Space-Mission-Exploratory-Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Analysis for All Space Missions from 1957<a name='back-to-top'></a>\n",
    "\n",
    "\n",
    "## Background\n",
    "\n",
    "Space has always been a fascinating topic to me. In elementary school I dressed up as Sally Ride for an autobiography project and my mom even purchased me a telescope to use in our backyard. My interest in space and love for data analysis has driven me to conduct an exploratory analysis on this dataset, All Space Missions From 1957, from Kaggle [(data source)](https://www.kaggle.com/agirlcoding/all-space-missions-from-1957) using Python in Jupyter Notebook.\n",
    "\n",
    "## Analysis Questions\n",
    "                        \n",
    "The analysis intends to answer the following questions (jump to each section by clicking on the hyperlinks - only works in nbviewer):\n",
    "\n",
    "[**Company Name**](#analysis-on-comp)\n",
    "   1. [How many companies have launched space missions since 1957?](#analysis-on-comp-q1)\n",
    "   2. [Which 5 companies have launched the most space missions since 1957?](#analysis-on-comp-q2)\n",
    "   3. [For the 5 companies from the previous question, how many missions have been successful? Failed?](#analysis-on-comp-q3)\n",
    "\n",
    "[**Location**](#analysis-on-loc)\n",
    "1. [Which 5 countries have launched the most space missions since 1957?](#analysis-on-loc-q1)\n",
    "2. [From those 5 countries in Question 1, how many missions have been successful or failed?](#analysis-on-loc-q2)\n",
    "3. [For space missions launched from the USA, which state has launched the most space missions?](#analysis-on-loc-q3)\n",
    "\n",
    "[**Datum**](#analysis-on-datum)\n",
    "1. [Which 10 years had the most space missions occur?  And for the year with the most space missions, was there anything particularly special about this year?](#analysis-on-datum-q1) \n",
    "2. [Which year had the most successes? Most failures?](#analysis-on-datum-q2)\n",
    "3. [For the top 5 countries from the Analysis on Location in Q1, what is the trend of space mission from 1957 to present?](#analysis-on-datum-q3) \n",
    "4. [What month do most space missions occur?](#analysis-on-datum-q4)\n",
    "5. [What is the most \"popular\" hour to launch a space mission at?](#analysis-on-datum-q5)\n",
    "\n",
    "[**Rocket (Cost of Mission)**](#analysis-sm-cost)\n",
    "  1. [Which company has the most expensive space missions on average?](#analysis-sm-cost-q1)\n",
    "  2. [Which space mission was the most expensive of all time?](#analysis-sm-cost-q2)\n",
    "\n",
    "[**Status Rocket**](#analysis-status-rocket)\n",
    " 1. [How many countries currently have active rockets? And which countries are they?](#analysis-status-rocket-q1)\n",
    " 2. [Are there any countries that do not have any active rockets?](#analysis-status-rocket-q2)\n",
    "  \n",
    "## Initial Setup\n",
    "\n",
    "The analysis utilizes the following libraries:\n",
    "- Numpy\n",
    "- Pandas\n",
    "- Matplotlib\n",
    "- Seaborn\n",
    "- Plotly\n",
    "- Tabulate\n",
    "\n",
    "\n",
    "<p>\n",
    "<p>\n",
    "    \n",
    "[**Back to Top**](#back-to-top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Importing libraries\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import chart_studio.plotly as py\n",
    "import plotly.graph_objs as go\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "init_notebook_mode(connected=True) \n",
    "\n",
    "from tabulate import tabulate as tab"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The CSV file is read in as a dataframe called **sm** and two columns, \"Unnamed: 0\" and \"Unnamed: 0.1\" are dropped from the dataframe because they essentially count the number of rows, which is redundant with the index value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read in csv as a dataframe\n",
    "sm = pd.read_csv('Space_Corrected.csv')\n",
    "\n",
    "# dropping the unnamed columns\n",
    "sm.drop(['Unnamed: 0', 'Unnamed: 0.1'], axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preliminary Dataframe Info\n",
    "\n",
    "The table below displays each original data frame column and a short description of the data contained in each column.\n",
    "\n",
    "|Column Name   |Description   |\n",
    "|:------------------------------|:------------------------------|\n",
    "|Company Name   |Name of the company that deployed the space mission.   |\n",
    "|Location   |Where the space mission launched from.   |\n",
    "|Datum   |Date and time of launch.   |\n",
    "|Detail   |Name of the rocket from the mission.   |\n",
    "|Status Rocket   |Indicates whether the rocket is active or retired.   |\n",
    "|Rocket   |Cost of the mission in millions USD.   |\n",
    "|Status Mission   |Indicates the result of the mission: failure, partial failure, prelaunch failure, or success.   |\n",
    "\n",
    "<p>\n",
    "    \n",
    "[**Back to Top**](#back-to-top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4324 entries, 0 to 4323\n",
      "Data columns (total 7 columns):\n",
      " #   Column          Non-Null Count  Dtype \n",
      "---  ------          --------------  ----- \n",
      " 0   Company Name    4324 non-null   object\n",
      " 1   Location        4324 non-null   object\n",
      " 2   Datum           4324 non-null   object\n",
      " 3   Detail          4324 non-null   object\n",
      " 4   Status Rocket   4324 non-null   object\n",
      " 5    Rocket         964 non-null    object\n",
      " 6   Status Mission  4324 non-null   object\n",
      "dtypes: object(7)\n",
      "memory usage: 236.6+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['Company Name', 'Location', 'Datum', 'Detail', 'Status Rocket',\n",
       "       ' Rocket', 'Status Mission'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# getting general information about the data frame\n",
    "sm.info()\n",
    "sm.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[**Back to Top**](#back-to-top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis on Company Name <a name = \"analysis-on-comp\"></a>\n",
    "           \n",
    "The following analysis intends to answer these questions:\n",
    "\n",
    "   1. How many companies have launched space missions since 1957?\n",
    "   2. Which 5 companies have launched the most space missions since 1957?\n",
    "   3. For the 5 companies from the previous question, how many missions have been successful? Failed?\n",
    "    \n",
    "### 1. How many companies have launched space missions since 1957? <a name = \"analysis-on-comp-q1\"></a>\n",
    "\n",
    "56 companies have launched space missions since 1957."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "56"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm['Company Name'].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Which 5 companies have launched the most space missions since 1957? <a name = \"analysis-on-comp-q2\"></a>\n",
    "\n",
    "The table below indicates the 5 companies who have launched the most space missions since 1957, in order from highest to lowest are: RVSN USSR, Arianespace, General Dynamics, CASC, and NASA. The figure below indicates Arianespace, General Dynamics, CASC, and NASA have launched around the same number of space missions since 1957."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒══════════════════╤═════════╕\n",
      "│ Company Name     │   Count │\n",
      "╞══════════════════╪═════════╡\n",
      "│ RVSN USSR        │    1777 │\n",
      "├──────────────────┼─────────┤\n",
      "│ Arianespace      │     279 │\n",
      "├──────────────────┼─────────┤\n",
      "│ General Dynamics │     251 │\n",
      "├──────────────────┼─────────┤\n",
      "│ CASC             │     251 │\n",
      "├──────────────────┼─────────┤\n",
      "│ NASA             │     203 │\n",
      "╘══════════════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "table1 = pd.DataFrame(sm['Company Name'].value_counts().head())\n",
    "print(tab(table1, headers = ['Company Name', 'Count'], tablefmt='fancy_grid'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 700x350 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# figure size\n",
    "plt.figure(figsize=(10,5), dpi = 70)\n",
    "\n",
    "# generating plot\n",
    "sm['Company Name'].value_counts().head().plot(kind = 'bar', color = '#a7bbc7')\n",
    "\n",
    "# plot aesthetics (titles, labels, etc.)\n",
    "plt.title('Companies Who Have Launched The Most Space Missions Since 1957 (Top 5)', size = 14, pad = 15)\n",
    "\n",
    "plt.tick_params(axis = 'both', pad = 5)\n",
    "plt.xlabel('Company', labelpad = 15, size = 12)\n",
    "plt.xticks(rotation = 360)\n",
    "\n",
    "plt.ylabel('Count', labelpad = 15, size = 12)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('Figures/most-missions.jpg', dpi = 100, transparent = False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. For the 5 companies with the most launched space missions, how many of those missions have succeeded or failed? <a name = \"analysis-on-comp-q3\"></a>\n",
    "\n",
    "General conclusions from the table and figure below are:\n",
    "- RVSN USSR has the highest number of successful (1,614) and failed (121) space missions\n",
    "- NASA has the lowest number of successful space missions (186) compared to the other 4 companies.\n",
    "- Arianespace has the lowest number of failed space missions (7) compared to the other 4 companies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating a new dataframe with only the top 5 companiess\n",
    "top_5 = ['RVSN USSR', 'Arianespace', 'General Dynamics', 'CASC', 'NASA']\n",
    "top_5_filter = sm['Company Name'].isin(top_5)\n",
    "sm5 = pd.DataFrame(sm[top_5_filter])\n",
    "sm5 = pd.DataFrame(sm5[(sm5['Status Mission']=='Failure') | (sm5['Status Mission']=='Success')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "# success vs failure for top 5 companies\n",
    "table2 = sm5.groupby(['Company Name','Status Mission'])['Company Name'].count().reset_index(name='Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒══════════════════╤═══════════╤═══════════╕\n",
      "│ Status Mission   │   Failure │   Success │\n",
      "│                  │           │           │\n",
      "│ Company Name     │           │           │\n",
      "╞══════════════════╪═══════════╪═══════════╡\n",
      "│ RVSN USSR        │       121 │      1614 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ Arianespace      │         7 │       269 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ CASC             │        14 │       231 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ General Dynamics │        37 │       203 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ NASA             │        11 │       186 │\n",
      "╘══════════════════╧═══════════╧═══════════╛\n"
     ]
    }
   ],
   "source": [
    "# generating table \n",
    "## Note that there are four categories for STATUS MISSION, but only SUCCESS and FAILURE are shown in the table ##\n",
    "print(tab(table2.pivot(columns = ['Status Mission'], \n",
    "                       values = 'Count', \n",
    "                       index = 'Company Name').replace(np.nan, 0).sort_values(by = ['Success', 'Failure'], ascending = False), \n",
    "          headers =['Status Mission\\n\\nCompany Name', 'Failure', 'Success'],\n",
    "         tablefmt=\"fancy_grid\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x375 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,5), dpi = 75)\n",
    "\n",
    "sns.countplot(x = 'Company Name', data = sm5, hue = 'Status Mission', palette = 'BuPu')\n",
    "\n",
    "plt.title('Top 5 Companies by Successful and Failed Space Missions', size = 14, pad = 15)\n",
    "plt.ylabel('Count', labelpad = 15, size = 12)\n",
    "plt.xlabel('Company', labelpad = 15, size = 12)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('Figures/top-5-success-failures-company.jpg', dpi = 100, transparent = False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[**Back to Top**](#back-to-top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis on Location <a name = 'analysis-on-loc'></a>\n",
    "\n",
    "The following analysis intends to answer the following questions:\n",
    "\n",
    "1. Which 5 countries have launched the most space missions since 1957?\n",
    "2. From those 5 countries in Question 1, how many missions have been successful or failed?\n",
    "3. In respect to space missions launched from the USA, which state has launched the most space missions?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Finding unique locations\n",
    "sm['Location'].unique()\n",
    "\n",
    "## Create new column called 'Country' ##\n",
    "\n",
    "# countries - the choices list\n",
    "countries = ['USA', 'China', 'Kazakhstan', \n",
    "             'Japan', 'New Zealand', 'Israel', \n",
    "             'Russia', 'France', 'India', 'North Korea', \n",
    "             'Brazil','Australia', 'Kenya', 'Iran', \n",
    "             'Other (Sea)', 'South Korea', 'Spain']\n",
    "\n",
    "# conditions - the condition list\n",
    "conditions = [(sm['Location'].str.contains('USA')) | \n",
    "              sm['Location'].str.contains('New Mexico') | \n",
    "              sm['Location'].str.contains('LP-41, Kauai'),\n",
    "                 (sm['Location'].str.contains('China')) | \n",
    "              (sm['Location'].str.contains('Tai Rui Barge, Yellow Sea')),\n",
    "                 (sm['Location'].str.contains('Kazakhstan')),\n",
    "                 (sm['Location'].str.contains('Japan')),\n",
    "                 (sm['Location'].str.contains('New Zealand')),\n",
    "                 (sm['Location'].str.contains('Israel')),\n",
    "                 (sm['Location'].str.contains('Russia')),\n",
    "                 (sm['Location'].str.contains('France')),\n",
    "                 (sm['Location'].str.contains('India')),\n",
    "                 (sm['Location'].str.contains('North Korea')),\n",
    "                 (sm['Location'].str.contains('Brazil')),\n",
    "                 (sm['Location'].str.contains('Australia')),\n",
    "                 (sm['Location'].str.contains('Kenya')), \n",
    "              (sm['Location'].str.contains('Shahrud Missile Test Site')) |  \n",
    "              (sm['Location'].str.contains('Imam Khomeini Spaceport')),\n",
    "             (sm['Location'].str.contains('Kiritimati Launch Area')) | \n",
    "              (sm['Location'].str.contains(' Barents Sea Launch Area')),\n",
    "             (sm['Location'].str.contains('South Korea')),\n",
    "             (sm['Location'].str.contains('Stargazer, Base Aerea de'))]\n",
    "\n",
    "# generating new column using numpy select (condition list, choice list, default value for NA values)\n",
    "sm['Country'] = np.select(conditions, countries, default = 'NA')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Which 5 countries have launched the most space missions since 1957? <a name = \"analysis-on-loc-q1\"></a>\n",
    "The table and figure below indicates Russia has launched the most space missions since 1957, a total of 1,395 space missions. However, the United States has launched almost the same amount of space missions, 1,349, since 1957."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒════════════╤═════════╕\n",
      "│ Country    │   Count │\n",
      "╞════════════╪═════════╡\n",
      "│ Russia     │    1395 │\n",
      "├────────────┼─────────┤\n",
      "│ USA        │    1349 │\n",
      "├────────────┼─────────┤\n",
      "│ Kazakhstan │     701 │\n",
      "├────────────┼─────────┤\n",
      "│ France     │     303 │\n",
      "├────────────┼─────────┤\n",
      "│ China      │     269 │\n",
      "╘════════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "# which 5 countries have launched the most space missions since 1957?\n",
    "table3 = pd.DataFrame(sm.groupby('Country')['Country'].count().sort_values(ascending = False)).head()\n",
    "\n",
    "# generating table\n",
    "print(tab(table3, headers = ['Country', 'Count'], tablefmt=\"fancy_grid\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x375 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating bar plot\n",
    "plt.figure(figsize = (10, 5), dpi = 75)\n",
    "\n",
    "sm.groupby('Country')['Country'].count().sort_values(ascending = False).head().plot(kind = 'bar', color = '#a7bbc7' )\n",
    "\n",
    "plt.title('Top 5 Countries Who Have Launched the Most Space Missions Since 1957', size = 14, pad = 15)\n",
    "plt.xlabel('Country', size = 12, labelpad = 15)\n",
    "plt.xticks(rotation = 360)\n",
    "\n",
    "plt.ylabel('Count', size = 12, labelpad = 15)\n",
    "\n",
    "\n",
    "plt.savefig('Figures/country-most-missions.jpg', dpi = 100, transparent = False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating a new dataframe with just those 5 countries\n",
    "smc5 = pd.DataFrame(sm[(sm['Country'] == 'Russia') | (sm['Country'] == 'USA') |\n",
    "                       (sm['Country'] == 'Kazakhstan') | (sm['Country'] == 'France') |\n",
    "                       (sm['Country'] == 'China')])\n",
    "smc5 = pd.DataFrame(smc5[(smc5['Status Mission']=='Success') | (smc5['Status Mission']=='Failure')])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. From those 5 countries in Question 1, how many missions have been successful or failed? <a name =\"analysis-on-loc-q2\"></a>\n",
    "\n",
    "General conclusions from the table and figure below are:\n",
    "- Russia has the **highest number of successful** space missions since 1957 (1,303 successful missions).\n",
    "- China has the **lowest number of successful** space missions since 1957 (244 successful missions).\n",
    "- The United States has the **highest number of failed** space missions since 1957 (129 failed missions).\n",
    "- France has the **lowest number of failed** space missions since 1957 (13 failed missions)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒══════════════════╤═══════════╤═══════════╕\n",
      "│ Status Mission   │   Failure │   Success │\n",
      "│                  │           │           │\n",
      "│ Country          │           │           │\n",
      "╞══════════════════╪═══════════╪═══════════╡\n",
      "│ Russia           │        62 │      1303 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ USA              │       129 │      1186 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ Kazakhstan       │        72 │       608 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ France           │        13 │       285 │\n",
      "├──────────────────┼───────────┼───────────┤\n",
      "│ China            │        19 │       244 │\n",
      "╘══════════════════╧═══════════╧═══════════╛\n"
     ]
    }
   ],
   "source": [
    "# generate table\n",
    "## Note that there are four categories for STATUS MISSION, but only SUCCESS and FAILURE are shown in the table ##\n",
    "table4 = pd.DataFrame(smc5.groupby(['Country', 'Status Mission'])['Country'].count().reset_index(name = 'Count'))\n",
    "print(tab(table4.pivot(index = 'Country', \n",
    "                       columns = ['Status Mission'], \n",
    "                       values = 'Count').replace(np.nan, 0).sort_values(by = ['Success', 'Failure'], ascending = False), \n",
    "          tablefmt='fancy_grid',\n",
    "         headers = ['Status Mission\\n\\nCountry','Failure','Success']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x375 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 5), dpi = 75)\n",
    "\n",
    "sns.countplot(data = smc5, x = 'Country', hue = 'Status Mission', palette = 'BuPu' )\n",
    "\n",
    "plt.title('Top 5 Countries by Successful and Failed Space Missions', pad = 20, size = 16)\n",
    "plt.xlabel('Country', labelpad = 15,size = 14)\n",
    "plt.ylabel('Count', labelpad = 15,size = 14)\n",
    "\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('Figures/top-5-success-failures-country.jpg', dpi = 100, transparent = False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Targeting the USA, now making a new column called 'USA State'\n",
    "\n",
    "# start by creating a new dataframe just with USA\n",
    "usa_sm = pd.DataFrame(data = sm[sm['Country'] == 'USA'])\n",
    "usa_sm.reset_index(inplace = True)\n",
    "\n",
    "# find the unique States in the USA\n",
    "usa_sm['Location'].unique()\n",
    "\n",
    "# creation of new 'USA State' column\n",
    "states = ['Florida', 'Texas', 'California', 'Hawaii', 'Alaska', 'Virginia', 'New Mexico', 'Marshall Islands']\n",
    "\n",
    "state_cond = [(usa_sm['Location'].str.contains('Florida')),\n",
    "              (usa_sm['Location'].str.contains('Texas')),\n",
    "              (usa_sm['Location'].str.contains('California')),\n",
    "              (usa_sm['Location'].str.contains('LP-41, Kauai')),\n",
    "              (usa_sm['Location'].str.contains('Alaska')),\n",
    "              (usa_sm['Location'].str.contains('Virginia')),\n",
    "             (usa_sm['Location'].str.contains('Vertical Launch Area')),\n",
    "             (usa_sm['Location'].str.contains('Ronald Reagan Ballistic'))]\n",
    "\n",
    "usa_sm['USA State'] = np.select(state_cond, states, default = 'NA')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. For the space missions launched from the USA, which state has launched the most space missions? <a name =\"analysis-on-loc-q3\"></a>\n",
    "\n",
    "The table and figure below indidcates the state of Florida has launched the most space missions since 1957, a total of 834 space missions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒════════════╤═════════╕\n",
      "│ State      │   Count │\n",
      "╞════════════╪═════════╡\n",
      "│ Florida    │     834 │\n",
      "├────────────┼─────────┤\n",
      "│ California │     454 │\n",
      "├────────────┼─────────┤\n",
      "│ Virginia   │      31 │\n",
      "├────────────┼─────────┤\n",
      "│ Texas      │      13 │\n",
      "├────────────┼─────────┤\n",
      "│ New Mexico │       4 │\n",
      "├────────────┼─────────┤\n",
      "│ Alaska     │       3 │\n",
      "├────────────┼─────────┤\n",
      "│ Hawaii     │       1 │\n",
      "╘════════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "table5 = pd.DataFrame(usa_sm[usa_sm['USA State'] != 'Marshall Islands'].groupby('USA State')['USA State'].count().sort_values(ascending = False))\n",
    "print(tab(table5, tablefmt=\"fancy_grid\", headers = ['State', 'Count']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "# generate map plot\n",
    "data = dict(type = 'choropleth',\n",
    "            locations = ['AK', 'CA', 'FL', 'HI', 'NM', 'TX', 'VA'],\n",
    "            locationmode = 'USA-states',\n",
    "            colorscale= 'PuBu',\n",
    "            text= ['Alaska', 'California', 'Florida', 'Hawaii', 'New Mexico', 'Texas', 'Virginia'],\n",
    "            z = (usa_sm[usa_sm['USA State'] != 'Marshall Islands'].groupby('USA State')['USA State'].count()),\n",
    "            colorbar = {'title':'Count'})\n",
    "\n",
    "layout = dict(geo = {'scope':'usa'})\n",
    "\n",
    "choromap = go.Figure(data = [data],layout = layout)\n",
    "\n",
    "# add title to plot\n",
    "choromap.update_layout(title_text = \"Space Mission Launches in the United States\")\n",
    "\n",
    "# export image\n",
    "choromap.write_image('Figures/usa-space-launches-new.jpg', width = 700, height = 450, scale = 2)\n",
    "\n",
    "# show image, although this will not be displayed in the notebook since it's HTML, so I used markdown to embed the image file\n",
    "#iplot(choromap, show_link = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src = \"https://raw.githubusercontent.com/julietwomack/SpaceMissions/main/Figures/usa-space-launches-new.jpg\" width = \"80%\" style = \"border: 1.5px solid black\"></img>\n",
    "<p>\n",
    "<p>\n",
    "    \n",
    "[**Back to Top**](#back-to-top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis on Datum <a name =\"analysis-on-datum\"></a>\n",
    "\n",
    "The analysis intends to answer the following questions:\n",
    "1. Which 10 years had the most space missions cccur?\n",
    "    - For the year with the most space missions, was there anything particularly special about this year?\n",
    "2. Which year had the most successes? Most failures?\n",
    "3. For the top 5 countries from the Analysis on Location in Q1, what is the trend of space mission from 1957 to present? \n",
    "4. What month do most space missions occur?\n",
    "5. What is the most \"popular\" hour to launch a space mission at?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "# converting \"datum\" column to datetime\n",
    "sm['Datum'] = pd.to_datetime(sm['Datum'])\n",
    "\n",
    "# creating new columns from Datum\n",
    "sm['Hour'] = sm['Datum'].apply(lambda t: t.hour)\n",
    "sm['Month'] = sm['Datum'].apply(lambda t: t.month)\n",
    "sm['Year'] = sm['Datum'].apply(lambda t: t.year)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Which 10 years had the most space missions occur? <a name =\"analysis-on-datum-q1\"></a>\n",
    "\n",
    "The table and figure below indicates 1971 had the most space missions occur, 119. In modern-day, 2018 had 117 space missions. Overall, the 1970's appears to be a \"popular\" decade for space exploration with 1971, 1973, 1975, 1976, and 1977 all being within the Top 10.\n",
    "\n",
    "#### For the year with the most space missions, was there anything particularly special about this year?\n",
    "\n",
    "In 1971 three astronauts part of the [Soyuz 11 mission](https://en.wikipedia.org/wiki/Soyuz_11) were killed in space while reentering Earth's atmosphere. Those three men were the only *known* human deaths to occur in space ([Wikipedia](https://en.wikipedia.org/wiki/1971_in_spaceflight))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒════════╤═════════╕\n",
      "│   Year │   Count │\n",
      "╞════════╪═════════╡\n",
      "│   1971 │     119 │\n",
      "├────────┼─────────┤\n",
      "│   2018 │     117 │\n",
      "├────────┼─────────┤\n",
      "│   1977 │     114 │\n",
      "├────────┼─────────┤\n",
      "│   1975 │     113 │\n",
      "├────────┼─────────┤\n",
      "│   1976 │     113 │\n",
      "├────────┼─────────┤\n",
      "│   2019 │     109 │\n",
      "├────────┼─────────┤\n",
      "│   1970 │     107 │\n",
      "├────────┼─────────┤\n",
      "│   1967 │     106 │\n",
      "├────────┼─────────┤\n",
      "│   1973 │     103 │\n",
      "├────────┼─────────┤\n",
      "│   1968 │     103 │\n",
      "╘════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "# what year had the most space missions - top 10?\n",
    "\n",
    "# creating a new dataframe with the counts and outputting the table\n",
    "table6 = pd.DataFrame(sm.groupby('Year')['Year'].count().sort_values(ascending = False).head(10))\n",
    "print(tab(table6, tablefmt=\"fancy_grid\", headers = ['Year', 'Count']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
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XXuV9zCVJkjQJSdZV1V7TzWuhx3w2BwMXV9VPgbsCt1TVrQBVdQtwW5I7T7KCkiRJ0rZq+ps/kzwMeANwwEDxcBd/ZtnGkcCRU9OrV68eWf0kSZKkUWm2xzzJ/YH/Azy7qi7vi38E7JzkDv0ydwJ2qKobZ9pOVR1XVXtNPVatmvOoF0mSJGnRNNljnmQt8CngxVX1tanyqqoknwIOAd4DHAp8crHrd8oZ5y72U/6aZz9u70lXQZIkSSM08WCe5HjgycCKJBvpAvntgHsAx3bXfgLw9Kq6EngVcHKSVwLXAs9Z9EpLkiRJIzbxYF5VR8ww60UzLL8BePT4aiRJkiQtvmbHmEuSJEnLicFckiRJasDEh7JoaWvhQljwYlhJkrT02WMuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAu7JII9TCXWq8Q40kSUuTPeaSJElSAwzmkiRJUgMcyiJpLFoY1gPtDO1poT1aaQtJ0vTsMZckSZIaYDCXJEmSGmAwlyRJkhpgMJckSZIaYDCXJEmSGmAwlyRJkhpgMJckSZIaYDCXJEmSGuAXDEmSFlULX7YEfuGSpPbYYy5JkiQ1wGAuSZIkNcBgLkmSJDXAMeaSJE2QY+4lTbHHXJIkSWqAwVySJElqgENZJElSExzWo+XOHnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQHelUWSJKlB3qVms+XSFvaYS5IkSQ0wmEuSJEkNMJhLkiRJDZh4ME/y9iQbk2waKj8myfoklyU5aKB8tyRf6cu/lGTN4tdakiRJGq2JB3Pgo8DDBwuSHADsDTwQ2B94W5Jd+tlvBj5UVffv133jItZVkiRJGouJB/OqOruqfjBUfCBwYlVtqqqrgbOBA5IE+GPgg/1yHwCeuni1lSRJksZj4sF8BmuBDQPTV/VldwVuqapbAarqFuC2JHeeaUNJjkxyydTjhhtuGGe9JUmSpAVpNZgD1MDvmaF8eN6vb6TquKraa+qxatWqkVVQkiRJGpVWg/kGYPeB6bXARuBHwM5J7gCQ5E7ADlV14+JXUZIkSRqdVoP5acChSVb0d13ZFzi9qgr4FHBIv9yhwCcnVEdJkiRpZFZOugJJjgeeDKxIshH4VFUdkeTxwKV0Q1deXlU39au8Cjg5ySuBa4HnTKLekiRJ0ihNPJhX1REzlB8FHDVN+Qbg0eOulyRJkrSYWh3KIkmSJC0rBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQEGc0mSJKkBBnNJkiSpAQZzSZIkqQFNB/MkT0xyfv84J8meffkxSdYnuSzJQZOupyRJkrStVk66ArN4N/CEqlqX5HDg9UneA+wNPBC4J3Buks9V1U2TrKgkSZK0LZruMQcK2LX//c7ANcCBwIlVtamqrgbOBg6YUP0kSZKkkWi9x/wQ4FNJfg7cAuwDfAD42MAyVwFrJ1A3SZIkaWSaDeZJVgCvBvavqguTPB/4IF0veg0uOst2jgSOnJpevXr1GGorSZIkbZuWh7I8FNi1qi7spz8MPAbYAOw+sNxaYONMG6mq46pqr6nHqlWrxlVfSZIkacFaDuZXAw9Icu9++onAOuA04NAkK5KsAfYFTp9QHSVJkqSRaHYoS1Vdk+SVwOlJNgE3Ay+oqm8neTxwKd2Qlpd7RxZJkiQtdc0Gc4Cqej/w/mnKjwKOWvwaSZIkSePR8lAWSZIkadkwmEuSJEkNMJhLkiRJDTCYS5IkSQ0wmEuSJEkNMJhLkiRJDTCYS5IkSQ0wmEuSJEkNMJhLkiRJDTCYS5IkSQ0wmEuSJEkNMJhLkiRJDTCYS5IkSQ0wmEuSJEkNMJhLkiRJDTCYS5IkSQ0wmEuSJEkNMJhLkiRJDZhzME/yqRnKPzm66kiSJEnL03x6zB89Q/m+o6iIJEmStJytnG2BJC/rf91h4Pcp/wW4duS1kiRJkpaZWYM58Iz+5w4DvwP8CvgBcNiI6yRJkiQtO7MG86raHyDJP1TVK8ZfJUmSJGn5mUuPOQBToTzJKmCXoXlXjbhekiRJ0rIy52Ce5A+BDwC7AxmYVcCKEddLkiRJWlbmc1eW44H3ArsBqwYedxlDvSRJkqRlZc495sC9gaOrqsZVGUmSJGm5mk+P+aeAPxxXRSRJkqTlbD495jcBn+y/AXSLe5dX1V+NtFaSJEnSMjOfYL4DcFr/+6ox1EWSJElatuZzu8Q/H2dFJEmSpOVsPrdL3H2med7HXJIkSdo28xnKciXdPcun7mE+eHcW72MuSZIkbYP5BPPhceVrgNcA/zq66kiSJEnL03zGmN84VHRjksOBbwInjbRWkiRJ0jIzn/uYT2cn4O6jqIgkSZK0nM3n4s+3DhXdCXgC8PFRVkiSJElajubTY75q6PH/gNcDLxpDvQBIsnOSDya5LMl3khzRlx+TZH1fftC4nl+SJElaLK3fx/ytwEVV9bwkAe6e5ABgb+CBwD2Bc5N8rqpumkD9JEmSpJGYz11ZSPL7wKHAWmAj8IGq+rdxVCzJLsBTgN0BqqqA65IcCJxYVZuAq5OcDRwAfGwc9ZAkSZIWw5yHsiR5NnA63X3Mv9IXfzbJc8ZRMeA3gR8A70jyzSSfSLIH3UnBhoHlrurLppXkyCSXTD1uuOGGMVVXkiRJWrj59Jj/LfDkqvryVEGSk4B3AR8ZdcWAHYDfBf6mql6c5IXACcDP2PLLjTLNuv+pqo4Djpua3muvvWori0uSJEkTMZ+LP+8NfHWo7By6Lxoahw3Aj6vqM/30ycDD+vLdB5abGlYjSZIkLVnzCeYXA0cMlb0IuGR01dmsqn4AXJTkEX3R4/s6nAYcmmRFkjXAvnRDbCRJkqQlaz5DWf4C+EySI4ErgT2AewBPGnmtNnsJ8L4kOwE/AV5YVeuSPB64lG5Iy8u9I4skSZKWulmDeZKVwL2q6rwk9wOeTDd85CTgbOD746pcVV0C/P405UcBR43reSVJkqTFNpce878E9gSeX1U30o31BiDJe4F1wFvGUz1JkiRpeZjLGPODgTfNMO8Y4JDRVUeSJElanuYSzO9TVZdNN6Mv3326eZIkSZLmbk53ZUlyl/mUS5IkSZqfuQTzc4HnzjDvOcDXRlcdSZIkaXmay8WfRwOfTrIzcApwNd2XDT0beBXjvV2iJEmStCzMGsyr6uwkBwP/BLxhYNaVwMFVdc6Y6iZJkiQtG3P6gqGq+lfgX5P8FnB34IczXRAqSZIkaf7m882fVNXlwOVjqoskSZK0bM3priySJEmSxstgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1YEkE8yTvTLJpYPqYJOuTXJbkoEnWTZIkSRqFlZOuwGySPBrYaWD6AGBv4IHAPYFzk3yuqm6aUBUlSZKkbdZ0j3mSHYE3Aa8YKD4QOLGqNlXV1cDZwAGTqJ8kSZI0Kk0Hc+A1wPuq6vqBsrXAhoHpq/qyaSU5MsklU48bbrhhTFWVJEmSFq7ZYJ7kIcDvAe+fZnYNLrq17VTVcVW119Rj1apVo6ymJEmSNBLNBnNgH2Av4LtJrgRW9D83ALsPLLcW2LjotZMkSZJGqNlgXlX/u6rWVNUeVbUH8Mv+52nAoUlWJFkD7AucPsGqSpIkSdus+buyDKuqzyd5PHAp3ZCWl3tHFkmSJC11SyaYV9XKgd+PAo6aYHUkSZKkkWp2KIskSZK0nBjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGNBvMk+yW5Mwk65JclOQNA/OOSbI+yWVJDppkPSVJkqRRWDnpCmzFJuCvq+q8JLcHPp/kqcCtwN7AA4F7Aucm+VxV3TTBukqSJEnbpNke86q6pqrO63+/DbgAuA9wIHBiVW2qqquBs4EDJldTSZIkads1G8wHJbkr8HTgDGAtsGFg9lV9mSRJkrRktTyUBYAkOwKnAm+tqnVJAGpwkVnWPxI4cmp69erV46imJEmStE2a7jFPsgI4CTivqt7WF28Adh9YbC2wcaZtVNVxVbXX1GPVqlXjq7AkSZK0QE0Hc+DdwE+BowbKTgMOTbIiyRpgX+D0SVROkiRJGpVmh7Ik2Qd4PnAR8K1+CMsJVfXPSR4PXEo3pOXl3pFFkiRJS12zwbyqvsoM48er6ii27EWXJEmSlrTWh7JIkiRJy4LBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJaoDBXJIkSWqAwVySJElqgMFckiRJasCSDeZJ9k9ySZL1SU5IsnLSdZIkSZIWakkG8yQrgPcBz6yq+wE7A4dMtlaSJEnSwi3JYA48EthYVRf30+8DDpxgfSRJkqRtkqqadB3mLclBwDOq6rn99J7AyVX10GmWPRI4cqDovsB3F6WiM1sF3DDhOrTE9tjMttiS7bEl22Mz22JLtsdmtsWWbI/NWmmLtVW163QzlvK47MEzisy4UNVxwHHjr87cJbmkqvaadD1aYXtsZltsyfbYku2xmW2xJdtjM9tiS7bHZkuhLZbqUJYNwO4D02uBjROqiyRJkrTNlmowPw+4d5Kps57nA6dNsD6SJEnSNlmSwbyqfgm8CDg1yXrgZ8CHJlureWlqaE0DbI/NbIst2R5bsj02sy22ZHtsZltsyfbYrPm2WJIXf0qSJEnbmyXZYy5JkiRtbwzmkiRJUgMM5pIkSVIDDOaSJElSAwzmI5Dk7Uk2Jtk0ULZrklOSXNg/nj4w79NJzu8f65PcMDDvY0mu7+82s+Qk2S3JmUnWJbkoyRsG5h3T7+9l/be3TpW/oF/+V0n2Hdre8/rtfDvJ55OsXsz92VajOjaSPGKg/PwkP07ytgns0jYZ8d9KDbXJbyzu3mybEbfF6iSfTPKd/vGURd6dbTaG947XJbk4ySVJXreY+zIKIz4+nt233X8kOXqRd2Wbzbct+vl/k+TS/hg4oS/zfXTL/ys7Jfl6///1oiTHJ1lSXzw5qmOjL28jb1SVj218APsC9wQ2DZS9GXhL//tvABcCu0yz7t8C7x6Y/iPgocD6Se/XAtviXsAj+t9vD3wJeCpwAPBlum+bvTfdl0Tt0i/3EOC3gLOAfQe2dQfgx8Dd+umjgWMnvY+TOjaG5l0O/MGk92+S7TG4jaX4GHFbnA48q/99JXDXSe/fAtpjlO8dTwLOAXYEVtB9z8V+k97HSRwf/XIb+vZd2bfL/pPev3G2BXAw8HHg9v306hm2u6zfR+k6Z3fufw9wKnDopPdvEscGDeUNe8xHoKrOrqofDBU/GPhsP/8nwDrgidOs/lwG7sFeVV8AbphmuSWhqq6pqvP6328DLgDuAxwInFhVm6rqauBsun+4VNUFVXX5NJubOj53ShJgV+Cace/DKI3y2JiSZG+6W52eM9rajt842mOpGlVbJHkgcPeq+pd+vU1V9aNx1XtcRvze8WDgi1X1i+q+9+IM4FmLsR+jMsK/lSfStcU1VbUJ+ABdmy4ZC2iLlwH/qz+OqKprh7fp+yhU1a+q6ua+fAfgjmOp8BiN8NhoJm8YzMfnG8Czktwuyb3pzup2G1wgySPpztLOnkD9xi7JXYGn0/1TXEvXazPlqr5sRlX1M+AIun/QVwMPYwl8OcAcbOuxcQjw4bHXcvEstD1ul+Tfk3wjyV8tXnXHaiFt8QDguv6j228l+XD/t7dkbet7B107PinJnZPcAXgaQ+24RC3k+FhI+y0FW2uLB9C9/l9P8tUkfzTN+r6Pbi4/D7gOuBk4aXGqO1bzPjZayhsG8/F5E7AJ+CbwLrqPZTcNLfNnwEnVf26yPUmyI93HYm+tqnV98eB+Zg7b2BV4MfCgqloDfB5466jrOgELPjaS7EDX87c9/UNZaHvsXlWPpBu28Kwkf7oYlR2zhbTFDsB+wJuq6qHAlcCxi1LbMRjFe0f/yeMHgS/SDfO5gF9vx6VooX8r82q/JWJrbbES+I2qehTwEuCkJLtMrej76Jb/V6rqEcBq4BfAM8df1bGb97HRUt5YUoP8l5L+7OslU9NJPgFcOjC9EvhTun+o25UkK+jOus+rqqkLazYAuw8sthb42iybOgC4tqo29tMn0Y0NW9K28dh4It31B0vy4uDpLLQ9po6LqrouyYeBvYGPLkadx2WBbXEVcHFVnd9Pn9w/lpwRvndQVf8I/GO/3b9kOwjmCzw+NtCNxZ+yFtjIEjdLW2yg7/mtqguSbAD+C3B+P9/30V9f/9YkJwEvBT4y3tqO1wKPjfvRSN6wx3xM+o9Qd+x/3xe4L90Z2JQDgKuq6tLp1l/i3g38FDhqoOw04NAkK5Ksofto6fRZtvM94Pf6M1no3kwvGXVlF9s2HhuHsB2Ns4aFtUeSVf0QBZLcke4iwQsWr9bjscBj4zzg9knu008/Hrh4Meo7BiN57+g/wr57//sa4HDg+PFUefEs8Pj4LPCYdHfuWQk8j65Nl7RZ2uJU+usQkuxGN4zhyoHVfR/tlrtn+rtZ9SfFzwAuWrRKj8kCj4128sYoryRdrg+6N/yNdB8XbuynH0V3xfc6ujsGPGBonZOBl02zrU/RXXCwqd/W3056/+bZFvv07XAhXe/E+VP7CRwDrO/b5ZkD6xzW7+sv6Ma5XTAw79V9G36b7g9r90nv4wSPjV2BG1mCd9wYdXsAv98fY9+mC6FvBG436f2b4LHxaOBbfXt8BrjXpPdvAe0xsvcOuuE9F/ePC4CnTHr/Jnx8PLtf7z+AN05638bdFsAudCcfF/XH0dMG5vk+urns4X37XNC31XuAnSa9fxM8NprIG+krI0mSJGmCHMoiSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSZIkNcBgLkmSJDXAYC5JkiQ1wGAuSctUkg8k+cRQ2T2SXJ/k6ROqliQtW6mqSddBkjQBSe4MXAj8j6r6UF/2MeDmqjp0RM+xsqo2jWJbkrS9s8dckpapqroReD7wj0nWJDkYeBTwsiTvSHJVkuuSfLAP8QAk+XCS7yf5aZJvJNl/YN5hSc5P8rok1wIfXfQdk6QlymAuSctYVZ0BnAJ8CPhnuqD+HuAuwEOA+wI7AO8YWO1MYE/grv26pybZZWD+g4FNwO7AIWPeBUnabjiURZKWuSQ7AeuA04FXA9cCd6+qH/fzfwu4GLhjVf1ymvVvAJ5SVV9Nchjwln79Xy3SLkjSdmHlpCsgSZqsqrolyRXARcAedJ+mXpFkcLFfAauTXAP8HfAs4J59+a7A3QaWvdpQLknzZzCXJA3aQBe211TVz4ZnJvkz4GDgCcDlVVV9j/lgijeUS9ICOMZckvSfqupa4OPAO5LcDSDJ6iTP6BfZFbgN+CFw+ySv6cskSdvIYC5JGnYY8BPg35P8FPgK8PB+3gfoxpt/D7gC+DldL7skaRt58ackSZLUAHvMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBhjMJUmSpAYYzCVJkqQGGMwlSZKkBvx/TCGsrxZEz4UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 750x375 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generating the plot\n",
    "\n",
    "plt.figure(figsize = (10, 5), dpi = 75)\n",
    "\n",
    "sm.groupby('Year')['Year'].count().sort_values(ascending = False).head(10).plot(kind = 'bar', color = '#a7bbc7')\n",
    "\n",
    "plt.xticks(rotation = 360)\n",
    "plt.tick_params(axis = 'both', pad = 5)\n",
    "plt.xlabel('Year', size = 12, labelpad = 10)\n",
    "plt.ylabel('Count', size = 12, labelpad = 10)\n",
    "\n",
    "plt.title('Top 10 Years With The Most Space Missions', size = 14, pad = 15)\n",
    "plt.tight_layout()\n",
    "plt.savefig('Figures/top-10-years.jpg', dpi = 150, transparent = False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Which year had the most successes? Most failures? <a name =\"analysis-on-datum-q2\"></a>\n",
    "\n",
    "The first table below indicates 2018 had the highest number of successful space missions, 113. The second table below indicates 1956 and 1960 had the highest number of failed space missions, 20 for each year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 701,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒═══════════════════════════╤═════════╕\n",
      "│   Status Mission: Success │         │\n",
      "│                           │         │\n",
      "│                      Year │   Count │\n",
      "╞═══════════════════════════╪═════════╡\n",
      "│                      2018 │     113 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1977 │     110 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1976 │     108 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1975 │     107 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1971 │     105 │\n",
      "╘═══════════════════════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "# which year (since 1957) had the most successes? Failures?\n",
    "\n",
    "# getting counts for successes\n",
    "table7 = pd.DataFrame(sm.loc[(sm['Status Mission']=='Success')].groupby(['Year', \n",
    "                                                   'Status Mission'])['Year'].count().sort_values(ascending = False).head(5).reset_index(name = 'Count'))\n",
    "\n",
    "# generating table\n",
    "print(tab(table7.pivot(index = 'Year', \n",
    "                       columns = 'Status Mission', \n",
    "                       values = 'Count').sort_values(by = 'Success', ascending = False), \n",
    "          tablefmt=\"fancy_grid\",headers = ['Status Mission: Success\\n\\nYear', '\\n\\nCount']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 702,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒═══════════════════════════╤═════════╕\n",
      "│   Status Mission: Failure │         │\n",
      "│                           │         │\n",
      "│                      Year │   Count │\n",
      "╞═══════════════════════════╪═════════╡\n",
      "│                      1958 │      20 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1960 │      20 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1961 │      17 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1969 │      17 │\n",
      "├───────────────────────────┼─────────┤\n",
      "│                      1962 │      15 │\n",
      "╘═══════════════════════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "# getting counts for failures\n",
    "table8 = pd.DataFrame(sm.loc[(sm['Status Mission']=='Failure')].groupby(['Year', \n",
    "                                                   'Status Mission'])['Year'].count().sort_values(ascending = False).head(5).reset_index(name = 'Count'))\n",
    "\n",
    "print(tab(table8.pivot(index = 'Year',\n",
    "                      columns = 'Status Mission',\n",
    "                      values = 'Count').sort_values(by = 'Failure', ascending = False), tablefmt='fancy_grid',\n",
    "         headers = ['Status Mission: Failure\\n\\nYear', '\\n\\nCount']))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. For the top 5 countries from the [Analysis on Location, Q1](#analysis-on-loc-q1), what is the trend for the number of space missions from 1957 to present? <a name =\"analysis-on-datum-q3\"></a>\n",
    "\n",
    "    \n",
    "General conclusions from the figure below are:\n",
    "    \n",
    "- Overall, Russia and the USA appear to be the \"big players\" in space exploration prior to 1990.\n",
    "- Russia consistently launches the most space missions in the 1970's.\n",
    "- The USA consistently launches the most space missions overtime.\n",
    "- China rises as a contendor against the USA prior to 2020 in regard to number of space missions.\n",
    "- Between the 1990's and 2000, Russia, Kazakhstan, and France launched around the same number of space missions per year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create data frame for each top 5 country\n",
    "USA = pd.DataFrame(sm.loc[sm['Country'] == 'USA'].groupby('Year').count()['Country'].reset_index(name = 'Count'))\n",
    "RU = pd.DataFrame(sm.loc[sm['Country'] == 'Russia'].groupby('Year').count()['Country'].reset_index(name = 'Count'))\n",
    "KZ = pd.DataFrame(sm.loc[sm['Country'] == 'Kazakhstan'].groupby('Year').count()['Country'].reset_index(name = 'Count'))\n",
    "FR = pd.DataFrame(sm.loc[sm['Country'] == 'France'].groupby('Year').count()['Country'].reset_index(name = 'Count'))\n",
    "CN = pd.DataFrame(sm.loc[sm['Country'] == 'China'].groupby('Year').count()['Country'].reset_index(name = 'Count'))\n",
    "\n",
    "# generate the figure (line graph)\n",
    "plt.figure(figsize = (15, 7), dpi = 100)\n",
    "\n",
    "plt.plot(USA['Year'], USA['Count'], label = 'USA')\n",
    "plt.plot(RU['Year'], RU['Count'], label = 'Russia')\n",
    "plt.plot(KZ['Year'], KZ['Count'], label = 'Kazakhstan')\n",
    "plt.plot(FR['Year'], FR['Count'], label = 'France')\n",
    "plt.plot(CN['Year'], CN['Count'], label = 'China')\n",
    "\n",
    "plt.title('Number of Space Missions per Year for the Top 5 Countries', size = 20, pad = 20)\n",
    "\n",
    "plt.tick_params(axis = 'both', pad = 5)\n",
    "plt.xlabel('Year', size = 16, labelpad = 20)\n",
    "plt.xticks(size = 14)\n",
    "\n",
    "plt.ylabel('Number of Space Missions Since 1957', size = 16, labelpad = 20)\n",
    "plt.yticks(size = 14)\n",
    "\n",
    "plt.legend(bbox_to_anchor =(1,1), prop = {'size': 15})\n",
    "plt.savefig('Figures/count-by-country-year.jpg', dpi = 150, transparent = False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. What month do most space missions occur? <a name =\"analysis-on-datum-q4\"></a>\n",
    "\n",
    "The table and figure below indicates most space missions occur in December with 450 being launched in December since 1957. June has the second highest number of space missions launched with 402 space missions launched during this month since 1957. Overall, there does not appear to be a seasonal pattern/trend for when space missions are launched."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 704,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating a dictionary for month and mapping it onto the month column\n",
    "dmonth = {1: 'Jan', 2: 'Feb', 3: 'Mar', 4: 'Apr', 5: 'May', 6: 'Jun', 7:'Jul',\n",
    "         8:'Aug', 9:'Sep', 10:'Oct',11:'Nov', 12:'Dec'}\n",
    "\n",
    "sm ['Month'] = sm['Month'].map(dmonth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 705,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒═════════╤════════╕\n",
      "│ Month   │   Year │\n",
      "╞═════════╪════════╡\n",
      "│ Dec     │    450 │\n",
      "├─────────┼────────┤\n",
      "│ Jun     │    402 │\n",
      "├─────────┼────────┤\n",
      "│ Apr     │    383 │\n",
      "├─────────┼────────┤\n",
      "│ Oct     │    381 │\n",
      "├─────────┼────────┤\n",
      "│ Aug     │    373 │\n",
      "├─────────┼────────┤\n",
      "│ Sep     │    365 │\n",
      "├─────────┼────────┤\n",
      "│ Mar     │    353 │\n",
      "├─────────┼────────┤\n",
      "│ Jul     │    351 │\n",
      "├─────────┼────────┤\n",
      "│ Nov     │    336 │\n",
      "├─────────┼────────┤\n",
      "│ Feb     │    336 │\n",
      "├─────────┼────────┤\n",
      "│ May     │    326 │\n",
      "├─────────┼────────┤\n",
      "│ Jan     │    268 │\n",
      "╘═════════╧════════╛\n"
     ]
    }
   ],
   "source": [
    "table9 = pd.DataFrame(sm.groupby('Month')['Month'].count().sort_values(ascending = False))\n",
    "print(tab(table9, headers = ['Month', 'Year'], tablefmt='fancy_grid'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 706,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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19tN0rdo7JHl+P/vQBdRjHfN4T8z3uZuvxXoOACZO6AZY3lqS+6QbSfziqvpRVX2zqs5MN2jRa9Kd53pQa+0TM2zjNemu3/zTqvqfJD9Nsn+6QYae0wfg7sG6SwEd3N89rKp+XFUn9us8Pt21tdetZNcC98R0LVwPSPL9qjqjqk6sqouTnJJu0LFRr07XzXWnJMdW1U/7fTslXdfrb6a7hvhM3eYn4S5J3p5uILSz+/r+b7qW2HslOT3J20bK753u0meXV9VpVfU/VXVBusHUNkny/1prP8oG9M/RM9P1DnhJ//hTz+U/pnsuX9BfS31wrbUj070eLkk3yvb3q+rcfv++m+TSdN3Q75HkKyPrtXSDgp2f5CFJzq2qk6rqrHQtqbdMd37xe8ce7+dZ26r+3qo6v39dXpBuYLv1trjPY//+L13IvGWSH1bVCVV1XFUdMcdNvTfduf8/qKpvV9X3k3wtyXZJPp2ZL+eXrB1QbdMs7Nrci2K+z90CHm+xngOAiRO6AZa3d6e7Rvdb0o2AvUmSXdNdRuvHST6Y5Pdba3+7nm0ckeRR6c67vke6bq1fTvLQ1tp0X2Bfni7YfT9dS9tdkhyTLtzMeE5pa+3cdK3n+6dr7b1DunNaL03XXfY1Y+VvaK09M10r7ZH97N9Ocvt054S+K92X+8U4P3Sx/EuSA5J8NV0r/a7pAtS3krwwyf1ba5eNlN833Q8mZ6U7HvdJcnWSTyR5cGvttbN94Nbap9Id38PTtfrumu4Hl08k2bO19q/z3625a619Jt31j6cuX7d5X6c7pXvtvCPJrq21F4+t94N0z/NBSc5N1019+3TH9JlJ9p2h9ff/pWv1/V66c7vvlOQ/050T/+NF38EuYB6arofBbukGjpvtmAVTLk43OOEH0/US2SndD1OvSDdQ4S/Xs+6n+/WTRW7lnq/5PncLsBjPAcDE1eJ+NgKwXFTVOekC806ttXMmWxtgLvqu8xem+2Hl9gu9VBgAk6OlGwBg+Xl6uvOnPylwA6xsQjcAwDLSXwHg5f3d9Z33DcAKIHQDACwDVfXKqvpakh+mu4b20a214yZbKwAWSugGAFge7pFkz3SXY/v3dAOJAbDCGUgNAAAABqKlGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAPZdNIVWA2qqpLcIckVk64LAAAAS2brJBe01tpMBYTuxXGHJOdPuhIAAAAsuTsm+clMC4XuxXFFkpx33nnZZpttJl0XAAAABnb55ZfnTne6U7KBHs9C9yLaZptthG4AAABuYiA1AAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwkE0nXQHWdcQxJ0y6CuvYZ689Jl0FAACAFUdLNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIGsqtBdVftXVauqg0fmVVUdUFUXVNU1VXVcVe0ytt4WVfXOqrq4qq6qqk9V1R2XfAcAAABYVVZN6K6q3ZM8J8mpY4tenuRlSV6QZPckFyb5YlVtPVLm4CR/nGSfJHsmuWWSz1TVJgNXGwAAgFVs00lXYDFU1S2THJ7kL5L83cj8SvKSJG9orX28n7dvkouSPC3Je6tq2yTPTvLM1toxfZlnJDkvyV5Jjlq6PWGujjjmhElXYR377LXHpKsAAAAsE6ulpfufk3x2KjSP2CnJDkmOnprRWluT5CtJHtjP2i3JZmNlLkhy+kiZm+m7o28zNSXZerpyAAAAbNxWfEt3Ve2TLjjfb5rFO/S3F43NvyjJXUbKXNda+/k0ZXbI9PZP8rq51xYAAICNyYpu6a6qOyV5R5Knt9auXU/RNr7qNPPW2fx6yhyYZNuRyaBrAAAArGNFh+50LdzbJzmpqm6oqhuSPDjJi/q/p1q4x1ustx9ZdmGSzatqu/WUuZnW2prW2uVTU5IrFmFfAAAAWGVWeuj+UpJ7J9l1ZDox3aBquyb5UbpQ/YipFapq83TB/Bv9rJOSXD9W5vZJ7jVSBgAAAOZsRZ/T3Vq7It2AZzepqquSXNJaO72/f3CSV1XVWUnOSvKqJFcn+XC/jcuq6v1J3lpVlyS5NMlBSU5LMj4wGwAAAMzaig7ds/TmJFsmeXeS7ZJ8M8kj+8A+5aVJbkjy0b7sl5Ls11q7cYnrCgAAwCqy6kJ3a+0hY/dbkgP6aaZ1rk3ywn4CAACARbHSz+kGAACAZUvoBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGMiqu2QYML0jjjlh0lVYxz577THpKgAAwKCEboARy/HHicQPFAAAK5Xu5QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgLhkGwLy4vBoAwIZp6QYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0csBYGDLcaR3o7wDwNLQ0g0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGMimk64AAMCUI445YdJVWMc+e+0x6SoAsIJp6QYAAICBaOkGAFiB9AoAWBm0dAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABjIppOuAAAADOWIY06YdBWmtc9ee0y6CutwrGAYWroBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjrdAMAAMzBcrymueuZL19augEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABjIig7dVfXcqjq1qi7vp+Or6lEjy6uqDqiqC6rqmqo6rqp2GdvGFlX1zqq6uKquqqpPVdUdl35vAAAAWG1WdOhOcn6SVya5Xz99OcknR4L1y5O8LMkLkuye5MIkX6yqrUe2cXCSP06yT5I9k9wyyWeqapOl2AEAAABWrxUdultrn26tfa61dmY/vTrJlUn2qKpK8pIkb2itfby1dnqSfZP8apKnJUlVbZvk2Un+urV2TGvt20mekeTeSfaawC4BAACwiqzo0D2qqjapqn2SbJXk+CQ7JdkhydFTZVpra5J8JckD+1m7JdlsrMwFSU4fKTPdY21RVdtMTUm2nqksAAAAG68VH7qr6t5VdWWSNUn+Jckft9a+ly5wJ8lFY6tcNLJshyTXtdZ+vp4y09k/yWUj0/nz3wMAAABWqxUfupOckWTXJHskeU+Sw6pq55Hlbax8TTNv3IbKHJhk25HJwGsAAACsY8WH7tbada21H7TWTmyt7Z/kO0lenG7QtGTdFuvts7b1+8Ikm1fVduspM91jrmmtXT41JbliwTsCAADAqrPiQ/c0KskWSc5OF6ofcdOCqs2TPDjJN/pZJyW5fqzM7ZPca6QMAAAAzMumk67AQlTVG5N8Psl56QYz2yfJQ5Ls3VprVXVwkldV1VlJzkryqiRXJ/lwkrTWLquq9yd5a1VdkuTSJAclOS3JMUu7NwAAAKw2Kzp0J7ldkn9Pcvt0A5qdmi5wf7Ff/uYkWyZ5d5LtknwzySNba6PdwV+a5IYkH+3LfinJfq21G5dkDwAAAFi1VnTobq09ewPLW5ID+mmmMtcmeWE/AQAAwKJZjed0AwAAwLIgdAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQDaddAUAAABYnY445oRJV2Ed++y1x5I+npZuAAAAGIjQDQAAAAOZV+iuqhur6v4zLNutqm5cWLUAAABg5ZtvS3dtYJttntsFAACAVWMh3ctnCta7JblsAdsFAACAVWHWo5dX1YuTvLi/25IcWVVrxoptmWT7JP+5ONUDAACAlWsulwz7WZLv9n/vmORHSX4xVmZNktOSvGOhFQMAAICVbtahu7X2kSQfSZKqOjbJc1tr3x+qYgAAALDSzaWl+yattYcudkUAAABgtZlX6E6Sqqokuye5S7pzuW+mtfbBBdQLAAAAVrx5he6quluSTyX5rUx/+bCWROgGAABgozbflu5/TvIrSZ6S5NR0A6gBAAAAI+Ybuu+f5C9aay4NBgAAADO4xTzXuzLJ5YtZEQAAAFht5hu6P5DkaYtZEQAAAFht5tu9/PQkT62qTyX5dJJLxgu01j6+kIoBAADASjff0P3h/nanJI+dZnlLssk8tw0AAACrwnxD90MXtRYAAACwCs0rdLfWvrLYFQEAAIDVZr4DqQEAAAAbMK+W7qr68gaKtNbaw+ezbQAAAFgt5ntO9y3SDZY26rZJ7p7kZ0nOXEilAAAAYDWY7zndD5luflXdLcknk7x+AXUCAACAVWFRz+lurZ2Z5C1J3ryY2wUAAICVaIiB1M5Jcq8BtgsAAAAryhCh+4lJLhhguwAAALCizHf08kOmmb1Fkvsk2TnJyxdSKQAAAFgN5jt6+cOy7ujl16brWn5ga+3DC6kUAAAArAbzHb18x0WuBwAAAKw6Q5zTDQAAAGT+3ctTVbdO8tIkD09ymyQXJzkmycGttZ8vTvUAAABg5ZpXS3dV/XqSk5O8Osm2Sc5Ncqskr0lyclXdYbEqCAAAACvVfLuXvzHJlkke0FrbpbX2iNbaLkke0M9/42JVEAAAAFaq+YbuvZP8XWvtW6Mz+/uvTfKohVYMAAAAVrr5hu5t010ebDpn98sBAABgozbf0H12ksfMsOxR/XIAAADYqM139PIPJHlTVd0iyWFJfprk9kmekeSFSV65ONUDAACAlWu+ofstSX4zyQuSPH9kfiX519baQQutGAAAAKx08wrdrbWW5C+r6m1JHpruOt2XJPlya+3MRawfAAAArFizDt1VtV2S9yX5QGvtM0nSWjsjyRkjZR5bVQcmeU5r7ZLFriwAAACsJHMZSO3Pk9w3yRfWU+YLSe6dm3c5BwAAgI3SXEL3Pkn+rbV2w0wF+mX/luRxC60YAAAArHRzCd13S3LiLMqd3JcFAACAjdpcQvemSa6fRbnrk2w2v+oAAADA6jGX0P3TJDvPotwuSS6cX3UAAABg9ZhL6P5KkudV1Yyt2P2y5yY5dqEVAwAAgJVuLqH77UnukeQTVXWH8YX9vCOT3L0vCwAAABu1WV+nu7V2alU9P8m7k5xdVSclObtfvFOS3dKF+Oe21k5b9JoCAADACjOXlu601v4tyYOSHJ3kPkme2k/3SXeN7t9vrb1vsSs5k6rav6q+VVVXVNXPqurIqrr7WJmqqgOq6oKquqaqjquqXcbKbFFV76yqi6vqqqr6VFXdcan2AwAAgNVpTqE7SVprx7fW/jDJNkl26KdtWmt/1Fo7YbEruAEPTvLPSfZI8oh0LfdHV9VWI2VenuRlSV6QZPd0g7x9saq2HilzcJI/Tnct8j2T3DLJZ6pqk6F3AAAAgNVr1t3Lx7XWfpnkZ4tYl/nUYe/R+1X1Z+nqtFuSr1ZVJXlJkje01j7el9k3yUVJnpbkvVW1bZJnJ3lma+2YvswzkpyXZK8kR40/blVtkWSLkVlbj5cBAACAObd0L3Pb9reX9rc7pWuJP3qqQGttTbqR2B/Yz9ot3XXFR8tckOT0kTLj9k9y2ch0/uJUHwAAgNVk1YTuvlX7bUm+3lo7vZ+9Q3970Vjxi0aW7ZDkutbaz9dTZtyB6QL+1OT8bwAAANYx7+7ly9C70g3otuc0y9rY/Zpm3rgZy/St5WtuKlg1+1oCAACw0VgVLd1V9c4kj0vy0NbaaFfvC/vb8Rbr7bO29fvCJJtX1XbrKQMAAABztqJDd385sHcleUKSh7XWzh4rcna6UP2IkXU2Tzfq+Tf6WScluX6szO2T3GukDAAAAMzZSu9e/s/pRiH/oyRXVNVUi/ZlrbVrWmutqg5O8qqqOivJWUleleTqJB9OktbaZVX1/iRvrapL0g3CdlCS05Ics6R7AwAAwKqy0kP3c/vb48bm/1mSQ/u/35xkyyTvTrJdkm8meWRr7YqR8i9NckOSj/Zlv5Rkv9bajYPUGgAAgI3Cig7drbUNjmDWWmtJDuinmcpcm+SF/QQAAACLYkWf0w0AAADLmdANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAANZ0aG7qh5UVZ+uqguqqlXV48eWV1Ud0C+/pqqOq6pdxspsUVXvrKqLq+qqqvpUVd1xSXcEAACAVWlFh+4kWyX5TpIXzLD85Ule1i/fPcmFSb5YVVuPlDk4yR8n2SfJnklumeQzVbXJQHUGAABgI7HppCuwEK21zyf5fJJU1c2WVTfjJUne0Fr7eD9v3yQXJXlakvdW1bZJnp3kma21Y/oyz0hyXpK9khw13eNW1RZJthiZtfV05QAAANi4rfSW7vXZKckOSY6emtFaW5PkK0ke2M/aLclmY2UuSHL6SJnp7J/kspHp/MWsOAAAAKvDag7dO/S3F43Nv2hk2Q5Jrmut/Xw9ZaZzYJJtRybngAMAALCOFd29fJba2P2aZt649ZbpW8zX3FR4rGs7AAAAJKu7pfvC/na8xXr7rG39vjDJ5lW13XrKAAAAwLys5tB9drpQ/YipGVW1eZIHJ/lGP+ukJNePlbl9knuNlAEAAIB5WdHdy6vqlknuOjJrp6raNcmlrbVzq+rgJK+qqrOSnJXkVUmuTvLhJGmtXVZV70/y1qq6JMmlSQ5KclqSY5ZsRwAAAFiVVnToTnK/JMeO3H9bf3tYkv2SvDnJlknenWS7JN9M8sjW2hUj67w0yQ1JPtqX/VKS/VprNw5acwAAAFa9FR26W2vHpRv0bKblLckB/TRTmWuTvLCfAAAAYNGs5nO6AQAAYKKEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0AwAAwECEbgAAABiI0A0AAAADEboBAABgIEI3AAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNDdq6rnVdXZVXVtVZ1UVb8/6ToBAACwsgndSarqKUkOTvKGJL+d5GtJPl9Vd55kvQAAAFjZNp10BZaJlyV5f2vtff39l1TVHyR5bpL9xwtX1RZJthiZtXWSXH755YtSmauvumpRtrOYFmvfFptjNXuO1ewsx+OUOFZz4VjNznI8ToljNReO1ewsx+OUOFZz4VjNznI8TsnqPlaz3U611hblAVeqqto8ydVJntRa+8TI/Hck2bW19uBp1jkgyeuWrJIAAAAsV3dsrf1kpoVaupPbJtkkyUVj8y9KssMM6xyY5G1j826d5NLFrdqCbZ3k/CR3THLFhOuynDlOs+dYzZ5jNXuO1ew5VrPjOM2eYzV7jtXsOVaz51jN3nI9VlsnuWB9BYTutcab/GuaeV3B1tYkWTM2e9n156iqqT+vaK0tu/otF47T7DlWs+dYzZ5jNXuO1ew4TrPnWM2eYzV7jtXsOVazt4yP1QbrYiC15OIkN2bdVu3ts27rNwAAAMzaRh+6W2vXJTkpySPGFj0iyTeWvkYAAACsFrqXd96W5N+r6sQkxyd5TpI7J/mXidZq4dYkeX3W7QrPzTlOs+dYzZ5jNXuO1ew5VrPjOM2eYzV7jtXsOVaz51jN3oo9Vhv96OVTqup5SV6e5PZJTk/y0tbaVydbKwAAAFYyoRsAAAAGstGf0w0AAABDEboBAABgIEI3AAAADEToBgDgZqqqVdXjJ10PVg+vKTZmQvcKU1WH9h9araqur6qLquqLVfWsqvJ8TqM/ZkdOuh4rQVU9sKpurKovTLouy11V3amq3l9VF1TVdVX146p6R1XdZpbrP6R/H99q4KpOjNfT7FTV9lX13qo6t6rWVNWFVXVUVf3upOu23Iz8D1znkp5V9e5+2aETqNqy53/h9EZeU68cm//4qjLa8Jix76Gj010nXbflwufU/Kz2zyghbWX6QrpLm+2Y5FFJjk3yjiSfqSrXXmchnpXknUn2rKo7L2RDVbXJav0hqKp+I8mJSe6W5KlJ7prkr5I8PMnxVXXrCVZvOVm019Mq919J7ptk33SvqcclOS6J19H0zkuyT1VtOTWjqn4l3Xvx3IVsuKo2W2DdWJmuTfKKqtpu0hVZIaa+h45OZ0+0RsvPYJ9TrEyr8gvxRmBNa+3C1tpPWmsnt9bemOSP0gXw/ZKkqratqn+tqp9V1eVV9eWquu/oRqrqcVV1YlVdW1UXV9XHl35XllZVnVNVLxmbd0pVHTByv1XVn1fVJ6rq6qo6q6oet9R1XWpVtVWSJyd5T5LPpH8t9cumWmUfU1Xf6V8z36yqe4+U2a+qflFVj62q7yVZk+QuS7wbS+Wfk1yX5JGtta+01s5trX0+yV5Jfj3JG5KkqraoqjdX1Xl9C+ZZVfXsqtox3Y9lSfLz1fir9wZeT/tV1S/Gyq/TqlRVf9d/hl1RVe+rqjdV1SmDV34J9T0d9kzyitbasa21H7fW/qe1dmBr7bN9mfV+nlfVAf3n2F/2r7Wrq+pjq7gXxcnpvrQ+YWTeE9J9yf321Iyq2ruqvt5/Ll1SVZ+pqt8cWb5j/957clUdV1XXJnnGUu3EJM3mf+FG5pgkFybZf6YCVfXEqvpu/1l+TlX99ciyA6vqhGnWObWqXj9MlSdq6nvo6HRjVf1hVZ3Uf0f4UVW9bprGoNtX1eer6pqqOruqnjSRPRjeYn1Ofbmq3jW64aq6Tf86fNjA+zAxc/j8fkJVHdv/3/tOLeMeYkL3KtFa+3KS7yR5QlVVks8m2SHJo5Pslu7N/6XqW+Cq6jFJPt6X++10LXQnTqDqy9Xrknw0yX2SfC7J4bX6Wy+fkuSM1toZST6U5M/619KotyT5myS7J/lZkk/VzVuGfjXdl5Y/T7JLX2ZV6V8Hf5Dk3a21a0aXtdYuTHJ4kqf0x+6DSfZJ8qIk90zXGn5lun+6T+xXu3u6VoIXL8kOLJ3ZvJ5mVFVPT/LqJK9I9xl2bpLnDlHRCbuynx5fVVuML5zN53nvrul+5PjDJHsn2TXdj0Or1QeS/NnI/WclOWSszFZJ3pbu8+rhSX6Z5BO1bg+cf0zyT+neo0cNUluWuxuTvCrJC6vqjuMLq2q3dN8Jjkhy7yQHJPmHqtqvL3J4kgeMhYJd+rKHD1rzZaKq/iDdZ/0/Jdk5yV+m+7H11WNF/yFre/d8KMlHquqeS1fTJbUYn1PvS/K0sf8PT09yQdb+eL8azfbz+w1JDkr3P+/MdK+n5dnrt7VmWkFTkkOTHDnDsiOSfC/Jw5JclmSLseU/SPKc/u9vJPnQpPdnqY9ZknOSvGRs+SlJDhi535L8w8j9rdK92fee9L4MfJz+O8mL+783TfJ/Sfbq7z+kPy5PGSl/6yRXJ3lyf3+/vsx9J70vAx+nB/T7+fgZlr+0X37//navGcpNHdNbTXqfJvB62i/JL8bKP777l3TT/ROSvGuszNeTnDLpfRvgWD0xyaVJrumP2xuT3KdfNpvP8wOS3JDkjiPL904XJHaY9P4t8rE6NMmRSW6brkvwjul61FzTzzsyyaEzrPtr/XvuXv39Hfv7L570fi3lsev/nu3/wsdPut5LfFyOT/L+/u+bPpPSBeejx9Z7c5Lvjtz/TpLXjNx/Y5L/mfT+DXS8bsjaHwyvTPKxJF9Nsv9Y2WckuWDsNfWesTInpPsRe+L7ttivqUX6nNoiySXpv2v1876d5HWT3s+hjtssj8vU5/ezR8rs3M+7x6T3ZbpJS/fqUulebLsluWWSS6rqyqkpyU5Jpn6F3TXJlyZSy5Xh1Kk/WmtXJbkiyfaTq86wquru6ULiEUnSWrshyX+k+1V21PFTf7TWLk1yRrrWoSnXZeTYbaSmWnN3Shd6vjLBukzEHF5P63P3JP8zNm/8/qrQWvuvJHdIdy73Uel+kDm5b0Wbzed5kpzbWjt/5P7x6Xqz3X34PVh6rbWL0/UA2DddS9Jn+3k3qarfrKoP991cL8/ac07HxxfQy4spr0iyb1XtPDb/nul+EBv130l+q6o26e8fnq4FcqqHylOzelu5j033PXJqelG6z6rXjn1O/Vu67uS/OrLu8TffVI7Pzb9HrBqL8TnVWluTrkfAs/ryu6brJXDoUuzDpMzh83v0O+dP+9tl+X19eTa/M1/3TPeivEW6F95Dpinzi/72mmmWbQx+mbWhaMp0A+dcP3a/ZXWfjvHsdJ8HPxnpAVxJrq8NDywzeh7uNa3/uXEV+0G6fd453a/V4+6R5OfpegFsrDb0eprt+3D8tTTr7ukrTWvt2iRf7Ke/r6r3JXl9kndnw5/n025y7HY1OiTJ1LmOz59m+afTncrxF+m6Yt4iyelJNh8rd9VQFVzGZvse3Ki01r5aVUela6U+dGTRVKNGxuaN+nCSN1XV7yTZMsmd0v/wuApd1Vr7weiMvtvv69Kdujju2g1sz+fU+j+n3pfklP7Uh2cl+VJr7ceD1Xh5mO3n9+j39anX0bL8vi50rxL9YAr3TvL2JOenO//vhtbaOTOscmq6cyQ+sCQVXD7+L935s0mSqtomXYvRRqs/9+VPk/x1kqPHFv9Xul/uT+/v75F+1M0+PN0tyfeXpqbLQ2vtkqr6YpLnVdXb28h53VW1Q7rj9cEkp6X74H9wukF6xl3X324yzbIVa5avpx8m2bqqtup7kiRda8moM9K1lv/7yLz7LXqFl6/vpeveenI2/HmeJHeuqju01i7o7/9uumB15pCVnLAvZO0XsJudi13dpfvumeQvW2tf6+ftubTVW9b8L5zZ/um6746+d76XbsDDUQ9McmZr7cYkaa2dX1VfTfcZt2WSY1prFy1BfZeLk5PcfTyMT2OPdP8jR+9/e4ayq8GCP6daa6dV1YnpAujTkrxw0BpP2Gr9/Ba6V6Yt+i/3myS5Xbpz9/ZPN0LwB9N90To+yZFV9Yp0X17vkG4QniNbayema0H5UlX9MN0vsZsmeVRr7c1LvTNL7MtJ9quqT6drjfyHdF2AN2aPTbJduvPYLhtdUFX/ma7V8qX9rNdW1SVJLko3eMXFmb61d7V7QbpxEY6qqr9L18Nkl3QDzf0kyatba5dW1WFJDqmqF6U73+8uSbZvrX00yY/T/Sr72Kr6XLpeAldOYF8W22xeTw9P1xPgjVX1znTher+x7bwzyb/1XzS+kW5gtvsk+dGgtV9i/ZeLj6VrDTk13aks90vy8iSfTPeDzYY+z5OuJemwqvqbJNukG8zoo60b3G9Vat1oyfec+nts8c/TnQf5nKr6abouiW9a4iouZ/4XzqC1dmpVHZ6bB5u3JvlWVb0m3akyv5vu/8DzxlY/PN0YC5tn7f/NjcXfp7t07XnpPtN+me4z+96ttb8bKfek/nP96+l+oLh/uv8Lq9Iifk69L12L+dVJPjFQdZeLVfn5vSyb39mgvdN1Nzwn3S9oD013Ps0ftdZu7Lv3PjrdoBaHpPu19oh0gw5clCStteOSPCndOYSnpPsH/ICl24UldYt0g34kyYHpjstn0o1KfmS6VreN2bPT/SJ/2TTL/itdC+Tv9Pdfme6a8CelayV5XGvtumnWW9Vaa2elC0Y/TPcF7IdJ/jXdeW6/25/vnnSjbf9nui7C3093fttW/TZ+kq4r3pvSvS9vdkmQFWw2r6cd0w2w8+h0PQKemu6L6k1aa4ene78elK4FZad03T031E1xpbkyyTfTfUH/arpeJf+Q7rXygtl8nvd+kK5b5+fS9TA4PesGglWntXZ5a+3yaeb/Mt2VA3ZLdyzenuRvl7h6y43/hbP3mox0H2+tnZzu6gD7pHs9/X2S17bWDh1b72NJbpPuSh5HLkVFl4vW2lHpfnR9RJJvpRsg7WXpfmAe9bp0x/HUdOc6P7219r0lrOqSW6TPqY+ke/9+uD8daTW6RbpeXavy87tW/+mXbOyq6gtJftBae8Gk67JSVdVD0gXK7Vprv5hoZdho9d36L2ytPXPSdVlOqru28uNba7tOuCosY/4XwspVVXdK19i2e/8j0Kqz2j+jdC9n1erPOX5gugGI/mWytQHmoh/t9q/SnQN3Y7rW8L3StaIAs+R/IaxcVbVZup6Fb0pywmoM3BvLZ5TQzWp2SJLd052L9ckJ1wWYm6lu1X+X7jqlZyR5YmttukHpgJn5Xwgr1++l62l4ZpI/mXBdhrJRfEbpXg4AAAADMZAaAAAADEToBgAAgIEI3QAAADAQoRsAAAAGInQDAADAQIRuAAAAGIjQDQAAAAMRugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICBCN0AAAAwEKEbAAAABiJ0A8AqV1X7VVXrp4dMs7yq6gf98uMGrMcDq+qAqrrVNMvOqarPDPXYADApQjcAbDyuSPLsaeY/OMlv9suH9MAkr0tyq4EfBwCWDaEbADYe/5HkiVW1zdj8Zyc5Psm5S18lAFjdhG4A2Hh8pL996tSMqto2yROTHDJeuKpuXVXvrqqfVNV1VfWjqnpDVW0xVq5V1buq6plV9b9VdXVVfaeqHjtS5oAkb+nvnj1Td/eq2ruqTq6qa6rq+1X1rMXYcQCYFKEbADYelyf5zySjQfapSX6ZrhX8JlX1K0mOTfKnSd6W5DFJPpTk5Uk+Ps22H5PkBUlemy7EX5rkE1X1G/3y9yV5Z//3E5L8bj+dPLKN+yZ5a5K3J/mjJKcmeX9VPWjuuwoAy8Omk64AALCkDklybFXt0lr7broA/rHW2hVVNVpu3yT3SfLk1trH+nlfrKork/xjVT2itfbFkfJbJtmrtXZFklTVyUkuSPLkJG9qrZ1fVVPd17/dWjtnmrrdNsnvtdbO7bfx1SQPT/K0JF9d8J4DwARo6QaAjctXkvwwybOq6t5Jds80XcuTPCzJVelaxkcd2t8+fGz+sVOBO0laaxcl+VmSu8yhbqdMBe5+G9cmOXOO2wCAZUVLNwBsRFprrao+kORFSX4lyZmtta9NU/Q2SS5srbWx9X9WVTf0y0ddMs021qRrAZ+txdgGACwrWroBYONzaLqu3H+V5AMzlLkkye1qrM95VW2f7kf7i4esIACsFkI3AGxkWms/STeS+KeTHDZDsS8luWWSx4/N/9OR5XO1pr/Vcg3ARkP3cgDYCLXWXrmBIh9M8vwkh1XVjklOS7Jnklcl+Vxr7Zh5POxp/e2Lq+qwJNcnOWP0XHAAWG20dAMA6+gHMXtoksOT/G2SzyfZL8lB6S75NZ9tHpfkwCR/mOTrSb6VZLeF1xYAlq8aGx8FAAAAWCRaugEAAGAgQjcAAAAMROgGAACAgQjdAAAAMBChGwAAAAYidAMAAMBAhG4AAAAYiNANAAAAAxG6AQAAYCBCNwAAAAxE6AYAAICB/H/UKH9OUCBQWQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 5), dpi = 100)\n",
    "\n",
    "sm.groupby('Month')['Month'].count().sort_values(ascending = False).plot(kind='bar', color = '#a7bbc7')\n",
    "\n",
    "plt.title('Space Mission Count by Month', size = 16, pad = 20)\n",
    "plt.xticks(rotation = 360)\n",
    "plt.xlabel('Month', size = 12, labelpad = 15)\n",
    "plt.ylabel('Count', size = 12, labelpad = 15)\n",
    "\n",
    "plt.savefig('Figures/space-mission-count-by-month.jpg', dpi = 100)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What is the most \"popular\" hour to launch a space mission at? <a name =\"analysis-on-datum-q5\"></a>\n",
    "\n",
    "The table below indicates midnight (00:00) is the most \"popular\" hour for space missions to launch at followed by 11 AM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 747,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒════════╤═════════╕\n",
      "│   Hour │   Count │\n",
      "╞════════╪═════════╡\n",
      "│      0 │     312 │\n",
      "├────────┼─────────┤\n",
      "│     11 │     235 │\n",
      "├────────┼─────────┤\n",
      "│      9 │     230 │\n",
      "├────────┼─────────┤\n",
      "│     12 │     228 │\n",
      "├────────┼─────────┤\n",
      "│     10 │     219 │\n",
      "├────────┼─────────┤\n",
      "│     22 │     203 │\n",
      "├────────┼─────────┤\n",
      "│     13 │     201 │\n",
      "├────────┼─────────┤\n",
      "│      8 │     194 │\n",
      "├────────┼─────────┤\n",
      "│     14 │     191 │\n",
      "├────────┼─────────┤\n",
      "│     21 │     179 │\n",
      "├────────┼─────────┤\n",
      "│     18 │     178 │\n",
      "├────────┼─────────┤\n",
      "│      7 │     176 │\n",
      "├────────┼─────────┤\n",
      "│     23 │     176 │\n",
      "├────────┼─────────┤\n",
      "│      1 │     164 │\n",
      "├────────┼─────────┤\n",
      "│     15 │     159 │\n",
      "├────────┼─────────┤\n",
      "│     20 │     153 │\n",
      "├────────┼─────────┤\n",
      "│      5 │     148 │\n",
      "├────────┼─────────┤\n",
      "│      6 │     147 │\n",
      "├────────┼─────────┤\n",
      "│      3 │     147 │\n",
      "├────────┼─────────┤\n",
      "│     16 │     146 │\n",
      "├────────┼─────────┤\n",
      "│     19 │     145 │\n",
      "├────────┼─────────┤\n",
      "│      4 │     140 │\n",
      "├────────┼─────────┤\n",
      "│     17 │     139 │\n",
      "├────────┼─────────┤\n",
      "│      2 │     114 │\n",
      "╘════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "# most popular hour for space launches?\n",
    "table12 = pd.DataFrame(sm.groupby('Hour')['Hour'].count().sort_values(ascending = False))\n",
    "print(tab(table12, tablefmt=\"fancy_grid\", headers = ['Hour', 'Count']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[**Back to Top**](#back-to-top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis on Rocket (Cost of Mission) <a name =\"analysis-sm-cost\"></a>\n",
    "\n",
    "The analysis intends to answer the following questions:\n",
    "  1. Which company has the most expensive space missions on average?\n",
    "  2. Which space mission was the most expensive of all time?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "# renaming the column 'Rocket' to 'Cost of Mission' because it makes more sense contextually\n",
    "sm.rename(columns = {' Rocket':'Cost of Mission'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "# noticed some values of 'Cost of Mission' were strings instead of numerical values, \n",
    "# so I am changing those instances to be numerical. Also, checking the original source of the data, NextSpaceFlight.com,\n",
    "# it appears the two missions that are said to be $5000.0 million USD are ACTUALLY $3000.0 millions USD, so I am making that\n",
    "# correction.\n",
    "\n",
    "sm.loc[sm['Cost of Mission'] == '5,000.0 ', 'Cost of Mission'] = 3000.0\n",
    "sm.loc[sm['Cost of Mission'] == '1,160.0 ', 'Cost of Mission'] = 1160.0\n",
    "sm['Cost of Mission'] = pd.to_numeric(sm['Cost of Mission'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Which company has the most expensive space missions on average? <a name =\"analysis-sm-cost-q1\"></a>\n",
    "\n",
    "The RVSN USSR has the highest average cost for space missions. However, this may not be accurate because most values for 'Cost of Mission' are NA for RVSN USSR. There are only two recorded 'Cost of Mission' for RVSN USSR and both are 3,000 (in millions USD). The plot below indicates no other company has an average space mission cost as high as RVSN USSR."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 709,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Company Name\n",
       "RVSN USSR    3000.0\n",
       "Name: Cost of Mission, dtype: float64"
      ]
     },
     "execution_count": 709,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm.groupby('Company Name').mean()['Cost of Mission'].dropna().sort_values(ascending = False).round(2).head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x750 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20, 10), dpi = 75)\n",
    "sm.groupby('Company Name').mean()['Cost of Mission'].dropna().sort_values(ascending = False).round(2).plot(kind = 'bar', \n",
    "                                                                                                           color = '#a7bbc7')\n",
    "plt.title('Average Cost of Mission (in millions USD) by Company', size = 22, pad = 20)\n",
    "plt.xlabel('Company', size = 18, labelpad = 20)\n",
    "plt.ylabel('Avg. Cost of Mission (in millions USD)', size = 18, labelpad = 20)\n",
    "plt.xticks(size = 16)\n",
    "plt.yticks(size = 16)\n",
    "plt.tight_layout(pad = 4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Which space mission was the most expensive of all time? <a name =\"analysis-sm-cost-q2\"></a>\n",
    "\n",
    "The table below indicates the two most expensive space missions were in 1987 and 1988 from RVSN USSR, the [Energiya/Polyus](https://nextspaceflight.com/launches/details/1119) and [Energiya/Buran](https://nextspaceflight.com/launches/details/1120), respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 711,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Location</th>\n",
       "      <th>Datum</th>\n",
       "      <th>Detail</th>\n",
       "      <th>Status Rocket</th>\n",
       "      <th>Cost of Mission</th>\n",
       "      <th>Status Mission</th>\n",
       "      <th>Country</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1916</th>\n",
       "      <td>RVSN USSR</td>\n",
       "      <td>Site 110/37, Baikonur Cosmodrome, Kazakhstan</td>\n",
       "      <td>1988-11-15 03:00:00+00:00</td>\n",
       "      <td>Energiya/Buran | Buran</td>\n",
       "      <td>StatusRetired</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>Success</td>\n",
       "      <td>Kazakhstan</td>\n",
       "      <td>3</td>\n",
       "      <td>Nov</td>\n",
       "      <td>1988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>RVSN USSR</td>\n",
       "      <td>Site 250, Baikonur Cosmodrome, Kazakhstan</td>\n",
       "      <td>1987-05-15 17:30:00+00:00</td>\n",
       "      <td>Energiya/Polyus | Polyus Space Station</td>\n",
       "      <td>StatusRetired</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>Success</td>\n",
       "      <td>Kazakhstan</td>\n",
       "      <td>17</td>\n",
       "      <td>May</td>\n",
       "      <td>1987</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Company Name                                      Location  \\\n",
       "1916    RVSN USSR  Site 110/37, Baikonur Cosmodrome, Kazakhstan   \n",
       "2000    RVSN USSR     Site 250, Baikonur Cosmodrome, Kazakhstan   \n",
       "\n",
       "                          Datum                                  Detail  \\\n",
       "1916  1988-11-15 03:00:00+00:00                  Energiya/Buran | Buran   \n",
       "2000  1987-05-15 17:30:00+00:00  Energiya/Polyus | Polyus Space Station   \n",
       "\n",
       "      Status Rocket  Cost of Mission Status Mission     Country  Hour Month  \\\n",
       "1916  StatusRetired           3000.0        Success  Kazakhstan     3   Nov   \n",
       "2000  StatusRetired           3000.0        Success  Kazakhstan    17   May   \n",
       "\n",
       "      Year  \n",
       "1916  1988  \n",
       "2000  1987  "
      ]
     },
     "execution_count": 711,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we know from the previous question there are two instances where a space mission cost 5000 (in millions USD)\n",
    "sm[sm['Cost of Mission'] == 3000.00]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[**Back to Top**](#back-to-top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis on Status Rocket <a name = \"analysis-status-rocket\"></a>\n",
    "The analysis intends to answer the following questions:\n",
    "  1. How many countries still have active rockets?\n",
    "      - Which countries are they?\n",
    "  2. Are there any countries that do not have any active rockets?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 712,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Status Rocket\n",
       "StatusActive      790\n",
       "StatusRetired    3534\n",
       "Name: Status Rocket, dtype: int64"
      ]
     },
     "execution_count": 712,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cleaning up the values in the \"Status Rocket column\"\n",
    "# it appears the only categories are 'Status Active' or 'Status Retired'\n",
    "sm.groupby('Status Rocket')['Status Rocket'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 713,
   "metadata": {},
   "outputs": [],
   "source": [
    "# changing 'StatusActive' to 'Active' and 'StatusRetired' to 'Retired'\n",
    "sm.loc[sm['Status Rocket'] == 'StatusActive', 'Status Rocket'] = 'Active'\n",
    "sm.loc[sm['Status Rocket'] == 'StatusRetired', 'Status Rocket'] = 'Retired'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. How many countries currently have active rockets? And which countries are they? <a name = \"analysis-status-rocket-q1\"></a>\n",
    "\n",
    "There are 14 countries that have active rockets. They are listed in the table below.\n",
    "- China and the United States have the most active rockets currently, 224 and 213, respectively.\n",
    "- Spain has the fewest number of active rockets, 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 714,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 714,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many countries still have active rockets?\n",
    "sm['Country'].loc[sm['Status Rocket'] == 'Active'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 715,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒═════════════╤═════════╕\n",
      "│ Country     │   Count │\n",
      "╞═════════════╪═════════╡\n",
      "│ China       │     224 │\n",
      "├─────────────┼─────────┤\n",
      "│ USA         │     213 │\n",
      "├─────────────┼─────────┤\n",
      "│ France      │     113 │\n",
      "├─────────────┼─────────┤\n",
      "│ India       │      50 │\n",
      "├─────────────┼─────────┤\n",
      "│ Kazakhstan  │      44 │\n",
      "├─────────────┼─────────┤\n",
      "│ Japan       │      38 │\n",
      "├─────────────┼─────────┤\n",
      "│ Russia      │      36 │\n",
      "├─────────────┼─────────┤\n",
      "│ Other (Sea) │      36 │\n",
      "├─────────────┼─────────┤\n",
      "│ New Zealand │      13 │\n",
      "├─────────────┼─────────┤\n",
      "│ Iran        │      10 │\n",
      "├─────────────┼─────────┤\n",
      "│ Israel      │       5 │\n",
      "├─────────────┼─────────┤\n",
      "│ North Korea │       3 │\n",
      "├─────────────┼─────────┤\n",
      "│ Brazil      │       3 │\n",
      "├─────────────┼─────────┤\n",
      "│ Spain       │       2 │\n",
      "╘═════════════╧═════════╛\n"
     ]
    }
   ],
   "source": [
    "# which countries still have active rockets?\n",
    "table10 = pd.DataFrame(sm.loc[sm['Status Rocket'] == 'Active'].groupby('Country')['Country'].count().sort_values(ascending = False))\n",
    "print(tab(table10, tablefmt = 'fancy_grid', headers = ['Country', 'Count']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Are there any countries that do not have any active rockets? <a name = \"analysis-status-rocket-q2\"></a>\n",
    "\n",
    "The table below indicates Australia, South Korea, and Kenya are the only countries that **do not** currently have active rockets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 740,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "╒═════════════════════════════════════╤══════════╤═══════════╕\n",
      "│ Status  Rocket: Active or Retired   │          │           │\n",
      "│                                     │          │           │\n",
      "│ Country                             │   Active │   Retired │\n",
      "╞═════════════════════════════════════╪══════════╪═══════════╡\n",
      "│ Australia                           │        0 │         6 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ South Korea                         │        0 │         3 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Kenya                               │        0 │         9 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Spain                               │        2 │         0 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Brazil                              │        3 │         0 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ North Korea                         │        3 │         2 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Israel                              │        5 │         6 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Iran                                │       10 │         4 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ New Zealand                         │       13 │         0 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Russia                              │       36 │      1359 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Other (Sea)                         │       36 │         3 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Japan                               │       38 │        88 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ Kazakhstan                          │       44 │       657 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ India                               │       50 │        26 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ France                              │      113 │       190 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ USA                                 │      213 │      1136 │\n",
      "├─────────────────────────────────────┼──────────┼───────────┤\n",
      "│ China                               │      224 │        45 │\n",
      "╘═════════════════════════════════════╧══════════╧═══════════╛\n"
     ]
    }
   ],
   "source": [
    "table11 = pd.DataFrame(sm.groupby(['Country', 'Status Rocket'])['Country'].count().reset_index(name = 'Count'))\n",
    "\n",
    "print(tab(table11.pivot(index = 'Country', \n",
    "                        columns = 'Status Rocket', \n",
    "                        values = 'Count').fillna(0).sort_values('Active'), \n",
    "    tablefmt = \"fancy_grid\", headers = ['Status  Rocket: Active or Retired\\n\\nCountry','\\n\\nActive', '\\n\\nRetired']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[**Back to Top**](#back-to-top)"
   ]
  }
 ],
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