{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fetching data from GHO\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:33:08.018430Z",
     "start_time": "2021-05-11T16:33:06.120279Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "from ghoclient import GHOSession, index\n",
    "import pandas as pd\n",
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:33:09.276756Z",
     "start_time": "2021-05-11T16:33:08.900843Z"
    }
   },
   "outputs": [],
   "source": [
    "GC = GHOSession()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Listing indicator codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:33:53.674405Z",
     "start_time": "2021-05-11T16:33:52.257465Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of available indicators: 3466\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>@Label</th>\n",
       "      <th>@DisplaySequence</th>\n",
       "      <th>@URL</th>\n",
       "      <th>Attr</th>\n",
       "      <th>Display</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MDG_0000000001</td>\n",
       "      <td>2</td>\n",
       "      <td>https://www.who.int/data/gho/indicator-metadat...</td>\n",
       "      <td>[{'@Category': 'DISPLAY_FR', 'Value': {'Displa...</td>\n",
       "      <td>Infant mortality rate (probability of dying be...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MDG_0000000003</td>\n",
       "      <td>5</td>\n",
       "      <td>https://www.who.int/data/gho/indicator-metadat...</td>\n",
       "      <td>[{'@Category': 'DEFINITION_XML', 'Value': {'Di...</td>\n",
       "      <td>Adolescent birth rate (per 1000 women aged 15-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MDG_0000000005</td>\n",
       "      <td>10</td>\n",
       "      <td>https://www.who.int/data/gho/indicator-metadat...</td>\n",
       "      <td>[{'@Category': 'CATEGORY', 'Value': {'Display'...</td>\n",
       "      <td>Contraceptive prevalence (%)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MDG_0000000006</td>\n",
       "      <td>5</td>\n",
       "      <td>https://www.who.int/data/gho/indicator-metadat...</td>\n",
       "      <td>[{'@Category': 'CATEGORY', 'Value': {'Display'...</td>\n",
       "      <td>Unmet need for family planning (%)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MDG_0000000007</td>\n",
       "      <td>5</td>\n",
       "      <td>https://www.who.int/data/gho/indicator-metadat...</td>\n",
       "      <td>[{'@Category': 'DISPLAY_FR', 'Value': {'Displa...</td>\n",
       "      <td>Under-five mortality rate (probability of dyin...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           @Label @DisplaySequence  \\\n",
       "0  MDG_0000000001                2   \n",
       "1  MDG_0000000003                5   \n",
       "2  MDG_0000000005               10   \n",
       "3  MDG_0000000006                5   \n",
       "4  MDG_0000000007                5   \n",
       "\n",
       "                                                @URL  \\\n",
       "0  https://www.who.int/data/gho/indicator-metadat...   \n",
       "1  https://www.who.int/data/gho/indicator-metadat...   \n",
       "2  https://www.who.int/data/gho/indicator-metadat...   \n",
       "3  https://www.who.int/data/gho/indicator-metadat...   \n",
       "4  https://www.who.int/data/gho/indicator-metadat...   \n",
       "\n",
       "                                                Attr  \\\n",
       "0  [{'@Category': 'DISPLAY_FR', 'Value': {'Displa...   \n",
       "1  [{'@Category': 'DEFINITION_XML', 'Value': {'Di...   \n",
       "2  [{'@Category': 'CATEGORY', 'Value': {'Display'...   \n",
       "3  [{'@Category': 'CATEGORY', 'Value': {'Display'...   \n",
       "4  [{'@Category': 'DISPLAY_FR', 'Value': {'Displa...   \n",
       "\n",
       "                                             Display  \n",
       "0  Infant mortality rate (probability of dying be...  \n",
       "1  Adolescent birth rate (per 1000 women aged 15-...  \n",
       "2                       Contraceptive prevalence (%)  \n",
       "3                 Unmet need for family planning (%)  \n",
       "4  Under-five mortality rate (probability of dyin...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "codes = GC.get_data_codes(format='dataframe')\n",
    "print(f\"Number of available indicators: {len(codes)}\")\n",
    "codes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Serching by keyword\n",
    "Since the codes are not exactly mnemonic, we can search for all codes about tuberculosis, for example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:38:32.695928Z",
     "start_time": "2021-05-11T16:38:32.675866Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>code</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TB_1</td>\n",
       "      <td>Tuberculosis treatment coverage</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>UHC_TB_DT</td>\n",
       "      <td>Tuberculosis detection and treatment</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WHS3_522</td>\n",
       "      <td>Number of reported cases of tuberculosis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TB_e_prev_num</td>\n",
       "      <td>Number of prevalent tuberculosis cases</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TB_e_inc_num</td>\n",
       "      <td>Number of incident tuberculosis cases</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>TB_tot_newrel</td>\n",
       "      <td>Tuberculosis - new and relapse cases</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>TB_newinc</td>\n",
       "      <td>Tuberculosis - new and relapse cases</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>TB_c_newinc</td>\n",
       "      <td>Tuberculosis - new and relapse cases</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>TB_effective_treatment_coverage</td>\n",
       "      <td>Tuberculosis effective treatment coverage (%)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>MDG_0000000022</td>\n",
       "      <td>Tuberculosis detection rate under DOTS (%)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>MDG_0000000024</td>\n",
       "      <td>Tuberculosis treatment success under DOTS (%)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>WHS3_54</td>\n",
       "      <td>Number of reported cases of tuberculosis (DOTS)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>MDG_0000000023</td>\n",
       "      <td>Prevalence of tuberculosis (per 100 000 popula...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>MDG_0000000030</td>\n",
       "      <td>Smear-positive tuberculosis case-detection rat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>MDG_0000000031</td>\n",
       "      <td>Smear-positive tuberculosis treatment-success ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>TB_e_mort_exc_tbhiv_num</td>\n",
       "      <td>Number of deaths due to tuberculosis, excludin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>TB_8_c_cdr</td>\n",
       "      <td>Case detection rate for all forms of tuberculosis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>TB_e_inc_tbhiv_num</td>\n",
       "      <td>Number of incident tuberculosis cases,  (HIV-p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>TB_e_inc_num_014</td>\n",
       "      <td>Number of incident tuberculosis cases in child...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>Incidence of tuberculosis (per 100 000 populat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>TB_e_inc_tbhiv_100k</td>\n",
       "      <td>Incidence of tuberculosis (per 100 000 populat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>TB_c_lab_cul_5m</td>\n",
       "      <td>Laboratories providing tuberculosis diagnostic...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>TB_c_new_snep_tsr</td>\n",
       "      <td>Treatment success rate for new pulmonary smear...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>MDG_0000000017</td>\n",
       "      <td>Deaths due to tuberculosis among HIV-negative ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>MDG_0000000018</td>\n",
       "      <td>Deaths due to tuberculosis among HIV-positive ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>TB_c_lab_sm_100k</td>\n",
       "      <td>Laboratories providing tuberculosis diagnostic...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               code  \\\n",
       "0                              TB_1   \n",
       "1                         UHC_TB_DT   \n",
       "2                          WHS3_522   \n",
       "3                     TB_e_prev_num   \n",
       "4                      TB_e_inc_num   \n",
       "5                     TB_tot_newrel   \n",
       "6                         TB_newinc   \n",
       "7                       TB_c_newinc   \n",
       "8   TB_effective_treatment_coverage   \n",
       "9                    MDG_0000000022   \n",
       "10                   MDG_0000000024   \n",
       "11                          WHS3_54   \n",
       "12                   MDG_0000000023   \n",
       "13                   MDG_0000000030   \n",
       "14                   MDG_0000000031   \n",
       "15          TB_e_mort_exc_tbhiv_num   \n",
       "16                       TB_8_c_cdr   \n",
       "17               TB_e_inc_tbhiv_num   \n",
       "18                 TB_e_inc_num_014   \n",
       "19                   MDG_0000000020   \n",
       "20              TB_e_inc_tbhiv_100k   \n",
       "21                  TB_c_lab_cul_5m   \n",
       "22                TB_c_new_snep_tsr   \n",
       "23                   MDG_0000000017   \n",
       "24                   MDG_0000000018   \n",
       "25                 TB_c_lab_sm_100k   \n",
       "\n",
       "                                          description  \n",
       "0                     Tuberculosis treatment coverage  \n",
       "1                Tuberculosis detection and treatment  \n",
       "2            Number of reported cases of tuberculosis  \n",
       "3              Number of prevalent tuberculosis cases  \n",
       "4               Number of incident tuberculosis cases  \n",
       "5                Tuberculosis - new and relapse cases  \n",
       "6                Tuberculosis - new and relapse cases  \n",
       "7                Tuberculosis - new and relapse cases  \n",
       "8       Tuberculosis effective treatment coverage (%)  \n",
       "9          Tuberculosis detection rate under DOTS (%)  \n",
       "10      Tuberculosis treatment success under DOTS (%)  \n",
       "11    Number of reported cases of tuberculosis (DOTS)  \n",
       "12  Prevalence of tuberculosis (per 100 000 popula...  \n",
       "13  Smear-positive tuberculosis case-detection rat...  \n",
       "14  Smear-positive tuberculosis treatment-success ...  \n",
       "15  Number of deaths due to tuberculosis, excludin...  \n",
       "16  Case detection rate for all forms of tuberculosis  \n",
       "17  Number of incident tuberculosis cases,  (HIV-p...  \n",
       "18  Number of incident tuberculosis cases in child...  \n",
       "19  Incidence of tuberculosis (per 100 000 populat...  \n",
       "20  Incidence of tuberculosis (per 100 000 populat...  \n",
       "21  Laboratories providing tuberculosis diagnostic...  \n",
       "22  Treatment success rate for new pulmonary smear...  \n",
       "23  Deaths due to tuberculosis among HIV-negative ...  \n",
       "24  Deaths due to tuberculosis among HIV-positive ...  \n",
       "25  Laboratories providing tuberculosis diagnostic...  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index.build_index(codes)\n",
    "results = index.search('tuberculosis')\n",
    "results = pd.DataFrame(results)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at the \"Incidence of tuberculosis (per 100 000 population per year)\": `MDG_0000000020`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:37:33.102083Z",
     "start_time": "2021-05-11T16:37:22.543391Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GHO</th>\n",
       "      <th>PUBLISHSTATE</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>REGION</th>\n",
       "      <th>WORLDBANKINCOMEGROUP</th>\n",
       "      <th>COUNTRY</th>\n",
       "      <th>Display Value</th>\n",
       "      <th>Numeric</th>\n",
       "      <th>Low</th>\n",
       "      <th>High</th>\n",
       "      <th>Comments</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2006</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>356 [312-404]</td>\n",
       "      <td>356.0</td>\n",
       "      <td>312.0</td>\n",
       "      <td>404.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2013</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>291 [258-326]</td>\n",
       "      <td>291.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2015</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270 [240-302]</td>\n",
       "      <td>270.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2004</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AGO</td>\n",
       "      <td>350 [227-500]</td>\n",
       "      <td>350.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2013</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AGO</td>\n",
       "      <td>376 [243-537]</td>\n",
       "      <td>376.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>537.0</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4056</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2018</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UGA</td>\n",
       "      <td>200 [118-304]</td>\n",
       "      <td>200.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4073</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2013</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ZAF</td>\n",
       "      <td>1110 [770-1500]</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4074</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2016</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ZAF</td>\n",
       "      <td>805 [561-1090]</td>\n",
       "      <td>805.0</td>\n",
       "      <td>561.0</td>\n",
       "      <td>1090.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4075</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2013</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>437 [283-625]</td>\n",
       "      <td>437.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>625.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4076</th>\n",
       "      <td>MDG_0000000020</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2010</td>\n",
       "      <td>AFR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>416 [324-518]</td>\n",
       "      <td>416.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>518.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>949 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 GHO PUBLISHSTATE  YEAR REGION WORLDBANKINCOMEGROUP COUNTRY  \\\n",
       "15    MDG_0000000020    PUBLISHED  2006    AFR                  NaN     NaN   \n",
       "16    MDG_0000000020    PUBLISHED  2013    AFR                  NaN     NaN   \n",
       "17    MDG_0000000020    PUBLISHED  2015    AFR                  NaN     NaN   \n",
       "40    MDG_0000000020    PUBLISHED  2004    AFR                  NaN     AGO   \n",
       "41    MDG_0000000020    PUBLISHED  2013    AFR                  NaN     AGO   \n",
       "...              ...          ...   ...    ...                  ...     ...   \n",
       "4056  MDG_0000000020    PUBLISHED  2018    AFR                  NaN     UGA   \n",
       "4073  MDG_0000000020    PUBLISHED  2013    AFR                  NaN     ZAF   \n",
       "4074  MDG_0000000020    PUBLISHED  2016    AFR                  NaN     ZAF   \n",
       "4075  MDG_0000000020    PUBLISHED  2013    AFR                  NaN     ZMB   \n",
       "4076  MDG_0000000020    PUBLISHED  2010    AFR                  NaN     ZWE   \n",
       "\n",
       "        Display Value  Numeric    Low    High  Comments  \n",
       "15      356 [312-404]    356.0  312.0   404.0       NaN  \n",
       "16      291 [258-326]    291.0  258.0   326.0       NaN  \n",
       "17      270 [240-302]    270.0  240.0   302.0       NaN  \n",
       "40      350 [227-500]    350.0  227.0   500.0       NaN  \n",
       "41      376 [243-537]    376.0  243.0   537.0       NaN  \n",
       "...               ...      ...    ...     ...       ...  \n",
       "4056    200 [118-304]    200.0  118.0   304.0       NaN  \n",
       "4073  1110 [770-1500]   1110.0  770.0  1500.0       NaN  \n",
       "4074   805 [561-1090]    805.0  561.0  1090.0       NaN  \n",
       "4075    437 [283-625]    437.0  283.0   625.0       NaN  \n",
       "4076    416 [324-518]    416.0  324.0   518.0       NaN  \n",
       "\n",
       "[949 rows x 11 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = GC.fetch_data_from_codes(code='MDG_0000000020')\n",
    "data = data[(data.REGION=='AFR')]\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-30T17:56:26.365292Z",
     "start_time": "2020-06-30T17:56:26.335785Z"
    },
    "scrolled": false
   },
   "source": [
    "Now let's find indicators related to water"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:39:34.876725Z",
     "start_time": "2021-05-11T16:39:34.853713Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>code</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WAS_0000000001</td>\n",
       "      <td>Access to improved drinking water sources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EQ_HANDWASHING</td>\n",
       "      <td>Households with soap and water at a handwashin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>WSH_10_WAT</td>\n",
       "      <td>Number of diarrhoea deaths from inadequate water</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WSH_20_WAT</td>\n",
       "      <td>Attributable fraction of diarrhoea to inadequa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>WSH_30_WAT</td>\n",
       "      <td>Number of diarrhoea DALYs from inadequate water</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RADON_Q405</td>\n",
       "      <td>Radon in national drinking-water regulations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>WHS5_122</td>\n",
       "      <td>Population using improved drinking-water sourc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>WSH_5</td>\n",
       "      <td>Water, sanitation and hygiene attributable DAL...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>EQ_WATER</td>\n",
       "      <td>Population using improved drinking-water sourc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>EQ_WATERIMPROVED</td>\n",
       "      <td>Households using an improved drinking-water so...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>EQ_WATERPIPED</td>\n",
       "      <td>Households using a piped drinking-water source...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>WSH_09</td>\n",
       "      <td>Water, sanitation and hygiene - population att...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>WSH_WATER_SAFELY_MANAGED</td>\n",
       "      <td>Population using safely managed drinking-water...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>Population using at least basic drinking-water...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>WSH_10</td>\n",
       "      <td>Number of diarrhoea deaths from inadequate wat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>WSH_40_WAT</td>\n",
       "      <td>Diarrhoea deaths from inadequate water in chil...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>WSH_50_WAT</td>\n",
       "      <td>Diarrhoea DALYs from inadequate water in child...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>WSH_20</td>\n",
       "      <td>Attributable fraction of diarrhoea to inadequa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>WSH_30</td>\n",
       "      <td>Number of diarrhoea DALYs from inadequate wate...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NLIS_NU_CA_017</td>\n",
       "      <td>NLIS: Population using improved drinking-water...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>EQ_WATERPREMISES</td>\n",
       "      <td>Households using a piped onto premises drinkin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>WSH_2</td>\n",
       "      <td>Water, sanitation and hygiene attributable dea...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>WSH_3</td>\n",
       "      <td>Water, sanitation and hygiene attributable dea...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>WSH_6</td>\n",
       "      <td>Water, sanitation and hygiene attributable DAL...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>WSH_7</td>\n",
       "      <td>Water, sanitation and hygiene attributable DAL...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>WSH_40</td>\n",
       "      <td>Diarrhoea deaths from inadequate water, sanita...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>WSH_50</td>\n",
       "      <td>Diarrhoea DALYs from inadequate water, sanitat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>WSH_4</td>\n",
       "      <td>Water, sanitation and hygiene  attributable de...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>WSH_8</td>\n",
       "      <td>Water, sanitation and hygiene  attributable DA...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>SDGODAWS</td>\n",
       "      <td>Amount of water- and sanitation-related offici...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        code  \\\n",
       "0             WAS_0000000001   \n",
       "1             EQ_HANDWASHING   \n",
       "2                 WSH_10_WAT   \n",
       "3                 WSH_20_WAT   \n",
       "4                 WSH_30_WAT   \n",
       "5                 RADON_Q405   \n",
       "6                   WHS5_122   \n",
       "7                      WSH_5   \n",
       "8                   EQ_WATER   \n",
       "9           EQ_WATERIMPROVED   \n",
       "10             EQ_WATERPIPED   \n",
       "11                    WSH_09   \n",
       "12  WSH_WATER_SAFELY_MANAGED   \n",
       "13           WSH_WATER_BASIC   \n",
       "14                    WSH_10   \n",
       "15                WSH_40_WAT   \n",
       "16                WSH_50_WAT   \n",
       "17                    WSH_20   \n",
       "18                    WSH_30   \n",
       "19            NLIS_NU_CA_017   \n",
       "20          EQ_WATERPREMISES   \n",
       "21                     WSH_2   \n",
       "22                     WSH_3   \n",
       "23                     WSH_6   \n",
       "24                     WSH_7   \n",
       "25                    WSH_40   \n",
       "26                    WSH_50   \n",
       "27                     WSH_4   \n",
       "28                     WSH_8   \n",
       "29                  SDGODAWS   \n",
       "\n",
       "                                          description  \n",
       "0           Access to improved drinking water sources  \n",
       "1   Households with soap and water at a handwashin...  \n",
       "2    Number of diarrhoea deaths from inadequate water  \n",
       "3   Attributable fraction of diarrhoea to inadequa...  \n",
       "4     Number of diarrhoea DALYs from inadequate water  \n",
       "5        Radon in national drinking-water regulations  \n",
       "6   Population using improved drinking-water sourc...  \n",
       "7   Water, sanitation and hygiene attributable DAL...  \n",
       "8   Population using improved drinking-water sourc...  \n",
       "9   Households using an improved drinking-water so...  \n",
       "10  Households using a piped drinking-water source...  \n",
       "11  Water, sanitation and hygiene - population att...  \n",
       "12  Population using safely managed drinking-water...  \n",
       "13  Population using at least basic drinking-water...  \n",
       "14  Number of diarrhoea deaths from inadequate wat...  \n",
       "15  Diarrhoea deaths from inadequate water in chil...  \n",
       "16  Diarrhoea DALYs from inadequate water in child...  \n",
       "17  Attributable fraction of diarrhoea to inadequa...  \n",
       "18  Number of diarrhoea DALYs from inadequate wate...  \n",
       "19  NLIS: Population using improved drinking-water...  \n",
       "20  Households using a piped onto premises drinkin...  \n",
       "21  Water, sanitation and hygiene attributable dea...  \n",
       "22  Water, sanitation and hygiene attributable dea...  \n",
       "23  Water, sanitation and hygiene attributable DAL...  \n",
       "24  Water, sanitation and hygiene attributable DAL...  \n",
       "25  Diarrhoea deaths from inadequate water, sanita...  \n",
       "26  Diarrhoea DALYs from inadequate water, sanitat...  \n",
       "27  Water, sanitation and hygiene  attributable de...  \n",
       "28  Water, sanitation and hygiene  attributable DA...  \n",
       "29  Amount of water- and sanitation-related offici...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "water_codes = index.search('water')\n",
    "pd.DataFrame(water_codes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not all indicators are available for all countries in recent years, so we can easily check what's available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:47:25.343538Z",
     "start_time": "2021-05-11T16:47:12.019412Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking WAS_0000000001: Access to improved drinking water sources\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking EQ_HANDWASHING: Households with soap and water at a handwashing facility (%)\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_10_WAT: Number of diarrhoea deaths from inadequate water\n",
      "\tLatest year available for WSH_10_WAT in Africa: 2016\n",
      "\tCode available on all countries for 2016\n",
      "Checking WSH_20_WAT: Attributable fraction of diarrhoea to inadequate water\n",
      "\tLatest year available for WSH_20_WAT in Africa: 2016\n",
      "Checking WSH_30_WAT: Number of diarrhoea DALYs from inadequate water\n",
      "\tLatest year available for WSH_30_WAT in Africa: 2016\n",
      "\tCode available on all countries for 2016\n",
      "Checking RADON_Q405: Radon in national drinking-water regulations\n",
      "\tLatest year available for RADON_Q405 in Africa: 2019\n",
      "Checking WHS5_122: Population using improved drinking-water sources (%)\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_5: Water, sanitation and hygiene attributable DALYs ('000)\n",
      "\tLatest year available for WSH_5 in Africa: 2004\n",
      "Checking EQ_WATER: Population using improved drinking-water sources (%)\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking EQ_WATERIMPROVED: Households using an improved drinking-water source (%)\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking EQ_WATERPIPED: Households using a piped drinking-water source (%)\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_09: Water, sanitation and hygiene - population attributable fractions\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_WATER_SAFELY_MANAGED: Population using safely managed drinking-water services (%)\n",
      "\tLatest year available for WSH_WATER_SAFELY_MANAGED in Africa: 2017\n",
      "Checking WSH_WATER_BASIC: Population using at least basic drinking-water services (%)\n",
      "\tLatest year available for WSH_WATER_BASIC in Africa: 2017\n",
      "\tCode available on all countries for 2017\n",
      "Checking WSH_10: Number of diarrhoea deaths from inadequate water, sanitation and hygiene\n",
      "\tLatest year available for WSH_10 in Africa: 2016\n",
      "\tCode available on all countries for 2016\n",
      "Checking WSH_40_WAT: Diarrhoea deaths from inadequate water in children under 5 years\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_50_WAT: Diarrhoea DALYs from inadequate water in children under 5 years\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_20: Attributable fraction of diarrhoea to inadequate water, sanitation and hygiene\n",
      "\tLatest year available for WSH_20 in Africa: 2016\n",
      "Checking WSH_30: Number of diarrhoea DALYs from inadequate water, sanitation and hygiene\n",
      "\tLatest year available for WSH_30 in Africa: 2016\n",
      "\tCode available on all countries for 2016\n",
      "Checking NLIS_NU_CA_017: NLIS: Population using improved drinking-water sources (%)\n",
      "\tLatest year available for NLIS_NU_CA_017 in Africa: 2017\n",
      "Checking EQ_WATERPREMISES: Households using a piped onto premises drinking-water source (%)\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_2: Water, sanitation and hygiene attributable deaths ('000) in children under 5 years\n",
      "\tLatest year available for WSH_2 in Africa: 2004\n",
      "Checking WSH_3: Water, sanitation and hygiene attributable deaths per 100'000 capita\n",
      "\tLatest year available for WSH_3 in Africa: 2004\n",
      "Checking WSH_6: Water, sanitation and hygiene attributable DALYs ('000) in children under 5 years\n",
      "\tLatest year available for WSH_6 in Africa: 2004\n",
      "Checking WSH_7: Water, sanitation and hygiene attributable DALYs per 100'000 capita\n",
      "\tLatest year available for WSH_7 in Africa: 2004\n",
      "Checking WSH_40: Diarrhoea deaths from inadequate water, sanitation and hygiene in children under 5 years\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_50: Diarrhoea DALYs from inadequate water, sanitation and hygiene in children under 5 years\n",
      "\tno data available:\n",
      "\t   'DataFrame' object has no attribute 'REGION'\n",
      "Checking WSH_4: Water, sanitation and hygiene  attributable deaths per 100'000 children under 5 years\n",
      "\tLatest year available for WSH_4 in Africa: 2004\n",
      "Checking WSH_8: Water, sanitation and hygiene  attributable DALYs per 100'000 children under 5 years\n",
      "\tLatest year available for WSH_8 in Africa: 2004\n",
      "Checking SDGODAWS: Amount of water- and sanitation-related official development assistance that is part of a government-coordinated spending plan (current US$ millions)\n",
      "\tLatest year available for SDGODAWS in Africa: nan\n"
     ]
    }
   ],
   "source": [
    "for c in water_codes:\n",
    "    print(f\"Checking {c['code']}: {c['description']}\")\n",
    "    data = GC.fetch_data_from_codes(code=c['code'])\n",
    "    try:\n",
    "        data = data[(data.REGION=='AFR')&(data.YEAR==data.YEAR.max())]\n",
    "        print(f\"\\tLatest year available for {c['code']} in Africa: {data.YEAR.max()}\")\n",
    "    except AttributeError as e:\n",
    "        print(\"\\tno data available:\\n\\t  \", e)\n",
    "    if len(data) >=54:\n",
    "        print(f\"\\tCode available on all countries for {data.YEAR.max()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-11T16:45:45.328322Z",
     "start_time": "2021-05-11T16:45:44.344529Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GHO</th>\n",
       "      <th>PUBLISHSTATE</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>REGION</th>\n",
       "      <th>COUNTRY</th>\n",
       "      <th>RESIDENCEAREATYPE</th>\n",
       "      <th>Display Value</th>\n",
       "      <th>Numeric</th>\n",
       "      <th>Low</th>\n",
       "      <th>High</th>\n",
       "      <th>Comments</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>DZA</td>\n",
       "      <td>RUR</td>\n",
       "      <td>89.0</td>\n",
       "      <td>88.69096</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>DZA</td>\n",
       "      <td>TOTL</td>\n",
       "      <td>94.0</td>\n",
       "      <td>93.55589</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>DZA</td>\n",
       "      <td>URB</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.44293</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>AGO</td>\n",
       "      <td>RUR</td>\n",
       "      <td>27.0</td>\n",
       "      <td>27.44429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>AGO</td>\n",
       "      <td>TOTL</td>\n",
       "      <td>56.0</td>\n",
       "      <td>55.84290</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10420</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>TOTL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>59.96376</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10421</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>URB</td>\n",
       "      <td>84.0</td>\n",
       "      <td>83.86312</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10473</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>RUR</td>\n",
       "      <td>50.0</td>\n",
       "      <td>49.80476</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10474</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>TOTL</td>\n",
       "      <td>64.0</td>\n",
       "      <td>64.05123</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10475</th>\n",
       "      <td>WSH_WATER_BASIC</td>\n",
       "      <td>PUBLISHED</td>\n",
       "      <td>2017</td>\n",
       "      <td>AFR</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>URB</td>\n",
       "      <td>94.0</td>\n",
       "      <td>93.99767</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>141 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   GHO PUBLISHSTATE  YEAR REGION COUNTRY RESIDENCEAREATYPE  \\\n",
       "159    WSH_WATER_BASIC    PUBLISHED  2017    AFR     DZA               RUR   \n",
       "160    WSH_WATER_BASIC    PUBLISHED  2017    AFR     DZA              TOTL   \n",
       "161    WSH_WATER_BASIC    PUBLISHED  2017    AFR     DZA               URB   \n",
       "267    WSH_WATER_BASIC    PUBLISHED  2017    AFR     AGO               RUR   \n",
       "268    WSH_WATER_BASIC    PUBLISHED  2017    AFR     AGO              TOTL   \n",
       "...                ...          ...   ...    ...     ...               ...   \n",
       "10420  WSH_WATER_BASIC    PUBLISHED  2017    AFR     ZMB              TOTL   \n",
       "10421  WSH_WATER_BASIC    PUBLISHED  2017    AFR     ZMB               URB   \n",
       "10473  WSH_WATER_BASIC    PUBLISHED  2017    AFR     ZWE               RUR   \n",
       "10474  WSH_WATER_BASIC    PUBLISHED  2017    AFR     ZWE              TOTL   \n",
       "10475  WSH_WATER_BASIC    PUBLISHED  2017    AFR     ZWE               URB   \n",
       "\n",
       "       Display Value   Numeric  Low  High  Comments  \n",
       "159             89.0  88.69096  NaN   NaN       NaN  \n",
       "160             94.0  93.55589  NaN   NaN       NaN  \n",
       "161             95.0  95.44293  NaN   NaN       NaN  \n",
       "267             27.0  27.44429  NaN   NaN       NaN  \n",
       "268             56.0  55.84290  NaN   NaN       NaN  \n",
       "...              ...       ...  ...   ...       ...  \n",
       "10420           60.0  59.96376  NaN   NaN       NaN  \n",
       "10421           84.0  83.86312  NaN   NaN       NaN  \n",
       "10473           50.0  49.80476  NaN   NaN       NaN  \n",
       "10474           64.0  64.05123  NaN   NaN       NaN  \n",
       "10475           94.0  93.99767  NaN   NaN       NaN  \n",
       "\n",
       "[141 rows x 11 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = GC.fetch_data_from_codes(code='WSH_WATER_BASIC')\n",
    "data = data[(data.REGION=='AFR')&(data.YEAR==data.YEAR.max())]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
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