dcasmr/StackedBar.ipynb Secret

## StackedBar.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data source and header Infographic. [Missing migrants project:](https://missingmigrants.iom.int) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "'''\n",
    "Author: Luc Zio\n",
    "PythonStatistics.net\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Migrants.csv\",encoding ='latin-1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Web ID</th>\n",
       "      <th>Region_of_Incident</th>\n",
       "      <th>Reported_Year</th>\n",
       "      <th>Number_Dead</th>\n",
       "      <th>Total_Dead_and_Missing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>44025</td>\n",
       "      <td>US-Mexico Border</td>\n",
       "      <td>2017</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>44026</td>\n",
       "      <td>Mediterranean</td>\n",
       "      <td>2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>44027</td>\n",
       "      <td>Mediterranean</td>\n",
       "      <td>2017</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>44017</td>\n",
       "      <td>US-Mexico Border</td>\n",
       "      <td>2017</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>44024</td>\n",
       "      <td>US-Mexico Border</td>\n",
       "      <td>2017</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Web ID Region_of_Incident  Reported_Year  Number_Dead  \\\n",
       "0   44025   US-Mexico Border           2017         10.0   \n",
       "1   44026      Mediterranean           2017          NaN   \n",
       "2   44027      Mediterranean           2017          1.0   \n",
       "3   44017   US-Mexico Border           2017          1.0   \n",
       "4   44024   US-Mexico Border           2017          1.0   \n",
       "\n",
       "   Total_Dead_and_Missing  \n",
       "0                      10  \n",
       "1                       2  \n",
       "2                       1  \n",
       "3                       1  \n",
       "4                       1  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Subset the migrants deaths to certain regions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df2 = df.loc[df['Region_of_Incident'].isin(['Horn of Africa','Mediterranean','Middle East','North Africa','Sub-Saharan Africa'])]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a crosstab tables with the total deaths and missings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Summary = pd.crosstab(df2['Region_of_Incident'], df2['Reported_Year'], values=df2['Total_Dead_and_Missing'],aggfunc=np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Reported_Year</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Region_of_Incident</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Horn of Africa</th>\n",
       "      <td>265</td>\n",
       "      <td>135</td>\n",
       "      <td>235</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mediterranean</th>\n",
       "      <td>3283</td>\n",
       "      <td>3785</td>\n",
       "      <td>5143</td>\n",
       "      <td>3095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Middle East</th>\n",
       "      <td>39</td>\n",
       "      <td>36</td>\n",
       "      <td>114</td>\n",
       "      <td>208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Africa</th>\n",
       "      <td>89</td>\n",
       "      <td>801</td>\n",
       "      <td>1382</td>\n",
       "      <td>467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sub-Saharan Africa</th>\n",
       "      <td>268</td>\n",
       "      <td>74</td>\n",
       "      <td>92</td>\n",
       "      <td>387</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Reported_Year       2014  2015  2016  2017\n",
       "Region_of_Incident                        \n",
       "Horn of Africa       265   135   235   170\n",
       "Mediterranean       3283  3785  5143  3095\n",
       "Middle East           39    36   114   208\n",
       "North Africa          89   801  1382   467\n",
       "Sub-Saharan Africa   268    74    92   387"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use seaborn to style and pandas to plot the bar graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sWZLq1aszdepUteP09fU1PkfJkiXR0tJSBoA/7enzPU/ufk9PLoH/JXS55wIYP368Sgtb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5kzZ9KkSRPmzZvH1atX6d69O4AkeFpSoUIF9uzZQ35+vpqkLV++nIEDBzJq1ChMTEwoV64crVq1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\n5E4IIYQQ4g0iyZ0QQgghxBvk/wChurJIy/2E5AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x26a48e733c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "flatui = [\"#9b59b6\", \"#3498db\", \"#95a5a6\", \"#e74c3c\", \"#34495e\", \"#2ecc71\"]\n",
    "plt.rcParams[\"figure.figsize\"] = [10,6]\n",
    "sns.set_context(\"notebook\", font_scale=1.5, rc={\"font.size\":16,\"axes.titlesize\":16,\"axes.labelsize\":16})\n",
    "sns.set_style(\"darkgrid\")\n",
    "Summary.plot(kind=\"bar\", stacked=False,color=flatui)\n",
    "plt.title('Number of deaths or missing African migrants \\n Period of 2014 thru 2017')\n",
    "plt.ylabel('Number of deaths or missing migrants')\n",
    "plt.xlabel('Region of casualties')\n",
    "plt.xticks(rotation=-45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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