Chapter Five - Summary Statistics and Aggregation**\n\n * Describe numeric and categorical data\n\n * Aggregate and data\n \n\n6. **Chapter Six - Case Study**\n",
+ "supporting": [
+ "index_files"
+ ],
"filters": [
"rmarkdown/pagebreak.lua"
],
diff --git a/_freeze/site_libs/clipboard/clipboard.min.js b/_freeze/site_libs/clipboard/clipboard.min.js
new file mode 100644
index 0000000..1103f81
--- /dev/null
+++ b/_freeze/site_libs/clipboard/clipboard.min.js
@@ -0,0 +1,7 @@
+/*!
+ * clipboard.js v2.0.11
+ * https://clipboardjs.com/
+ *
+ * Licensed MIT © Zeno Rocha
+ */
+!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return b}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),r=n.n(e);function c(t){try{return document.execCommand(t)}catch(t){return}}var a=function(t){t=r()(t);return c("cut"),t};function o(t,e){var n,o,t=(n=t,o="rtl"===document.documentElement.getAttribute("dir"),(t=document.createElement("textarea")).style.fontSize="12pt",t.style.border="0",t.style.padding="0",t.style.margin="0",t.style.position="absolute",t.style[o?"right":"left"]="-9999px",o=window.pageYOffset||document.documentElement.scrollTop,t.style.top="".concat(o,"px"),t.setAttribute("readonly",""),t.value=n,t);return e.container.appendChild(t),e=r()(t),c("copy"),t.remove(),e}var f=function(t){var e=1
Download the bikes data (CSV, 54 KB)
-Download the imbd scores (CSV, 204 KB)
+Download the imbd scores (CSV, 204 KB)
-Download the netflix data (CSV, 3.6 MB )
+Download the netflix data (CSV, 3.6 MB )
-Download the police data (XLSX, 77 KB)
+Download the police data (XLSX, 77 KB)
-Download the revenue data (CSV, 1 KB)
+Download the revenue data (CSV, 1 KB)
-Download the titanic cleaned data (CSV, 84 KB)
+Download the titanic cleaned data (CSV, 84 KB)
-Download the titanic data (CSV, 86 KB)
\ No newline at end of file +Download the titanic data (CSV, 86 KB)
\ No newline at end of file