Norwegian Development Funds.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import the Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.dates as mdates "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from subprocess import check_output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "funds = pd.read_csv('funds.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Agreement Number</th>\n",
       "      <th>Agreement Title</th>\n",
       "      <th>Agreement Partner</th>\n",
       "      <th>Group of Agreement Partner</th>\n",
       "      <th>Implementing Partner</th>\n",
       "      <th>Description of Agreement</th>\n",
       "      <th>Main Sector</th>\n",
       "      <th>Sub Sector</th>\n",
       "      <th>Target Area</th>\n",
       "      <th>Recipient Country</th>\n",
       "      <th>...</th>\n",
       "      <th>Policy Marker - Climate Change Mitigation</th>\n",
       "      <th>Policy Marker - Climate Change Adaptation</th>\n",
       "      <th>Policy Marker - Reproductive. maternal. newborn and child health</th>\n",
       "      <th>Extending Agency</th>\n",
       "      <th>Budget Post: Chapter</th>\n",
       "      <th>Budget Post: Post</th>\n",
       "      <th>Year</th>\n",
       "      <th>Disbursements (1000 NOK)</th>\n",
       "      <th>Disbursements (1000 $)</th>\n",
       "      <th>Unnamed: 27</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FK/4032</td>\n",
       "      <td>Fredskorpset personell exchange</td>\n",
       "      <td>Strømmestiftelsen</td>\n",
       "      <td>NGO Norwegian</td>\n",
       "      <td>Strømmestiftelsen</td>\n",
       "      <td>Exchange of personnel betwn partners in Norway...</td>\n",
       "      <td>240 - Banking and financial services</td>\n",
       "      <td>40 - Informal/semi-formal financial  intermedi...</td>\n",
       "      <td>Economic development and trade</td>\n",
       "      <td>Uganda</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Fredskorpset</td>\n",
       "      <td>160 - Sivilt samfunn og demokratiutvikling</td>\n",
       "      <td>50 - Fredskorpset</td>\n",
       "      <td>2004</td>\n",
       "      <td>28.76</td>\n",
       "      <td>4.27</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GLO-05/273-12</td>\n",
       "      <td>Primary school textbook production/Resource Ce...</td>\n",
       "      <td>Utdanningsforbundet</td>\n",
       "      <td>NGO Norwegian</td>\n",
       "      <td>PATC - Pan-African Teachers' Centre</td>\n",
       "      <td>PATC runs 1) a regional book poduction project...</td>\n",
       "      <td>160 - Other social infrastructure and services</td>\n",
       "      <td>20 - Employment policy and administrative mana...</td>\n",
       "      <td>Health and social services</td>\n",
       "      <td>Africa Regional</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Norad</td>\n",
       "      <td>160 - Sivilt samfunn og demokratiutvikling</td>\n",
       "      <td>70 - Sivilt samfunn</td>\n",
       "      <td>2009</td>\n",
       "      <td>486.00</td>\n",
       "      <td>77.41</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TAN-08/073</td>\n",
       "      <td>Africa Umoja Concert</td>\n",
       "      <td>Norsk Kulturskoleråd</td>\n",
       "      <td>Norwegian public sector</td>\n",
       "      <td>Norsk Kulturskoleråd</td>\n",
       "      <td>Financial support to Tanzanian participation a...</td>\n",
       "      <td>160 - Other social infrastructure and services</td>\n",
       "      <td>61 - Culture and recreation</td>\n",
       "      <td>Health and social services</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Ministry of Foreign Affairs</td>\n",
       "      <td>160 - Sivilt samfunn og demokratiutvikling</td>\n",
       "      <td>73 - Kultur</td>\n",
       "      <td>2008</td>\n",
       "      <td>200.00</td>\n",
       "      <td>35.04</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06-2060235</td>\n",
       "      <td>KS-Local Government Assoc in BIH</td>\n",
       "      <td>KS - Kommunesektorens organisasjon</td>\n",
       "      <td>NGO Norwegian</td>\n",
       "      <td>KS - Kommunesektorens organisasjon</td>\n",
       "      <td>Description is missing</td>\n",
       "      <td>151 - Government and civil society. general</td>\n",
       "      <td>40 - Government administration</td>\n",
       "      <td>Good governance</td>\n",
       "      <td>Bosnia-Herzegovina</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Ministry of Foreign Affairs</td>\n",
       "      <td>164 - Fred. forsoning og demokrati</td>\n",
       "      <td>71 - ODA-godkjente land på Balkan</td>\n",
       "      <td>2006</td>\n",
       "      <td>1000.00</td>\n",
       "      <td>155.89</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NGA-04/001</td>\n",
       "      <td>INTSOK kurs i brønnboring</td>\n",
       "      <td>INTSOK</td>\n",
       "      <td>NGO Norwegian</td>\n",
       "      <td>INTSOK</td>\n",
       "      <td>Kompetanseoverføring høsten 2004  Seminar i br...</td>\n",
       "      <td>322 - Mineral resources/ mining</td>\n",
       "      <td>62 - Oil and gas</td>\n",
       "      <td>Economic development and trade</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Ministry of Foreign Affairs</td>\n",
       "      <td>150 - Bistand til Afrika</td>\n",
       "      <td>78 - Regionbevilgning for Afrika</td>\n",
       "      <td>2004</td>\n",
       "      <td>360.00</td>\n",
       "      <td>53.42</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Agreement Number                                    Agreement Title  \\\n",
       "0          FK/4032                    Fredskorpset personell exchange   \n",
       "1    GLO-05/273-12  Primary school textbook production/Resource Ce...   \n",
       "2       TAN-08/073                               Africa Umoja Concert   \n",
       "3       06-2060235                   KS-Local Government Assoc in BIH   \n",
       "4       NGA-04/001                          INTSOK kurs i brønnboring   \n",
       "\n",
       "                    Agreement Partner Group of Agreement Partner  \\\n",
       "0                   Strømmestiftelsen              NGO Norwegian   \n",
       "1                 Utdanningsforbundet              NGO Norwegian   \n",
       "2                Norsk Kulturskoleråd    Norwegian public sector   \n",
       "3  KS - Kommunesektorens organisasjon              NGO Norwegian   \n",
       "4                              INTSOK              NGO Norwegian   \n",
       "\n",
       "                  Implementing Partner  \\\n",
       "0                    Strømmestiftelsen   \n",
       "1  PATC - Pan-African Teachers' Centre   \n",
       "2                 Norsk Kulturskoleråd   \n",
       "3   KS - Kommunesektorens organisasjon   \n",
       "4                               INTSOK   \n",
       "\n",
       "                            Description of Agreement  \\\n",
       "0  Exchange of personnel betwn partners in Norway...   \n",
       "1  PATC runs 1) a regional book poduction project...   \n",
       "2  Financial support to Tanzanian participation a...   \n",
       "3                             Description is missing   \n",
       "4  Kompetanseoverføring høsten 2004  Seminar i br...   \n",
       "\n",
       "                                      Main Sector  \\\n",
       "0            240 - Banking and financial services   \n",
       "1  160 - Other social infrastructure and services   \n",
       "2  160 - Other social infrastructure and services   \n",
       "3     151 - Government and civil society. general   \n",
       "4                 322 - Mineral resources/ mining   \n",
       "\n",
       "                                          Sub Sector  \\\n",
       "0  40 - Informal/semi-formal financial  intermedi...   \n",
       "1  20 - Employment policy and administrative mana...   \n",
       "2                        61 - Culture and recreation   \n",
       "3                     40 - Government administration   \n",
       "4                                   62 - Oil and gas   \n",
       "\n",
       "                      Target Area   Recipient Country     ...       \\\n",
       "0  Economic development and trade              Uganda     ...        \n",
       "1      Health and social services     Africa Regional     ...        \n",
       "2      Health and social services            Tanzania     ...        \n",
       "3                 Good governance  Bosnia-Herzegovina     ...        \n",
       "4  Economic development and trade             Nigeria     ...        \n",
       "\n",
       "  Policy Marker - Climate Change Mitigation  \\\n",
       "0                                         0   \n",
       "1                                         0   \n",
       "2                                         0   \n",
       "3                                         0   \n",
       "4                                         0   \n",
       "\n",
       "  Policy Marker - Climate Change Adaptation  \\\n",
       "0                                         0   \n",
       "1                                         0   \n",
       "2                                         0   \n",
       "3                                         0   \n",
       "4                                         0   \n",
       "\n",
       "   Policy Marker - Reproductive. maternal. newborn and child health  \\\n",
       "0                                                  0                  \n",
       "1                                                  0                  \n",
       "2                                                  0                  \n",
       "3                                                  0                  \n",
       "4                                                  0                  \n",
       "\n",
       "              Extending Agency                        Budget Post: Chapter  \\\n",
       "0                 Fredskorpset  160 - Sivilt samfunn og demokratiutvikling   \n",
       "1                        Norad  160 - Sivilt samfunn og demokratiutvikling   \n",
       "2  Ministry of Foreign Affairs  160 - Sivilt samfunn og demokratiutvikling   \n",
       "3  Ministry of Foreign Affairs          164 - Fred. forsoning og demokrati   \n",
       "4  Ministry of Foreign Affairs                    150 - Bistand til Afrika   \n",
       "\n",
       "                   Budget Post: Post  Year  Disbursements (1000 NOK)  \\\n",
       "0                  50 - Fredskorpset  2004                     28.76   \n",
       "1                70 - Sivilt samfunn  2009                    486.00   \n",
       "2                        73 - Kultur  2008                    200.00   \n",
       "3  71 - ODA-godkjente land på Balkan  2006                   1000.00   \n",
       "4   78 - Regionbevilgning for Afrika  2004                    360.00   \n",
       "\n",
       "   Disbursements (1000 $)  Unnamed: 27  \n",
       "0                    4.27          NaN  \n",
       "1                   77.41          NaN  \n",
       "2                   35.04          NaN  \n",
       "3                  155.89          NaN  \n",
       "4                   53.42          NaN  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "funds.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 94310 entries, 0 to 94309\n",
      "Data columns (total 28 columns):\n",
      "Agreement Number                                                    94310 non-null object\n",
      "Agreement Title                                                     94310 non-null object\n",
      "Agreement Partner                                                   94310 non-null object\n",
      "Group of Agreement Partner                                          94310 non-null object\n",
      "Implementing Partner                                                94307 non-null object\n",
      "Description of Agreement                                            80633 non-null object\n",
      "Main Sector                                                         94310 non-null object\n",
      "Sub Sector                                                          94310 non-null object\n",
      "Target Area                                                         94310 non-null object\n",
      "Recipient Country                                                   94310 non-null object\n",
      "Recipient Region                                                    94310 non-null object\n",
      "Type of Assistance                                                  94310 non-null object\n",
      "Policy Marker - Environment                                         94310 non-null int64\n",
      "Policy Marker - Gender Equality                                     94310 non-null int64\n",
      "Policy Marker - Good Governance and Human Rights                    94310 non-null int64\n",
      "Policy Marker - Biodiversity                                        94310 non-null int64\n",
      "Policy Marker - Desertification                                     94310 non-null int64\n",
      "Policy Marker - Trade Development                                   94310 non-null int64\n",
      "Policy Marker - Climate Change Mitigation                           94310 non-null int64\n",
      "Policy Marker - Climate Change Adaptation                           94310 non-null int64\n",
      "Policy Marker - Reproductive. maternal. newborn and child health    94310 non-null int64\n",
      "Extending Agency                                                    94309 non-null object\n",
      "Budget Post: Chapter                                                94310 non-null object\n",
      "Budget Post: Post                                                   94310 non-null object\n",
      "Year                                                                94310 non-null int64\n",
      "Disbursements (1000 NOK)                                            94310 non-null float64\n",
      "Disbursements (1000 $)                                              94310 non-null float64\n",
      "Unnamed: 27                                                         0 non-null float64\n",
      "dtypes: float64(3), int64(10), object(15)\n",
      "memory usage: 20.1+ MB\n"
     ]
    }
   ],
   "source": [
    "funds.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Checking for Null Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <th>94284</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <th>94285</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <th>94295</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>94301</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>94304</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94305</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94306</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94307</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94308</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94309</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>94310 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Agreement Number Agreement Title Agreement Partner  \\\n",
       "0                False           False             False   \n",
       "1                False           False             False   \n",
       "2                False           False             False   \n",
       "3                False           False             False   \n",
       "4                False           False             False   \n",
       "5                False           False             False   \n",
       "6                False           False             False   \n",
       "7                False           False             False   \n",
       "8                False           False             False   \n",
       "9                False           False             False   \n",
       "10               False           False             False   \n",
       "11               False           False             False   \n",
       "12               False           False             False   \n",
       "13               False           False             False   \n",
       "14               False           False             False   \n",
       "15               False           False             False   \n",
       "16               False           False             False   \n",
       "17               False           False             False   \n",
       "18               False           False             False   \n",
       "19               False           False             False   \n",
       "20               False           False             False   \n",
       "21               False           False             False   \n",
       "22               False           False             False   \n",
       "23               False           False             False   \n",
       "24               False           False             False   \n",
       "25               False           False             False   \n",
       "26               False           False             False   \n",
       "27               False           False             False   \n",
       "28               False           False             False   \n",
       "29               False           False             False   \n",
       "...                ...             ...               ...   \n",
       "94280            False           False             False   \n",
       "94281            False           False             False   \n",
       "94282            False           False             False   \n",
       "94283            False           False             False   \n",
       "94284            False           False             False   \n",
       "94285            False           False             False   \n",
       "94286            False           False             False   \n",
       "94287            False           False             False   \n",
       "94288            False           False             False   \n",
       "94289            False           False             False   \n",
       "94290            False           False             False   \n",
       "94291            False           False             False   \n",
       "94292            False           False             False   \n",
       "94293            False           False             False   \n",
       "94294            False           False             False   \n",
       "94295            False           False             False   \n",
       "94296            False           False             False   \n",
       "94297            False           False             False   \n",
       "94298            False           False             False   \n",
       "94299            False           False             False   \n",
       "94300            False           False             False   \n",
       "94301            False           False             False   \n",
       "94302            False           False             False   \n",
       "94303            False           False             False   \n",
       "94304            False           False             False   \n",
       "94305            False           False             False   \n",
       "94306            False           False             False   \n",
       "94307            False           False             False   \n",
       "94308            False           False             False   \n",
       "94309            False           False             False   \n",
       "\n",
       "      Group of Agreement Partner Implementing Partner  \\\n",
       "0                          False                False   \n",
       "1                          False                False   \n",
       "2                          False                False   \n",
       "3                          False                False   \n",
       "4                          False                False   \n",
       "5                          False                False   \n",
       "6                          False                False   \n",
       "7                          False                False   \n",
       "8                          False                False   \n",
       "9                          False                False   \n",
       "10                         False                False   \n",
       "11                         False                False   \n",
       "12                         False                False   \n",
       "13                         False                False   \n",
       "14                         False                False   \n",
       "15                         False                False   \n",
       "16                         False                False   \n",
       "17                         False                False   \n",
       "18                         False                False   \n",
       "19                         False                False   \n",
       "20                         False                False   \n",
       "21                         False                False   \n",
       "22                         False                False   \n",
       "23                         False                False   \n",
       "24                         False                False   \n",
       "25                         False                False   \n",
       "26                         False                False   \n",
       "27                         False                False   \n",
       "28                         False                False   \n",
       "29                         False                False   \n",
       "...                          ...                  ...   \n",
       "94280                      False                False   \n",
       "94281                      False                False   \n",
       "94282                      False                False   \n",
       "94283                      False                False   \n",
       "94284                      False                False   \n",
       "94285                      False                False   \n",
       "94286                      False                False   \n",
       "94287                      False                False   \n",
       "94288                      False                False   \n",
       "94289                      False                False   \n",
       "94290                      False                False   \n",
       "94291                      False                False   \n",
       "94292                      False                False   \n",
       "94293                      False                False   \n",
       "94294                      False                False   \n",
       "94295                      False                False   \n",
       "94296                      False                False   \n",
       "94297                      False                False   \n",
       "94298                      False                False   \n",
       "94299                      False                False   \n",
       "94300                      False                False   \n",
       "94301                      False                False   \n",
       "94302                      False                False   \n",
       "94303                      False                False   \n",
       "94304                      False                False   \n",
       "94305                      False                False   \n",
       "94306                      False                False   \n",
       "94307                      False                False   \n",
       "94308                      False                False   \n",
       "94309                      False                False   \n",
       "\n",
       "      Description of Agreement Main Sector Sub Sector Target Area  \\\n",
       "0                        False       False      False       False   \n",
       "1                        False       False      False       False   \n",
       "2                        False       False      False       False   \n",
       "3                        False       False      False       False   \n",
       "4                        False       False      False       False   \n",
       "5                        False       False      False       False   \n",
       "6                        False       False      False       False   \n",
       "7                        False       False      False       False   \n",
       "8                         True       False      False       False   \n",
       "9                        False       False      False       False   \n",
       "10                       False       False      False       False   \n",
       "11                       False       False      False       False   \n",
       "12                       False       False      False       False   \n",
       "13                       False       False      False       False   \n",
       "14                        True       False      False       False   \n",
       "15                        True       False      False       False   \n",
       "16                       False       False      False       False   \n",
       "17                       False       False      False       False   \n",
       "18                        True       False      False       False   \n",
       "19                       False       False      False       False   \n",
       "20                       False       False      False       False   \n",
       "21                       False       False      False       False   \n",
       "22                       False       False      False       False   \n",
       "23                       False       False      False       False   \n",
       "24                       False       False      False       False   \n",
       "25                        True       False      False       False   \n",
       "26                       False       False      False       False   \n",
       "27                       False       False      False       False   \n",
       "28                       False       False      False       False   \n",
       "29                       False       False      False       False   \n",
       "...                        ...         ...        ...         ...   \n",
       "94280                     True       False      False       False   \n",
       "94281                    False       False      False       False   \n",
       "94282                    False       False      False       False   \n",
       "94283                    False       False      False       False   \n",
       "94284                     True       False      False       False   \n",
       "94285                    False       False      False       False   \n",
       "94286                    False       False      False       False   \n",
       "94287                    False       False      False       False   \n",
       "94288                    False       False      False       False   \n",
       "94289                    False       False      False       False   \n",
       "94290                    False       False      False       False   \n",
       "94291                    False       False      False       False   \n",
       "94292                    False       False      False       False   \n",
       "94293                    False       False      False       False   \n",
       "94294                    False       False      False       False   \n",
       "94295                    False       False      False       False   \n",
       "94296                    False       False      False       False   \n",
       "94297                    False       False      False       False   \n",
       "94298                    False       False      False       False   \n",
       "94299                    False       False      False       False   \n",
       "94300                    False       False      False       False   \n",
       "94301                    False       False      False       False   \n",
       "94302                    False       False      False       False   \n",
       "94303                    False       False      False       False   \n",
       "94304                    False       False      False       False   \n",
       "94305                    False       False      False       False   \n",
       "94306                    False       False      False       False   \n",
       "94307                    False       False      False       False   \n",
       "94308                    False       False      False       False   \n",
       "94309                    False       False      False       False   \n",
       "\n",
       "      Recipient Country     ...     Policy Marker - Climate Change Mitigation  \\\n",
       "0                 False     ...                                         False   \n",
       "1                 False     ...                                         False   \n",
       "2                 False     ...                                         False   \n",
       "3                 False     ...                                         False   \n",
       "4                 False     ...                                         False   \n",
       "5                 False     ...                                         False   \n",
       "6                 False     ...                                         False   \n",
       "7                 False     ...                                         False   \n",
       "8                 False     ...                                         False   \n",
       "9                 False     ...                                         False   \n",
       "10                False     ...                                         False   \n",
       "11                False     ...                                         False   \n",
       "12                False     ...                                         False   \n",
       "13                False     ...                                         False   \n",
       "14                False     ...                                         False   \n",
       "15                False     ...                                         False   \n",
       "16                False     ...                                         False   \n",
       "17                False     ...                                         False   \n",
       "18                False     ...                                         False   \n",
       "19                False     ...                                         False   \n",
       "20                False     ...                                         False   \n",
       "21                False     ...                                         False   \n",
       "22                False     ...                                         False   \n",
       "23                False     ...                                         False   \n",
       "24                False     ...                                         False   \n",
       "25                False     ...                                         False   \n",
       "26                False     ...                                         False   \n",
       "27                False     ...                                         False   \n",
       "28                False     ...                                         False   \n",
       "29                False     ...                                         False   \n",
       "...                 ...     ...                                           ...   \n",
       "94280             False     ...                                         False   \n",
       "94281             False     ...                                         False   \n",
       "94282             False     ...                                         False   \n",
       "94283             False     ...                                         False   \n",
       "94284             False     ...                                         False   \n",
       "94285             False     ...                                         False   \n",
       "94286             False     ...                                         False   \n",
       "94287             False     ...                                         False   \n",
       "94288             False     ...                                         False   \n",
       "94289             False     ...                                         False   \n",
       "94290             False     ...                                         False   \n",
       "94291             False     ...                                         False   \n",
       "94292             False     ...                                         False   \n",
       "94293             False     ...                                         False   \n",
       "94294             False     ...                                         False   \n",
       "94295             False     ...                                         False   \n",
       "94296             False     ...                                         False   \n",
       "94297             False     ...                                         False   \n",
       "94298             False     ...                                         False   \n",
       "94299             False     ...                                         False   \n",
       "94300             False     ...                                         False   \n",
       "94301             False     ...                                         False   \n",
       "94302             False     ...                                         False   \n",
       "94303             False     ...                                         False   \n",
       "94304             False     ...                                         False   \n",
       "94305             False     ...                                         False   \n",
       "94306             False     ...                                         False   \n",
       "94307             False     ...                                         False   \n",
       "94308             False     ...                                         False   \n",
       "94309             False     ...                                         False   \n",
       "\n",
       "      Policy Marker - Climate Change Adaptation  \\\n",
       "0                                         False   \n",
       "1                                         False   \n",
       "2                                         False   \n",
       "3                                         False   \n",
       "4                                         False   \n",
       "5                                         False   \n",
       "6                                         False   \n",
       "7                                         False   \n",
       "8                                         False   \n",
       "9                                         False   \n",
       "10                                        False   \n",
       "11                                        False   \n",
       "12                                        False   \n",
       "13                                        False   \n",
       "14                                        False   \n",
       "15                                        False   \n",
       "16                                        False   \n",
       "17                                        False   \n",
       "18                                        False   \n",
       "19                                        False   \n",
       "20                                        False   \n",
       "21                                        False   \n",
       "22                                        False   \n",
       "23                                        False   \n",
       "24                                        False   \n",
       "25                                        False   \n",
       "26                                        False   \n",
       "27                                        False   \n",
       "28                                        False   \n",
       "29                                        False   \n",
       "...                                         ...   \n",
       "94280                                     False   \n",
       "94281                                     False   \n",
       "94282                                     False   \n",
       "94283                                     False   \n",
       "94284                                     False   \n",
       "94285                                     False   \n",
       "94286                                     False   \n",
       "94287                                     False   \n",
       "94288                                     False   \n",
       "94289                                     False   \n",
       "94290                                     False   \n",
       "94291                                     False   \n",
       "94292                                     False   \n",
       "94293                                     False   \n",
       "94294                                     False   \n",
       "94295                                     False   \n",
       "94296                                     False   \n",
       "94297                                     False   \n",
       "94298                                     False   \n",
       "94299                                     False   \n",
       "94300                                     False   \n",
       "94301                                     False   \n",
       "94302                                     False   \n",
       "94303                                     False   \n",
       "94304                                     False   \n",
       "94305                                     False   \n",
       "94306                                     False   \n",
       "94307                                     False   \n",
       "94308                                     False   \n",
       "94309                                     False   \n",
       "\n",
       "      Policy Marker - Reproductive. maternal. newborn and child health  \\\n",
       "0                                                  False                 \n",
       "1                                                  False                 \n",
       "2                                                  False                 \n",
       "3                                                  False                 \n",
       "4                                                  False                 \n",
       "5                                                  False                 \n",
       "6                                                  False                 \n",
       "7                                                  False                 \n",
       "8                                                  False                 \n",
       "9                                                  False                 \n",
       "10                                                 False                 \n",
       "11                                                 False                 \n",
       "12                                                 False                 \n",
       "13                                                 False                 \n",
       "14                                                 False                 \n",
       "15                                                 False                 \n",
       "16                                                 False                 \n",
       "17                                                 False                 \n",
       "18                                                 False                 \n",
       "19                                                 False                 \n",
       "20                                                 False                 \n",
       "21                                                 False                 \n",
       "22                                                 False                 \n",
       "23                                                 False                 \n",
       "24                                                 False                 \n",
       "25                                                 False                 \n",
       "26                                                 False                 \n",
       "27                                                 False                 \n",
       "28                                                 False                 \n",
       "29                                                 False                 \n",
       "...                                                  ...                 \n",
       "94280                                              False                 \n",
       "94281                                              False                 \n",
       "94282                                              False                 \n",
       "94283                                              False                 \n",
       "94284                                              False                 \n",
       "94285                                              False                 \n",
       "94286                                              False                 \n",
       "94287                                              False                 \n",
       "94288                                              False                 \n",
       "94289                                              False                 \n",
       "94290                                              False                 \n",
       "94291                                              False                 \n",
       "94292                                              False                 \n",
       "94293                                              False                 \n",
       "94294                                              False                 \n",
       "94295                                              False                 \n",
       "94296                                              False                 \n",
       "94297                                              False                 \n",
       "94298                                              False                 \n",
       "94299                                              False                 \n",
       "94300                                              False                 \n",
       "94301                                              False                 \n",
       "94302                                              False                 \n",
       "94303                                              False                 \n",
       "94304                                              False                 \n",
       "94305                                              False                 \n",
       "94306                                              False                 \n",
       "94307                                              False                 \n",
       "94308                                              False                 \n",
       "94309                                              False                 \n",
       "\n",
       "      Extending Agency Budget Post: Chapter Budget Post: Post   Year  \\\n",
       "0                False                False             False  False   \n",
       "1                False                False             False  False   \n",
       "2                False                False             False  False   \n",
       "3                False                False             False  False   \n",
       "4                False                False             False  False   \n",
       "5                False                False             False  False   \n",
       "6                False                False             False  False   \n",
       "7                False                False             False  False   \n",
       "8                False                False             False  False   \n",
       "9                False                False             False  False   \n",
       "10               False                False             False  False   \n",
       "11               False                False             False  False   \n",
       "12               False                False             False  False   \n",
       "13               False                False             False  False   \n",
       "14               False                False             False  False   \n",
       "15               False                False             False  False   \n",
       "16               False                False             False  False   \n",
       "17               False                False             False  False   \n",
       "18               False                False             False  False   \n",
       "19               False                False             False  False   \n",
       "20               False                False             False  False   \n",
       "21               False                False             False  False   \n",
       "22               False                False             False  False   \n",
       "23               False                False             False  False   \n",
       "24               False                False             False  False   \n",
       "25               False                False             False  False   \n",
       "26               False                False             False  False   \n",
       "27               False                False             False  False   \n",
       "28               False                False             False  False   \n",
       "29               False                False             False  False   \n",
       "...                ...                  ...               ...    ...   \n",
       "94280            False                False             False  False   \n",
       "94281            False                False             False  False   \n",
       "94282            False                False             False  False   \n",
       "94283            False                False             False  False   \n",
       "94284            False                False             False  False   \n",
       "94285            False                False             False  False   \n",
       "94286            False                False             False  False   \n",
       "94287            False                False             False  False   \n",
       "94288            False                False             False  False   \n",
       "94289            False                False             False  False   \n",
       "94290            False                False             False  False   \n",
       "94291            False                False             False  False   \n",
       "94292            False                False             False  False   \n",
       "94293            False                False             False  False   \n",
       "94294            False                False             False  False   \n",
       "94295            False                False             False  False   \n",
       "94296            False                False             False  False   \n",
       "94297            False                False             False  False   \n",
       "94298            False                False             False  False   \n",
       "94299            False                False             False  False   \n",
       "94300            False                False             False  False   \n",
       "94301            False                False             False  False   \n",
       "94302            False                False             False  False   \n",
       "94303            False                False             False  False   \n",
       "94304            False                False             False  False   \n",
       "94305            False                False             False  False   \n",
       "94306            False                False             False  False   \n",
       "94307            False                False             False  False   \n",
       "94308            False                False             False  False   \n",
       "94309            False                False             False  False   \n",
       "\n",
       "      Disbursements (1000 NOK) Disbursements (1000 $) Unnamed: 27  \n",
       "0                        False                  False        True  \n",
       "1                        False                  False        True  \n",
       "2                        False                  False        True  \n",
       "3                        False                  False        True  \n",
       "4                        False                  False        True  \n",
       "5                        False                  False        True  \n",
       "6                        False                  False        True  \n",
       "7                        False                  False        True  \n",
       "8                        False                  False        True  \n",
       "9                        False                  False        True  \n",
       "10                       False                  False        True  \n",
       "11                       False                  False        True  \n",
       "12                       False                  False        True  \n",
       "13                       False                  False        True  \n",
       "14                       False                  False        True  \n",
       "15                       False                  False        True  \n",
       "16                       False                  False        True  \n",
       "17                       False                  False        True  \n",
       "18                       False                  False        True  \n",
       "19                       False                  False        True  \n",
       "20                       False                  False        True  \n",
       "21                       False                  False        True  \n",
       "22                       False                  False        True  \n",
       "23                       False                  False        True  \n",
       "24                       False                  False        True  \n",
       "25                       False                  False        True  \n",
       "26                       False                  False        True  \n",
       "27                       False                  False        True  \n",
       "28                       False                  False        True  \n",
       "29                       False                  False        True  \n",
       "...                        ...                    ...         ...  \n",
       "94280                    False                  False        True  \n",
       "94281                    False                  False        True  \n",
       "94282                    False                  False        True  \n",
       "94283                    False                  False        True  \n",
       "94284                    False                  False        True  \n",
       "94285                    False                  False        True  \n",
       "94286                    False                  False        True  \n",
       "94287                    False                  False        True  \n",
       "94288                    False                  False        True  \n",
       "94289                    False                  False        True  \n",
       "94290                    False                  False        True  \n",
       "94291                    False                  False        True  \n",
       "94292                    False                  False        True  \n",
       "94293                    False                  False        True  \n",
       "94294                    False                  False        True  \n",
       "94295                    False                  False        True  \n",
       "94296                    False                  False        True  \n",
       "94297                    False                  False        True  \n",
       "94298                    False                  False        True  \n",
       "94299                    False                  False        True  \n",
       "94300                    False                  False        True  \n",
       "94301                    False                  False        True  \n",
       "94302                    False                  False        True  \n",
       "94303                    False                  False        True  \n",
       "94304                    False                  False        True  \n",
       "94305                    False                  False        True  \n",
       "94306                    False                  False        True  \n",
       "94307                    False                  False        True  \n",
       "94308                    False                  False        True  \n",
       "94309                    False                  False        True  \n",
       "\n",
       "[94310 rows x 28 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "funds.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x162430254a8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MHDkSFStWfO94vfeeGjVqICYmBgUKFEDlypW1sZ06dZJ6/SVKlMD9+/dx//597XMiAdPO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x16243025e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(funds.isnull(),yticklabels=False,cbar=False,cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "funds.drop('Unnamed: 27',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x16243056c88>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rVi0kJCSgUKFCqFKlijb2k08+kf45SpUqhZs3b+LmzZva90QCppOT02tvWuvXrw9vb2+c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\nAABpoDABAEgDhQkAQBr+A9irHEqcj2GQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x16243330668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(funds.isnull(),yticklabels=False,cbar=False,cmap='viridis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Checking Back on the Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 94310 entries, 0 to 94309\n",
      "Data columns (total 27 columns):\n",
      "Agreement Number                                                    94310 non-null object\n",
      "Agreement Title                                                     94310 non-null object\n",
      "Agreement Partner                                                   94310 non-null object\n",
      "Group of Agreement Partner                                          94310 non-null object\n",
      "Implementing Partner                                                94307 non-null object\n",
      "Description of Agreement                                            80633 non-null object\n",
      "Main Sector                                                         94310 non-null object\n",
      "Sub Sector                                                          94310 non-null object\n",
      "Target Area                                                         94310 non-null object\n",
      "Recipient Country                                                   94310 non-null object\n",
      "Recipient Region                                                    94310 non-null object\n",
      "Type of Assistance                                                  94310 non-null object\n",
      "Policy Marker - Environment                                         94310 non-null int64\n",
      "Policy Marker - Gender Equality                                     94310 non-null int64\n",
      "Policy Marker - Good Governance and Human Rights                    94310 non-null int64\n",
      "Policy Marker - Biodiversity                                        94310 non-null int64\n",
      "Policy Marker - Desertification                                     94310 non-null int64\n",
      "Policy Marker - Trade Development                                   94310 non-null int64\n",
      "Policy Marker - Climate Change Mitigation                           94310 non-null int64\n",
      "Policy Marker - Climate Change Adaptation                           94310 non-null int64\n",
      "Policy Marker - Reproductive. maternal. newborn and child health    94310 non-null int64\n",
      "Extending Agency                                                    94309 non-null object\n",
      "Budget Post: Chapter                                                94310 non-null object\n",
      "Budget Post: Post                                                   94310 non-null object\n",
      "Year                                                                94310 non-null int64\n",
      "Disbursements (1000 NOK)                                            94310 non-null float64\n",
      "Disbursements (1000 $)                                              94310 non-null float64\n",
      "dtypes: float64(2), int64(10), object(15)\n",
      "memory usage: 19.4+ MB\n"
     ]
    }
   ],
   "source": [
    "funds.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1624318c048>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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aT5/elqlTh/59Ukvr17eN2GMN1047tWXGjKH/2Yy180nG3jm9eD4bR2agYar+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\ngAAAAADgJGgAAQAAAMBJ/D+77vKpR3nyCwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x162431b5f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.barplot(x='Year',y='Disbursements (1000 $)',data=funds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x16243213c88>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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34+NHXNoKTJ48OSeddFI6deqUxo0bJ0lOPPHE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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x162432ae1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,15))\n",
    "sns.barplot(x='Recipient Region',y='Disbursements (1000 $)',data=funds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x162459b8d30>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x162459b8e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,15))\n",
    "sns.barplot(x='Target Area',y='Disbursements (1000 $)',data=funds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x16247271208>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Vr1499e7dW19++eVV9avI60r9TaNGjXT48GF5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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x162472276d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,15))\n",
    "sns.barplot(x='Target Area',y='Disbursements (1000 NOK)',data=funds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x16247291d30>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LFRVEUIoaqy9iwAU1xqBGxQRRY0SiuCAgMoiyzPz+sE6kQNB4YFje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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x16247291630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,15))\n",
    "sns.barplot(x='Type of Assistance',y='Disbursements (1000 $)',data=funds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1624bcc4e10>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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TTz+dWq2Www47LO3tRW4PADDurFlzexLBEQCA1lOkCNZqtdx+++2555579npL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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1624bc8e550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,15))\n",
    "sns.boxplot(x='Main Sector',y='Disbursements (1000 $)',data=funds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}