Communicable.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "from pandas import Series, DataFrame\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set_style('whitegrid')\n",
    "%matplotlib inline\n",
    "\n",
    "from __future__ import division"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "problems_df = pd.read_csv('communicable.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1196 entries, 0 to 1195\n",
      "Data columns (total 4 columns):\n",
      "Year                                   1196 non-null object\n",
      "District                               1196 non-null object\n",
      "Communicable and infectious disease    1196 non-null object\n",
      "Number of people                       1196 non-null int64\n",
      "dtypes: int64(1), object(3)\n",
      "memory usage: 46.7+ KB\n"
     ]
    }
   ],
   "source": [
    "problems_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Number of people</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Communicable and infectious disease</th>\n",
       "      <th>Confirmed Meningitis</th>\n",
       "      <th>HIV/AIDS</th>\n",
       "      <th>Leprosy</th>\n",
       "      <th>STD/STI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009/010</th>\n",
       "      <td>1581</td>\n",
       "      <td>3864</td>\n",
       "      <td>2536</td>\n",
       "      <td>50112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010/011</th>\n",
       "      <td>1552</td>\n",
       "      <td>2240</td>\n",
       "      <td>1572</td>\n",
       "      <td>42992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011/012</th>\n",
       "      <td>1403</td>\n",
       "      <td>2151</td>\n",
       "      <td>1880</td>\n",
       "      <td>41370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012/013</th>\n",
       "      <td>2801</td>\n",
       "      <td>3243</td>\n",
       "      <td>2304</td>\n",
       "      <td>45892</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Number of people                   \\\n",
       "Communicable and infectious disease Confirmed Meningitis HIV/AIDS Leprosy   \n",
       "Year                                                                        \n",
       "2009/010                                            1581     3864    2536   \n",
       "2010/011                                            1552     2240    1572   \n",
       "2011/012                                            1403     2151    1880   \n",
       "2012/013                                            2801     3243    2304   \n",
       "\n",
       "                                             \n",
       "Communicable and infectious disease STD/STI  \n",
       "Year                                         \n",
       "2009/010                              50112  \n",
       "2010/011                              42992  \n",
       "2011/012                              41370  \n",
       "2012/013                              45892  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_df = problems_df.pivot_table(index='Year',columns='Communicable and infectious disease',aggfunc=sum)\n",
    "year_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f684b38ea50>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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PAK8HLmicf24t36v2fxXlVYE3DaaPDs6s1/NBYColf8TlEbF+H/X70r7qYLBO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\nGIwgAgAAABiMIAIAAAAYzP8AbOzrc4k/e68AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6859618e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "year_df.plot(figsize=(12,5),kind='bar').legend(loc='center left', bbox_to_anchor=(1, 0.5), prop={'size':15})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Number of people</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Communicable and infectious disease</th>\n",
       "      <th>Confirmed Meningitis</th>\n",
       "      <th>HIV/AIDS</th>\n",
       "      <th>Leprosy</th>\n",
       "      <th>STD/STI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Communicable and infectious disease</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Number of people</th>\n",
       "      <th>Confirmed Meningitis</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.371484</td>\n",
       "      <td>0.394429</td>\n",
       "      <td>0.227642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HIV/AIDS</th>\n",
       "      <td>0.371484</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.939495</td>\n",
       "      <td>0.978907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leprosy</th>\n",
       "      <td>0.394429</td>\n",
       "      <td>0.939495</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.864225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STD/STI</th>\n",
       "      <td>0.227642</td>\n",
       "      <td>0.978907</td>\n",
       "      <td>0.864225</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         Number of people  \\\n",
       "Communicable and infectious disease                  Confirmed Meningitis   \n",
       "                 Communicable and infectious disease                        \n",
       "Number of people Confirmed Meningitis                            1.000000   \n",
       "                 HIV/AIDS                                        0.371484   \n",
       "                 Leprosy                                         0.394429   \n",
       "                 STD/STI                                         0.227642   \n",
       "\n",
       "                                                                          \\\n",
       "Communicable and infectious disease                   HIV/AIDS   Leprosy   \n",
       "                 Communicable and infectious disease                       \n",
       "Number of people Confirmed Meningitis                 0.371484  0.394429   \n",
       "                 HIV/AIDS                             1.000000  0.939495   \n",
       "                 Leprosy                              0.939495  1.000000   \n",
       "                 STD/STI                              0.978907  0.864225   \n",
       "\n",
       "                                                                \n",
       "Communicable and infectious disease                    STD/STI  \n",
       "                 Communicable and infectious disease            \n",
       "Number of people Confirmed Meningitis                 0.227642  \n",
       "                 HIV/AIDS                             0.978907  \n",
       "                 Leprosy                              0.864225  \n",
       "                 STD/STI                              1.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "idx = problems_df.groupby(['Year','Communicable and infectious disease'], sort=False)['Number of people'].transform(max) == problems_df['Number of people']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>District</th>\n",
       "      <th>Communicable and infectious disease</th>\n",
       "      <th>Number of people</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Parbat</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>1458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Parbat</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Bardiya</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>5057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Rukum</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Jhapa</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Morang</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Bardiya</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>4837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Achham</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>608</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Jhapa</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>3290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>662</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Dhanusha</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>779</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Gulmi</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Achham</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>1197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>908</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Jhapa</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>2895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>962</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Dhanusha</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Palpa</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1169</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Achham</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Year  District Communicable and infectious disease  Number of people\n",
       "185   2009/010    Parbat                            HIV/AIDS              1458\n",
       "186   2009/010    Parbat                             Leprosy               406\n",
       "204   2009/010   Bardiya                             STD/STI              5057\n",
       "251   2009/010     Rukum                Confirmed Meningitis               210\n",
       "310   2010/011     Jhapa                             Leprosy               175\n",
       "315   2010/011    Morang                Confirmed Meningitis               292\n",
       "524   2010/011   Bardiya                             STD/STI              4837\n",
       "569   2010/011    Achham                            HIV/AIDS               551\n",
       "608   2012/013     Jhapa                             STD/STI              3290\n",
       "662   2012/013  Dhanusha                             Leprosy               281\n",
       "779   2012/013     Gulmi                Confirmed Meningitis               627\n",
       "869   2012/013    Achham                            HIV/AIDS              1197\n",
       "908   2011/012     Jhapa                             STD/STI              2895\n",
       "962   2011/012  Dhanusha                             Leprosy               302\n",
       "1083  2011/012     Palpa                Confirmed Meningitis               303\n",
       "1169  2011/012    Achham                            HIV/AIDS               865"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "problems_df[idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>District</th>\n",
       "      <th>Communicable and infectious disease</th>\n",
       "      <th>Number of people</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>2009/010</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2010/011</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>1538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>753</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>755</th>\n",
       "      <td>2012/013</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1052</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>STD/STI</td>\n",
       "      <td>994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1053</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>HIV/AIDS</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Leprosy</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1055</th>\n",
       "      <td>2011/012</td>\n",
       "      <td>Kaski</td>\n",
       "      <td>Confirmed Meningitis</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Year District Communicable and infectious disease  Number of people\n",
       "156   2009/010    Kaski                             STD/STI               428\n",
       "157   2009/010    Kaski                            HIV/AIDS                 8\n",
       "158   2009/010    Kaski                             Leprosy                65\n",
       "159   2009/010    Kaski                Confirmed Meningitis                34\n",
       "452   2010/011    Kaski                             STD/STI               426\n",
       "453   2010/011    Kaski                            HIV/AIDS                 9\n",
       "454   2010/011    Kaski                             Leprosy                35\n",
       "455   2010/011    Kaski                Confirmed Meningitis               195\n",
       "752   2012/013    Kaski                             STD/STI              1538\n",
       "753   2012/013    Kaski                            HIV/AIDS               140\n",
       "754   2012/013    Kaski                             Leprosy                25\n",
       "755   2012/013    Kaski                Confirmed Meningitis               268\n",
       "1052  2011/012    Kaski                             STD/STI               994\n",
       "1053  2011/012    Kaski                            HIV/AIDS                71\n",
       "1054  2011/012    Kaski                             Leprosy                20\n",
       "1055  2011/012    Kaski                Confirmed Meningitis               238"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "problems_df[problems_df.District=='Kaski']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "idx = problems_df.groupby(['District','Communicable and infectious disease'], sort=False)['Number of people'].transform(max) == problems_df['Number of people']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f6846c34890>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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QiIjIFODt6qJp5y4aSspoLCujt7kl6NjwhHiSc3JIyc0hac0awmNjgo7trKlh+xe/PHB7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\ns5sPAf8DXGOttf15HtK1vgRqh6y1Nw15S0REpOj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NT3+tHiFcgOB8YLMxZnfOz0vD0zwR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\n0Dj93kv+WXAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6844b7e6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.factorplot('Year', 'Number of people', hue='Communicable and infectious disease',data=problems_df[idx], aspect=3, size=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}