Tuberculosis data cleaning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "18af2a8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ce2c7e51",
   "metadata": {},
   "outputs": [],
   "source": [
    "tb = pd.read_excel(\"TB_burden_countries_2022-08-02.xlsx\",0\n",
    "                )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "55616c2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso2</th>\n",
       "      <th>iso3</th>\n",
       "      <th>iso_numeric</th>\n",
       "      <th>g_whoregion</th>\n",
       "      <th>year</th>\n",
       "      <th>e_pop_num</th>\n",
       "      <th>e_inc_100k</th>\n",
       "      <th>e_inc_100k_lo</th>\n",
       "      <th>e_inc_100k_hi</th>\n",
       "      <th>...</th>\n",
       "      <th>cfr</th>\n",
       "      <th>cfr_lo</th>\n",
       "      <th>cfr_hi</th>\n",
       "      <th>cfr_pct</th>\n",
       "      <th>cfr_pct_lo</th>\n",
       "      <th>cfr_pct_hi</th>\n",
       "      <th>c_newinc_100k</th>\n",
       "      <th>c_cdr</th>\n",
       "      <th>c_cdr_lo</th>\n",
       "      <th>c_cdr_hi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2000</td>\n",
       "      <td>20779957</td>\n",
       "      <td>190.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2001</td>\n",
       "      <td>21606992</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2002</td>\n",
       "      <td>22600774</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2003</td>\n",
       "      <td>23680871</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2004</td>\n",
       "      <td>24726689</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>74.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2005</td>\n",
       "      <td>25654274</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2006</td>\n",
       "      <td>26433058</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2007</td>\n",
       "      <td>27100542</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2008</td>\n",
       "      <td>27722281</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2009</td>\n",
       "      <td>28394806</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2010</td>\n",
       "      <td>29185511</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2011</td>\n",
       "      <td>30117411</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>93.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2012</td>\n",
       "      <td>31161378</td>\n",
       "      <td>189.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        country iso2 iso3  iso_numeric g_whoregion  year  e_pop_num  \\\n",
       "0   Afghanistan   AF  AFG            4         EMR  2000   20779957   \n",
       "1   Afghanistan   AF  AFG            4         EMR  2001   21606992   \n",
       "2   Afghanistan   AF  AFG            4         EMR  2002   22600774   \n",
       "3   Afghanistan   AF  AFG            4         EMR  2003   23680871   \n",
       "4   Afghanistan   AF  AFG            4         EMR  2004   24726689   \n",
       "5   Afghanistan   AF  AFG            4         EMR  2005   25654274   \n",
       "6   Afghanistan   AF  AFG            4         EMR  2006   26433058   \n",
       "7   Afghanistan   AF  AFG            4         EMR  2007   27100542   \n",
       "8   Afghanistan   AF  AFG            4         EMR  2008   27722281   \n",
       "9   Afghanistan   AF  AFG            4         EMR  2009   28394806   \n",
       "10  Afghanistan   AF  AFG            4         EMR  2010   29185511   \n",
       "11  Afghanistan   AF  AFG            4         EMR  2011   30117411   \n",
       "12  Afghanistan   AF  AFG            4         EMR  2012   31161378   \n",
       "\n",
       "    e_inc_100k  e_inc_100k_lo  e_inc_100k_hi  ...  cfr  cfr_lo  cfr_hi  \\\n",
       "0        190.0          122.0          271.0  ...  NaN     NaN     NaN   \n",
       "1        189.0          122.0          271.0  ...  NaN     NaN     NaN   \n",
       "2        189.0          122.0          270.0  ...  NaN     NaN     NaN   \n",
       "3        189.0          122.0          270.0  ...  NaN     NaN     NaN   \n",
       "4        189.0          122.0          270.0  ...  NaN     NaN     NaN   \n",
       "5        189.0          122.0          270.0  ...  NaN     NaN     NaN   \n",
       "6        189.0          122.0          270.0  ...  NaN     NaN     NaN   \n",
       "7        189.0          122.0          270.0  ...  NaN     NaN     NaN   \n",
       "8        189.0          122.0          271.0  ...  NaN     NaN     NaN   \n",
       "9        189.0          122.0          271.0  ...  NaN     NaN     NaN   \n",
       "10       189.0          122.0          271.0  ...  NaN     NaN     NaN   \n",
       "11       189.0          122.0          271.0  ...  NaN     NaN     NaN   \n",
       "12       189.0          122.0          270.0  ...  NaN     NaN     NaN   \n",
       "\n",
       "    cfr_pct  cfr_pct_lo  cfr_pct_hi  c_newinc_100k  c_cdr  c_cdr_lo  c_cdr_hi  \n",
       "0       NaN         NaN         NaN           34.0   18.0      13.0      28.0  \n",
       "1       NaN         NaN         NaN           47.0   25.0      17.0      38.0  \n",
       "2       NaN         NaN         NaN           61.0   32.0      23.0      50.0  \n",
       "3       NaN         NaN         NaN           58.0   31.0      22.0      48.0  \n",
       "4       NaN         NaN         NaN           74.0   39.0      28.0      61.0  \n",
       "5       NaN         NaN         NaN           85.0   45.0      32.0      70.0  \n",
       "6       NaN         NaN         NaN           96.0   51.0      36.0      79.0  \n",
       "7       NaN         NaN         NaN          106.0   56.0      39.0      87.0  \n",
       "8       NaN         NaN         NaN          102.0   54.0      38.0      83.0  \n",
       "9       NaN         NaN         NaN           92.0   49.0      34.0      75.0  \n",
       "10      NaN         NaN         NaN           96.0   51.0      35.0      79.0  \n",
       "11      NaN         NaN         NaN           93.0   49.0      34.0      76.0  \n",
       "12      NaN         NaN         NaN           92.0   49.0      34.0      75.0  \n",
       "\n",
       "[13 rows x 50 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tb.head(13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "961a2446",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4487 entries, 0 to 4486\n",
      "Data columns (total 50 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   country                   4487 non-null   object \n",
      " 1   iso2                      4466 non-null   object \n",
      " 2   iso3                      4487 non-null   object \n",
      " 3   iso_numeric               4487 non-null   int64  \n",
      " 4   g_whoregion               4487 non-null   object \n",
      " 5   year                      4487 non-null   int64  \n",
      " 6   e_pop_num                 4487 non-null   int64  \n",
      " 7   e_inc_100k                4487 non-null   float64\n",
      " 8   e_inc_100k_lo             4487 non-null   float64\n",
      " 9   e_inc_100k_hi             4487 non-null   float64\n",
      " 10  e_inc_num                 4487 non-null   int64  \n",
      " 11  e_inc_num_lo              4487 non-null   int64  \n",
      " 12  e_inc_num_hi              4487 non-null   int64  \n",
      " 13  e_tbhiv_prct              3857 non-null   float64\n",
      " 14  e_tbhiv_prct_lo           3857 non-null   float64\n",
      " 15  e_tbhiv_prct_hi           3857 non-null   float64\n",
      " 16  e_inc_tbhiv_100k          3857 non-null   float64\n",
      " 17  e_inc_tbhiv_100k_lo       3857 non-null   float64\n",
      " 18  e_inc_tbhiv_100k_hi       3857 non-null   float64\n",
      " 19  e_inc_tbhiv_num           3857 non-null   float64\n",
      " 20  e_inc_tbhiv_num_lo        3857 non-null   float64\n",
      " 21  e_inc_tbhiv_num_hi        3857 non-null   float64\n",
      " 22  e_mort_exc_tbhiv_100k     4466 non-null   float64\n",
      " 23  e_mort_exc_tbhiv_100k_lo  4466 non-null   float64\n",
      " 24  e_mort_exc_tbhiv_100k_hi  4466 non-null   float64\n",
      " 25  e_mort_exc_tbhiv_num      4466 non-null   float64\n",
      " 26  e_mort_exc_tbhiv_num_lo   4466 non-null   float64\n",
      " 27  e_mort_exc_tbhiv_num_hi   4466 non-null   float64\n",
      " 28  e_mort_tbhiv_100k         4466 non-null   float64\n",
      " 29  e_mort_tbhiv_100k_lo      4466 non-null   float64\n",
      " 30  e_mort_tbhiv_100k_hi      4466 non-null   float64\n",
      " 31  e_mort_tbhiv_num          4466 non-null   float64\n",
      " 32  e_mort_tbhiv_num_lo       4466 non-null   float64\n",
      " 33  e_mort_tbhiv_num_hi       4466 non-null   float64\n",
      " 34  e_mort_100k               4466 non-null   float64\n",
      " 35  e_mort_100k_lo            4466 non-null   float64\n",
      " 36  e_mort_100k_hi            4466 non-null   float64\n",
      " 37  e_mort_num                4466 non-null   float64\n",
      " 38  e_mort_num_lo             4466 non-null   float64\n",
      " 39  e_mort_num_hi             4466 non-null   float64\n",
      " 40  cfr                       211 non-null    float64\n",
      " 41  cfr_lo                    211 non-null    float64\n",
      " 42  cfr_hi                    211 non-null    float64\n",
      " 43  cfr_pct                   211 non-null    float64\n",
      " 44  cfr_pct_lo                211 non-null    float64\n",
      " 45  cfr_pct_hi                211 non-null    float64\n",
      " 46  c_newinc_100k             4322 non-null   float64\n",
      " 47  c_cdr                     4220 non-null   float64\n",
      " 48  c_cdr_lo                  4220 non-null   float64\n",
      " 49  c_cdr_hi                  4220 non-null   float64\n",
      "dtypes: float64(40), int64(6), object(4)\n",
      "memory usage: 1.7+ MB\n"
     ]
    }
   ],
   "source": [
    "tb.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fc27094e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso2</th>\n",
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       "      <th>e_inc_100k</th>\n",
       "      <th>e_inc_100k_lo</th>\n",
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       "      <th>...</th>\n",
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\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>False</td>\n",
       "      <td>...</td>\n",
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       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4483</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>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4484</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>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4485</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>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4486</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>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4487 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country   iso2   iso3  iso_numeric  g_whoregion   year  e_pop_num  \\\n",
       "0       False  False  False        False        False  False      False   \n",
       "1       False  False  False        False        False  False      False   \n",
       "2       False  False  False        False        False  False      False   \n",
       "3       False  False  False        False        False  False      False   \n",
       "4       False  False  False        False        False  False      False   \n",
       "...       ...    ...    ...          ...          ...    ...        ...   \n",
       "4482    False  False  False        False        False  False      False   \n",
       "4483    False  False  False        False        False  False      False   \n",
       "4484    False  False  False        False        False  False      False   \n",
       "4485    False  False  False        False        False  False      False   \n",
       "4486    False  False  False        False        False  False      False   \n",
       "\n",
       "      e_inc_100k  e_inc_100k_lo  e_inc_100k_hi  ...    cfr  cfr_lo  cfr_hi  \\\n",
       "0          False          False          False  ...   True    True    True   \n",
       "1          False          False          False  ...   True    True    True   \n",
       "2          False          False          False  ...   True    True    True   \n",
       "3          False          False          False  ...   True    True    True   \n",
       "4          False          False          False  ...   True    True    True   \n",
       "...          ...            ...            ...  ...    ...     ...     ...   \n",
       "4482       False          False          False  ...   True    True    True   \n",
       "4483       False          False          False  ...   True    True    True   \n",
       "4484       False          False          False  ...   True    True    True   \n",
       "4485       False          False          False  ...   True    True    True   \n",
       "4486       False          False          False  ...  False   False   False   \n",
       "\n",
       "      cfr_pct  cfr_pct_lo  cfr_pct_hi  c_newinc_100k  c_cdr  c_cdr_lo  \\\n",
       "0        True        True        True          False  False     False   \n",
       "1        True        True        True          False  False     False   \n",
       "2        True        True        True          False  False     False   \n",
       "3        True        True        True          False  False     False   \n",
       "4        True        True        True          False  False     False   \n",
       "...       ...         ...         ...            ...    ...       ...   \n",
       "4482     True        True        True          False  False     False   \n",
       "4483     True        True        True          False  False     False   \n",
       "4484     True        True        True          False  False     False   \n",
       "4485     True        True        True          False  False     False   \n",
       "4486    False       False       False          False  False     False   \n",
       "\n",
       "      c_cdr_hi  \n",
       "0        False  \n",
       "1        False  \n",
       "2        False  \n",
       "3        False  \n",
       "4        False  \n",
       "...        ...  \n",
       "4482     False  \n",
       "4483     False  \n",
       "4484     False  \n",
       "4485     False  \n",
       "4486     False  \n",
       "\n",
       "[4487 rows x 50 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tb.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2321778b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country                        0\n",
       "iso2                          21\n",
       "iso3                           0\n",
       "iso_numeric                    0\n",
       "g_whoregion                    0\n",
       "year                           0\n",
       "e_pop_num                      0\n",
       "e_inc_100k                     0\n",
       "e_inc_100k_lo                  0\n",
       "e_inc_100k_hi                  0\n",
       "e_inc_num                      0\n",
       "e_inc_num_lo                   0\n",
       "e_inc_num_hi                   0\n",
       "e_tbhiv_prct                 630\n",
       "e_tbhiv_prct_lo              630\n",
       "e_tbhiv_prct_hi              630\n",
       "e_inc_tbhiv_100k             630\n",
       "e_inc_tbhiv_100k_lo          630\n",
       "e_inc_tbhiv_100k_hi          630\n",
       "e_inc_tbhiv_num              630\n",
       "e_inc_tbhiv_num_lo           630\n",
       "e_inc_tbhiv_num_hi           630\n",
       "e_mort_exc_tbhiv_100k         21\n",
       "e_mort_exc_tbhiv_100k_lo      21\n",
       "e_mort_exc_tbhiv_100k_hi      21\n",
       "e_mort_exc_tbhiv_num          21\n",
       "e_mort_exc_tbhiv_num_lo       21\n",
       "e_mort_exc_tbhiv_num_hi       21\n",
       "e_mort_tbhiv_100k             21\n",
       "e_mort_tbhiv_100k_lo          21\n",
       "e_mort_tbhiv_100k_hi          21\n",
       "e_mort_tbhiv_num              21\n",
       "e_mort_tbhiv_num_lo           21\n",
       "e_mort_tbhiv_num_hi           21\n",
       "e_mort_100k                   21\n",
       "e_mort_100k_lo                21\n",
       "e_mort_100k_hi                21\n",
       "e_mort_num                    21\n",
       "e_mort_num_lo                 21\n",
       "e_mort_num_hi                 21\n",
       "cfr                         4276\n",
       "cfr_lo                      4276\n",
       "cfr_hi                      4276\n",
       "cfr_pct                     4276\n",
       "cfr_pct_lo                  4276\n",
       "cfr_pct_hi                  4276\n",
       "c_newinc_100k                165\n",
       "c_cdr                        267\n",
       "c_cdr_lo                     267\n",
       "c_cdr_hi                     267\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rows missing in each column\n",
    "tb.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "25f10249",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['country', 'iso2', 'iso3', 'iso_numeric', 'g_whoregion', 'year',\n",
       "       'e_pop_num', 'e_inc_100k', 'e_inc_100k_lo', 'e_inc_100k_hi',\n",
       "       'e_inc_num', 'e_inc_num_lo', 'e_inc_num_hi', 'e_tbhiv_prct',\n",
       "       'e_tbhiv_prct_lo', 'e_tbhiv_prct_hi', 'e_inc_tbhiv_100k',\n",
       "       'e_inc_tbhiv_100k_lo', 'e_inc_tbhiv_100k_hi', 'e_inc_tbhiv_num',\n",
       "       'e_inc_tbhiv_num_lo', 'e_inc_tbhiv_num_hi', 'e_mort_exc_tbhiv_100k',\n",
       "       'e_mort_exc_tbhiv_100k_lo', 'e_mort_exc_tbhiv_100k_hi',\n",
       "       'e_mort_exc_tbhiv_num', 'e_mort_exc_tbhiv_num_lo',\n",
       "       'e_mort_exc_tbhiv_num_hi', 'e_mort_tbhiv_100k', 'e_mort_tbhiv_100k_lo',\n",
       "       'e_mort_tbhiv_100k_hi', 'e_mort_tbhiv_num', 'e_mort_tbhiv_num_lo',\n",
       "       'e_mort_tbhiv_num_hi', 'e_mort_100k', 'e_mort_100k_lo',\n",
       "       'e_mort_100k_hi', 'e_mort_num', 'e_mort_num_lo', 'e_mort_num_hi', 'cfr',\n",
       "       'cfr_lo', 'cfr_hi', 'cfr_pct', 'cfr_pct_lo', 'cfr_pct_hi',\n",
       "       'c_newinc_100k', 'c_cdr', 'c_cdr_lo', 'c_cdr_hi'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tb.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "947f2229",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso3</th>\n",
       "      <th>g_whoregion</th>\n",
       "      <th>year</th>\n",
       "      <th>e_pop_num</th>\n",
       "      <th>e_inc_100k</th>\n",
       "      <th>e_inc_num</th>\n",
       "      <th>e_tbhiv_prct</th>\n",
       "      <th>e_inc_tbhiv_100k</th>\n",
       "      <th>e_inc_tbhiv_num</th>\n",
       "      <th>e_mort_exc_tbhiv_100k</th>\n",
       "      <th>e_mort_exc_tbhiv_num</th>\n",
       "      <th>e_mort_tbhiv_100k</th>\n",
       "      <th>e_mort_tbhiv_num</th>\n",
       "      <th>e_mort_100k</th>\n",
       "      <th>e_mort_num</th>\n",
       "      <th>c_newinc_100k</th>\n",
       "      <th>c_cdr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2000</td>\n",
       "      <td>20779957</td>\n",
       "      <td>190.0</td>\n",
       "      <td>39000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>0.17</td>\n",
       "      <td>35.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2001</td>\n",
       "      <td>21606992</td>\n",
       "      <td>189.0</td>\n",
       "      <td>41000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>6.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>0.30</td>\n",
       "      <td>65.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2002</td>\n",
       "      <td>22600774</td>\n",
       "      <td>189.0</td>\n",
       "      <td>43000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>6.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>62.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2003</td>\n",
       "      <td>23680871</td>\n",
       "      <td>189.0</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>6.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>0.29</td>\n",
       "      <td>69.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2004</td>\n",
       "      <td>24726689</td>\n",
       "      <td>189.0</td>\n",
       "      <td>47000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>0.29</td>\n",
       "      <td>71.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>39.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4482</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2016</td>\n",
       "      <td>14030338</td>\n",
       "      <td>233.0</td>\n",
       "      <td>33000</td>\n",
       "      <td>65.00</td>\n",
       "      <td>151.00</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>4200.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>5400.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4483</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2017</td>\n",
       "      <td>14236599</td>\n",
       "      <td>221.0</td>\n",
       "      <td>31000</td>\n",
       "      <td>63.00</td>\n",
       "      <td>140.00</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>27.00</td>\n",
       "      <td>3800.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4484</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2018</td>\n",
       "      <td>14438812</td>\n",
       "      <td>210.0</td>\n",
       "      <td>30000</td>\n",
       "      <td>62.00</td>\n",
       "      <td>130.00</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4600.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4485</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2019</td>\n",
       "      <td>14645473</td>\n",
       "      <td>199.0</td>\n",
       "      <td>29000</td>\n",
       "      <td>60.00</td>\n",
       "      <td>119.00</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>31.00</td>\n",
       "      <td>4600.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>6300.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4486</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2020</td>\n",
       "      <td>14862927</td>\n",
       "      <td>193.0</td>\n",
       "      <td>29000</td>\n",
       "      <td>54.00</td>\n",
       "      <td>104.00</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2100.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4487 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          country iso3 g_whoregion  year  e_pop_num  e_inc_100k  e_inc_num  \\\n",
       "0     Afghanistan  AFG         EMR  2000   20779957       190.0      39000   \n",
       "1     Afghanistan  AFG         EMR  2001   21606992       189.0      41000   \n",
       "2     Afghanistan  AFG         EMR  2002   22600774       189.0      43000   \n",
       "3     Afghanistan  AFG         EMR  2003   23680871       189.0      45000   \n",
       "4     Afghanistan  AFG         EMR  2004   24726689       189.0      47000   \n",
       "...           ...  ...         ...   ...        ...         ...        ...   \n",
       "4482     Zimbabwe  ZWE         AFR  2016   14030338       233.0      33000   \n",
       "4483     Zimbabwe  ZWE         AFR  2017   14236599       221.0      31000   \n",
       "4484     Zimbabwe  ZWE         AFR  2018   14438812       210.0      30000   \n",
       "4485     Zimbabwe  ZWE         AFR  2019   14645473       199.0      29000   \n",
       "4486     Zimbabwe  ZWE         AFR  2020   14862927       193.0      29000   \n",
       "\n",
       "      e_tbhiv_prct  e_inc_tbhiv_100k  e_inc_tbhiv_num  e_mort_exc_tbhiv_100k  \\\n",
       "0             0.02              0.03              7.0                   68.0   \n",
       "1             0.01              0.03              6.0                   63.0   \n",
       "2             0.01              0.03              6.0                   57.0   \n",
       "3             0.01              0.03              6.0                   58.0   \n",
       "4             0.01              0.03              7.0                   51.0   \n",
       "...            ...               ...              ...                    ...   \n",
       "4482         65.00            151.00          21000.0                    8.6   \n",
       "4483         63.00            140.00          20000.0                    8.3   \n",
       "4484         62.00            130.00          19000.0                    7.7   \n",
       "4485         60.00            119.00          17000.0                   11.0   \n",
       "4486         54.00            104.00          16000.0                   14.0   \n",
       "\n",
       "      e_mort_exc_tbhiv_num  e_mort_tbhiv_100k  e_mort_tbhiv_num  e_mort_100k  \\\n",
       "0                  14000.0               0.17              35.0         68.0   \n",
       "1                  14000.0               0.30              65.0         63.0   \n",
       "2                  13000.0               0.27              62.0         57.0   \n",
       "3                  14000.0               0.29              69.0         58.0   \n",
       "4                  13000.0               0.29              71.0         52.0   \n",
       "...                    ...                ...               ...          ...   \n",
       "4482                1200.0              30.00            4200.0         38.0   \n",
       "4483                1200.0              27.00            3800.0         35.0   \n",
       "4484                1100.0              24.00            3500.0         32.0   \n",
       "4485                1700.0              31.00            4600.0         43.0   \n",
       "4486                2100.0              40.00            5900.0         54.0   \n",
       "\n",
       "      e_mort_num  c_newinc_100k  c_cdr  \n",
       "0        14000.0           34.0   18.0  \n",
       "1        14000.0           47.0   25.0  \n",
       "2        13000.0           61.0   32.0  \n",
       "3        14000.0           58.0   31.0  \n",
       "4        13000.0           74.0   39.0  \n",
       "...          ...            ...    ...  \n",
       "4482      5400.0          190.0   81.0  \n",
       "4483      5000.0          182.0   82.0  \n",
       "4484      4600.0          175.0   83.0  \n",
       "4485      6300.0          143.0   72.0  \n",
       "4486      8000.0          106.0   55.0  \n",
       "\n",
       "[4487 rows x 18 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Drop columns that are not needed\n",
    "new_dataset= tb.drop([\"iso2\",\"iso_numeric\",\"e_inc_100k_lo\",\"e_inc_100k_hi\",\"e_inc_num_lo\",\"e_inc_num_hi\",\"e_tbhiv_prct_lo\",\"e_tbhiv_prct_hi\",\"e_inc_tbhiv_100k_lo\",\"e_inc_tbhiv_100k_hi\",\"e_inc_tbhiv_num_lo\",\"e_inc_tbhiv_num_hi\",\"e_mort_exc_tbhiv_100k_lo\",\"e_mort_exc_tbhiv_100k_hi\",\"e_mort_exc_tbhiv_num_lo\",\"e_mort_exc_tbhiv_num_hi\",\"e_mort_tbhiv_100k_lo\",\"e_mort_tbhiv_100k_hi\",\"e_mort_tbhiv_num_lo\",\"e_mort_tbhiv_num_hi\",\"e_mort_100k_lo\",\"e_mort_100k_hi\",\"e_mort_num_lo\",\"e_mort_num_hi\",\"cfr\",\"cfr_lo\",\"cfr_hi\",\"cfr_pct_lo\",\"cfr_pct_hi\",\"cfr_pct\",\n",
    "\"c_cdr_lo\",\"c_cdr_hi\"], axis= 1)\n",
    "display(new_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c78c6178",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4487 entries, 0 to 4486\n",
      "Data columns (total 18 columns):\n",
      " #   Column                 Non-Null Count  Dtype  \n",
      "---  ------                 --------------  -----  \n",
      " 0   country                4487 non-null   object \n",
      " 1   iso3                   4487 non-null   object \n",
      " 2   g_whoregion            4487 non-null   object \n",
      " 3   year                   4487 non-null   int64  \n",
      " 4   e_pop_num              4487 non-null   int64  \n",
      " 5   e_inc_100k             4487 non-null   float64\n",
      " 6   e_inc_num              4487 non-null   int64  \n",
      " 7   e_tbhiv_prct           3857 non-null   float64\n",
      " 8   e_inc_tbhiv_100k       3857 non-null   float64\n",
      " 9   e_inc_tbhiv_num        3857 non-null   float64\n",
      " 10  e_mort_exc_tbhiv_100k  4466 non-null   float64\n",
      " 11  e_mort_exc_tbhiv_num   4466 non-null   float64\n",
      " 12  e_mort_tbhiv_100k      4466 non-null   float64\n",
      " 13  e_mort_tbhiv_num       4466 non-null   float64\n",
      " 14  e_mort_100k            4466 non-null   float64\n",
      " 15  e_mort_num             4466 non-null   float64\n",
      " 16  c_newinc_100k          4322 non-null   float64\n",
      " 17  c_cdr                  4220 non-null   float64\n",
      "dtypes: float64(12), int64(3), object(3)\n",
      "memory usage: 631.1+ KB\n"
     ]
    }
   ],
   "source": [
    "new_dataset.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a60bfacb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country                    0\n",
       "iso3                       0\n",
       "g_whoregion                0\n",
       "year                       0\n",
       "e_pop_num                  0\n",
       "e_inc_100k                 0\n",
       "e_inc_num                  0\n",
       "e_tbhiv_prct             630\n",
       "e_inc_tbhiv_100k         630\n",
       "e_inc_tbhiv_num          630\n",
       "e_mort_exc_tbhiv_100k     21\n",
       "e_mort_exc_tbhiv_num      21\n",
       "e_mort_tbhiv_100k         21\n",
       "e_mort_tbhiv_num          21\n",
       "e_mort_100k               21\n",
       "e_mort_num                21\n",
       "c_newinc_100k            165\n",
       "c_cdr                    267\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_dataset.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b20c8a54",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_Tb_data = new_dataset.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "35377c30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso3</th>\n",
       "      <th>g_whoregion</th>\n",
       "      <th>year</th>\n",
       "      <th>e_pop_num</th>\n",
       "      <th>e_inc_100k</th>\n",
       "      <th>e_inc_num</th>\n",
       "      <th>e_tbhiv_prct</th>\n",
       "      <th>e_inc_tbhiv_100k</th>\n",
       "      <th>e_inc_tbhiv_num</th>\n",
       "      <th>e_mort_exc_tbhiv_100k</th>\n",
       "      <th>e_mort_exc_tbhiv_num</th>\n",
       "      <th>e_mort_tbhiv_100k</th>\n",
       "      <th>e_mort_tbhiv_num</th>\n",
       "      <th>e_mort_100k</th>\n",
       "      <th>e_mort_num</th>\n",
       "      <th>c_newinc_100k</th>\n",
       "      <th>c_cdr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2000</td>\n",
       "      <td>20779957</td>\n",
       "      <td>190.0</td>\n",
       "      <td>39000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>0.17</td>\n",
       "      <td>35.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2001</td>\n",
       "      <td>21606992</td>\n",
       "      <td>189.0</td>\n",
       "      <td>41000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>6.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>0.30</td>\n",
       "      <td>65.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2002</td>\n",
       "      <td>22600774</td>\n",
       "      <td>189.0</td>\n",
       "      <td>43000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>6.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>0.27</td>\n",
       "      <td>62.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2003</td>\n",
       "      <td>23680871</td>\n",
       "      <td>189.0</td>\n",
       "      <td>45000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>6.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>0.29</td>\n",
       "      <td>69.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>EMR</td>\n",
       "      <td>2004</td>\n",
       "      <td>24726689</td>\n",
       "      <td>189.0</td>\n",
       "      <td>47000</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>0.29</td>\n",
       "      <td>71.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>39.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4482</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2016</td>\n",
       "      <td>14030338</td>\n",
       "      <td>233.0</td>\n",
       "      <td>33000</td>\n",
       "      <td>65.00</td>\n",
       "      <td>151.00</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>4200.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>5400.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4483</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2017</td>\n",
       "      <td>14236599</td>\n",
       "      <td>221.0</td>\n",
       "      <td>31000</td>\n",
       "      <td>63.00</td>\n",
       "      <td>140.00</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>27.00</td>\n",
       "      <td>3800.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4484</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2018</td>\n",
       "      <td>14438812</td>\n",
       "      <td>210.0</td>\n",
       "      <td>30000</td>\n",
       "      <td>62.00</td>\n",
       "      <td>130.00</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>4600.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4485</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2019</td>\n",
       "      <td>14645473</td>\n",
       "      <td>199.0</td>\n",
       "      <td>29000</td>\n",
       "      <td>60.00</td>\n",
       "      <td>119.00</td>\n",
       "      <td>17000.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>31.00</td>\n",
       "      <td>4600.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>6300.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4486</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AFR</td>\n",
       "      <td>2020</td>\n",
       "      <td>14862927</td>\n",
       "      <td>193.0</td>\n",
       "      <td>29000</td>\n",
       "      <td>54.00</td>\n",
       "      <td>104.00</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2100.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4487 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          country iso3 g_whoregion  year  e_pop_num  e_inc_100k  e_inc_num  \\\n",
       "0     Afghanistan  AFG         EMR  2000   20779957       190.0      39000   \n",
       "1     Afghanistan  AFG         EMR  2001   21606992       189.0      41000   \n",
       "2     Afghanistan  AFG         EMR  2002   22600774       189.0      43000   \n",
       "3     Afghanistan  AFG         EMR  2003   23680871       189.0      45000   \n",
       "4     Afghanistan  AFG         EMR  2004   24726689       189.0      47000   \n",
       "...           ...  ...         ...   ...        ...         ...        ...   \n",
       "4482     Zimbabwe  ZWE         AFR  2016   14030338       233.0      33000   \n",
       "4483     Zimbabwe  ZWE         AFR  2017   14236599       221.0      31000   \n",
       "4484     Zimbabwe  ZWE         AFR  2018   14438812       210.0      30000   \n",
       "4485     Zimbabwe  ZWE         AFR  2019   14645473       199.0      29000   \n",
       "4486     Zimbabwe  ZWE         AFR  2020   14862927       193.0      29000   \n",
       "\n",
       "      e_tbhiv_prct  e_inc_tbhiv_100k  e_inc_tbhiv_num  e_mort_exc_tbhiv_100k  \\\n",
       "0             0.02              0.03              7.0                   68.0   \n",
       "1             0.01              0.03              6.0                   63.0   \n",
       "2             0.01              0.03              6.0                   57.0   \n",
       "3             0.01              0.03              6.0                   58.0   \n",
       "4             0.01              0.03              7.0                   51.0   \n",
       "...            ...               ...              ...                    ...   \n",
       "4482         65.00            151.00          21000.0                    8.6   \n",
       "4483         63.00            140.00          20000.0                    8.3   \n",
       "4484         62.00            130.00          19000.0                    7.7   \n",
       "4485         60.00            119.00          17000.0                   11.0   \n",
       "4486         54.00            104.00          16000.0                   14.0   \n",
       "\n",
       "      e_mort_exc_tbhiv_num  e_mort_tbhiv_100k  e_mort_tbhiv_num  e_mort_100k  \\\n",
       "0                  14000.0               0.17              35.0         68.0   \n",
       "1                  14000.0               0.30              65.0         63.0   \n",
       "2                  13000.0               0.27              62.0         57.0   \n",
       "3                  14000.0               0.29              69.0         58.0   \n",
       "4                  13000.0               0.29              71.0         52.0   \n",
       "...                    ...                ...               ...          ...   \n",
       "4482                1200.0              30.00            4200.0         38.0   \n",
       "4483                1200.0              27.00            3800.0         35.0   \n",
       "4484                1100.0              24.00            3500.0         32.0   \n",
       "4485                1700.0              31.00            4600.0         43.0   \n",
       "4486                2100.0              40.00            5900.0         54.0   \n",
       "\n",
       "      e_mort_num  c_newinc_100k  c_cdr  \n",
       "0        14000.0           34.0   18.0  \n",
       "1        14000.0           47.0   25.0  \n",
       "2        13000.0           61.0   32.0  \n",
       "3        14000.0           58.0   31.0  \n",
       "4        13000.0           74.0   39.0  \n",
       "...          ...            ...    ...  \n",
       "4482      5400.0          190.0   81.0  \n",
       "4483      5000.0          182.0   82.0  \n",
       "4484      4600.0          175.0   83.0  \n",
       "4485      6300.0          143.0   72.0  \n",
       "4486      8000.0          106.0   55.0  \n",
       "\n",
       "[4487 rows x 18 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(new_Tb_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "65f99ca4",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_Tb_data.to_excel('TB_cleaned.xlsx', index= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c11c6794",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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