getting_cleaning_data

Purpose of the project

project for the coursera course "getting and cleaning data"

The purpose of this project is to demonstrate your ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis. You will be graded by your peers on a series of yes/no questions related to the project. You will be required to submit: 1) a tidy data set as described below, 2) a link to a Github repository with your script for performing the analysis, and 3) a code book that describes the variables, the data, and any transformations or work that you performed to clean up the data called CodeBook.md. You should also include a README.md in the repo with your scripts. This repo explains how all of the scripts work and how they are connected.

One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone. A full description is available at the site where the data was obtained:

http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

Here are the data for the project:

https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip

You should create one R script called run_analysis.R that does the following.

1. Merges the training and the test sets to create one data set.
2. Extracts only the measurements on the mean and standard deviation for each measurement.
3. Uses descriptive activity names to name the activities in the data set
4. Appropriately labels the data set with descriptive variable names.
5. From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.

Project content

The project contains the following items:

• run_analysis.R: The script that creates the tidy data set
• CodeBook.md: the list of the different steps taken to fetch the original data and generate the tidy data set
• README.md: this file. Explains what this project is all about and what it contains.
• dataset_and_attributes_info.md: some description of the data set and the attributes, taken from the original web site (archive.ics.uci.edu).

How to produce the tidy data set

1. Clone the project on your computer.
2. Open a R console or in RStudio.
3. Set its working directory to the root of the project.
4. execute the run_analysis.R script using source("run_analysis.R") command
5. the result data set is in the dataset_tidy variable. It is also avaiable in the dataset_tidy.txt file.