prodigi_infotech_task_01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Importing important libraries_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Checking Data :_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
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       "    .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>Series Name</th>\n",
       "      <th>Series Code</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>2022</th>\n",
       "      <th>2021</th>\n",
       "      <th>2020</th>\n",
       "      <th>2019</th>\n",
       "      <th>2018</th>\n",
       "      <th>2017</th>\n",
       "      <th>...</th>\n",
       "      <th>2010</th>\n",
       "      <th>2009</th>\n",
       "      <th>2008</th>\n",
       "      <th>2007</th>\n",
       "      <th>2006</th>\n",
       "      <th>2005</th>\n",
       "      <th>2004</th>\n",
       "      <th>2003</th>\n",
       "      <th>2002</th>\n",
       "      <th>2001</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>4.112877e+07</td>\n",
       "      <td>4.009946e+07</td>\n",
       "      <td>3.897223e+07</td>\n",
       "      <td>3.776950e+07</td>\n",
       "      <td>3.668678e+07</td>\n",
       "      <td>3.564342e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>2.818967e+07</td>\n",
       "      <td>2.738531e+07</td>\n",
       "      <td>2.642720e+07</td>\n",
       "      <td>2.590330e+07</td>\n",
       "      <td>2.544294e+07</td>\n",
       "      <td>2.441119e+07</td>\n",
       "      <td>2.355355e+07</td>\n",
       "      <td>2.264513e+07</td>\n",
       "      <td>2.100026e+07</td>\n",
       "      <td>1.968863e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "      <td>2.775634e+06</td>\n",
       "      <td>2.811666e+06</td>\n",
       "      <td>2.837849e+06</td>\n",
       "      <td>2.854191e+06</td>\n",
       "      <td>2.866376e+06</td>\n",
       "      <td>2.873457e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>2.913021e+06</td>\n",
       "      <td>2.927519e+06</td>\n",
       "      <td>2.947314e+06</td>\n",
       "      <td>2.970017e+06</td>\n",
       "      <td>2.992547e+06</td>\n",
       "      <td>3.011487e+06</td>\n",
       "      <td>3.026939e+06</td>\n",
       "      <td>3.039616e+06</td>\n",
       "      <td>3.051010e+06</td>\n",
       "      <td>3.060173e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>DZA</td>\n",
       "      <td>4.490322e+07</td>\n",
       "      <td>4.417797e+07</td>\n",
       "      <td>4.345167e+07</td>\n",
       "      <td>4.270537e+07</td>\n",
       "      <td>4.192701e+07</td>\n",
       "      <td>4.113655e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>3.585634e+07</td>\n",
       "      <td>3.519604e+07</td>\n",
       "      <td>3.456959e+07</td>\n",
       "      <td>3.398383e+07</td>\n",
       "      <td>3.343508e+07</td>\n",
       "      <td>3.295669e+07</td>\n",
       "      <td>3.251019e+07</td>\n",
       "      <td>3.205588e+07</td>\n",
       "      <td>3.162470e+07</td>\n",
       "      <td>3.120098e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>ASM</td>\n",
       "      <td>4.427300e+04</td>\n",
       "      <td>4.503500e+04</td>\n",
       "      <td>4.618900e+04</td>\n",
       "      <td>4.732100e+04</td>\n",
       "      <td>4.842400e+04</td>\n",
       "      <td>4.946300e+04</td>\n",
       "      <td>...</td>\n",
       "      <td>5.484900e+04</td>\n",
       "      <td>5.536600e+04</td>\n",
       "      <td>5.589100e+04</td>\n",
       "      <td>5.638300e+04</td>\n",
       "      <td>5.683700e+04</td>\n",
       "      <td>5.725400e+04</td>\n",
       "      <td>5.762600e+04</td>\n",
       "      <td>5.794100e+04</td>\n",
       "      <td>5.817700e+04</td>\n",
       "      <td>5.832400e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>AND</td>\n",
       "      <td>7.982400e+04</td>\n",
       "      <td>7.903400e+04</td>\n",
       "      <td>7.770000e+04</td>\n",
       "      <td>7.634300e+04</td>\n",
       "      <td>7.501300e+04</td>\n",
       "      <td>7.383700e+04</td>\n",
       "      <td>...</td>\n",
       "      <td>7.151900e+04</td>\n",
       "      <td>7.385200e+04</td>\n",
       "      <td>7.605500e+04</td>\n",
       "      <td>7.816800e+04</td>\n",
       "      <td>8.022100e+04</td>\n",
       "      <td>7.982600e+04</td>\n",
       "      <td>7.693300e+04</td>\n",
       "      <td>7.390700e+04</td>\n",
       "      <td>7.084900e+04</td>\n",
       "      <td>6.782000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1080</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Virgin Islands (U.S.)</td>\n",
       "      <td>VIR</td>\n",
       "      <td>4.661338e+01</td>\n",
       "      <td>4.676444e+01</td>\n",
       "      <td>4.691464e+01</td>\n",
       "      <td>4.705731e+01</td>\n",
       "      <td>4.718591e+01</td>\n",
       "      <td>4.731421e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>4.780106e+01</td>\n",
       "      <td>4.783454e+01</td>\n",
       "      <td>4.787006e+01</td>\n",
       "      <td>4.787760e+01</td>\n",
       "      <td>4.787070e+01</td>\n",
       "      <td>4.785267e+01</td>\n",
       "      <td>4.782515e+01</td>\n",
       "      <td>4.778913e+01</td>\n",
       "      <td>4.775493e+01</td>\n",
       "      <td>4.772513e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1081</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>PSE</td>\n",
       "      <td>4.989368e+01</td>\n",
       "      <td>4.987784e+01</td>\n",
       "      <td>4.985896e+01</td>\n",
       "      <td>4.983554e+01</td>\n",
       "      <td>4.981137e+01</td>\n",
       "      <td>4.978597e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>4.987634e+01</td>\n",
       "      <td>4.989868e+01</td>\n",
       "      <td>4.992145e+01</td>\n",
       "      <td>4.994763e+01</td>\n",
       "      <td>4.998332e+01</td>\n",
       "      <td>5.002865e+01</td>\n",
       "      <td>5.008995e+01</td>\n",
       "      <td>5.016754e+01</td>\n",
       "      <td>5.024820e+01</td>\n",
       "      <td>5.032163e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1082</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>YEM</td>\n",
       "      <td>5.051903e+01</td>\n",
       "      <td>5.053852e+01</td>\n",
       "      <td>5.055432e+01</td>\n",
       "      <td>5.057132e+01</td>\n",
       "      <td>5.059661e+01</td>\n",
       "      <td>5.061696e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>5.059417e+01</td>\n",
       "      <td>5.058269e+01</td>\n",
       "      <td>5.056888e+01</td>\n",
       "      <td>5.055363e+01</td>\n",
       "      <td>5.053901e+01</td>\n",
       "      <td>5.052251e+01</td>\n",
       "      <td>5.050272e+01</td>\n",
       "      <td>5.048167e+01</td>\n",
       "      <td>5.045994e+01</td>\n",
       "      <td>5.043724e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>4.934460e+01</td>\n",
       "      <td>4.934495e+01</td>\n",
       "      <td>4.933830e+01</td>\n",
       "      <td>4.932623e+01</td>\n",
       "      <td>4.930909e+01</td>\n",
       "      <td>4.928840e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>4.905638e+01</td>\n",
       "      <td>4.898140e+01</td>\n",
       "      <td>4.888844e+01</td>\n",
       "      <td>4.878478e+01</td>\n",
       "      <td>4.867694e+01</td>\n",
       "      <td>4.857140e+01</td>\n",
       "      <td>4.847690e+01</td>\n",
       "      <td>4.839363e+01</td>\n",
       "      <td>4.831365e+01</td>\n",
       "      <td>4.822997e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>4.721414e+01</td>\n",
       "      <td>4.716715e+01</td>\n",
       "      <td>4.713068e+01</td>\n",
       "      <td>4.709980e+01</td>\n",
       "      <td>4.707624e+01</td>\n",
       "      <td>4.705161e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>4.699589e+01</td>\n",
       "      <td>4.704955e+01</td>\n",
       "      <td>4.710607e+01</td>\n",
       "      <td>4.716643e+01</td>\n",
       "      <td>4.719096e+01</td>\n",
       "      <td>4.723143e+01</td>\n",
       "      <td>4.732410e+01</td>\n",
       "      <td>4.738763e+01</td>\n",
       "      <td>4.742843e+01</td>\n",
       "      <td>4.746047e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1085 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Series Name        Series Code  \\\n",
       "0                            Population, total        SP.POP.TOTL   \n",
       "1                            Population, total        SP.POP.TOTL   \n",
       "2                            Population, total        SP.POP.TOTL   \n",
       "3                            Population, total        SP.POP.TOTL   \n",
       "4                            Population, total        SP.POP.TOTL   \n",
       "...                                        ...                ...   \n",
       "1080  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1081  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1082  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1083  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1084  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "\n",
       "               Country Name Country Code          2022          2021  \\\n",
       "0               Afghanistan          AFG  4.112877e+07  4.009946e+07   \n",
       "1                   Albania          ALB  2.775634e+06  2.811666e+06   \n",
       "2                   Algeria          DZA  4.490322e+07  4.417797e+07   \n",
       "3            American Samoa          ASM  4.427300e+04  4.503500e+04   \n",
       "4                   Andorra          AND  7.982400e+04  7.903400e+04   \n",
       "...                     ...          ...           ...           ...   \n",
       "1080  Virgin Islands (U.S.)          VIR  4.661338e+01  4.676444e+01   \n",
       "1081     West Bank and Gaza          PSE  4.989368e+01  4.987784e+01   \n",
       "1082            Yemen, Rep.          YEM  5.051903e+01  5.053852e+01   \n",
       "1083                 Zambia          ZMB  4.934460e+01  4.934495e+01   \n",
       "1084               Zimbabwe          ZWE  4.721414e+01  4.716715e+01   \n",
       "\n",
       "              2020          2019          2018          2017  ...  \\\n",
       "0     3.897223e+07  3.776950e+07  3.668678e+07  3.564342e+07  ...   \n",
       "1     2.837849e+06  2.854191e+06  2.866376e+06  2.873457e+06  ...   \n",
       "2     4.345167e+07  4.270537e+07  4.192701e+07  4.113655e+07  ...   \n",
       "3     4.618900e+04  4.732100e+04  4.842400e+04  4.946300e+04  ...   \n",
       "4     7.770000e+04  7.634300e+04  7.501300e+04  7.383700e+04  ...   \n",
       "...            ...           ...           ...           ...  ...   \n",
       "1080  4.691464e+01  4.705731e+01  4.718591e+01  4.731421e+01  ...   \n",
       "1081  4.985896e+01  4.983554e+01  4.981137e+01  4.978597e+01  ...   \n",
       "1082  5.055432e+01  5.057132e+01  5.059661e+01  5.061696e+01  ...   \n",
       "1083  4.933830e+01  4.932623e+01  4.930909e+01  4.928840e+01  ...   \n",
       "1084  4.713068e+01  4.709980e+01  4.707624e+01  4.705161e+01  ...   \n",
       "\n",
       "              2010          2009          2008          2007          2006  \\\n",
       "0     2.818967e+07  2.738531e+07  2.642720e+07  2.590330e+07  2.544294e+07   \n",
       "1     2.913021e+06  2.927519e+06  2.947314e+06  2.970017e+06  2.992547e+06   \n",
       "2     3.585634e+07  3.519604e+07  3.456959e+07  3.398383e+07  3.343508e+07   \n",
       "3     5.484900e+04  5.536600e+04  5.589100e+04  5.638300e+04  5.683700e+04   \n",
       "4     7.151900e+04  7.385200e+04  7.605500e+04  7.816800e+04  8.022100e+04   \n",
       "...            ...           ...           ...           ...           ...   \n",
       "1080  4.780106e+01  4.783454e+01  4.787006e+01  4.787760e+01  4.787070e+01   \n",
       "1081  4.987634e+01  4.989868e+01  4.992145e+01  4.994763e+01  4.998332e+01   \n",
       "1082  5.059417e+01  5.058269e+01  5.056888e+01  5.055363e+01  5.053901e+01   \n",
       "1083  4.905638e+01  4.898140e+01  4.888844e+01  4.878478e+01  4.867694e+01   \n",
       "1084  4.699589e+01  4.704955e+01  4.710607e+01  4.716643e+01  4.719096e+01   \n",
       "\n",
       "              2005          2004          2003          2002          2001  \n",
       "0     2.441119e+07  2.355355e+07  2.264513e+07  2.100026e+07  1.968863e+07  \n",
       "1     3.011487e+06  3.026939e+06  3.039616e+06  3.051010e+06  3.060173e+06  \n",
       "2     3.295669e+07  3.251019e+07  3.205588e+07  3.162470e+07  3.120098e+07  \n",
       "3     5.725400e+04  5.762600e+04  5.794100e+04  5.817700e+04  5.832400e+04  \n",
       "4     7.982600e+04  7.693300e+04  7.390700e+04  7.084900e+04  6.782000e+04  \n",
       "...            ...           ...           ...           ...           ...  \n",
       "1080  4.785267e+01  4.782515e+01  4.778913e+01  4.775493e+01  4.772513e+01  \n",
       "1081  5.002865e+01  5.008995e+01  5.016754e+01  5.024820e+01  5.032163e+01  \n",
       "1082  5.052251e+01  5.050272e+01  5.048167e+01  5.045994e+01  5.043724e+01  \n",
       "1083  4.857140e+01  4.847690e+01  4.839363e+01  4.831365e+01  4.822997e+01  \n",
       "1084  4.723143e+01  4.732410e+01  4.738763e+01  4.742843e+01  4.746047e+01  \n",
       "\n",
       "[1085 rows x 26 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(r\"C:\\prodigy infotech\\worldpopulationdata.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# *Checking 5 rows of Dataset :*\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Series Name</th>\n",
       "      <th>Series Code</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>2022</th>\n",
       "      <th>2021</th>\n",
       "      <th>2020</th>\n",
       "      <th>2019</th>\n",
       "      <th>2018</th>\n",
       "      <th>2017</th>\n",
       "      <th>...</th>\n",
       "      <th>2010</th>\n",
       "      <th>2009</th>\n",
       "      <th>2008</th>\n",
       "      <th>2007</th>\n",
       "      <th>2006</th>\n",
       "      <th>2005</th>\n",
       "      <th>2004</th>\n",
       "      <th>2003</th>\n",
       "      <th>2002</th>\n",
       "      <th>2001</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>41128771.0</td>\n",
       "      <td>40099462.0</td>\n",
       "      <td>38972230.0</td>\n",
       "      <td>37769499.0</td>\n",
       "      <td>36686784.0</td>\n",
       "      <td>35643418.0</td>\n",
       "      <td>...</td>\n",
       "      <td>28189672.0</td>\n",
       "      <td>27385307.0</td>\n",
       "      <td>26427199.0</td>\n",
       "      <td>25903301.0</td>\n",
       "      <td>25442944.0</td>\n",
       "      <td>24411191.0</td>\n",
       "      <td>23553551.0</td>\n",
       "      <td>22645130.0</td>\n",
       "      <td>21000256.0</td>\n",
       "      <td>19688632.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "      <td>2775634.0</td>\n",
       "      <td>2811666.0</td>\n",
       "      <td>2837849.0</td>\n",
       "      <td>2854191.0</td>\n",
       "      <td>2866376.0</td>\n",
       "      <td>2873457.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2913021.0</td>\n",
       "      <td>2927519.0</td>\n",
       "      <td>2947314.0</td>\n",
       "      <td>2970017.0</td>\n",
       "      <td>2992547.0</td>\n",
       "      <td>3011487.0</td>\n",
       "      <td>3026939.0</td>\n",
       "      <td>3039616.0</td>\n",
       "      <td>3051010.0</td>\n",
       "      <td>3060173.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>DZA</td>\n",
       "      <td>44903225.0</td>\n",
       "      <td>44177969.0</td>\n",
       "      <td>43451666.0</td>\n",
       "      <td>42705368.0</td>\n",
       "      <td>41927007.0</td>\n",
       "      <td>41136546.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35856344.0</td>\n",
       "      <td>35196037.0</td>\n",
       "      <td>34569592.0</td>\n",
       "      <td>33983827.0</td>\n",
       "      <td>33435080.0</td>\n",
       "      <td>32956690.0</td>\n",
       "      <td>32510186.0</td>\n",
       "      <td>32055883.0</td>\n",
       "      <td>31624696.0</td>\n",
       "      <td>31200985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>ASM</td>\n",
       "      <td>44273.0</td>\n",
       "      <td>45035.0</td>\n",
       "      <td>46189.0</td>\n",
       "      <td>47321.0</td>\n",
       "      <td>48424.0</td>\n",
       "      <td>49463.0</td>\n",
       "      <td>...</td>\n",
       "      <td>54849.0</td>\n",
       "      <td>55366.0</td>\n",
       "      <td>55891.0</td>\n",
       "      <td>56383.0</td>\n",
       "      <td>56837.0</td>\n",
       "      <td>57254.0</td>\n",
       "      <td>57626.0</td>\n",
       "      <td>57941.0</td>\n",
       "      <td>58177.0</td>\n",
       "      <td>58324.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>AND</td>\n",
       "      <td>79824.0</td>\n",
       "      <td>79034.0</td>\n",
       "      <td>77700.0</td>\n",
       "      <td>76343.0</td>\n",
       "      <td>75013.0</td>\n",
       "      <td>73837.0</td>\n",
       "      <td>...</td>\n",
       "      <td>71519.0</td>\n",
       "      <td>73852.0</td>\n",
       "      <td>76055.0</td>\n",
       "      <td>78168.0</td>\n",
       "      <td>80221.0</td>\n",
       "      <td>79826.0</td>\n",
       "      <td>76933.0</td>\n",
       "      <td>73907.0</td>\n",
       "      <td>70849.0</td>\n",
       "      <td>67820.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Series Name  Series Code    Country Name Country Code        2022  \\\n",
       "0  Population, total  SP.POP.TOTL     Afghanistan          AFG  41128771.0   \n",
       "1  Population, total  SP.POP.TOTL         Albania          ALB   2775634.0   \n",
       "2  Population, total  SP.POP.TOTL         Algeria          DZA  44903225.0   \n",
       "3  Population, total  SP.POP.TOTL  American Samoa          ASM     44273.0   \n",
       "4  Population, total  SP.POP.TOTL         Andorra          AND     79824.0   \n",
       "\n",
       "         2021        2020        2019        2018        2017  ...  \\\n",
       "0  40099462.0  38972230.0  37769499.0  36686784.0  35643418.0  ...   \n",
       "1   2811666.0   2837849.0   2854191.0   2866376.0   2873457.0  ...   \n",
       "2  44177969.0  43451666.0  42705368.0  41927007.0  41136546.0  ...   \n",
       "3     45035.0     46189.0     47321.0     48424.0     49463.0  ...   \n",
       "4     79034.0     77700.0     76343.0     75013.0     73837.0  ...   \n",
       "\n",
       "         2010        2009        2008        2007        2006        2005  \\\n",
       "0  28189672.0  27385307.0  26427199.0  25903301.0  25442944.0  24411191.0   \n",
       "1   2913021.0   2927519.0   2947314.0   2970017.0   2992547.0   3011487.0   \n",
       "2  35856344.0  35196037.0  34569592.0  33983827.0  33435080.0  32956690.0   \n",
       "3     54849.0     55366.0     55891.0     56383.0     56837.0     57254.0   \n",
       "4     71519.0     73852.0     76055.0     78168.0     80221.0     79826.0   \n",
       "\n",
       "         2004        2003        2002        2001  \n",
       "0  23553551.0  22645130.0  21000256.0  19688632.0  \n",
       "1   3026939.0   3039616.0   3051010.0   3060173.0  \n",
       "2  32510186.0  32055883.0  31624696.0  31200985.0  \n",
       "3     57626.0     57941.0     58177.0     58324.0  \n",
       "4     76933.0     73907.0     70849.0     67820.0  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# *Checking last 5 rows of dataset :*\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Series Name</th>\n",
       "      <th>Series Code</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>2022</th>\n",
       "      <th>2021</th>\n",
       "      <th>2020</th>\n",
       "      <th>2019</th>\n",
       "      <th>2018</th>\n",
       "      <th>2017</th>\n",
       "      <th>...</th>\n",
       "      <th>2010</th>\n",
       "      <th>2009</th>\n",
       "      <th>2008</th>\n",
       "      <th>2007</th>\n",
       "      <th>2006</th>\n",
       "      <th>2005</th>\n",
       "      <th>2004</th>\n",
       "      <th>2003</th>\n",
       "      <th>2002</th>\n",
       "      <th>2001</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1080</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Virgin Islands (U.S.)</td>\n",
       "      <td>VIR</td>\n",
       "      <td>46.613382</td>\n",
       "      <td>46.764444</td>\n",
       "      <td>46.914637</td>\n",
       "      <td>47.057307</td>\n",
       "      <td>47.185912</td>\n",
       "      <td>47.314214</td>\n",
       "      <td>...</td>\n",
       "      <td>47.801059</td>\n",
       "      <td>47.834540</td>\n",
       "      <td>47.870063</td>\n",
       "      <td>47.877604</td>\n",
       "      <td>47.870702</td>\n",
       "      <td>47.852669</td>\n",
       "      <td>47.825150</td>\n",
       "      <td>47.789128</td>\n",
       "      <td>47.754932</td>\n",
       "      <td>47.725126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1081</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>PSE</td>\n",
       "      <td>49.893678</td>\n",
       "      <td>49.877839</td>\n",
       "      <td>49.858957</td>\n",
       "      <td>49.835542</td>\n",
       "      <td>49.811374</td>\n",
       "      <td>49.785969</td>\n",
       "      <td>...</td>\n",
       "      <td>49.876336</td>\n",
       "      <td>49.898677</td>\n",
       "      <td>49.921445</td>\n",
       "      <td>49.947631</td>\n",
       "      <td>49.983323</td>\n",
       "      <td>50.028649</td>\n",
       "      <td>50.089953</td>\n",
       "      <td>50.167544</td>\n",
       "      <td>50.248196</td>\n",
       "      <td>50.321633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1082</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>YEM</td>\n",
       "      <td>50.519031</td>\n",
       "      <td>50.538516</td>\n",
       "      <td>50.554317</td>\n",
       "      <td>50.571320</td>\n",
       "      <td>50.596614</td>\n",
       "      <td>50.616964</td>\n",
       "      <td>...</td>\n",
       "      <td>50.594170</td>\n",
       "      <td>50.582692</td>\n",
       "      <td>50.568876</td>\n",
       "      <td>50.553633</td>\n",
       "      <td>50.539012</td>\n",
       "      <td>50.522514</td>\n",
       "      <td>50.502720</td>\n",
       "      <td>50.481666</td>\n",
       "      <td>50.459941</td>\n",
       "      <td>50.437238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>49.344602</td>\n",
       "      <td>49.344951</td>\n",
       "      <td>49.338301</td>\n",
       "      <td>49.326233</td>\n",
       "      <td>49.309087</td>\n",
       "      <td>49.288400</td>\n",
       "      <td>...</td>\n",
       "      <td>49.056379</td>\n",
       "      <td>48.981404</td>\n",
       "      <td>48.888443</td>\n",
       "      <td>48.784780</td>\n",
       "      <td>48.676944</td>\n",
       "      <td>48.571398</td>\n",
       "      <td>48.476900</td>\n",
       "      <td>48.393634</td>\n",
       "      <td>48.313646</td>\n",
       "      <td>48.229968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>Population, male (% of total population)</td>\n",
       "      <td>SP.POP.TOTL.MA.ZS</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>47.214139</td>\n",
       "      <td>47.167153</td>\n",
       "      <td>47.130679</td>\n",
       "      <td>47.099796</td>\n",
       "      <td>47.076238</td>\n",
       "      <td>47.051613</td>\n",
       "      <td>...</td>\n",
       "      <td>46.995893</td>\n",
       "      <td>47.049546</td>\n",
       "      <td>47.106068</td>\n",
       "      <td>47.166435</td>\n",
       "      <td>47.190963</td>\n",
       "      <td>47.231433</td>\n",
       "      <td>47.324096</td>\n",
       "      <td>47.387633</td>\n",
       "      <td>47.428426</td>\n",
       "      <td>47.460469</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Series Name        Series Code  \\\n",
       "1080  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1081  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1082  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1083  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "1084  Population, male (% of total population)  SP.POP.TOTL.MA.ZS   \n",
       "\n",
       "               Country Name Country Code       2022       2021       2020  \\\n",
       "1080  Virgin Islands (U.S.)          VIR  46.613382  46.764444  46.914637   \n",
       "1081     West Bank and Gaza          PSE  49.893678  49.877839  49.858957   \n",
       "1082            Yemen, Rep.          YEM  50.519031  50.538516  50.554317   \n",
       "1083                 Zambia          ZMB  49.344602  49.344951  49.338301   \n",
       "1084               Zimbabwe          ZWE  47.214139  47.167153  47.130679   \n",
       "\n",
       "           2019       2018       2017  ...       2010       2009       2008  \\\n",
       "1080  47.057307  47.185912  47.314214  ...  47.801059  47.834540  47.870063   \n",
       "1081  49.835542  49.811374  49.785969  ...  49.876336  49.898677  49.921445   \n",
       "1082  50.571320  50.596614  50.616964  ...  50.594170  50.582692  50.568876   \n",
       "1083  49.326233  49.309087  49.288400  ...  49.056379  48.981404  48.888443   \n",
       "1084  47.099796  47.076238  47.051613  ...  46.995893  47.049546  47.106068   \n",
       "\n",
       "           2007       2006       2005       2004       2003       2002  \\\n",
       "1080  47.877604  47.870702  47.852669  47.825150  47.789128  47.754932   \n",
       "1081  49.947631  49.983323  50.028649  50.089953  50.167544  50.248196   \n",
       "1082  50.553633  50.539012  50.522514  50.502720  50.481666  50.459941   \n",
       "1083  48.784780  48.676944  48.571398  48.476900  48.393634  48.313646   \n",
       "1084  47.166435  47.190963  47.231433  47.324096  47.387633  47.428426   \n",
       "\n",
       "           2001  \n",
       "1080  47.725126  \n",
       "1081  50.321633  \n",
       "1082  50.437238  \n",
       "1083  48.229968  \n",
       "1084  47.460469  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Basic info of Dataset :_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1085 entries, 0 to 1084\n",
      "Data columns (total 26 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Series Name   1085 non-null   object \n",
      " 1   Series Code   1085 non-null   object \n",
      " 2   Country Name  1085 non-null   object \n",
      " 3   Country Code  1085 non-null   object \n",
      " 4   2022          1085 non-null   float64\n",
      " 5   2021          1085 non-null   float64\n",
      " 6   2020          1085 non-null   float64\n",
      " 7   2019          1085 non-null   float64\n",
      " 8   2018          1085 non-null   float64\n",
      " 9   2017          1085 non-null   float64\n",
      " 10  2016          1085 non-null   float64\n",
      " 11  2015          1085 non-null   float64\n",
      " 12  2014          1085 non-null   float64\n",
      " 13  2013          1085 non-null   float64\n",
      " 14  2012          1085 non-null   float64\n",
      " 15  2011          1085 non-null   float64\n",
      " 16  2010          1085 non-null   float64\n",
      " 17  2009          1085 non-null   float64\n",
      " 18  2008          1085 non-null   float64\n",
      " 19  2007          1085 non-null   float64\n",
      " 20  2006          1085 non-null   float64\n",
      " 21  2005          1085 non-null   float64\n",
      " 22  2004          1085 non-null   float64\n",
      " 23  2003          1085 non-null   float64\n",
      " 24  2002          1085 non-null   float64\n",
      " 25  2001          1085 non-null   float64\n",
      "dtypes: float64(22), object(4)\n",
      "memory usage: 220.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>2022</th>\n",
       "      <th>2021</th>\n",
       "      <th>2020</th>\n",
       "      <th>2019</th>\n",
       "      <th>2018</th>\n",
       "      <th>2017</th>\n",
       "      <th>2016</th>\n",
       "      <th>2015</th>\n",
       "      <th>2014</th>\n",
       "      <th>2013</th>\n",
       "      <th>...</th>\n",
       "      <th>2010</th>\n",
       "      <th>2009</th>\n",
       "      <th>2008</th>\n",
       "      <th>2007</th>\n",
       "      <th>2006</th>\n",
       "      <th>2005</th>\n",
       "      <th>2004</th>\n",
       "      <th>2003</th>\n",
       "      <th>2002</th>\n",
       "      <th>2001</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "      <td>1.085000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.461378e+07</td>\n",
       "      <td>1.449711e+07</td>\n",
       "      <td>1.437307e+07</td>\n",
       "      <td>1.422876e+07</td>\n",
       "      <td>1.407966e+07</td>\n",
       "      <td>1.392568e+07</td>\n",
       "      <td>1.376711e+07</td>\n",
       "      <td>1.360705e+07</td>\n",
       "      <td>1.344625e+07</td>\n",
       "      <td>1.328368e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>1.280537e+07</td>\n",
       "      <td>1.265031e+07</td>\n",
       "      <td>1.249535e+07</td>\n",
       "      <td>1.234099e+07</td>\n",
       "      <td>1.218858e+07</td>\n",
       "      <td>1.203685e+07</td>\n",
       "      <td>1.188626e+07</td>\n",
       "      <td>1.173626e+07</td>\n",
       "      <td>1.158653e+07</td>\n",
       "      <td>1.143598e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.832944e+07</td>\n",
       "      <td>7.801505e+07</td>\n",
       "      <td>7.763257e+07</td>\n",
       "      <td>7.712985e+07</td>\n",
       "      <td>7.657562e+07</td>\n",
       "      <td>7.596457e+07</td>\n",
       "      <td>7.528760e+07</td>\n",
       "      <td>7.461740e+07</td>\n",
       "      <td>7.394894e+07</td>\n",
       "      <td>7.325356e+07</td>\n",
       "      <td>...</td>\n",
       "      <td>7.113128e+07</td>\n",
       "      <td>7.047509e+07</td>\n",
       "      <td>6.982016e+07</td>\n",
       "      <td>6.915934e+07</td>\n",
       "      <td>6.849229e+07</td>\n",
       "      <td>6.780708e+07</td>\n",
       "      <td>6.710041e+07</td>\n",
       "      <td>6.638386e+07</td>\n",
       "      <td>6.565651e+07</td>\n",
       "      <td>6.490862e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.749000e+01</td>\n",
       "      <td>2.732503e+01</td>\n",
       "      <td>2.735104e+01</td>\n",
       "      <td>2.676295e+01</td>\n",
       "      <td>2.573928e+01</td>\n",
       "      <td>2.508394e+01</td>\n",
       "      <td>2.464721e+01</td>\n",
       "      <td>2.474106e+01</td>\n",
       "      <td>2.540718e+01</td>\n",
       "      <td>2.594943e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>2.425072e+01</td>\n",
       "      <td>2.339422e+01</td>\n",
       "      <td>2.356750e+01</td>\n",
       "      <td>2.520779e+01</td>\n",
       "      <td>2.831990e+01</td>\n",
       "      <td>3.096426e+01</td>\n",
       "      <td>3.129133e+01</td>\n",
       "      <td>3.137472e+01</td>\n",
       "      <td>3.146521e+01</td>\n",
       "      <td>3.156689e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.034029e+01</td>\n",
       "      <td>5.035172e+01</td>\n",
       "      <td>5.034171e+01</td>\n",
       "      <td>5.033040e+01</td>\n",
       "      <td>5.033917e+01</td>\n",
       "      <td>5.033041e+01</td>\n",
       "      <td>5.033966e+01</td>\n",
       "      <td>5.033554e+01</td>\n",
       "      <td>5.032504e+01</td>\n",
       "      <td>5.033767e+01</td>\n",
       "      <td>...</td>\n",
       "      <td>5.034833e+01</td>\n",
       "      <td>5.036836e+01</td>\n",
       "      <td>5.037388e+01</td>\n",
       "      <td>5.036880e+01</td>\n",
       "      <td>5.038085e+01</td>\n",
       "      <td>5.037186e+01</td>\n",
       "      <td>5.036210e+01</td>\n",
       "      <td>5.039432e+01</td>\n",
       "      <td>5.039371e+01</td>\n",
       "      <td>5.038254e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.465500e+05</td>\n",
       "      <td>1.463660e+05</td>\n",
       "      <td>1.461650e+05</td>\n",
       "      <td>1.459570e+05</td>\n",
       "      <td>1.457520e+05</td>\n",
       "      <td>1.441350e+05</td>\n",
       "      <td>1.406060e+05</td>\n",
       "      <td>1.371850e+05</td>\n",
       "      <td>1.349620e+05</td>\n",
       "      <td>1.328960e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>1.263090e+05</td>\n",
       "      <td>1.244660e+05</td>\n",
       "      <td>1.228070e+05</td>\n",
       "      <td>1.209490e+05</td>\n",
       "      <td>1.190890e+05</td>\n",
       "      <td>1.171330e+05</td>\n",
       "      <td>1.152950e+05</td>\n",
       "      <td>1.136960e+05</td>\n",
       "      <td>1.134500e+05</td>\n",
       "      <td>1.136410e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.903468e+06</td>\n",
       "      <td>5.856733e+06</td>\n",
       "      <td>5.831404e+06</td>\n",
       "      <td>5.814422e+06</td>\n",
       "      <td>5.774185e+06</td>\n",
       "      <td>5.686999e+06</td>\n",
       "      <td>5.629265e+06</td>\n",
       "      <td>5.544490e+06</td>\n",
       "      <td>5.524552e+06</td>\n",
       "      <td>5.480089e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>5.267970e+06</td>\n",
       "      <td>5.187356e+06</td>\n",
       "      <td>5.100083e+06</td>\n",
       "      <td>5.062560e+06</td>\n",
       "      <td>5.007301e+06</td>\n",
       "      <td>4.989584e+06</td>\n",
       "      <td>4.813244e+06</td>\n",
       "      <td>4.758988e+06</td>\n",
       "      <td>4.698968e+06</td>\n",
       "      <td>4.535518e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.417173e+09</td>\n",
       "      <td>1.412360e+09</td>\n",
       "      <td>1.411100e+09</td>\n",
       "      <td>1.407745e+09</td>\n",
       "      <td>1.402760e+09</td>\n",
       "      <td>1.396215e+09</td>\n",
       "      <td>1.387790e+09</td>\n",
       "      <td>1.379860e+09</td>\n",
       "      <td>1.371860e+09</td>\n",
       "      <td>1.363240e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>1.337705e+09</td>\n",
       "      <td>1.331260e+09</td>\n",
       "      <td>1.324655e+09</td>\n",
       "      <td>1.317885e+09</td>\n",
       "      <td>1.311020e+09</td>\n",
       "      <td>1.303720e+09</td>\n",
       "      <td>1.296075e+09</td>\n",
       "      <td>1.288400e+09</td>\n",
       "      <td>1.280400e+09</td>\n",
       "      <td>1.271850e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               2022          2021          2020          2019          2018  \\\n",
       "count  1.085000e+03  1.085000e+03  1.085000e+03  1.085000e+03  1.085000e+03   \n",
       "mean   1.461378e+07  1.449711e+07  1.437307e+07  1.422876e+07  1.407966e+07   \n",
       "std    7.832944e+07  7.801505e+07  7.763257e+07  7.712985e+07  7.657562e+07   \n",
       "min    2.749000e+01  2.732503e+01  2.735104e+01  2.676295e+01  2.573928e+01   \n",
       "25%    5.034029e+01  5.035172e+01  5.034171e+01  5.033040e+01  5.033917e+01   \n",
       "50%    1.465500e+05  1.463660e+05  1.461650e+05  1.459570e+05  1.457520e+05   \n",
       "75%    5.903468e+06  5.856733e+06  5.831404e+06  5.814422e+06  5.774185e+06   \n",
       "max    1.417173e+09  1.412360e+09  1.411100e+09  1.407745e+09  1.402760e+09   \n",
       "\n",
       "               2017          2016          2015          2014          2013  \\\n",
       "count  1.085000e+03  1.085000e+03  1.085000e+03  1.085000e+03  1.085000e+03   \n",
       "mean   1.392568e+07  1.376711e+07  1.360705e+07  1.344625e+07  1.328368e+07   \n",
       "std    7.596457e+07  7.528760e+07  7.461740e+07  7.394894e+07  7.325356e+07   \n",
       "min    2.508394e+01  2.464721e+01  2.474106e+01  2.540718e+01  2.594943e+01   \n",
       "25%    5.033041e+01  5.033966e+01  5.033554e+01  5.032504e+01  5.033767e+01   \n",
       "50%    1.441350e+05  1.406060e+05  1.371850e+05  1.349620e+05  1.328960e+05   \n",
       "75%    5.686999e+06  5.629265e+06  5.544490e+06  5.524552e+06  5.480089e+06   \n",
       "max    1.396215e+09  1.387790e+09  1.379860e+09  1.371860e+09  1.363240e+09   \n",
       "\n",
       "       ...          2010          2009          2008          2007  \\\n",
       "count  ...  1.085000e+03  1.085000e+03  1.085000e+03  1.085000e+03   \n",
       "mean   ...  1.280537e+07  1.265031e+07  1.249535e+07  1.234099e+07   \n",
       "std    ...  7.113128e+07  7.047509e+07  6.982016e+07  6.915934e+07   \n",
       "min    ...  2.425072e+01  2.339422e+01  2.356750e+01  2.520779e+01   \n",
       "25%    ...  5.034833e+01  5.036836e+01  5.037388e+01  5.036880e+01   \n",
       "50%    ...  1.263090e+05  1.244660e+05  1.228070e+05  1.209490e+05   \n",
       "75%    ...  5.267970e+06  5.187356e+06  5.100083e+06  5.062560e+06   \n",
       "max    ...  1.337705e+09  1.331260e+09  1.324655e+09  1.317885e+09   \n",
       "\n",
       "               2006          2005          2004          2003          2002  \\\n",
       "count  1.085000e+03  1.085000e+03  1.085000e+03  1.085000e+03  1.085000e+03   \n",
       "mean   1.218858e+07  1.203685e+07  1.188626e+07  1.173626e+07  1.158653e+07   \n",
       "std    6.849229e+07  6.780708e+07  6.710041e+07  6.638386e+07  6.565651e+07   \n",
       "min    2.831990e+01  3.096426e+01  3.129133e+01  3.137472e+01  3.146521e+01   \n",
       "25%    5.038085e+01  5.037186e+01  5.036210e+01  5.039432e+01  5.039371e+01   \n",
       "50%    1.190890e+05  1.171330e+05  1.152950e+05  1.136960e+05  1.134500e+05   \n",
       "75%    5.007301e+06  4.989584e+06  4.813244e+06  4.758988e+06  4.698968e+06   \n",
       "max    1.311020e+09  1.303720e+09  1.296075e+09  1.288400e+09  1.280400e+09   \n",
       "\n",
       "               2001  \n",
       "count  1.085000e+03  \n",
       "mean   1.143598e+07  \n",
       "std    6.490862e+07  \n",
       "min    3.156689e+01  \n",
       "25%    5.038254e+01  \n",
       "50%    1.136410e+05  \n",
       "75%    4.535518e+06  \n",
       "max    1.271850e+09  \n",
       "\n",
       "[8 rows x 22 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Columns ,Shape and Rows of Dataset :_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Series Name', 'Series Code', 'Country Name', 'Country Code', '2022',\n",
       "       '2021', '2020', '2019', '2018', '2017', '2016', '2015', '2014', '2013',\n",
       "       '2012', '2011', '2010', '2009', '2008', '2007', '2006', '2005', '2004',\n",
       "       '2003', '2002', '2001'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series Name      object\n",
       "Series Code      object\n",
       "Country Name     object\n",
       "Country Code     object\n",
       "2022            float64\n",
       "2021            float64\n",
       "2020            float64\n",
       "2019            float64\n",
       "2018            float64\n",
       "2017            float64\n",
       "2016            float64\n",
       "2015            float64\n",
       "2014            float64\n",
       "2013            float64\n",
       "2012            float64\n",
       "2011            float64\n",
       "2010            float64\n",
       "2009            float64\n",
       "2008            float64\n",
       "2007            float64\n",
       "2006            float64\n",
       "2005            float64\n",
       "2004            float64\n",
       "2003            float64\n",
       "2002            float64\n",
       "2001            float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1085, 26)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Checking duplicate vales :_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "        ...  \n",
       "1080    False\n",
       "1081    False\n",
       "1082    False\n",
       "1083    False\n",
       "1084    False\n",
       "Length: 1085, dtype: bool"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\25470550.py:1: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n",
      "  df = df.fillna(method=\"ffill\")  # type: ignore\n"
     ]
    }
   ],
   "source": [
    "df = df.fillna(method=\"ffill\")  # type: ignore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum().any()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Unique values_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Afghanistan', 'Albania', 'Algeria', 'American Samoa', 'Andorra',\n",
       "       'Angola', 'Antigua and Barbuda', 'Argentina', 'Armenia', 'Aruba',\n",
       "       'Australia', 'Austria', 'Azerbaijan', 'Bahamas, The', 'Bahrain',\n",
       "       'Bangladesh', 'Barbados', 'Belarus', 'Belgium', 'Belize', 'Benin',\n",
       "       'Bermuda', 'Bhutan', 'Bolivia', 'Bosnia and Herzegovina',\n",
       "       'Botswana', 'Brazil', 'British Virgin Islands',\n",
       "       'Brunei Darussalam', 'Bulgaria', 'Burkina Faso', 'Burundi',\n",
       "       'Cabo Verde', 'Cambodia', 'Cameroon', 'Canada', 'Cayman Islands',\n",
       "       'Central African Republic', 'Chad', 'Channel Islands', 'Chile',\n",
       "       'China', 'Colombia', 'Comoros', 'Congo, Dem. Rep.', 'Congo, Rep.',\n",
       "       'Costa Rica', \"Cote d'Ivoire\", 'Croatia', 'Cuba', 'Curacao',\n",
       "       'Cyprus', 'Czechia', 'Denmark', 'Djibouti', 'Dominica',\n",
       "       'Dominican Republic', 'Ecuador', 'Egypt, Arab Rep.', 'El Salvador',\n",
       "       'Equatorial Guinea', 'Eritrea', 'Estonia', 'Eswatini', 'Ethiopia',\n",
       "       'Faroe Islands', 'Fiji', 'Finland', 'France', 'French Polynesia',\n",
       "       'Gabon', 'Gambia, The', 'Georgia', 'Germany', 'Ghana', 'Gibraltar',\n",
       "       'Greece', 'Greenland', 'Grenada', 'Guam', 'Guatemala', 'Guinea',\n",
       "       'Guinea-Bissau', 'Guyana', 'Haiti', 'Honduras',\n",
       "       'Hong Kong SAR, China', 'Hungary', 'Iceland', 'India', 'Indonesia',\n",
       "       'Iran, Islamic Rep.', 'Iraq', 'Ireland', 'Isle of Man', 'Israel',\n",
       "       'Italy', 'Jamaica', 'Japan', 'Jordan', 'Kazakhstan', 'Kenya',\n",
       "       'Kiribati', \"Korea, Dem. People's Rep.\", 'Korea, Rep.', 'Kosovo',\n",
       "       'Kuwait', 'Kyrgyz Republic', 'Lao PDR', 'Latvia', 'Lebanon',\n",
       "       'Lesotho', 'Liberia', 'Libya', 'Liechtenstein', 'Lithuania',\n",
       "       'Luxembourg', 'Macao SAR, China', 'Madagascar', 'Malawi',\n",
       "       'Malaysia', 'Maldives', 'Mali', 'Malta', 'Marshall Islands',\n",
       "       'Mauritania', 'Mauritius', 'Mexico', 'Micronesia, Fed. Sts.',\n",
       "       'Moldova', 'Monaco', 'Mongolia', 'Montenegro', 'Morocco',\n",
       "       'Mozambique', 'Myanmar', 'Namibia', 'Nauru', 'Nepal',\n",
       "       'Netherlands', 'New Caledonia', 'New Zealand', 'Nicaragua',\n",
       "       'Niger', 'Nigeria', 'North Macedonia', 'Northern Mariana Islands',\n",
       "       'Norway', 'Oman', 'Pakistan', 'Palau', 'Panama',\n",
       "       'Papua New Guinea', 'Paraguay', 'Peru', 'Philippines', 'Poland',\n",
       "       'Portugal', 'Puerto Rico', 'Qatar', 'Romania',\n",
       "       'Russian Federation', 'Rwanda', 'Samoa', 'San Marino',\n",
       "       'Sao Tome and Principe', 'Saudi Arabia', 'Senegal', 'Serbia',\n",
       "       'Seychelles', 'Sierra Leone', 'Singapore',\n",
       "       'Sint Maarten (Dutch part)', 'Slovak Republic', 'Slovenia',\n",
       "       'Solomon Islands', 'Somalia', 'South Africa', 'South Sudan',\n",
       "       'Spain', 'Sri Lanka', 'St. Kitts and Nevis', 'St. Lucia',\n",
       "       'St. Martin (French part)', 'St. Vincent and the Grenadines',\n",
       "       'Sudan', 'Suriname', 'Sweden', 'Switzerland',\n",
       "       'Syrian Arab Republic', 'Tajikistan', 'Tanzania', 'Thailand',\n",
       "       'Timor-Leste', 'Togo', 'Tonga', 'Trinidad and Tobago', 'Tunisia',\n",
       "       'Turkiye', 'Turkmenistan', 'Turks and Caicos Islands', 'Tuvalu',\n",
       "       'Uganda', 'Ukraine', 'United Arab Emirates', 'United Kingdom',\n",
       "       'United States', 'Uruguay', 'Uzbekistan', 'Vanuatu',\n",
       "       'Venezuela, RB', 'Vietnam', 'Virgin Islands (U.S.)',\n",
       "       'West Bank and Gaza', 'Yemen, Rep.', 'Zambia', 'Zimbabwe'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Country Name\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['AFG', 'ALB', 'DZA', 'ASM', 'AND', 'AGO', 'ATG', 'ARG', 'ARM',\n",
       "       'ABW', 'AUS', 'AUT', 'AZE', 'BHS', 'BHR', 'BGD', 'BRB', 'BLR',\n",
       "       'BEL', 'BLZ', 'BEN', 'BMU', 'BTN', 'BOL', 'BIH', 'BWA', 'BRA',\n",
       "       'VGB', 'BRN', 'BGR', 'BFA', 'BDI', 'CPV', 'KHM', 'CMR', 'CAN',\n",
       "       'CYM', 'CAF', 'TCD', 'CHI', 'CHL', 'CHN', 'COL', 'COM', 'COD',\n",
       "       'COG', 'CRI', 'CIV', 'HRV', 'CUB', 'CUW', 'CYP', 'CZE', 'DNK',\n",
       "       'DJI', 'DMA', 'DOM', 'ECU', 'EGY', 'SLV', 'GNQ', 'ERI', 'EST',\n",
       "       'SWZ', 'ETH', 'FRO', 'FJI', 'FIN', 'FRA', 'PYF', 'GAB', 'GMB',\n",
       "       'GEO', 'DEU', 'GHA', 'GIB', 'GRC', 'GRL', 'GRD', 'GUM', 'GTM',\n",
       "       'GIN', 'GNB', 'GUY', 'HTI', 'HND', 'HKG', 'HUN', 'ISL', 'IND',\n",
       "       'IDN', 'IRN', 'IRQ', 'IRL', 'IMN', 'ISR', 'ITA', 'JAM', 'JPN',\n",
       "       'JOR', 'KAZ', 'KEN', 'KIR', 'PRK', 'KOR', 'XKX', 'KWT', 'KGZ',\n",
       "       'LAO', 'LVA', 'LBN', 'LSO', 'LBR', 'LBY', 'LIE', 'LTU', 'LUX',\n",
       "       'MAC', 'MDG', 'MWI', 'MYS', 'MDV', 'MLI', 'MLT', 'MHL', 'MRT',\n",
       "       'MUS', 'MEX', 'FSM', 'MDA', 'MCO', 'MNG', 'MNE', 'MAR', 'MOZ',\n",
       "       'MMR', 'NAM', 'NRU', 'NPL', 'NLD', 'NCL', 'NZL', 'NIC', 'NER',\n",
       "       'NGA', 'MKD', 'MNP', 'NOR', 'OMN', 'PAK', 'PLW', 'PAN', 'PNG',\n",
       "       'PRY', 'PER', 'PHL', 'POL', 'PRT', 'PRI', 'QAT', 'ROU', 'RUS',\n",
       "       'RWA', 'WSM', 'SMR', 'STP', 'SAU', 'SEN', 'SRB', 'SYC', 'SLE',\n",
       "       'SGP', 'SXM', 'SVK', 'SVN', 'SLB', 'SOM', 'ZAF', 'SSD', 'ESP',\n",
       "       'LKA', 'KNA', 'LCA', 'MAF', 'VCT', 'SDN', 'SUR', 'SWE', 'CHE',\n",
       "       'SYR', 'TJK', 'TZA', 'THA', 'TLS', 'TGO', 'TON', 'TTO', 'TUN',\n",
       "       'TUR', 'TKM', 'TCA', 'TUV', 'UGA', 'UKR', 'ARE', 'GBR', 'USA',\n",
       "       'URY', 'UZB', 'VUT', 'VEN', 'VNM', 'VIR', 'PSE', 'YEM', 'ZMB',\n",
       "       'ZWE'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Country Code\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Population, total', 'Population, female', 'Population, male',\n",
       "       'Population, female (% of total population)',\n",
       "       'Population, male (% of total population)'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Series Name\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['SP.POP.TOTL', 'SP.POP.TOTL.FE.IN', 'SP.POP.TOTL.MA.IN',\n",
       "       'SP.POP.TOTL.FE.ZS', 'SP.POP.TOTL.MA.ZS'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Series Code\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Removing Unneccessary ccolumns_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop([\"Series Name\", \"Country Code\"], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Series Code', 'Country Name', '2022', '2021', '2020', '2019', '2018',\n",
       "       '2017', '2016', '2015', '2014', '2013', '2012', '2011', '2010', '2009',\n",
       "       '2008', '2007', '2006', '2005', '2004', '2003', '2002', '2001'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Extraction of top 15 countries with highest population with respect to 2023:_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 15 countries that are most populated according to 2023 :\n",
      "89                  India\n",
      "41                  China\n",
      "206         United States\n",
      "90              Indonesia\n",
      "149              Pakistan\n",
      "144               Nigeria\n",
      "26                 Brazil\n",
      "15             Bangladesh\n",
      "161    Russian Federation\n",
      "127                Mexico\n",
      "98                  Japan\n",
      "64               Ethiopia\n",
      "155           Philippines\n",
      "58       Egypt, Arab Rep.\n",
      "44       Congo, Dem. Rep.\n",
      "Name: Country Name, dtype: object\n"
     ]
    }
   ],
   "source": [
    "total_population = df[df[\"Series Code\"] == \"SP.POP.TOTL\"]\n",
    "\n",
    "total_population_sorted_desc = total_population.sort_values(by=\"2022\", ascending=False)\n",
    "top_15_countries = total_population_sorted_desc.head(15)\n",
    "print(\"Top 15 countries that are most populated according to 2023 :\")\n",
    "print(top_15_countries[\"Country Name\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\1305970652.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x=\"2022\", y=\"Country Name\", data=top_15_countries, palette=\"coolwarm\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\1305970652.py:13: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x=\"2001\", y=\"Country Name\", data=top_15_countries, palette=\"coolwarm\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "plt.subplot(2, 2, 1)\n",
    "sns.barplot(x=\"2022\", y=\"Country Name\", data=top_15_countries, palette=\"coolwarm\")\n",
    "plt.title(\n",
    "    \"Top 15 populated countries in 2022\",\n",
    ")\n",
    "plt.xlabel(\"Population(in bn)\", fontsize=10)\n",
    "plt.ylabel(\"Country Name\", fontsize=10)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(15, 8))\n",
    "plt.subplot(2, 2, 2)\n",
    "sns.barplot(x=\"2001\", y=\"Country Name\", data=top_15_countries, palette=\"coolwarm\")\n",
    "plt.title(\"Top 15 populateed countries in 2001\")\n",
    "plt.xlabel(\"Population(in bn)\", fontsize=10)\n",
    "plt.ylabel(\"Country Name\", fontsize=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bottom 15 populated countries :\n",
      "201                       Tuvalu\n",
      "137                        Nauru\n",
      "150                        Palau\n",
      "27        British Virgin Islands\n",
      "183     St. Martin (French part)\n",
      "75                     Gibraltar\n",
      "164                   San Marino\n",
      "130                       Monaco\n",
      "114                Liechtenstein\n",
      "124             Marshall Islands\n",
      "172    Sint Maarten (Dutch part)\n",
      "3                 American Samoa\n",
      "200     Turks and Caicos Islands\n",
      "181          St. Kitts and Nevis\n",
      "146     Northern Mariana Islands\n",
      "Name: Country Name, dtype: object\n"
     ]
    }
   ],
   "source": [
    "total_population_sorted_asc = total_population.sort_values(\"2022\", ascending=True)\n",
    "bottom_15_countries = total_population_sorted_asc.head(15)\n",
    "\n",
    "print(\"Bottom 15 populated countries :\")\n",
    "print(bottom_15_countries[\"Country Name\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\1128048229.py:3: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x=\"2022\", y=\"Country Name\", data=bottom_15_countries, palette=\"coolwarm\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\1128048229.py:11: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x=\"2001\", y=\"Country Name\", data=bottom_15_countries, palette=\"coolwarm\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "plt.subplot(2, 2, 1)\n",
    "sns.barplot(x=\"2022\", y=\"Country Name\", data=bottom_15_countries, palette=\"coolwarm\")\n",
    "plt.title(\"Bottom 15 populated countries in 2022\")\n",
    "plt.xlabel(\"Population\", fontsize=10)\n",
    "plt.ylabel(\"country Nmae\", fontsize=10)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(15, 8))\n",
    "plt.subplot(2, 2, 2)\n",
    "sns.barplot(x=\"2001\", y=\"Country Name\", data=bottom_15_countries, palette=\"coolwarm\")\n",
    "plt.title(\"Bottom 15 populated countries in 2001\")\n",
    "plt.xlabel(\"Population\", fontsize=10)\n",
    "plt.ylabel(\"country Nmae\", fontsize=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Extraction of top 15 countries with highest male population:_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "523                 India\n",
      "475                 China\n",
      "640         United States\n",
      "524             Indonesia\n",
      "583              Pakistan\n",
      "578               Nigeria\n",
      "460                Brazil\n",
      "449            Bangladesh\n",
      "595    Russian Federation\n",
      "561                Mexico\n",
      "498              Ethiopia\n",
      "532                 Japan\n",
      "589           Philippines\n",
      "492      Egypt, Arab Rep.\n",
      "478      Congo, Dem. Rep.\n",
      "Name: Country Name, dtype: object\n"
     ]
    }
   ],
   "source": [
    "male_population = df[df[\"Series Code\"] == \"SP.POP.TOTL.MA.IN\"]\n",
    "male_population_sort = male_population.sort_values(by=\"2022\", ascending=False)\n",
    "male_population_highest = male_population_sort.head(15)\n",
    "print(male_population_highest[\"Country Name\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Extraction of top 15 countries with highest female population_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "258                 China\n",
      "306                 India\n",
      "423         United States\n",
      "307             Indonesia\n",
      "366              Pakistan\n",
      "243                Brazil\n",
      "361               Nigeria\n",
      "232            Bangladesh\n",
      "378    Russian Federation\n",
      "344                Mexico\n",
      "315                 Japan\n",
      "281              Ethiopia\n",
      "372           Philippines\n",
      "275      Egypt, Arab Rep.\n",
      "261      Congo, Dem. Rep.\n",
      "Name: Country Name, dtype: object\n"
     ]
    }
   ],
   "source": [
    "female_population = df[df[\"Series Code\"] == \"SP.POP.TOTL.FE.IN\"]\n",
    "female_population_sort = female_population.sort_values(by=\"2022\", ascending=False)\n",
    "female_population_highest = female_population_sort.head(15)\n",
    "print(female_population_highest[\"Country Name\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Creating bar pot for male and female population_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\3265618145.py:4: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\3265618145.py:15: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# bar plot for male population\n",
    "plt.figure(figsize=(15, 8))\n",
    "plt.subplot(2, 2, 1)\n",
    "sns.barplot(\n",
    "    x=\"2022\", y=\"Country Name\", data=male_population_highest, palette=\"coolwarm\"\n",
    ")\n",
    "plt.xlabel(\"Male Population\")\n",
    "plt.ylabel(\"Countries\")\n",
    "plt.title(\"Top 15 countries with higest male population(2022)\")\n",
    "plt.show()\n",
    "\n",
    "# bar plot for female population\n",
    "plt.figure(figsize=(15, 8))\n",
    "plt.subplot(2, 2, 2)\n",
    "sns.barplot(\n",
    "    x=\"2022\", y=\"Country Name\", data=female_population_highest, palette=\"coolwarm\"\n",
    ")\n",
    "plt.title(\"Top 15 countries with highest female population(2022)\")\n",
    "plt.xlabel(\" Female population\")\n",
    "plt.ylabel(\"Countries\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Extraction of top 15 countries with lowest male and female population_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Countries with lowest male populatuion\n",
      "580     Northern Mariana Islands\n",
      "606    Sint Maarten (Dutch part)\n",
      "615          St. Kitts and Nevis\n",
      "634     Turks and Caicos Islands\n",
      "437               American Samoa\n",
      "558             Marshall Islands\n",
      "548                Liechtenstein\n",
      "564                       Monaco\n",
      "598                   San Marino\n",
      "509                    Gibraltar\n",
      "617     St. Martin (French part)\n",
      "461       British Virgin Islands\n",
      "584                        Palau\n",
      "571                        Nauru\n",
      "635                       Tuvalu\n",
      "Name: Country Name, dtype: object\n"
     ]
    }
   ],
   "source": [
    "male_lowest_pop = male_population_sort.tail(15)\n",
    "print(\"Countries with lowest male populatuion\")\n",
    "print(male_lowest_pop[\"Country Name\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "countries with lowest female poulation (2022)\n",
      "398          St. Kitts and Nevis\n",
      "363     Northern Mariana Islands\n",
      "417     Turks and Caicos Islands\n",
      "220               American Samoa\n",
      "341             Marshall Islands\n",
      "389    Sint Maarten (Dutch part)\n",
      "331                Liechtenstein\n",
      "347                       Monaco\n",
      "381                   San Marino\n",
      "400     St. Martin (French part)\n",
      "292                    Gibraltar\n",
      "244       British Virgin Islands\n",
      "367                        Palau\n",
      "354                        Nauru\n",
      "418                       Tuvalu\n",
      "Name: Country Name, dtype: object\n"
     ]
    }
   ],
   "source": [
    "female_lowest_population = female_population_sort.tail(15)\n",
    "print(\"countries with lowest female poulation (2022)\")\n",
    "print(female_lowest_population[\"Country Name\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\4247327348.py:4: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(x=\"2022\", y=\"Country Name\", data=male_lowest_pop, palette=\"viridis\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\22831\\AppData\\Local\\Temp\\ipykernel_19220\\4247327348.py:14: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.barplot(\n"
     ]
    },
    {
     "data": {
      "image/png": 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/Q4YM4fLlyyxbtkzj2YCnT59iaGiYpX7m8zi5TeOaOXMmhw4dYtasWbn+O5KSkkKnTp0wNjZm1qxZ2dYpXrw49+/ff+N5/Nf8O57eEkL8K92+fZuyZctqJBGAckv39u3bGuVOTk5Z2nB2diYlJYV79+5hbW2dbT83b97ExcUl1wfTtI1FG3Z2dhrbmf/TfPjwIebm5nlqw8HB4Y11rl+/jlqtzvY6Aejr6yttjRgxggULFrBhwwYaNmxImzZt+PTTT5XkPycNGzYkKCiIp0+fcuzYMWxsbKhRowaenp4cO3aMFi1acPz4cTp37pyn88rJ69cMXl43bZPjzPfNxcUlyz5XV1f279+vPLTcsGFDXrx4wcmTJ7G1tSU+Pp6GDRvy+++/ayT4bm5uyoeF69evAyjJ8+sy319DQ0Nmz57NyJEjKVOmDB999BGtW7emV69eOf7evq3r168THR2tMeXpVfHx8Rrbr1/rzN8BW1vbbMtffQ9iY2OZNGkSO3fuzPLe5PY8R15/V9/k9eMdHR3R0dFRpkbdvn0bHR0d5cHPTNbW1lhaWmb5u65UqVKW+e3Ozs7Ay7nx+fFerVu3jvnz53PlyhXS0tKU8rz8jWdH23PU5m9L/dqzUK+bO3cuq1evZtq0abRq1Upjn7GxcZZnAADlGYlXPxy+avPmzUyYMIF+/frxxRdf5Nh3eno6Xbt25fLly+zdu5eyZctmW0+tVv8nv4PhTSTBF0KIV+T0P4rc7iDo6upmW/6m/3m+Kqf/Gb4qIyMDlUrF3r17s+0zcy1rePlwbEBAADt27ODAgQMMHTqU4OBgfvnlF8qXL59jHw0aNCAtLY2TJ09y7NgxZSSwYcOGHDt2jCtXrnDv3j2NEcK3kR/XTFteXl4YGRlx9OhR7OzsKF26NM7OzjRs2JAVK1aQmprKsWPHNEZ4MzIygJfz8LNL/l79UDls2DD8/PzYvn07+/fvZ+LEiQQHB/Pzzz9TvXr1fDuPjIwMPDw8WLBgQbb7X0/cc7rWb3oP0tPTadGiBQ8ePGDMmDFUrlwZExMT/vrrLwICApRrk1OMef1d1UZOf5/5meC9zb8Bmb7//nsCAgJo164do0aNonTp0ujq6hIcHKzxwH9+xvW6vPxtlSxZEnj5YS6nfw9CQ0MZM2YMAwcOZMKECVn229jYcPjw4SwJdlxcHEC2CfnBgwfp1asXvr6+rFq1KtfzGDBgALt27WLDhg05fsDOPIe8zOP/r5EEXwhRYCpUqMChQ4d4/Pixxsj5lStXlP2vyhwtfdW1a9coVqxYjqOV8HJU79SpU6SlpeU4MpjXWDJH319/CPBdRvghfxIQR0dH1Go1Dg4Oyqhjbjw8PPDw8GDChAnKQ6erVq1i+vTpOR5Tu3ZtDAwMOHbsGMeOHVNWw2nUqBGrV68mPDxc2c7N+xpRy3zfrl69mmXflStXKFWqFCYmJsDL1Txq167NsWPHsLOz0/jwkpqayoYNG/jnn380zi1zGlHp0qWzrDiSHUdHR0aOHMnIkSO5fv061apVY/78+Xz//fdA/v0eXLhwgWbNmhXodb506RLXrl1j3bp1Gg/V5uWBVG1/V3Ny/fp1jZHvGzdukJGRoUw5qlChAhkZGVy/fl3jYc9//vmHR48eZfk35saNG1kS0mvXrgEobb76b8Cr00fy8m/Ajz/+SMWKFQkLC9PoY/LkyRr1tHnftD3HvKhcuTIAt27dwsPDI8v+HTt20L9/f9q3b8/y5cuzbaNatWp8++23REdHayzleurUKWX/q06dOoW/vz9eXl5s2bIl1zuuo0aNIiQkhEWLFikP7Ofk1q1beHp65lrnv0jm4AshCkyrVq1IT09X1kjOtHDhQlQqFS1bttQoP3nypMY81Tt37rBjxw4++eSTHEel4OVc4vv372fpB/7/qFVeYzE3N6dUqVJZludcsWJFHs44ZyYmJu/8ra7t27dHV1eXKVOmZBnpVqvVyrzapKQkXrx4obHfw8MDHR2dbG+pv8rIyIhatWqxceNGYmNjNZLgp0+fsmTJEhwdHbGxscm1ncykuqC/ydbGxoZq1aqxbt06jb5+++03Dhw4kGVaQcOGDTl16hSHDx9Wzq1UqVK4uroye/ZspU4mb29vzM3NmTlzpsZ0i0z37t0DXs4Vfn35RkdHR8zMzDSueX78HnTu3Jm//vqL1atXZ9n39OlT5RmDd5X5N/fq75parWbx4sVvPDavv6tv8npyuXTpUgDl7zXz/V20aJFGvcy7G76+vhrlf//9N9u2bVO2k5KS+O6776hWrZpyhybzQ92r/wZkLnP7Jtlds1OnTinPr2TKXA0mL78L2p5jXtSsWRMDAwPOnj2bZd/Ro0fp2rUrjRo1YsOGDejoZJ8qtm3bFn19fY1/G9VqNatWraJcuXIaS2NGR0fj6+uLvb09u3btyvWO5dy5c5k3bx5ff/01X331Va7nkZiYyM2bN7NdhvO/TkbwhRAFxs/Pj6ZNmzJ+/HhiYmLw9PTkwIED7Nixg2HDhmk8ZAkvlzL09vZm6NChGBoaKv/jeHXJyez06tWL7777jhEjRnD69GkaNmzIkydPOHToEIMGDaJt27ZaxdK/f39mzZpF//798fLy4ujRo8oo39uqWbMmhw4dYsGCBZQtWxYHB4csa62/iaOjI9OnT2fcuHHExMTQrl07zMzMuHXrFtu2beOzzz4jMDCQn3/+mSFDhtCpUyecnZ158eIF69evR1dXlw4dOryxn4YNGzJr1iwsLCyU0b3SpUvj4uLC1atXlTX833S+AOPHj6dr167o6+vj5+enJP75ae7cubRs2ZK6devSr18/nj59ytKlS7GwsND43gJ4eW4zZszgzp07Gol8o0aN+N///oe9vb3GlAVzc3NWrlxJz549qVGjBl27dsXKyorY2Fh2795N/fr1WbZsGdeuXaNZs2Z07twZNzc39PT02LZtG//884/GUoY1a9Zk5cqVTJ8+nUqVKlG6dOlcpx9kp2fPnmzZsoWBAwdy+PBh6tevT3p6OleuXGHLli3s378fLy+vt7uYr6hcuTKOjo4EBgby119/YW5uzk8//ZSn5yTy+rv6Jrdu3aJNmzb4+Phw8uRJvv/+e7p3766M2Hp6etK7d2+++eYbHj16ROPGjTl9+jTr1q2jXbt2NG3aVKM9Z2dn+vXrx5kzZyhTpgxr167ln3/+ISQkRKnzySefYGdnR79+/Rg1ahS6urqsXbtWed9z07p1a8LCwvD398fX15dbt26xatUq3NzcSE5OVuoZGxvj5ubG5s2bcXZ2pkSJEri7u+Pu7p6lTW3PMS+MjIz45JNPOHToEFOnTlXKb9++TZs2bVCpVHTs2JGtW7dqHFe1alWqVq0KQPny5Rk2bBhz584lLS2NWrVqsX37do4dO8aGDRuUDzuPHz/G29ubhw8fMmrUqCwPBTs6OlK3bl0Atm3bxujRo3FycsLV1VW585WpRYsWlClTRtk+dOgQarWatm3ban0Nirz3tVyPEKLoe32ZTLX65TKDw4cPV5ctW1atr6+vdnJyUs+dO1fj68nV6pfL+Q0ePFj9/fffq52cnNSGhobq6tWrqw8fPpynvlNSUtTjx49XOzg4qPX19dXW1tbqjh07qm/evKl1LCkpKep+/fqpLSws1GZmZurOnTur4+Pjc1wm8969exrHZ7ec3pUrV9SNGjVSGxsbqwFlycyc2nh13+t++ukndYMGDdQmJiZqExMTdeXKldWDBw9WX716Va1Wq9V//PGHum/fvmpHR0e1kZGRukSJEuqmTZuqDx06lKdruXv3bjWgbtmypUZ5//791YB6zZo1WY55/dqo1Wr1tGnT1OXKlVPr6OhoXI/M9/p1FSpUyHYp0VfltIzpoUOH1PXr11cbGxurzc3N1X5+furLly9nOT4pKUmtq6urNjMzU7948UIp//7779VAjkvxHT58WO3t7a22sLBQGxkZqR0dHdUBAQHKsq73799XDx48WF25cmW1iYmJ2sLCQl2nTh31li1bNNq5e/eu2tfXV21mZqYG3rhkZnbLZKrVavXz58/Vs2fPVlepUkVtaGioLl68uLpmzZrqKVOmqBMTE5V62V3rzGv4+pKehw8fzrK86uXLl9XNmzdXm5qaqkuVKqUeMGCAsqTpq+/B2/6u5iSzvcuXL6s7duyoNjMzUxcvXlw9ZMgQ9dOnTzXqpqWlqadMmaL87dva2qrHjRunfvbsWbbXcv/+/eqqVauqDQ0N1ZUrV852Odlz586p69SpozYwMFDb2dmpFyxYkKdlMjMyMtQzZ85UV6hQQfk3bNeuXerevXurK1SooNHHiRMn1DVr1lQbGBho/P1kdy21PcfXvR6nWq1Wh4WFqVUqlTo2NlYpy/wdyOn1+t94enq6cr4GBgbqKlWqqL///nuNOpm/bzm9Xv2bzzz3nF6v//+gS5cu6gYNGmQ5X6FWq9TqAnyiSQgh8kilUml85bkQ4r8rKCiIKVOmcO/evXx7gNLe3h53d3d27dqVL+3926Wnp+Pm5kbnzp2ZNm1aYYejtbt37+Lg4MCmTZtkBD8bMgdfCCGEEOI/RldXl6lTp7J8+XKN6UP/FosWLcLDw0OS+xxIgi+EEEII8R/UpUsXHjx48NbLlhamWbNmcfr06cIO44MlCb4QQgghhBBFiMzBF0IIIYQQogiREXwhhBBCCCGKEEnwhRBCCCGEKELki66EKGAZGRn8/fffmJmZFejXygshhBCi6FCr1Tx+/JiyZcvm+I3COZEEX4gC9vfff2Nra1vYYQghhBDiX+jOnTsa37CdF5LgC1HAzMzMgJd/oObm5oUcjRBCCCH+DZKSkrC1tVXyCG1Igi9EAcucltO74Rj0dAwKORohhBBC5If9N0PeSz9vM71XHrIVQgghhBCiCJEEXwghhBBCiCJEEnwhhBBCCCGKEEnwi4gmTZowbNiwwg7jnahUKrZv317YYQAQEBBAu3btCjsMIYQQQgitSYKfT+7du8cXX3yBnZ0dhoaGWFtb4+3tTWRkpFLnbRPY7JLNH3/8ESMjI+bPnw9AWFgY06ZNU/bb29uzaNEijWNCQ0OxtLTUuv8PRUBAACqVilmzZmmUb9++Pd/Xl1+8eDGhoaH52qYQQgghxPsgq+jkkw4dOvD8+XPWrVtHxYoV+eeffwgPDychISHf+/r2228ZPHgwq1atok+fPgCUKFEi3/v5EBkZGTF79mw+//xzihcvXmD9WFhYFFjbQgghhBAFSUbw88GjR484duwYs2fPpmnTplSoUIHatWszbtw42rRpA7wcUQfw9/dHpVIp29qaM2cOX375JZs2bVKSe9CcotOkSRNu377N8OHDUalUqFQqIiIi6NOnD4mJiUpZUFAQACtWrMDJyQkjIyPKlClDx44dc+w/ISGBbt26Ua5cOYoVK4aHhwcbN27UqNOkSROGDh3K6NGjKVGiBNbW1kpfma5fv06jRo0wMjLCzc2NgwcP5un8mzdvjrW1NcHBwbnWO378OA0bNsTY2BhbW1uGDh3KkydPAPj666+pU6dOlmM8PT2ZOnUqkPWuyY8//oiHhwfGxsaULFmS5s2bK+0JIYQQQnxIJMHPB6amppiamrJ9+3ZSU1OzrXPmzBkAQkJCiIuLU7a1MWbMGKZNm8auXbvw9/fPsV5YWBjly5dn6tSpxMXFERcXR7169Vi0aBHm5uZKWWBgIGfPnmXo0KFMnTqVq1evsm/fPho1apRj28+ePaNmzZrs3r2b3377jc8++4yePXty+vRpjXrr1q3DxMSEU6dOMWfOHKZOnaok8RkZGbRv3x4DAwNOnTrFqlWrGDNmTJ6uga6uLjNnzmTp0qX8+eef2da5efMmPj4+dOjQgYsXL7J582aOHz/OkCFDAOjRowenT5/m5s2byjG///47Fy9epHv37lnai4uLo1u3bvTt25fo6GgiIiJo3749arU62/5TU1NJSkrSeAkhhBBCvC+S4OcDPT09QkNDWbduHZaWltSvX5+vv/6aixcvKnWsrKwAsLS0xNraWtnOq7179zJnzhx27NhBs2bNcq1bokQJdHV1MTMzw9raGmtrawwMDLCwsEClUillpqamxMbGYmJiQuvWralQoQLVq1dn6NChObZdrlw5AgMDqVatGhUrVuTLL7/Ex8eHLVu2aNSrWrUqkydPxsnJiV69euHl5UV4eDgAhw4d4sqVK3z33Xd4enrSqFEjZs6cmedr4e/vT7Vq1Zg8eXK2+4ODg+nRowfDhg3DycmJevXqsWTJEr777juePXtGlSpV8PT05IcfflCO2bBhA3Xq1KFSpUpZ2ouLi+PFixe0b98ee3t7PDw8GDRoEKampjn2b2FhobxsbW3zfG5CCCGEEO9KEvx80qFDB/7++2927tyJj48PERER1KhRI98e1KxatSr29vZMnjyZ5OTkfGkToEWLFlSoUIGKFSvSs2dPNmzYQEpKSo7109PTmTZtGh4eHpQoUQJTU1P2799PbGxslnhfZWNjQ3x8PADR0dHY2tpStmxZZX/dunW1inv27NmsW7eO6OjoLPsuXLhAaGiocmfF1NQUb29vMjIyuHXrFvByFD8zwVer1WzcuJEePXpk25enpyfNmjXDw8ODTp06sXr1ah4+fJhjbOPGjSMxMVF53blzR6tzE0IIIYR4F5Lg5yMjIyNatGjBxIkTOXHiBAEBATmOMmurXLlyRERE8Ndff+Hj48Pjx4/zpV0zMzN+/fVXNm7ciI2NDZMmTcLT05NHjx5lW3/u3LksXryYMWPGcPjwYaKiovD29ub58+ca9fT19TW2VSoVGRkZ+RIzQKNGjfD29mbcuHFZ9iUnJ/P5558TFRWlvC5cuMD169dxdHQEoFu3bly9epVff/2VEydOcOfOHbp06ZJtX7q6uhw8eJC9e/fi5ubG0qVLcXFxUT4svM7Q0BBzc3ONlxBCCCHE+yIJfgFyc3PTeBBTX1+f9PT0t26vQoUKHDlyhLt3774xyTcwMMjSV3Zl8HKKUfPmzZkzZw4XL14kJiaGn3/+Odt2IyMjadu2LZ9++imenp5UrFiRa9euaXUerq6u3Llzh7i4OKXsl19+0aoNgFmzZvF///d/nDx5UqO8Ro0aXL58mUqVKmV5GRgYAFC+fHkaN27Mhg0b2LBhAy1atKB06dI59qVSqahfvz5Tpkzh/PnzGBgYsG3bNq1jFkIIIYQoaJLg54OEhAQ+/vhjvv/+ey5evMitW7fYunUrc+bMoW3btko9e3t7wsPDuXv3rjLF4/Tp01SuXJm//vorT33Z2toSERFBfHw83t7eOT7AaW9vz9GjR/nrr7+4f/++UpacnEx4eDj3798nJSWFXbt2sWTJEqKiorh9+zbfffcdGRkZuLi4ZNuuk5MTBw8e5MSJE0RHR/P555/zzz//aHO5aN68Oc7OzvTu3ZsLFy5w7Ngxxo8fr1UbAB4eHvTo0YMlS5ZolI8ZM4YTJ04wZMgQoqKiuH79Ojt27FAess3Uo0cPNm3axNatW3OcngNw6tQpZs6cydmzZ4mNjSUsLIx79+7h6uqqdcxCCCGEEAVNEvx8YGpqSp06dVi4cCGNGjXC3d2diRMnMmDAAJYtW6bUmz9/PgcPHsTW1pbq1asDkJKSwtWrV0lLS8tzf+XLlyciIoL79+/nmORPnTqVmJgYHB0dlQd669Wrx8CBA+nSpQtWVlbMmTMHS0tLwsLC+Pjjj3F1dWXVqlVs3LiRKlWqZNv3hAkTqFGjBt7e3jRp0gRra2utv/FVR0eHbdu28fTpU2rXrk3//v2ZMWOGVm28ep6vT/2pWrUqR44c4dq1azRs2JDq1aszadIkjTn/AB07diQhIYGUlJRcz8Hc3JyjR4/SqlUrnJ2dmTBhAvPnz6dly5ZvFbMQQgghREFSqXNa608IkS+SkpKwsLDgY/vu6OkYFHY4QgghhMgH+2+GFGj7mflDYmKi1s/zyQi+EEIIIYQQRYgk+EIIIYQQQhQhkuALIYQQQghRhOgVdgBC/Fdsu7BS1sQXQgghRIGTEXwhhBBCCCGKEEnwhRBCCCGEKEIkwRdCCCGEEKIIkTn4QrwnHT8eh76eYWGHIYQQQvxr7f5lQWGH8K8gI/hCCCGEEEIUIZLgCyGEEEIIUYRIgi+EEEIIIUQRIgm+EEIIIYQQRch/PsEPCAigXbt2hR3GexcaGoqlpWVhh6E1lUrF9u3bC7yfJk2aMGzYsALvRwghhBAiv30wCX5AQAAqlYpZs2ZplG/fvh2VSvXO7cfExKBSqYiKinrntgpS5nUYOHBgln2DBw9GpVIREBDwzv106dKFa9euvXM7+eF9Je1CCCGEEP8FH0yCD2BkZMTs2bN5+PBhvrb7/PnzfG3vTdLT08nIyHjr421tbdm0aRNPnz5Vyp49e8YPP/yAnZ3dO8eXlpaGsbExpUuXfue2hBBCCCHEh+WDSvCbN2+OtbU1wcHBudb76aefqFKlCoaGhtjb2zN//nyN/fb29kybNo1evXphbm7OZ599hoODAwDVq1dHpVLRpEkTjWPmzZuHjY0NJUuWZPDgwaSlpSn7UlNTCQwMpFy5cpiYmFCnTh0iIiKU/ZnTXXbu3ImbmxuGhobExsZib2/PzJkz6du3L2ZmZtjZ2fHNN9+88TrUqFEDW1tbwsLClLKwsDDs7OyoXr26Rt19+/bRoEEDLC0tKVmyJK1bt+bmzZvK/sw7F5s3b6Zx48YYGRmxYcOGLFN0bt68Sdu2bSlTpgympqbUqlWLQ4cOZbmubzqfMWPG4OzsTLFixahYsSITJ07UuJZv8vz5c4YMGYKNjQ1GRkZUqFAh19+HN/UXFBREtWrVWL9+Pfb29lhYWNC1a1ceP36s1Hny5Am9evXC1NQUGxubLL9PACtWrMDJyQkjIyPKlClDx44d83xOQgghhBDv0weV4Ovq6jJz5kyWLl3Kn3/+mW2dc+fO0blzZ7p27cqlS5cICgpi4sSJhIaGatSbN28enp6enD9/nokTJ3L69GkADh06RFxcnEbyfPjwYW7evMnhw4dZt24doaGhGu0NGTKEkydPsmnTJi5evEinTp3w8fHh+vXrSp2UlBRmz57Nt99+y++//66Mjs+fPx8vLy/Onz/PoEGD+OKLL7h69eobr0Xfvn0JCQlRtteuXUufPn2y1Hvy5AkjRozg7NmzhIeHo6Ojg7+/f5Y7CGPHjuWrr74iOjoab2/vLO0kJyfTqlUrwsPDOX/+PD4+Pvj5+REbG6tR703nY2ZmRmhoKJcvX2bx4sWsXr2ahQsXvvF8My1ZsoSdO3eyZcsWrl69yoYNG7C3t8+xfl76u3nzJtu3b2fXrl3s2rWLI0eOaEwFGzVqFEeOHGHHjh0cOHCAiIgIfv31V2X/2bNnGTp0KFOnTuXq1avs27ePRo0a5RhTamoqSUlJGi8hhBBCiPflg/smW39/f6pVq8bkyZNZs2ZNlv0LFiygWbNmTJw4EQBnZ2cuX77M3LlzNeamf/zxx4wcOVLZ1tXVBaBkyZJYW1trtFm8eHGWLVuGrq4ulStXxtfXl/DwcAYMGEBsbCwhISHExsZStmxZAAIDA9m3bx8hISHMnDkTeDntZcWKFXh6emq03apVKwYNGgS8HG1euHAhhw8fxsXFJdfr8OmnnzJu3Dhu374NQGRkJJs2bdK4cwDQoUMHje21a9diZWXF5cuXcXd3V8qHDRtG+/btc+zP09NTI/Zp06axbds2du7cyZAhQ/J8PhMmTFDq2tvbExgYyKZNmxg9enSu55spNjYWJycnGjRogEqlokKFCrnWz0t/GRkZhIaGYmZmBkDPnj0JDw9nxowZJCcns2bNGr7//nuaNWsGwLp16yhfvrxGTCYmJrRu3RozMzMqVKiQ5U7Kq4KDg5kyZUqezlcIIYQQIr99UCP4mWbPns26deuIjo7Osi86Opr69etrlNWvX5/r16+Tnp6ulHl5eeW5vypVqigfAABsbGyIj48H4NKlS6Snp+Ps7IypqanyOnLkiMZUGAMDA6pWrZql7VfLVCoV1tbWStu5sbKywtfXl9DQUEJCQvD19aVUqVJZ6l2/fp1u3bpRsWJFzM3NldHu10fe33Q9kpOTCQwMxNXVFUtLS0xNTYmOjs7SzpvOZ/PmzdSvXx9ra2tMTU2ZMGFCljZyExAQQFRUFC4uLgwdOpQDBw7kWj8v/dnb2yvJPWi+vzdv3uT58+fUqVNH2V+iRAmND2AtWrSgQoUKVKxYkZ49e7JhwwZSUlJyjGncuHEkJiYqrzt37uT5/IUQQggh3tUHmeA3atQIb29vxo0b99ZtmJiY5Lmuvr6+xrZKpVKmuCQnJ6Orq8u5c+eIiopSXtHR0SxevFg5xtjYONvVfnJr+0369u1LaGgo69ato2/fvtnW8fPz48GDB6xevZpTp05x6tQpIOuDxW+6HoGBgWzbto2ZM2dy7NgxoqKi8PDwyNJObudz8uRJevToQatWrdi1axfnz59n/PjxWj3kXKNGDW7dusW0adN4+vQpnTt3znG+e177e5f3AF5OA/r111/ZuHEjNjY2TJo0CU9PTx49epRtfUNDQ8zNzTVeQgghhBDvywc3RSfTrFmzqFatWpapLK6urkRGRmqURUZG4uzsrDEK/zoDAwMAjVH+vKhevTrp6enEx8fTsGFDrY59Vz4+Pjx//hyVSpXtvPmEhASuXr3K6tWrldiOHz/+Vn1FRkYSEBCAv78/8PKDTUxMjFZtnDhxggoVKjB+/HilLHOKkTbMzc3p0qULXbp0oWPHjvj4+PDgwQNKlCiR7/05Ojqir6/PqVOnlBWKHj58yLVr12jcuLFST09Pj+bNm9O8eXMmT56MpaUlP//8c67TnoQQQgghCsMHm+B7eHjQo0cPlixZolE+cuRIatWqxbRp0+jSpQsnT55k2bJlrFixItf2SpcujbGxMfv27aN8+fIYGRlhYWHxxjicnZ3p0aMHvXr1Yv78+VSvXp179+4RHh5O1apV8fX1fafzzI2urq4yTSm7Dy/FixenZMmSfPPNN9jY2BAbG8vYsWPfqi8nJyfCwsLw8/NDpVIxceJErZf6dHJyIjY2lk2bNlGrVi12797Ntm3btGpjwYIF2NjYUL16dXR0dNi6dSvW1tbZfilXfvRnampKv379GDVqFCVLlqR06dKMHz8eHZ3/f3Nr165d/PHHHzRq1IjixYuzZ88eMjIy3vgchRBCCCFEYfggp+hkmjp1apYks0aNGmzZsoVNmzbh7u7OpEmTmDp16hu//ElPT48lS5bwv//9j7Jly9K2bds8xxESEkKvXr0YOXIkLi4utGvXjjNnzuTLmvRvktsUDx0dHTZt2sS5c+dwd3dn+PDhzJ079636WbBgAcWLF6devXr4+fnh7e1NjRo1tGqjTZs2DB8+nCFDhlCtWjVOnDihPAydV2ZmZsyZMwcvLy9q1apFTEwMe/bs0Ui487M/gLlz59KwYUP8/Pxo3rw5DRo0oGbNmsp+S0tLwsLC+Pjjj3F1dWXVqlVs3LiRKlWqaN2XEEIIIURBU6nVanVhByFEUZaUlISFhQUtag5CX8+wsMMRQggh/rV2/7KgsEN4bzLzh8TERK2f5/ugR/CFEEIIIYQQ2pEEXwghhBBCiCLkg33IVoii5sefg2XJTCGEEEIUOBnBF0IIIYQQogiRBF8IIYQQQogiRBJ8IYQQQgghihBJ8IUQQgghhChC5CFbId6Tjh1moK8v6+ALIYQQebF7z9TCDuFfS0bwhRBCCCGEKEIkwRdCCCGEEKIIkQRfCCGEEEKIIuQ/meDb29uzaNGiwg7jjd5XnBEREahUKh49elTgfb2rgIAA2rVrV+D9hIaGYmlpWeD9CCGEEELktw86wVepVLm+goKCCjvEQpeUlMT48eOpXLkyRkZGWFtb07x5c8LCwlCr1Xlqo169esTFxWFhYVHA0WbvfSXtQgghhBD/BR/0KjpxcXHKz5s3b2bSpElcvXpVKTM1NdWqvefPn2NgYJBv8RW2R48e0aBBAxITE5k+fTq1atVCT0+PI0eOMHr0aD7++OM8jUIbGBhgbW1d8AELIYQQQogC90GP4FtbWysvCwsLVCqVsr1q1SoaNGigUX/RokXY29sr25kjwzNmzKBs2bK4uLhk28+3336LpaUl4eHhAPz44494eHhgbGxMyZIlad68OU+ePMn22PT0dPr164eDgwPGxsa4uLiwePFijTqZccybNw8bGxtKlizJ4MGDSUtLU+rEx8fj5+eHsbExDg4ObNiw4Y3X5+uvvyYmJoZTp07Ru3dv3NzccHZ2ZsCAAURFRSkfgNavX4+XlxdmZmZYW1vTvXt34uPjlXaym6ITGRlJkyZNKFasGMWLF8fb25uHDx8CkJqaytChQyldujRGRkY0aNCAM2fOKMc+fPiQHj16YGVlhbGxMU5OToSEhLzxfDJpc/337dtHgwYNsLS0pGTJkrRu3ZqbN28q+2NiYlCpVISFhdG0aVOKFSuGp6cnJ0+e1GgnNDQUOzs7ihUrhr+/PwkJCRr7L1y4QNOmTTEzM8Pc3JyaNWty9uzZPJ+TEEIIIcT78kGP4OeH8PBwzM3NOXjwYLb758yZw5w5czhw4AC1a9cmLi6Obt26MWfOHPz9/Xn8+DHHjh3LcbpLRkYG5cuXZ+vWrZQsWZITJ07w2WefYWNjQ+fOnZV6hw8fxsbGhsOHD3Pjxg26dOlCtWrVGDBgAPDyQ8Dff//N4cOH0dfXZ+jQoRpJeHb9btq0iR49elC2bNks+1+9u5GWlsa0adNwcXEhPj6eESNGEBAQwJ49e7JtOyoqimbNmtG3b18WL16Mnp4ehw8fJj09HYDRo0fz008/sW7dOipUqMCcOXPw9vbmxo0blChRgokTJ3L58mX27t1LqVKluHHjBk+fPs3xXF6l7fV/8uQJI0aMoGrVqiQnJzNp0iT8/f2JiopCR+f/f34dP3488+bNw8nJifHjx9OtWzdu3LiBnp4ep06dol+/fgQHB9OuXTv27dvH5MmTNfrp0aMH1atXZ+XKlejq6hIVFYW+vn62MaWmppKamqpsJyUl5enchRBCCCHyQ5FP8E1MTPj222+znZozZswY1q9fz5EjR6hSpQrwMsF88eIF7du3p0KFCgB4eHjk2L6+vj5TpkxRth0cHDh58iRbtmzRSPCLFy/OsmXL0NXVpXLlyvj6+hIeHs6AAQO4du0ae/fu5fTp09SqVQuANWvW4OrqmmO/9+/f5+HDh1SuXPmN16Bv377KzxUrVmTJkiXUqlWL5OTkbKc5zZkzBy8vL1asWKGUZV6fJ0+esHLlSkJDQ2nZsiUAq1ev5uDBg6xZs4ZRo0YRGxtL9erV8fLyAtC4q/Im2l7/Dh06aGyvXbsWKysrLl++jLu7u1IeGBiIr68vAFOmTKFKlSrcuHGDypUrs3jxYnx8fBg9ejQAzs7OnDhxgn379inHx8bGMmrUKOV6Ozk55RhTcHCwxu+EEEIIIcT79EFP0ckPHh4e2Sb38+fPZ/Xq1Rw/flxJXgE8PT1p1qwZHh4edOrUidWrVytTU3KyfPlyatasiZWVFaampnzzzTfExsZq1KlSpQq6urrKto2NjTJCHx0djZ6eHjVr1lT2V65cOdf583l9gBbg3Llz+Pn5YWdnh5mZGY0bNwbIEmOmzBH87Ny8eZO0tDTq16+vlOnr61O7dm2io6MB+OKLL9i0aRPVqlVj9OjRnDhxIs+xanv9r1+/Trdu3ahYsSLm5ubKh4nXz61q1arKzzY2NgAa179OnToa9evWrauxPWLECPr370/z5s2ZNWuWxjSg140bN47ExETldefOnTefuBBCCCFEPvnXJvg6OjpZktxX57RnMjExyfb4hg0bkp6ezpYtWzTKdXV1OXjwIHv37sXNzY2lS5fi4uLCrVu3sm1n06ZNBAYG0q9fPw4cOEBUVBR9+vTh+fPnGvVen86hUqnIyMh443nmxMrKCktLS65cuZJrvSdPnuDt7Y25uTkbNmzgzJkzbNu2DSBLjJmMjY3fOi6Ali1bcvv2bYYPH87ff/9Ns2bNCAwMzNOx2l5/Pz8/Hjx4wOrVqzl16hSnTp0Csp7bq9dfpVIBaHX9g4KC+P333/H19eXnn3/Gzc1NuY6vMzQ0xNzcXOMlhBBCCPG+/GsTfCsrK+7evauR5EdFReX5+Nq1a7N3715mzpzJvHnzNPapVCrq16/PlClTOH/+PAYGBjkmc5GRkdSrV49BgwZRvXp1KlWqlOvobnYqV67MixcvOHfunFJ29erVXNel19HRoWvXrmzYsIG///47y/7k5GRevHjBlStXSEhIYNasWTRs2JDKlSvnOrcfXo52Zz5w/DpHR0cMDAyIjIxUytLS0jhz5gxubm5KmZWVFb179+b7779n0aJFfPPNN7n2+aq8Xv+EhASuXr3KhAkTaNasGa6urm+825IdV1dX5YNBpl9++SVLPWdnZ4YPH86BAwdo3769Vg8OCyGEEEK8L//aOfhNmjTh3r17zJkzh44dO7Jv3z727t2r1WhpvXr12LNnDy1btkRPT49hw4Zx6tQpwsPD+eSTTyhdujSnTp3i3r17Oc6Hd3Jy4rvvvmP//v04ODiwfv16zpw5g4ODQ57jcHFxwcfHh88//5yVK1cqsbxpJH3GjBlERERQp04dZsyYgZeXF/r6+hw7dozg4GDOnDmDnZ0dBgYGLF26lIEDB/Lbb78xbdq0XNsdN24cHh4eDBo0iIEDB2JgYMDhw4fp1KkTpUqV4osvvmDUqFGUKFECOzs75syZQ0pKCv369QNg0qRJ1KxZkypVqpCamsquXbtyfZ7gVdpc/+LFi1OyZEm++eYbbGxsiI2NZezYsXnq51VDhw6lfv36zJs3j7Zt27J//36N+fdPnz5l1KhRdOzYEQcHB/7880/OnDmTZf6/EEIIIcSH4F87gu/q6sqKFStYvnw5np6enD59Os/TQF7VoEEDdu/ezYQJE1i6dCnm5uYcPXqUVq1a4ezszIQJE5g/f77yQOnrPv/8c9q3b0+XLl2oU6cOCQkJDBo0SOs4QkJCKFu2LI0bN6Z9+/Z89tlnlC5dOtdjSpQowS+//MKnn37K9OnTqV69Og0bNmTjxo3MnTsXCwsLrKysCA0NZevWrbi5uTFr1qwsdyxe5+zszIEDB7hw4QK1a9embt267NixAz29l58HZ82aRYcOHejZsyc1atTgxo0b7N+/n+LFiwMv19UfN24cVatWpVGjRujq6rJp06Y8XQdtrr+Ojg6bNm3i3LlzuLu7M3z4cObOnZunfl710UcfsXr1ahYvXoynpycHDhxgwoQJyn5dXV0SEhLo1asXzs7OdO7cmZYtW8qDtEIIIYT4IKnU2jytKYTQWlJSEhYWFrRoPhp9fcPCDkcIIYT4V9i9Z2phh1CoMvOHxMRErZ/n+9eO4AshhBBCCCGykgRfCCGEEEKIIuRf+5CtEP82P/40XpbMFEIIIUSBkxF8IYQQQgghihBJ8IUQQgghhChCJMEXQgghhBCiCJEEXwghhBBCiCJEHrIV4j1pFzALPX2jwg5DCCGE+KAc2DypsEMocmQEXwghhBBCiCJEEnwhhBBCCCGKEEnwhRBCCCGEKEIkwf+PCwoKolq1aoUdhhBCCCGEyCeS4BeCkydPoquri6+vb2GHQmBgIOHh4YUdBtu2beOjjz7CwsICMzMzqlSpwrBhwwo7LCGEEEKIfx1J8AvBmjVr+PLLLzl69Ch///13ocSgVqt58eIFpqamlCxZslBiyBQeHk6XLl3o0KEDp0+f5ty5c8yYMYO0tLRCjUsIIYQQ4t9IEvz3LDk5mc2bN/PFF1/g6+tLaGioxv6IiAhUKhX79++nevXqGBsb8/HHHxMfH8/evXtxdXXF3Nyc7t27k5KSohyXkZFBcHAwDg4OGBsb4+npyY8//pil3b1791KzZk0MDQ05fvx4tlN01q5dS5UqVTA0NMTGxoYhQ4Yo+xYsWICHhwcmJibY2toyaNAgkpOTlf2hoaFYWlqyf/9+XF1dMTU1xcfHh7i4uByvyf/93/9Rv359Ro0ahYuLC87OzrRr147ly5crdW7evEnbtm0pU6YMpqam1KpVi0OHDmm0Y29vz/Tp0+nVqxempqZUqFCBnTt3cu/ePdq2bYupqSlVq1bl7NmzGsf99NNPyvna29szf/58jf3r16/Hy8sLMzMzrK2t6d69O/Hx8TmejxBCCCFEYZIE/z3bsmULlStXxsXFhU8//ZS1a9eiVquz1AsKCmLZsmWcOHGCO3fu0LlzZxYtWsQPP/zA7t27OXDgAEuXLlXqBwcH891337Fq1Sp+//13hg8fzqeffsqRI0c02h07diyzZs0iOjqaqlWrZul35cqVDB48mM8++4xLly6xc+dOKlWqpOzX0dFhyZIl/P7776xbt46ff/6Z0aNHa7SRkpLCvHnzWL9+PUePHiU2NpbAwMAcr4m1tTW///47v/32W451kpOTadWqFeHh4Zw/fx4fHx/8/PyIjY3VqLdw4ULq16/P+fPn8fX1pWfPnvTq1YtPP/2UX3/9FUdHR3r16qVc83PnztG5c2e6du3KpUuXCAoKYuLEiRofvNLS0pg2bRoXLlxg+/btxMTEEBAQkGOsqampJCUlabyEEEIIId4XlTq77FIUmPr169O5c2e++uorXrx4gY2NDVu3bqVJkybAy5H2pk2bcujQIZo1awbArFmzGDduHDdv3qRixYoADBw4kJiYGPbt20dqaiolSpTg0KFD1K1bV+mrf//+pKSk8MMPPyjtbt++nbZt2yp1goKC2L59O1FRUQCUK1eOPn36MH369Dydz48//sjAgQO5f/8+8HIEv0+fPty4cQNHR0cAVqxYwdSpU7l79262bTx58oTOnTuzZ88eKlSowEcffcQnn3xCjx49MDQ0zLFvd3d3Bg4cqNxhsLe3p2HDhqxfvx6Au3fvYmNjw8SJE5k6dSoAv/zyC3Xr1iUuLg5ra2t69OjBvXv3OHDggNLu6NGj2b17N7///nu2/Z49e5ZatWrx+PFjTE1Ns+wPCgpiypQpWcqb+o+TL7oSQgghXiNfdJW9pKQkLCwsSExMxNzcXKtjZQT/Pbp69SqnT5+mW7duAOjp6dGlSxfWrFmTpe6ro+tlypShWLFiSnKfWZY5TeTGjRukpKTQokULTE1Nldd3333HzZs3Ndr18vLKMb74+Hj+/vtv5YNFdjI/eJQrVw4zMzN69uxJQkKCxnShYsWKKck9gI2NTa5TWkxMTNi9ezc3btxgwoQJmJqaMnLkSGrXrq20m5ycTGBgIK6urlhaWmJqakp0dHSWEfzXrxuAh4dHlrLMeKKjo6lfv75GG/Xr1+f69eukp6cDL0f5/fz8sLOzw8zMjMaNGwNk6TvTuHHjSExMVF537tzJ8dyFEEIIIfKbXmEH8F+yZs0aXrx4QdmyZZUytVqNoaEhy5Ytw8LCQinX19dXflapVBrbmWUZGRkAyhz43bt3U65cOY16r4+Am5iY5BifsbFxrvHHxMTQunVrvvjiC2bMmEGJEiU4fvw4/fr14/nz5xQrVixL7Jmx5uVGkaOjI46OjvTv35/x48fj7OzM5s2b6dOnD4GBgRw8eJB58+ZRqVIljI2N6dixI8+fP9do4/XrllNZ5rV7kydPnuDt7Y23tzcbNmzAysqK2NhYvL29s/SdydDQMNc7D0IIIYQQBUkS/PfkxYsXfPfdd8yfP59PPvlEY1+7du3YuHEjAwcOfKu23dzcMDQ0JDY2VhldfhtmZmbY29sTHh5O06ZNs+w/d+4cGRkZzJ8/Hx2dlzd/tmzZ8tb95cbe3p5ixYrx5MkTACIjIwkICMDf3x94+aEmJibmnftxdXUlMjJSoywyMhJnZ2d0dXW5cuUKCQkJzJo1C1tbW4AsD+kKIYQQQnxIJMF/T3bt2sXDhw/p16+fxkg9QIcOHVizZs1bJ/hmZmYEBgYyfPhwMjIyaNCgAYmJiURGRmJubk7v3r3z3FZQUBADBw6kdOnStGzZksePHxMZGcmXX35JpUqVSEtLY+nSpfj5+REZGcmqVaveKubX+0xJSaFVq1ZUqFCBR48esWTJEtLS0mjRogUATk5OhIWF4efnh0qlYuLEiXkehc/NyJEjqVWrFtOmTaNLly6cPHmSZcuWsWLFCgDs7OwwMDBg6dKlDBw4kN9++41p06a9c79CCCGEEAVF5uC/J2vWrKF58+ZZknt4meCfPXuWixcvvnX706ZNY+LEiQQHB+Pq6oqPjw+7d+/GwcFBq3Z69+7NokWLWLFiBVWqVKF169Zcv34dAE9PTxYsWMDs2bNxd3dnw4YNBAcHv3XMmRo3bswff/xBr169qFy5Mi1btuTu3bscOHAAFxcX4OXynMWLF6devXr4+fnh7e1NjRo13rnvGjVqsGXLFjZt2oS7uzuTJk1i6tSpyio5VlZWhIaGsnXrVtzc3Jg1axbz5s17536FEEIIIQqKrKIjRAHLfApeVtERQgghspJVdLInq+gIIYQQQgghAEnwhRBCCCGEKFIkwRdCCCGEEKIIkVV0hHhPtoeO1XoOnRBCCCGEtmQEXwghhBBCiCJEEnwhhBBCCCGKEEnwhRBCCCGEKEJkDr4Q70nLwbPRM5B18IUQQrwfR9ZMLOwQRCGREXwhhBBCCCGKEEnwhRBCCCGEKEIkwRdCCCGEEKIIkQRfCCGEEEKIIkQSfKGIiIhApVLx6NGjd2rH3t6eRYsWKdsqlYrt27e/U5uZAgICaNeuXb60lZvQ0FAsLS0LvB8hhBBCiPwmCf4HIiAgAJVKxcCBA7PsGzx4MCqVioCAgPcf2HvwvpJ2IYQQQoj/AknwPyC2trZs2rSJp0+fKmXPnj3jhx9+wM7O7p3bT0tLe+c2hBBCCCHEh00S/A9IjRo1sLW1JSwsTCkLCwvDzs6O6tWra9Tdt28fDRo0wNLSkpIlS9K6dWtu3ryp7I+JiUGlUrF582YaN26MkZERGzZs4Pbt2/j5+VG8eHFMTEyoUqUKe/bs0Wj73LlzeHl5UaxYMerVq8fVq1eVfTdv3qRt27aUKVMGU1NTatWqxaFDh/L1Ovz44494eHhgbGxMyZIlad68OU+ePMm2bl6vQ1hYGE2bNqVYsWJ4enpy8uRJjXZCQ0Oxs7OjWLFi+Pv7k5CQoLH/woULNG3aFDMzM8zNzalZsyZnz57N1/MWQgghhMgPkuB/YPr27UtISIiyvXbtWvr06ZOl3pMnTxgxYgRnz54lPDwcHR0d/P39ycjI0Kg3duxYvvrqK6Kjo/H29mbw4MGkpqZy9OhRLl26xOzZszE1NdU4Zvz48cyfP5+zZ8+ip6dH3759lX3Jycm0atWK8PBwzp8/j4+PD35+fsTGxubL+cfFxdGtWzf69u1LdHQ0ERERtG/fHrVanW39vF6H8ePHExgYSFRUFM7OznTr1o0XL14AcOrUKfr168eQIUOIioqiadOmTJ8+XeP4Hj16UL58ec6cOcO5c+cYO3Ys+vr62caUmppKUlKSxksIIYQQ4n2Rb7L9wHz66aeMGzeO27dvAxAZGcmmTZuIiIjQqNehQweN7bVr12JlZcXly5dxd3dXyocNG0b79u2V7djYWDp06ICHhwcAFStWzBLDjBkzaNy4MfDyA4Kvry/Pnj3DyMgIT09PPD09lbrTpk1j27Zt7Ny5kyFDhrzbyfMywX/x4gXt27enQoUKAEqs2cnrdQgMDMTX1xeAKVOmUKVKFW7cuEHlypVZvHgxPj4+jB49GgBnZ2dOnDjBvn37lONjY2MZNWoUlStXBsDJySnHmIKDg5kyZYqWZy6EEEIIkT9kBP8DY2Vlha+vL6GhoYSEhODr60upUqWy1Lt+/TrdunWjYsWKmJubY29vD5BlJN3Ly0tje+jQoUyfPp369eszefJkLl68mKXtqlWrKj/b2NgAEB8fD7wcwQ8MDMTV1RVLS0tMTU2Jjo7OtxF8T09PmjVrhoeHB506dWL16tU8fPgwx/p5vQ65nVN0dDR16tTRqF+3bl2N7REjRtC/f3+aN2/OrFmzNKYBvW7cuHEkJiYqrzt37rz5xIUQQggh8okk+B+gvn37Ehoayrp16zSmx7zKz8+PBw8esHr1ak6dOsWpU6cAeP78uUY9ExMTje3+/fvzxx9/0LNnTy5duoSXlxdLly7VqPPq1BOVSgWgTHkJDAxk27ZtzJw5k2PHjhEVFYWHh0eWft+Wrq4uBw8eZO/evbi5ubF06VJcXFy4detWtvXzeh1yO6e8CAoK4vfff8fX15eff/4ZNzc3tm3blm1dQ0NDzM3NNV5CCCGEEO+LJPgfIB8fH54/f05aWhre3t5Z9ickJHD16lUmTJhAs2bNcHV1zXWU+3W2trYMHDiQsLAwRo4cyerVq/N8bGRkJAEBAfj7++Ph4YG1tTUxMTF5Pj4vVCoV9evXZ8qUKZw/fx4DA4Nsk+l3vQ6ZXF1dlQ8GmX755Zcs9ZydnRk+fDgHDhygffv2Gs9KCCGEEEJ8KGQO/gdIV1eX6Oho5efXFS9enJIlS/LNN99gY2NDbGwsY8eOzVPbw4YNo2XLljg7O/Pw4UMOHz6Mq6trnmNzcnIiLCwMPz8/VCoVEydO1Gok/E1OnTpFeHg4n3zyCaVLl+bUqVPcu3cv2xjf5Tq8aujQodSvX5958+bRtm1b9u/frzH//unTp4waNYqOHTvi4ODAn3/+yZkzZ7LM/xdCCCGE+BDICP4HKrepHTo6OmzatIlz587h7u7O8OHDmTt3bp7aTU9PZ/Dgwbi6uuLj44OzszMrVqzIc1wLFiygePHi1KtXDz8/P7y9valRo0aej38Tc3Nzjh49SqtWrXB2dmbChAnMnz+fli1bZqn7LtfhVR999BGrV69m8eLFeHp6cuDAASZMmKDs19XVJSEhgV69euHs7Eznzp1p2bKlPEgrhBBCiA+SSp3T+oNCiHyRlJSEhYUF9T79Gj0Do8IORwghxH/EkTUTCzsE8Q4y84fExEStn+eTEXwhhBBCCCGKEEnwhRBCCCGEKELkIVsh3pO9y8fIkplCCCGEKHAygi+EEEIIIUQRIgm+EEIIIYQQRYgk+EIIIYQQQhQhkuALIYQQQghRhMhDtkK8J81Gz5Z18IUQQhSok0tk7XshI/hCCCGEEEIUKZLgCyGEEEIIUYRIgi+EEEIIIUQR8sEn+CqViu3btxd2GEVOz549mTlzZmGHoYiIiEClUvHo0aPCDiVX+/bto1q1amRkZBR2KEIIIYQQ2SrUBP/evXt88cUX2NnZYWhoiLW1Nd7e3kRGRip14uLiaNmyZZ7bDA0NxdLSMk/1VCoVrq6uWfZt3boVlUqFvb19nvt9F0FBQVSrVu299AVw4cIF9uzZw9ChQ5WyJk2aoFKpUKlUGBoaUq5cOfz8/AgLC9O6/by+Bx86e3t7Fi1apFHm4+ODvr4+GzZsKJyghBBCCCHeoFAT/A4dOnD+/HnWrVvHtWvX2LlzJ02aNCEhIUGpY21tjaGhYYH0b2JiQnx8PCdPntQoX7NmDXZ2dgXS56vUajUvXrwo8H5et3TpUjp16oSpqalG+YABA4iLi+PmzZv89NNPuLm50bVrVz777LP3HmNhev78ea77AwICWLJkyXuKRgghhBBCO4WW4D969Ihjx44xe/ZsmjZtSoUKFahduzbjxo2jTZs2Sr1Xp+jExMSgUqkICwujadOmFCtWDE9PTyVBj4iIoE+fPiQmJiqj0UFBQTnGoKenR/fu3Vm7dq1S9ueffxIREUH37t016t68eZO2bdtSpkwZTE1NqVWrFocOHdKos379ery8vDAzM8Pa2pru3bsTHx+v7M+chrJ3715q1qyJoaEh33//PVOmTOHChQtKzKGhoco16t+/P1ZWVpibm/Pxxx9z4cIFpb3Mkf/169djb2+PhYUFXbt25fHjxzmec3p6Oj/++CN+fn5Z9hUrVgxra2vKly/PRx99xOzZs/nf//7H6tWrlXPNbipNVFQUKpWKmJiYXN+D1NRUxowZg62tLYaGhlSqVIk1a9ZoxHDu3Dm8vLwoVqwY9erV4+rVqzmeS+bvw6ZNm6hXrx5GRka4u7tz5MgRjfPt168fDg4OGBsb4+LiwuLFizXaCQgIoF27dsyYMYOyZcvi4uJCkyZNuH37NsOHD1fOI5Ofnx9nz57l5s2bOcYmhBBCCFFY3irBX79+PfXr16ds2bLcvn0bgEWLFrFjx448t2FqaoqpqSnbt28nNTVVq/7Hjx9PYGAgUVFRODs7061bN168eEG9evVYtGgR5ubmxMXFERcXR2BgYK5t9e3bly1btpCSkgK8nF7i4+NDmTJlNOolJyfTqlUrwsPDOX/+PD4+Pvj5+REbG6vUSUtLY9q0aVy4cIHt27cTExNDQEBAlj7Hjh3LrFmziI6OpkWLFowcOZIqVaooMXfp0gWATp06ER8fz969ezl37hw1atSgWbNmPHjwQGnr5s2bbN++nV27drFr1y6OHDnCrFmzcjzfixcvkpiYiJeX1xuvM0Dv3r0pXrx4nqfq5PYe9OrVi40bN7JkyRKio6P53//+l+Uuwvjx45k/fz5nz55FT0+Pvn37vrHPUaNGMXLkSM6fP0/dunXx8/NT7gJlZGRQvnx5tm7dyuXLl5k0aRJff/01W7Zs0WgjPDycq1evcvDgQXbt2kVYWBjly5dn6tSpynlksrOzo0yZMhw7dizbeFJTU0lKStJ4CSGEEEK8L1on+CtXrmTEiBG0atWKR48ekZ6eDoClpWWW+cq50dPTIzQ0lHXr1mFpaUn9+vX5+uuvuXjx4huPDQwMxNfXF2dnZ6ZMmcLt27e5ceMGBgYGWFhYoFKpsLa2xtraOksC+brq1atTsWJFfvzxR9RqNaGhodkmlZ6ennz++ee4u7vj5OTEtGnTcHR0ZOfOnUqdvn370rJlSypWrMhHH33EkiVL2Lt3L8nJyRptTZ06lRYtWuDo6Ei5cuUwNTVFT09PidnY2Jjjx49z+vRptm7dipeXF05OTsybNw9LS0t+/PFHpa2MjAxCQ0Nxd3enYcOG9OzZk/Dw8BzP9/bt2+jq6lK6dOk3XmcAHR0dnJ2diYmJyVP9nN6Da9eusWXLFtauXYu/vz8VK1akWbNmyoeZTDNmzKBx48a4ubkxduxYTpw4wbNnz3Ltc8iQIXTo0AFXV1dWrlyJhYWFcmdAX1+fKVOm4OXlhYODAz169KBPnz5ZEnwTExO+/fZbqlSpQpUqVShRogS6urrK3Rhra2uN+q9+uH1dcHAwFhYWysvW1jZP104IIYQQIj9oneAvXbqU1atXM378eHR1dZVyLy8vLl26pFVbHTp04O+//2bnzp34+PgQERFBjRo1lCkqOalatarys42NDYDGVBht9e3bl5CQEI4cOcKTJ09o1apVljrJyckEBgbi6uqKpaUlpqamREdHa4zgnzt3Dj8/P+zs7DAzM6Nx48YAGnWAPI2eX7hwgeTkZEqWLKnc7TA1NeXWrVsaU0Ps7e0xMzNTtm1sbHK9Fk+fPsXQ0FBjysmbqNVqrepnJyoqCl1dXeWa5ORt3tu6desqP+vp6eHl5UV0dLRStnz5cmrWrImVlRWmpqZ88803Wd4TDw8PDAwM8nw+xsbGyl2f140bN47ExETldefOnTy3K4QQQgjxrvS0PeDWrVtUr149S7mhoSFPnjzROgAjIyNatGhBixYtmDhxIv3792fy5MnZTm3JpK+vr/ycmXi+y7KFPXr0YPTo0QQFBdGzZ0/09LJelsDAQA4ePMi8efOoVKkSxsbGdOzYUXkg88mTJ3h7e+Pt7c2GDRuwsrIiNjYWb2/vLA9tmpiYvDGm5ORkbGxsiIiIyLLv1RVqXr0W8PJ65HYtSpUqRUpKCs+fP89TQpuens7169epVasW8HJEH14m/ZnS0tLe2I6xsfEb60D+v7ebNm0iMDCQ+fPnU7duXczMzJg7dy6nTp3SqJeX9+RVDx48wMrKKtt9hoaGBfZguBBCCCHEm2g9gu/g4EBUVFSW8n379mW75KS23Nzc3uqDQiYDAwNl2lBelShRgjZt2nDkyJEc53xHRkYSEBCAv78/Hh4eWFtba0xbuXLlCgkJCcyaNYuGDRtSuXLlPN9VyC7mGjVqcPfuXfT09KhUqZLGq1SpUlqd36syl+O8fPlynuqvW7eOhw8f0qFDBwAlqX11Tvrrvw/ZnY+HhwcZGRkaD8Dml19++UX5+cWLF5w7d075XYyMjKRevXoMGjSI6tWrU6lSpTw/HJvT79KzZ8+4efNmth90hRBCCCEKm9YJ/ogRIxg8eDCbN29GrVZz+vRpZsyYwbhx4xg9enSe20lISODjjz/m+++/5+LFi9y6dYutW7cyZ84c2rZtq21YCnt7e5KTkwkPD+f+/fs5TqN4XWhoKPfv36dy5crZ7ndyciIsLIyoqCguXLhA9+7dNUaW7ezsMDAwYOnSpfzxxx/s3LmTadOm5TnmW7duERUVxf3790lNTaV58+bUrVuXdu3aceDAAWJiYjhx4gTjx4/n7NmzeWo3O1ZWVtSoUYPjx49n2ZeSksLdu3f5888/+eWXXxgzZgwDBw7kiy++oGnTpgBUqlQJW1tbgoKCuH79Ort372b+/PlZzuf198De3p7evXvTt29ftm/fzq1bt4iIiMgyF/5tLF++nG3btnHlyhUGDx7Mw4cPlQ9qTk5OnD17lv3793Pt2jUmTpzImTNn8tSuvb09R48e5a+//uL+/ftK+S+//IKhoaHG1CAhhBBCiA+F1gl+//79mT17NhMmTCAlJYXu3buzcuVKFi9eTNeuXfPcjqmpKXXq1GHhwoU0atQId3d3Jk6cyIABA1i2bJm2YSnq1avHwIED6dKlC1ZWVsyZMydPxxkbG1OyZMkc9y9YsIDixYtTr149/Pz88Pb2pkaNGsp+KysrQkND2bp1K25ubsyaNYt58+blqe8OHTrg4+ND06ZNsbKyYuPGjahUKvbs2UOjRo3o06cPzs7OdO3aldu3b2dZ4Udb/fv3z/aLmlavXo2NjQ2Ojo60b9+ey5cvs3nzZlasWKHU0dfXZ+PGjVy5coWqVasye/Zspk+frtFOTu/BypUr6dixI4MGDaJy5coMGDDgne7WZJo1axazZs3C09OT48ePs3PnTuUux+eff0779u3p0qULderUISEhgUGDBuWp3alTpxITE4Ojo6PGdJyNGzfSo0cPihUr9s6xCyGEEELkN5X61cnUWkpJSSE5OTnPK7KID8PTp09xcXFh8+bN/+pR6JiYGBwcHDh//vx7+ybg+/fv4+LiwtmzZ3FwcMjTMUlJSVhYWOD1+dfoGRgVcIRCCCH+y04umVjYIYh8kpk/JCYmYm5urtWxWj9k+6pixYrJKOa/kLGxMd99953GtBORNzExMaxYsSLPyb0QQgghxPumdYKfkJDApEmTOHz4MPHx8VlWOHn1S5jEh6tJkyaFHcK/kpeXV56/JEwIIYQQojBoneD37NmTGzdu0K9fP8qUKfPO66ML8bbs7e15hxlm7134nDFa32ITQgghhNCW1gn+sWPHOH78OJ6engURjxBCCCGEEOIdaL2KTuXKlXn69GlBxCKEEEIIIYR4R1on+CtWrGD8+PEcOXKEhIQEkpKSNF5CCCGEEEKIwqP1FB1LS0uSkpL4+OOPNcrVajUqlUrrb5EVQgghhBBC5B+tE/wePXqgr6/PDz/8IA/ZCqGFxkGz0DWUdfCFEEK8m7PBkwo7BPGB0zrB/+233zh//jwuLi4FEY8QQgghhBDiHWg9B9/Ly4s7d+4URCxCCCGEEEKId6T1CP6XX37JV199xahRo/Dw8EBfX19jf9WqVfMtOCGEEEIIIYR2tE7wu3TpAkDfvn2VMpVKJQ/Z/kuoVCq2bdtGu3btPsj2CltoaCjDhg3j0aNHhR2KEEIIIcRb0TrBv3XrVkHEIfJRQEAAjx49Yvv27Vn2xcXFUbx48fcWS0REBE2bNuXhw4dYWlq+t37fNlHv0qULrVq1KpighBBCCCHeA60T/AoVKhREHOI9sba2LuwQPmjGxsYYGxsXdhhCCCGEEG9N64dsM12+fJl9+/axc+dOjZf4sKlUKo2R/Tt37tC5c2csLS0pUaIEbdu2JSYmRuOYtWvXUqVKFQwNDbGxsWHIkCEa++/fv4+/vz/FihXDyclJ+T2IiYmhadOmABQvXhyVSkVAQAAAGRkZBAcH4+DggLGxMZ6envz4449KmxEREahUKsLDw/Hy8qJYsWLUq1ePq1evKnUuXLhA06ZNMTMzw9zcnJo1a3L27FkiIiLo06cPiYmJqFQqVCoVQUFBAKSmphIYGEi5cuUwMTGhTp06REREKG2GhoZq3GkICgqiWrVqrF+/Hnt7eywsLOjatSuPHz9+y3dACCGEEKJgaZ3g//HHH3h6euLu7o6vry/t2rWjXbt2+Pv74+/vXxAxigKSlpaGt7c3ZmZmHDt2jMjISExNTfHx8eH58+cArFy5ksGDB/PZZ59x6dIldu7cSaVKlTTamTJlCp07d+bixYu0atWKHj168ODBA2xtbfnpp58AuHr1KnFxcSxevBiA4OBgvvvuO1atWsXvv//O8OHD+fTTTzly5IhG2+PHj2f+/PmcPXsWPT09jWc/evToQfny5Tlz5gznzp1j7Nix6OvrU69ePRYtWoS5uTlxcXHExcURGBgIwJAhQzh58iSbNm3i4sWLdOrUCR8fH65fv57jdbp58ybbt29n165d7Nq1iyNHjjBr1qwc66empso3PAshhBCi0Gg9Reerr77CwcGB8PBwHBwcOH36NAkJCYwcOZJ58+YVRIyigGzevJmMjAy+/fZb5QvLQkJCsLS0JCIigk8++YTp06czcuRIvvrqK+W4WrVqabQTEBBAt27dAJg5cyZLlizh9OnT+Pj4UKJECQBKly6tjIynpqYyc+ZMDh06RN26dQGoWLEix48f53//+x+NGzdW2p4xY4ayPXbsWHx9fXn27BlGRkbExsYyatQoKleuDICTk5NynIWFBSqVSmNKUmxsLCEhIcTGxlK2bFkAAgMD2bdvHyEhIcycOTPb65SRkUFoaChmZmYA9OzZk/DwcGbMmJFt/eDgYKZMmZLjdRdCCCGEKEhaJ/gnT57k559/plSpUujo6KCjo0ODBg0IDg5m6NChnD9/viDiFAXgwoUL3LhxQ0lcMz179oybN28SHx/P33//TbNmzXJt59WlUU1MTDA3Nyc+Pj7H+jdu3CAlJYUWLVpolD9//pzq1avn2LaNjQ0A8fHx2NnZMWLECPr378/69etp3rw5nTp1wtHRMcd+L126RHp6Os7OzhrlqamplCxZMsfj7O3tNa6RjY1Nruc3btw4RowYoWwnJSVha2ubY30hhBBCiPykdYKfnp6uJDulSpXi77//xsXFhQoVKmjMjxYfvuTkZGrWrMmGDRuy7LOyskJHJ28zuF7/LgSVSkVGRkau/QLs3r2bcuXKaewzNDTMse3MuwyZbQcFBdG9e3d2797N3r17mTx5Mps2bcpxqlhycjK6urqcO3cOXV1djX2mpqb5dn6GhoZZzkMIIYQQ4n3ROsF3d3fnwoULODg4UKdOHebMmYOBgQHffPMNFStWLIgYRQGpUaMGmzdvpnTp0pibm2dbx97envDwcOVhWW0ZGBgAaHw/gpubG4aGhsTGxmpMx3kbzs7OODs7M3z4cLp160ZISAj+/v4YGBhk+U6G6tWrk56eTnx8PA0bNnynfoUQQgghPlRaJ/gTJkzgyZMnAEydOpXWrVvTsGFDSpYsyebNm/M9QPF2EhMTiYqK0ih7fRpKjx49mDt3Lm3btmXq1KmUL1+e27dvExYWxujRoylfvjxBQUEMHDiQ0qVL07JlSx4/fkxkZCRffvllnuKoUKECKpWKXbt20apVK4yNjTEzMyMwMJDhw4eTkZFBgwYNSExMJDIyEnNzc3r37v3Gdp8+fcqoUaPo2LEjDg4O/Pnnn5w5c4YOHToALz+YJCcnEx4ejqenJ8WKFcPZ2ZkePXrQq1cv5s+fT/Xq1bl37x7h4eFUrVoVX1/fvF1cIYQQQogPmNYJvre3t/JzpUqVuHLlCg8ePFCWQRQfhoiIiCzz2fv166exXaxYMY4ePcqYMWNo3749jx8/ply5cjRr1kwZ0e/duzfPnj1j4cKFBAYGUqpUKTp27JjnOMqVK8eUKVMYO3Ysffr0oVevXoSGhjJt2jSsrKwIDg7mjz/+wNLSkho1avD111/nqV1dXV0SEhLo1asX//zzD6VKlaJ9+/bKw6316tVj4MCBdOnShYSEBCZPnkxQUBAhISHKg8N//fUXpUqV4qOPPqJ169Z5PichhBBCiA+ZSq1Wqws7CCGKsqSkJCwsLKg2fBy6hkaFHY4QQoh/ubPBkwo7BPEeZOYPiYmJOU6lzkmeR/BfXX88JyqVijVr1mgVgBBCCCGEECL/5DnBf/jwYY770tPTOXToEKmpqZLgCyGEEEIIUYjynOBv27Yt2/IdO3bw9ddfY2hoyKRJcstICCGEEEKIwvTWc/AjIyMZO3Ysv/76K0OGDGHs2LEUL148v+MT4l/vXebQCSGEEOK/6V3yh7x9k9ErLl++jJ+fH02aNMHZ2ZmrV68ye/ZsSe6FEEIIIYT4AOQ5wb9z5w59+vTB09MTPT09Ll68yJo1ayhfvnxBxieEEEIIIYTQQp7n4Lu4uKBSqRgxYgT169fn+vXrXL9+PUu9Nm3a5GuAQgghhBBCiLzL8xx8HZ03D/arVCrS09PfOSghipLMOXTu48eia2RY2OEIIYQoQFETggo7BFFEvJd18DMyMrQOTAghhBBCCPF+af2QrRBCCCGEEOLDJQm+EEIIIYQQRYgk+EIIIYQQQhQhkuALIYQQQghRhEiCL96rgIAAVCoVAwcOzLJv8ODBqFQqAgIC3n9gQgghhBBFhNYJfu/evTl69GhBxCL+I2xtbdm0aRNPnz5Vyp49e8YPP/yAnZ1dIUYmhBBCCPHvp3WCn5iYSPPmzXFycmLmzJn89ddfBRGXKMJq1KiBra0tYWFhSllYWBh2dnZUr15dKUtNTWXo0KGULl0aIyMjGjRowJkzZ5T9ERERqFQqwsPD8fLyolixYtSrV4+rV68qdW7evEnbtm0pU6YMpqam1KpVi0OHDmnEk5qaypgxY7C1tcXQ0JBKlSqxZs0aZf+RI0eoXbs2hoaG2NjYMHbsWF68eFEQl0YIIYQQ4p1pneBv376dv/76iy+++ILNmzdjb29Py5Yt+fHHH0lLSyuIGEUR1LdvX0JCQpTttWvX0qdPH406o0eP5qeffmLdunX8+uuvVKpUCW9vbx48eKBRb/z48cyfP5+zZ8+ip6dH3759lX3Jycm0atWK8PBwzp8/j4+PD35+fsTGxip1evXqxcaNG1myZAnR0dH873//w9TUFIC//vqLVq1aUatWLS5cuMDKlStZs2YN06dPz/HcUlNTSUpK0ngJIYQQQrwvef4m25z8+uuvhISE8O2332Jqasqnn37KoEGDcHJyyq8YRRESEBDAo0ePWL16Nba2tspoe+XKlblz5w79+/fH0tKS5cuXU7x4cUJDQ+nevTsAaWlp2NvbM2zYMEaNGkVERARNmzbl0KFDNGvWDIA9e/bg6+vL06dPMTIyyjYGd3d3Bg4cyJAhQ7h27RouLi4cPHiQ5s2bZ6k7fvx4fvrpJ6Kjo1GpVACsWLGCMWPGkJiYmO03PAcFBTFlypSs/co32QohRJEn32Qr8su7fJPtOz1kGxcXx8GDBzl48CC6urq0atWKS5cu4ebmxsKFC9+laVHEWVlZ4evrS2hoKCEhIfj6+lKqVCll/82bN0lLS6N+/fpKmb6+PrVr1yY6OlqjrapVqyo/29jYABAfHw+8HMEPDAzE1dUVS0tLTE1NiY6OVkbwo6Ki0NXVpXHjxtnGGR0dTd26dZXkHqB+/fokJyfz559/ZnvMuHHjSExMVF537tzR5tIIIYQQQrwTPW0PSEtLY+fOnYSEhHDgwAGqVq3KsGHD6N69u/LpYtu2bfTt25fhw4fne8Ci6Ojbty9DhgwBYPny5W/djr6+vvJzZiKekZEBQGBgIAcPHmTevHlUqlQJY2NjOnbsyPPnzwEwNjZ+635zYmhoiKGhjNQLIYQQonBoneDb2NiQkZFBt27dOH36NNWqVctSp2nTplhaWuZDeKIo8/Hx4fnz56hUKry9vTX2OTo6YmBgQGRkJBUqVABefrg8c+YMw4YNy3MfkZGRBAQE4O/vD7wc0Y+JiVH2e3h4kJGRwZEjR7KdouPq6spPP/2EWq1WPjxERkZiZmZG+fLltTxjIYQQQoiCp3WCv3DhQjp16pTj/GYAS0tLbt269U6BiaJPV1dXmW6jq6ursc/ExIQvvviCUaNGUaJECezs7JgzZw4pKSn069cvz304OTkRFhaGn58fKpWKiRMnKqP7APb29vTu3Zu+ffuyZMkSPD09uX37NvHx8XTu3JlBgwaxaNEivvzyS4YMGcLVq1eZPHkyI0aMyHb+vRBCCCFEYdMqQ0lLS6NPnz7cuHGjoOIR/zHm5uY5Pjgya9YsOnToQM+ePalRowY3btxg//79FC9ePM/tL1iwgOLFi1OvXj38/Pzw9vamRo0aGnVWrlxJx44dGTRoEJUrV2bAgAE8efIEgHLlyrFnzx5Onz6Np6cnAwcOpF+/fkyYMOHtT1oIIYQQogBpvYpOxYoV2bZtG56engUVkxBFSuZT8LKKjhBCFH2yio7IL+91FZ3x48fz9ddfZ1mLXAghhBBCCFH4tJ6Dv2zZMm7cuEHZsmWpUKECJiYmGvt//fXXfAtOCCGEEEIIoR2tE/y2bdtqrAkuhMibyNHjtL7FJoQQQgihrXf+JlshRO7eZQ6dEEIIIf6b3usc/IoVK5KQkJCl/NGjR1SsWFHb5oQQQgghhBD5SOsEPyYmhvT09Czlqamp/Pnnn/kSlBBCCCGEEOLt5HkO/s6dO5Wf9+/fj4WFhbKdnp5OeHg4Dg4O+RudEEIIIYQQQit5noOf+a2dKpWK1w/R19fH3t6e+fPn07p16/yPUoh/MWUd/OAxsg6+EEIUgqhhUwo7BCG09i5z8PM8gp+RkQGAg4MDZ86coVSpUtpFKYQQQgghhChwWi+TeevWrYKIQwghhBBCCJEPtE7wAcLDwwkPDyc+Pl4Z2c+0du3afAlMCCGEEEIIoT2tV9GZMmUKn3zyCeHh4dy/f5+HDx9qvIT4kNnb27No0aLCDkMIIYQQosBoPYK/atUqQkND6dmzZ0HEIwrRvXv3mDRpErt37+aff/6hePHieHp6MmnSJOrXr19g/cbExODg4ICOjg6xsbGUK1dO2RcXF4etrS3p6encunULe3v7d+rrzJkzmJiYvGPEQgghhBAfLq1H8J8/f069evUKIhZRyDp06MD58+dZt24d165dY+fOnTRp0iTbLzYrCOXKleO7777TKFu3bp1Gwv+2nj9/DoCVlRXFihV75/aEEEIIIT5UWif4/fv354cffiiIWEQhevToEceOHWP27Nk0bdqUChUqULt2bcaNG0ebNm2UegsWLMDDwwMTExNsbW0ZNGgQycnJyv7Q0FAsLS3Zv38/rq6umJqa4uPjQ1xc3Btj6N27NyEhIRplISEh9O7dW6MsPT2dfv364eDggLGxMS4uLixevFijTkBAAO3atWPGjBmULVsWFxcXIOsUHZVKxbfffou/vz/FihXDyclJ4zsfAI4cOULt2rUxNDTExsaGsWPH8uLFizeejxBCCCFEYdA6wX/27BkLFiygcePGfPnll4wYMULjJf6dTE1NMTU1Zfv27aSmpuZYT0dHhyVLlvD777+zbt06fv75Z0aPHq1RJyUlhXnz5rF+/XqOHj1KbGwsgYGBb4yhTZs2PHz4kOPHjwNw/PhxHj58iJ+fn0a9jIwMypcvz9atW7l8+TKTJk3i66+/ZsuWLRr1wsPDuXr1KgcPHmTXrl059jtlyhQ6d+7MxYsXadWqFT169ODBgwcA/PXXX7Rq1YpatWpx4cIFVq5cyZo1a5g+fXqO7aWmppKUlKTxEkIIIYR4X7Seg3/x4kWqVasGwG+//aaxT6VS5UtQ4v3T09MjNDSUAQMGsGrVKmrUqEHjxo3p2rUrVatWVeoNGzZM+dne3p7p06czcOBAVqxYoZSnpaWxatUqHB0dARgyZAhTp059Ywz6+vp8+umnrF27lgYNGrB27Vo+/fRT9PX1s9SbMuX/f2mJg4MDJ0+eZMuWLXTu3FkpNzEx4dtvv8XAwCDXfgMCAujWrRsAM2fOZMmSJZw+fRofHx9WrFiBra0ty5YtQ6VSUblyZf7++2/GjBnDpEmTlC+Ae1VwcLBGfEIIIYQQ75PWCf7hw4cLIg7xAejQoQO+vr4cO3aMX375hb179zJnzhy+/fZbAgICADh06BDBwcFcuXKFpKQkXrx4wbNnz0hJSVHmthcrVkxJ7gFsbGyIj4/PUwx9+/alXr16zJw5k61bt3Ly5Mlsp8MsX76ctWvXEhsby9OnT3n+/LnywTOTh4fHG5N7QOMDjImJCebm5kq80dHR1K1bV+PDa/369UlOTubPP//Ezs4uS3vjxo3TuJuVlJSEra3tG+MQQgghhMgPWk/REUWbkZERLVq0YOLEiZw4cYKAgAAmT54MvFztpnXr1lStWpWffvqJc+fOsXz5cuD/P8QKZBlxV6lUqNXqPPXv4eFB5cqV6datG66urri7u2eps2nTJgIDA+nXrx8HDhwgKiqKPn36aMQA5Hm1nOziff37HbRhaGiIubm5xksIIYQQ4n3RegS/adOmuU7F+fnnn98pIPFhcXNzY/v27QCcO3eOjIwM5s+fr0xNeX3ee37o27cvgwYNYuXKldnuj4yMpF69egwaNEgpu3nzZr7HAeDq6spPP/2EWq1Wfu8jIyMxMzOjfPnyBdKnEEIIIcS70HoEv1q1anh6eiovNzc3nj9/zq+//oqHh0dBxCjeg4SEBD7++GO+//57Ll68yK1bt9i6dStz5syhbdu2AFSqVIm0tDSWLl3KH3/8wfr161m1alW+xzJgwADu3btH//79s93v5OTE2bNn2b9/P9euXWPixImcOXMm3+MAGDRoEHfu3OHLL7/kypUr7Nixg8mTJzNixIhs598LIYQQQhQ2rUfwFy5cmG15UFCQxnKJ4t/F1NSUOnXqsHDhQm7evElaWhq2trYMGDCAr7/+GgBPT08WLFjA7NmzGTduHI0aNSI4OJhevXrlayx6enqUKlUqx/2ff/4558+fp0uXLqhUKrp168agQYPYu3dvvsYBL9fm37NnD6NGjcLT05MSJUrQr18/JkyYkO99CSGEEELkB5U6r5Oj3+DGjRvUrl1bWV5QCPFSUlISFhYWuAePQdfIsLDDEUKI/5yoYbKymfj3ycwfEhMTtX6eL9/mGJw8eRIjI6P8ak4IIYQQQgjxFrSeotO+fXuNbbVaTVxcHGfPnmXixIn5FpgQQgghhBBCe1on+BYWFhrbOjo6uLi4MHXqVD755JN8C0yIoiZy0NeyZKYQQgghCpzWCX5ISEhBxCGEEEIIIYTIB1on+JnOnTtHdHQ0AFWqVKF69er5FpQQQgghhBDi7Wid4MfHx9O1a1ciIiKwtLQE4NGjRzRt2pRNmzZhZWWV3zEKIYQQQggh8kjrVXS+/PJLHj9+zO+//86DBw948OABv/32G0lJSQwdOrQgYhRCCCGEEELkkdbr4FtYWHDo0CFq1aqlUX769Gk++eQTHj16lJ/xCfGvl7mOba3lgegZyzr4Qgjxrk70mV7YIQhR4N7rOvgZGRno6+tnKdfX1ycjI0Pb5oQQQgghhBD5SOsE/+OPP+arr77i77//Vsr++usvhg8fTrNmzfI1OCGEEEIIIYR2tE7wly1bRlJSEvb29jg6OuLo6IiDgwNJSUksXbq0IGIUQgghhBBC5JHWCb6trS2//voru3fvZtiwYQwbNow9e/bw66+/Ur58+YKI8T/J3t6eRYsWvXM7V69exdramsePH797UAVIpVKxffv2wg4jV/fv36d06dL8+eefhR2KEEIIIUSOtE7w4WUy1qJFC7788ku+/PJLmjdvnt9x5cm9e/f44osvsLOzw9DQEGtra7y9vYmMjNSI9W0Sx4CAAFQqFQMHDsyyb/DgwahUKgICAt4h+pdCQ0OV5UZfdebMGT777LN3bn/cuHF8+eWXmJmZARAREYFKpcrymjBhwjv3VZQEBATQrl07jbJSpUrRq1cvJk+eXDhBCSGEEELkQZ4T/J9//hk3NzeSkpKy7EtMTKRKlSocO3YsX4N7kw4dOnD+/HnWrVvHtWvX2LlzJ02aNCEhISFf2re1tWXTpk08ffpUKXv27Bk//PADdnZ279x+WlpajvusrKwoVqzYO7UfGxvLrl27sv0gcvXqVeLi4pTX2LFjs9RJT0//zz04/aZz7tOnDxs2bODBgwfvMSohhBBCiLzLc4K/aNEiBgwYkO0yPRYWFnz++ecsWLAgX4PLzaNHjzh27BizZ8+madOmVKhQgdq1azNu3DjatGkDvJzmAuDv749KpVK286pGjRrY2toSFhamlIWFhWFnZ5flm3v37dtHgwYNsLS0pGTJkrRu3ZqbN28q+2NiYlCpVGzevJnGjRtjZGTEhg0b6NOnD4mJicpIelBQkBL7q1N0VCoV3377Lf7+/hQrVgwnJyd27tyZa/xbtmzB09OTcuXKZdlXunRprK2tlZepqalyN2Hnzp24ublhaGhIbGwsqampBAYGUq5cOUxMTKhTpw4RERFKW5nH7d+/H1dXV0xNTfHx8SEuLk6jz7Vr11KlShUMDQ2xsbFhyJAhGvvv37+v1fnZ29szbdo0unXrhomJCeXKlWP58uUadRYsWICHhwcmJibY2toyaNAgkpOTs8T+6jn37duXdevWsWPHDuV9yTzfKlWqULZsWbZt25ZrbEIIIYQQhSXPCf6FCxfw8fHJcf8nn3zCuXPn8iWovDA1NcXU1JTt27eTmpqabZ0zZ84AEBISQlxcnLKtjb59+xISEqJsr127lj59+mSp9+TJE0aMGMHZs2cJDw9HR0cHf3//LKPBY8eO5auvviI6OpqmTZuyaNEizM3NlZH0wMDAHGOZMmUKnTt35uLFi7Rq1YoePXrkOpJ87NgxvLy8tDrflJQUZs+ezbfffsvvv/9O6dKlGTJkCCdPnmTTpk1cvHiRTp064ePjw/Xr1zWOmzdvHuvXr+fo0aPExsZqnMvKlSsZPHgwn332GZcuXWLnzp1UqlTpnc4PYO7cuXh6enL+/Hnl2h48eFDZr6Ojw5IlS/j9999Zt24dP//8M6NHj871nJcsWULnzp2VDylxcXHUq1dPqV+7du1c71alpqaSlJSk8RJCCCGEeF/08lrxn3/+yXb9e6UhPT3u3buXL0HlhZ6eHqGhoQwYMIBVq1ZRo0YNGjduTNeuXalatSrwcpoLgKWlJdbW1m/Vz6effsq4ceO4ffs2AJGRkWzatEljBBteThd61dq1a7GysuLy5cu4u7sr5cOGDaN9+/bKtoWFBSqVKk/xBQQE0K1bNwBmzpzJkiVLOH36dI4fvG7fvp1jgv/6A9GZ55eWlsaKFSvw9PQEXk7zCQkJITY2lrJlywIQGBjIvn37CAkJYebMmcpxq1atwtHREYAhQ4YwdepUpf3p06czcuRIvvrqK6Xs9S9L0/b8AOrXr69ML3J2diYyMpKFCxfSokUL4OX1zmRvb8/06dMZOHAgK1asUMpfP2cAY2NjUlNTs31fypYty/nz53OMKTg4mClTpuS4XwghhBCiIOV5BL9cuXL89ttvOe6/ePEiNjY2+RJUXnXo0IG///6bnTt34uPjQ0REBDVq1CA0NDTf+rCyssLX15fQ0FBCQkLw9fWlVKlSWepdv36dbt26UbFiRczNzZXpQLGxsRr1tB1Rf1XmBxcAExMTzM3NiY+Pz7H+06dPMTIyynbfsWPHiIqKUl7FixcHwMDAQKOfS5cukZ6ejrOzs3LXxNTUlCNHjmhMQSpWrJiS3APY2NgoscXHx/P333+/8XsStD0/gLp162bZjo6OVrYPHTpEs2bNKFeuHGZmZvTs2ZOEhARSUlKUOq+f85sYGxtrHP+6cePGkZiYqLzu3LmT57aFEEIIId5VnkfwW7VqxcSJE/Hx8cmSND59+pTJkyfTunXrfA/wTYyMjGjRogUtWrRg4sSJ9O/fn8mTJ+fLCjeZ+vbtq8wXf32OdyY/Pz8qVKjA6tWrKVu2LBkZGbi7u/P8+XONeiYmJm8dx+t3UFQqVa4PhJYqVYqHDx9mu8/BwSHb1XuMjY1RqVTKdnJyMrq6upw7dw5dXV2NuqamprnGplarlTbzQtvze5OYmBhat27NF198wYwZMyhRogTHjx+nX79+PH/+XHmI+fVzfpMHDx4od4eyY2hoiKGh4VvHLYQQQgjxLvKc4E+YMIGwsDCcnZ0ZMmQILi4uAFy5coXly5eTnp7O+PHjCyzQvHJzc9NYFlNfX5/09PR3atPHx4fnz5+jUqnw9vbOsj8hIYGrV6+yevVqGjZsCMDx48fz1LaBgcE7x5eT6tWrc/ny5XduIz09nfj4eOXctGVmZoa9vT3h4eE0bdr0neJ53S+//JJl29XVFYBz586RkZHB/Pnz0dF5ebNqy5YteWo3t/flt99+o0mTJm8ftBBCCCFEAcrzFJ0yZcpw4sQJ3N3dGTduHP7+/vj7+/P111/j7u7O8ePHKVOmTEHGqiEhIYGPP/6Y77//nosXL3Lr1i22bt3KnDlzaNu2rVIvM7G8e/euMpp9+vRpKleuzF9//ZWnvnR1dYmOjuby5ctZRrEBihcvTsmSJfnmm2+4ceMGP//8MyNGjMhT2/b29iQnJxMeHs79+/dznfqhLW9vb06ePPlOHyCcnZ3p0aMHvXr1IiwsjFu3bnH69GmCg4PZvXt3ntsJCgpi/vz5LFmyhOvXr/Prr7/myzcfR0ZGMmfOHK5du8by5cvZunWrMs+/UqVKpKWlsXTpUv744w/Wr1/PqlWr8tSuvb09Fy9e5OrVq9y/f19Z0jQlJYVz587xySefvHPsQgghhBAFQasvuqpQoQJ79uzh/v37nDp1il9++YX79++zZ88eHBwcCirGbJmamlKnTh0WLlxIo0aNcHd3Z+LEiQwYMIBly5Yp9ebPn8/BgwextbVVlrZMSUnh6tWrua5D/zpzc/NslwiFlyu1bNq0iXPnzuHu7s7w4cOZO3duntqtV68eAwcOpEuXLlhZWTFnzpw8x/QmLVu2RE9Pj0OHDr1TOyEhIfTq1YuRI0fi4uJCu3btOHPmjFbfBdC7d28WLVrEihUrqFKlCq1bt9ZYhedtjRw5krNnz1K9enWmT5/OggULlLssnp6eLFiwgNmzZ+Pu7s6GDRsIDg7OU7sDBgzAxcUFLy8vrKyslC9P27FjB3Z2dm99N0MIIYQQoqCp1JkTpUWRtHz5cnbu3Mn+/fsLO5R8Z29vz7BhwzRWyiloH330EUOHDqV79+55PiYpKQkLCwtqLQ9Ez1jm5gshxLs60Wd6YYcgRIHLzB8SExNzHGTOSZ7n4It/p88//5xHjx7x+PFjzMzMCjucf7X79+/Tvn17ZSlPIYQQQogPkST4RZyent4H8fBzUVCqVKksX5IlhBBCCPGhkQRf/GvFxMQUdghCCCGEEB8cSfCFeE8OfTpR6zl0QgghhBDa0moVHSGEEEIIIcSHTRJ8IYQQQgghihBJ8IUQQgghhChCZA6+EO9J152T0C8m6+ALIURe7Gg/u7BDEOJfS0bwhRBCCCGEKEIkwRdCCCGEEKIIkQRfCCGEEEKIIkQSfCGEEEIIIYoQSfBFoVCpVGzfvh14+Y20KpWKqKioAunL3t6eRYsWFUjbQgghhBAfGknwRb67e/cuX331FZUqVcLIyIgyZcpQv359Vq5cSUpKCgBxcXG0bNmyUOJ79cOFEEIIIURRI8tkinz1xx9/UL9+fSwtLZk5cyYeHh4YGhpy6dIlvvnmG8qVK0ebNm2wtrZ+p37UajXp6eno6RXer/Dz588xMDAotP6FEEIIIbIjI/giXw0aNAg9PT3Onj1L586dcXV1pWLFirRt25bdu3fj5+cHZD+KfuXKFerVq4eRkRHu7u4cOXJE2RcREYFKpWLv3r3UrFkTQ0NDjh8/zs2bN2nbti1lypTB1NSUWrVqcejQoRzjs7e3B8Df3x+VSqVs56Ude3t7pk2bRq9evTA3N+ezzz579wsmhBBCCJHPJMEX+SYhIYEDBw4wePBgTExMsq2jUqlyPH7UqFGMHDmS8+fPU7duXfz8/EhISNCoM3bsWGbNmkV0dDRVq1YlOTmZVq1aER4ezvnz5/Hx8cHPz4/Y2Nhs+zhz5gwAISEhxMXFKdt5bWfevHl4enpy/vx5Jk6cmG0fqampJCUlabyEEEIIId4XSfBFvrlx4wZqtRoXFxeN8lKlSmFqaoqpqSljxozJ8fghQ4bQoUMHXF1dWblyJRYWFqxZs0ajztSpU2nRogWOjo6UKFECT09PPv/8c9zd3XFycmLatGk4Ojqyc+fObPuwsrICwNLSEmtra2U7r+18/PHHjBw5EkdHRxwdHbPtIzg4GAsLC+Vla2ub+4UTQgghhMhHkuCLAnf69GmioqKoUqUKqampOdarW7eu8rOenh5eXl5ER0dr1PHy8tLYTk5OJjAwEFdXVywtLTE1NSU6OjrHEfyc5LWd1/vPzrhx40hMTFRed+7c0SoWIYQQQoh3IQ/ZinxTqVIlVCoVV69e1SivWLEiAMbGxu/cx+tTfwIDAzl48CDz5s2jUqVKGBsb07FjR54/f65Vu3ltJ6epR68yNDTE0NBQq/6FEEIIIfKLjOCLfFOyZElatGjBsmXLePLkidbH//LLL8rPL1684Ny5c7i6uuZ6TGRkJAEBAfj7++Ph4YG1tTUxMTG5HqOvr096evo7tyOEEEII8SGSBF/kqxUrVvDixQu8vLzYvHkz0dHRXL16le+//54rV66gq6ub47HLly9n27ZtXLlyhcGDB/Pw4UP69u2ba39OTk6EhYURFRXFhQsX6N69OxkZGbkeY29vT3h4OHfv3uXhw4dv3Y4QQgghxIdIEnyRrxwdHTl//jzNmzdn3LhxeHp64uXlxdKlSwkMDGTatGk5Hjtr1ixmzZqFp6cnx48fZ+fOnZQqVSrX/hYsWEDx4sWpV68efn5+eHt7U6NGjVyPmT9/PgcPHsTW1pbq1au/dTtCCCGEEB8ilVqtVhd2EEIUZUlJSVhYWNBy/VfoF5O5+UIIkRc72s8u7BCEKFSZ+UNiYiLm5uZaHSsj+EIIIYQQQhQhkuALIYQQQghRhMgymUK8J5vaTNX6FpsQQgghhLZkBF8IIYQQQogiRBJ8IYQQQgghihBJ8IUQQgghhChCJMEXQgghhBCiCJGHbIV4T0ZFjMbARNbBF0KI3CxttriwQxDiX09G8IUQQgghhChCJMEXQgghhBCiCJEEXwghhBBCiCJEEvx8FBoaiqWl5RvrqVQqtm/fnqc2tamrjYCAANq1a/fO7eT1nPNLREQEKpWKR48eFXhfBXXthRBCCCEKkiT4rwkICEClUimvkiVL4uPjw8WLF994bJcuXbh27ZqyHRQURLVq1bLUi4uLo2XLlvkZtsLDw4OBAwdmu2/9+vUYGhpy//59Fi9eTGho6Dv39/o5v433mbQLIYQQQhR1kuBnw8fHh7i4OOLi4ggPD0dPT4/WrVvnekxaWhrGxsaULl36je1bW1tjaFgwq6n069ePTZs28fTp/2vv3qOiuM//gb8XZZf7LgiygIggiKgoFZGYREWkWYwxaJKjEbSSGm/VRFpJkEYDagxGE1o1Xvozp2At8dao8RgaqijRoEGxghIJUcRAWtQEuXrhIp/fH36ZOnIRlMuyeb/OmXOYmWdmnpnn7O6zszPDnUbzEhIS8OKLL8LW1hZqtbrFM+81NTWt2l5r95mIiIiIOgcb/CaoVCpotVpotVr4+Phg6dKlKCoqwk8//QQAuHr1KhQKBXbv3o2xY8fCxMQESUlJsstVEhMTsWLFCmRnZ0u/BjScMX/w0o+amhosWrQIDg4OMDExgYuLC+Li4mT5/Pzzz5gyZQrMzMzg4eGBgwcPNpv7jBkzcOfOHXz22Wey6QUFBUhLS8Ps2bMBNL5EJyAgAIsWLUJERARsbW2h0+kAAAcPHoSHhwdMTEwwbtw4bN++XXa2/eFLdBp+tdixYwf69esHtVqNV199FZWVla0+/j/88AMmTZoEa2trmJubY/DgwUhOTm4ytqSkBNOnT4eTkxPMzMzg7e2NnTt3ymICAgLw5ptv4u2334aNjQ20Wi1iY2NlMZcuXcKYMWNgYmKCQYMG4fDhw7L5rakTERERkT5gg/8IVVVV+Pvf/w53d3f06tVLNm/p0qVYvHgxcnNzpYa4wbRp07BkyRIMHjxY+jVg2rRpjda/YcMGHDx4EHv27EFeXh6SkpLQr18/WcyKFSswdepUnD9/Hs8//zzCwsJw8+bNJvO1tbVFSEgI/vrXv8qmJyYmok+fPnjuueea3dft27dDqVQiPT0dW7duRUFBAV555RVMnjwZ2dnZmDdvHt55552WDhcAID8/HwcOHMChQ4dw6NAhfPXVV1izZs0jl2uwcOFCVFdX4/jx47hw4QI++OADWFhYNBl79+5d+Pr64osvvkBOTg7mzp2LmTNn4vTp0432zdzcHBkZGVi7di1WrlwpNfH19fV46aWXoFQqkZGRga1btyIqKkq2fGvq1KC6uhoVFRWygYiIiKiz8B9dNeHQoUNSQ3nr1i04ODjg0KFDMDKSfx+KiIjASy+91OQ6TE1NYWFhgZ49e0Kr1Ta7rcLCQnh4eODZZ5+FQqGAi4tLo5jw8HBMnz4dAPD+++9jw4YNOH36NIKDg5tc5+zZszFhwgQUFBTA1dUVQghs374ds2bNarQPD/Lw8MDatWul8aVLl8LT0xPr1q0DAHh6eiInJwerV69udh3A/YY5MTERlpaWAICZM2ciNTX1kcs1KCwsxMsvvwxvb28AgJubW7OxTk5OiIyMlMbfeOMNpKSkYM+ePRg5cqQ0fejQoYiJiZH28+OPP0Zqaip+/etf48iRI/juu++QkpICR0dHAPeP84P3SbSmTg3i4uKwYsWKVu0rERERUXvjGfwmjBs3DllZWcjKysLp06eh0+kwYcIE/PDDD7K4ESNGPPG2wsPDkZWVBU9PT7z55pv417/+1Shm6NCh0t/m5uawsrLCjRs3ml3nr3/9a/Tp0wcJCQkAgNTUVBQWFuK1115rMRdfX1/ZeF5eHvz8/GTTHmyam9OvXz+puQcABweHFvN92Jtvvon33nsPzzzzDGJiYlq8wfnevXtYtWoVvL29YWNjAwsLC6SkpKCwsFAW9+AxfDin3NxcODs7S809AIwaNUoW35o6NYiOjkZ5ebk0FBUVtXrfiYiIiJ4UG/wmmJubw93dHe7u7vDz88Mnn3yCW7duYdu2bY3intTw4cNRUFCAVatW4c6dO5g6dSpeeeUVWYyxsbFsXKFQoL6+vtl1GhkZITw8HNu3b0d9fT0SEhIwbty4Fs+EA+2zP4+T78Nef/11XLlyBTNnzsSFCxcwYsQIbNy4scnYdevWYf369YiKisKxY8eQlZUFnU7X6CbhJ82pNXVqoFKpYGVlJRuIiIiIOgsb/FZQKBQwMjJq8sk0LVEqlbh3794j46ysrDBt2jRs27YNu3fvxmeffdbsNfat9dprr6GoqAj79u3D/v37pZtr28LT0xOZmZmyaWfOnHmivFrL2dkZ8+fPx759+7BkyZJGX64apKenIyQkBDNmzMCwYcPg5ubW5sd2enl5oaioCMXFxdK0b775plFcR9SJiIiIqL3xGvwmVFdX49q1awCA0tJSfPzxx6iqqsKkSZPatJ5+/fqhoKAAWVlZ6NOnDywtLRs9HjM+Ph4ODg741a9+BSMjI+zduxdarfaJ/3mUq6srAgMDMXfuXKhUqmbvFWjJvHnzEB8fj6ioKMyePRtZWVmyJwF1lIiICEyYMAEDBgxAaWkpjh07Bi8vryZjPTw88I9//AMnT56EtbU14uPjcf36dQwaNKjV2wsKCsKAAQMwa9YsrFu3DhUVFY1uJu6oOhERERG1N57Bb8KXX34JBwcHODg4wN/fH2fOnMHevXsREBDQpvW8/PLLCA4Oxrhx42BnZ9fo8Y0AYGlpibVr12LEiBHw8/PD1atXkZyc3OLNsK01e/ZslJaWIjQ0FCYmJm1e3tXVFf/4xz+wb98+DB06FFu2bJEa3456jj9w/7r6hQsXwsvLC8HBwRgwYAA2b97cZOyyZcswfPhw6HQ6BAQEQKvVtvk/9BoZGWH//v24c+cORo4ciddff73RDcEdWSciIiKi9qQQQoiuToK6j9WrV2Pr1q28cbQNKioqoFarMffzeVCad9wXIyIiQ7Bx/PquToFILzT0D+Xl5W2+n4+X6FCLNm/eDD8/P/Tq1Qvp6elYt24dFi1a1NVpEREREVEz2OBTiy5duoT33nsPN2/eRN++fbFkyRJER0d3dVpERERE1AxeokPUwZ7kJzYiIiL6ZXqS/oF3CBIRERERGRA2+EREREREBoQNPhERERGRAWGDT0RERERkQPgUHaJOEn9qDkzMlV2dBtFjWfrsjq5OgYiIWoln8ImIiIiIDAgbfCIiIiIiA8IGn4iIiIjIgLDBp1+MxMREaDSark6DiIiIqEOxwaduJTw8HAqFAgqFAkqlEu7u7li5ciXq6uq6OjUiIiIivcCn6FC3ExwcjISEBFRXVyM5ORkLFy6EsbExoqOjuzo1IiIioi7HM/jU7ahUKmi1Wri4uGDBggUICgrCwYMHER8fD29vb5ibm8PZ2Rm/+93vUFVV1ex68vPzERISAnt7e1hYWMDPzw9HjhyRxSgUChw4cEA2TaPRIDExsQP2jIiIiOjJscGnbs/U1BQ1NTUwMjLChg0b8O2332L79u04evQo3n777WaXq6qqwvPPP4/U1FScO3cOwcHBmDRpEgoLC58on+rqalRUVMgGIiIios7CBp+6LSEEjhw5gpSUFAQGBiIiIgLjxo1Dv379EBgYiPfeew979uxpdvlhw4Zh3rx5GDJkCDw8PLBq1Sr0798fBw8efKK84uLioFarpcHZ2fmJ1kdERETUFmzwqds5dOgQLCwsYGJiggkTJmDatGmIjY3FkSNHMH78eDg5OcHS0hIzZ85ESUkJbt++3eR6qqqqEBkZCS8vL2g0GlhYWCA3N/eJz+BHR0ejvLxcGoqKip5ofURERERtwZtsqdsZN24ctmzZAqVSCUdHR/Ts2RNXr17FCy+8gAULFmD16tWwsbHB119/jdmzZ6OmpgZmZmaN1hMZGYnDhw/jww8/hLu7O0xNTfHKK6+gpqZGilEoFBBCyJarra1tMT+VSgWVStU+O0tERETURmzwqdsxNzeHu7u7bNrZs2dRX1+Pjz76CEZG93+YaunyHABIT09HeHg4pkyZAuD+Gf2rV6/KYuzs7FBcXCyNX7p0qdlfBIiIiIj0AS/RIYPg7u6O2tpabNy4EVeuXMGOHTuwdevWFpfx8PDAvn37kJWVhezsbISGhqK+vl4WExgYiI8//hjnzp1DZmYm5s+fD2Nj447cFSIiIqInwgafDMKwYcMQHx+PDz74AEOGDEFSUhLi4uJaXCY+Ph7W1tZ4+umnMWnSJOh0OgwfPlwW89FHH8HZ2RmjR49GaGgoIiMjm7zch4iIiEhfKMTDFxgTUbuqqKiAWq1GzJdTYWKu7Op0iB7L0md3dHUKRES/KA39Q3l5OaysrNq0LM/gExEREREZEDb4REREREQGhA0+EREREZEB4WMyiTrJH0Zta/M1dERERERtxTP4REREREQGhA0+EREREZEBYYNPRERERGRAeA0+USfZfWYKTM35kvulmfFUSlenQEREvzA8g09EREREZEDY4BMRERERGRA2+EREREREBoQNPhERERGRAWGDT0RERERkQNjgk94KDw+HQqHAmjVrZNMPHDgAhULRRVkRERER6Tc2+KTXTExM8MEHH6C0tLRTt1tbW9up2yMiIiJqL2zwSa8FBQVBq9UiLi6uyfklJSWYPn06nJycYGZmBm9vb+zcuVMW069fP/z5z3+WTfPx8UFsbKw0rlAosGXLFrz44oswNzfH6tWrkZiYCI1GI1uOvx4QERGRvmODT3qtR48eeP/997Fx40b8+OOPjebfvXsXvr6++OKLL5CTk4O5c+di5syZOH36dJu3FRsbiylTpuDChQv47W9/+9g5V1dXo6KiQjYQERERdRY2+KT3pkyZAh8fH8TExDSa5+TkhMjISPj4+MDNzQ1vvPEGgoODsWfPnjZvJzQ0FK+99hrc3NzQt2/fx843Li4OarVaGpydnR97XURERERtxQafuoUPPvgA27dvR25urmz6vXv3sGrVKnh7e8PGxgYWFhZISUlBYWFhm7cxYsSIdsk1Ojoa5eXl0lBUVNQu6yUiIiJqDTb41C2MGTMGOp0O0dHRsunr1q3D+vXrERUVhWPHjiErKws6nQ41NTVSjJGREYQQsuWauonW3NxcNt7a5R6mUqlgZWUlG4iIiIg6S8+uToCotdasWQMfHx94enpK09LT0xESEoIZM2YAAOrr6/H9999j0KBBUoydnR2Ki4ul8YqKChQUFDxye3Z2dqisrMStW7ek5j8rK6ud9oaIiIioY/AMPnUb3t7eCAsLw4YNG6RpHh4eOHz4ME6ePInc3FzMmzcP169fly0XGBiIHTt24MSJE7hw4QJmzZqFHj16PHJ7/v7+MDMzwx//+Efk5+fj008/RWJiYnvvFhEREVG7YoNP3crKlStRX18vjS9btgzDhw+HTqdDQEAAtFotJk+eLFsmOjoaY8eOxQsvvICJEydi8uTJ6N+//yO3ZWNjg7///e9ITk6WHr/54KM1iYiIiPSRQjx8kTERtauKigqo1Wr8vyOBMDXnVXG/NDOeSunqFIiIqBtq6B/Ky8vbfD8fz+ATERERERkQNvhERERERAaE1wsQdZJpfvv5yEwiIiLqcDyDT0RERERkQNjgExEREREZEDb4REREREQGhA0+EREREZEB4U22RJ0kPXMszC0e/R90ST+NGZnZ1SkQERG1Cs/gExEREREZEDb4REREREQGhA0+EREREZEBYYNP9JCAgABERER0dRpEREREj4UNPukVhULR4hAbG9vVKRIRERHpNT5Fh/RKcXGx9Pfu3bvx7rvvIi8vT5pmYWHRFWkRERERdRs8g096RavVSoNarYZCoZDGt27dimeffVYW/+c//xn9+vUDAPzrX/+CiYkJysrKZDGLFy9GYGAgAKCkpATTp0+Hk5MTzMzM4O3tjZ07d7aYk0KhwIEDB2TTNBoNEhMTn2RXiYiIiDoEG3wyGOPHj4dGo8Fnn30mTbt37x52796NsLAwAMDdu3fh6+uLL774Ajk5OZg7dy5mzpyJ06dPt1se1dXVqKiokA1EREREnYUNPhmMHj164NVXX8Wnn34qTUtNTUVZWRlefvllAICTkxMiIyPh4+MDNzc3vPHGGwgODsaePXvaLY+4uDio1WppcHZ2brd1ExERET0KG3wyKGFhYUhLS8N///tfAEBSUhImTpwIjUYD4P4Z/VWrVsHb2xs2NjawsLBASkoKCgsL2y2H6OholJeXS0NRUVG7rZuIiIjoUdjgU7dhZGQEIYRsWm1trWzcz88P/fv3x65du3Dnzh3s379fujwHANatW4f169cjKioKx44dQ1ZWFnQ6HWpqaprdrkKheOR2H6RSqWBlZSUbiIiIiDoLn6JD3YadnR2uXbsGIQQUCgUAICsrq1FcWFgYkpKS0KdPHxgZGWHixInSvPT0dISEhGDGjBkAgPr6enz//fcYNGhQi9t98Ok+ly5dwu3bt9tpr4iIiIjaF8/gU7cREBCAn376CWvXrkV+fj42bdqEf/7zn43iwsLC8O9//xurV6/GK6+8ApVKJc3z8PDA4cOHcfLkSeTm5mLevHm4fv16i9sNDAzExx9/jHPnziEzMxPz58+HsbFxu+8fERERUXtgg0/dhpeXFzZv3oxNmzZh2LBhOH36NCIjIxvFubu7Y+TIkTh//rzs8hwAWLZsGYYPHw6dToeAgABotVpMnjy5xe1+9NFHcHZ2xujRoxEaGorIyEiYmZm1564RERERtRuFePjiYiJqVxUVFVCr1UhO9YG5RY+uToce05iRmV2dAhER/YI09A/l5eVtvp+PZ/CJiIiIiAwIG3wiIiIiIgPCp+gQdZJnRnzFR2YSERFRh+MZfCIiIiIiA8Iz+EQdrOE+9oqKii7OhIiIiLqLhr7hcZ6HwwafqIOVlJQAAJydnbs4EyIiIupuKisroVar27QMG3yiDmZjYwMAKCwsbPMLlDpORUUFnJ2dUVRUxHsj9Ajrop9YF/3Euuiv9qiNEAKVlZVwdHRs87Js8Ik6mJHR/Vtd1Go134D1kJWVFeuih1gX/cS66CfWRX89aW0e98Qgb7IlIiIiIjIgbPCJiIiIiAwIG3yiDqZSqRATEwOVStXVqdADWBf9xLroJ9ZFP7Eu+qura6MQj/PsHSIiIiIi0ks8g09EREREZEDY4BMRERERGRA2+EREREREBoQNPhERERGRAWGDT9TBNm3ahH79+sHExAT+/v44ffp0V6dkMGJjY6FQKGTDwIEDpfl3797FwoUL0atXL1hYWODll1/G9evXZesoLCzExIkTYWZmht69e+Ott95CXV2dLCYtLQ3Dhw+HSqWCu7s7EhMTO2P3uo3jx49j0qRJcHR0hEKhwIEDB2TzhRB499134eDgAFNTUwQFBeHSpUuymJs3byIsLAxWVlbQaDSYPXs2qqqqZDHnz5/H6NGjYWJiAmdnZ6xdu7ZRLnv37sXAgQNhYmICb29vJCcnt/v+dhePqkt4eHij109wcLAshnVpf3FxcfDz84OlpSV69+6NyZMnIy8vTxbTme9d/Iy6rzV1CQgIaPSamT9/vixGb+oiiKjD7Nq1SyiVSvHXv/5VfPvtt2LOnDlCo9GI69evd3VqBiEmJkYMHjxYFBcXS8NPP/0kzZ8/f75wdnYWqampIjMzUzz11FPi6aeflubX1dWJIUOGiKCgIHHu3DmRnJwsbG1tRXR0tBRz5coVYWZmJv7whz+Iixcvio0bN4oePXqIL7/8slP3VZ8lJyeLd955R+zbt08AEPv375fNX7NmjVCr1eLAgQMiOztbvPjii8LV1VXcuXNHigkODhbDhg0T33zzjThx4oRwd3cX06dPl+aXl5cLe3t7ERYWJnJycsTOnTuFqamp+Mtf/iLFpKenix49eoi1a9eKixcvimXLlgljY2Nx4cKFDj8G+uhRdZk1a5YIDg6WvX5u3rwpi2Fd2p9OpxMJCQkiJydHZGVlieeff1707dtXVFVVSTGd9d7Fz6j/aU1dxo4dK+bMmSN7zZSXl0vz9akubPCJOtDIkSPFwoULpfF79+4JR0dHERcX14VZGY6YmBgxbNiwJueVlZUJY2NjsXfvXmlabm6uACBOnTolhLjfABkZGYlr165JMVu2bBFWVlaiurpaCCHE22+/LQYPHixb97Rp04ROp2vnvTEMDzeS9fX1QqvVinXr1knTysrKhEqlEjt37hRCCHHx4kUBQJw5c0aK+ec//ykUCoX4z3/+I4QQYvPmzcLa2lqqixBCREVFCU9PT2l86tSpYuLEibJ8/P39xbx589p1H7uj5hr8kJCQZpdhXTrHjRs3BADx1VdfCSE6972Ln1HNe7guQtxv8BcvXtzsMvpUF16iQ9RBampqcPbsWQQFBUnTjIyMEBQUhFOnTnVhZobl0qVLcHR0hJubG8LCwlBYWAgAOHv2LGpra2XHf+DAgejbt690/E+dOgVvb2/Y29tLMTqdDhUVFfj222+lmAfX0RDDGrZOQUEBrl27JjuGarUa/v7+sjpoNBqMGDFCigkKCoKRkREyMjKkmDFjxkCpVEoxOp0OeXl5KC0tlWJYq7ZJS0tD79694enpiQULFqCkpESax7p0jvLycgCAjY0NgM577+JnVMserkuDpKQk2NraYsiQIYiOjsbt27elefpUl56tjiSiNvn5559x79492QsdAOzt7fHdd991UVaGxd/fH4mJifD09ERxcTFWrFiB0aNHIycnB9euXYNSqYRGo5EtY29vj2vXrgEArl271mR9Gua1FFNRUYE7d+7A1NS0g/bOMDQcx6aO4YPHuHfv3rL5PXv2hI2NjSzG1dW10Toa5llbWzdbq4Z1kFxwcDBeeukluLq6Ij8/H3/84x8xYcIEnDp1Cj169GBdOkF9fT0iIiLwzDPPYMiQIQDQae9dpaWl/IxqRlN1AYDQ0FC4uLjA0dER58+fR1RUFPLy8rBv3z4A+lUXNvhE1G1NmDBB+nvo0KHw9/eHi4sL9uzZw8ab6BFeffVV6W9vb28MHToU/fv3R1paGsaPH9+Fmf1yLFy4EDk5Ofj666+7OhV6QHN1mTt3rvS3t7c3HBwcMH78eOTn56N///6dnWaLeIkOUQextbVFjx49Gj354Pr169BqtV2UlWHTaDQYMGAALl++DK1Wi5qaGpSVlcliHjz+Wq22yfo0zGspxsrKil8iWqHhOLb0OtBqtbhx44Zsfl1dHW7evNkuteLrrXXc3Nxga2uLy5cvA2BdOtqiRYtw6NAhHDt2DH369JGmd9Z7Fz+jmtZcXZri7+8PALLXjL7UhQ0+UQdRKpXw9fVFamqqNK2+vh6pqakYNWpUF2ZmuKqqqpCfnw8HBwf4+vrC2NhYdvzz8vJQWFgoHf9Ro0bhwoULsibm8OHDsLKywqBBg6SYB9fREMMato6rqyu0Wq3sGFZUVCAjI0NWh7KyMpw9e1aKOXr0KOrr66UP0FGjRuH48eOora2VYg4fPgxPT09YW1tLMazV4/vxxx9RUlICBwcHAKxLRxFCYNGiRdi/fz+OHj3a6BKnznrv4meU3KPq0pSsrCwAkL1m9KYurb4dl4jabNeuXUKlUonExERx8eJFMXfuXKHRaGR32NPjW7JkiUhLSxMFBQUiPT1dBAUFCVtbW3Hjxg0hxP1HzfXt21ccPXpUZGZmilGjRolRo0ZJyzc80uy5554TWVlZ4ssvvxR2dnZNPtLsrbfeErm5uWLTpk18TOZDKisrxblz58S5c+cEABEfHy/OnTsnfvjhByHE/cdkajQa8fnnn4vz58+LkJCQJh+T+atf/UpkZGSIr7/+Wnh4eMgex1hWVibs7e3FzJkzRU5Ojti1a5cwMzNr9DjGnj17ig8//FDk5uaKmJiYX/TjGFuqS2VlpYiMjBSnTp0SBQUF4siRI2L48OHCw8ND3L17V1oH69L+FixYINRqtUhLS5M9bvH27dtSTGe9d/Ez6n8eVZfLly+LlStXiszMTFFQUCA+//xz4ebmJsaMGSOtQ5/qwgafqINt3LhR9O3bVyiVSjFy5EjxzTffdHVKBmPatGnCwcFBKJVK4eTkJKZNmyYuX74szb9z54743e9+J6ytrYWZmZmYMmWKKC4ulq3j6tWrYsKECcLU1FTY2tqKJUuWiNraWlnMsWPHhI+Pj1AqlcLNzU0kJCR0xu51G8eOHRMAGg2zZs0SQtx/VOby5cuFvb29UKlUYvz48SIvL0+2jpKSEjF9+nRhYWEhrKysxGuvvSYqKytlMdnZ2eLZZ58VKpVKODk5iTVr1jTKZc+ePWLAgAFCqVSKwYMHiy+++KLD9lvftVSX27dvi+eee07Y2dkJY2Nj4eLiIubMmdOogWBd2l9TNQEge1/pzPcufkbd96i6FBYWijFjxggbGxuhUqmEu7u7eOutt2TPwRdCf+qi+L+dIiIiIiIiA8Br8ImIiIiIDAgbfCIiIiIiA8IGn4iIiIjIgLDBJyIiIiIyIGzwiYiIiIgMCBt8IiIiIiIDwgafiIiIiMiAsMEnIiIiIjIgbPCJiIgeITY2Fj4+Pl2dRrsICAhARESE3qyHiNofG3wiItIbaWlpUCgUjYZly5Z1dWpPLDw8XNofpVIJd3d3rFy5EnV1dV2dWosaalJWViabvm/fPqxataprkiKiFvXs6gSIiIgelpeXBysrK2ncwsKiC7NpP8HBwUhISEB1dTWSk5OxcOFCGBsbIzo6uqtTazMbG5uuToGImsEz+EREpHd69+4NrVYrDQ0NflFREaZOnQqNRgMbGxuEhITg6tWr0nLh4eGYPHky3n//fdjb20Oj0Uhnyd966y3Y2NigT58+SEhIkG0vKioKAwYMgJmZGdzc3LB8+XLU1ta2mOMnn3wCLy8vmJiYYODAgdi8efMj90ulUkGr1cLFxQULFixAUFAQDh48CAAoLS3Fb37zG1hbW8PMzAwTJkzApUuXpGUTExOh0Whw4MABeHh4wMTEBDqdDkVFRY32/0EREREICAhoNqcdO3ZgxIgRsLS0hFarRWhoKG7cuAEAuHr1KsaNGwcAsLa2hkKhQHh4OIDGl+i0Nv+UlBR4eXnBwsICwcHBKC4ufuRxI6K2YYNPRETdQm1tLXQ6HSwtLXHixAmkp6dLTWJNTY0Ud/ToUfz3v//F8ePHER8fj5iYGLzwwguwtrZGRkYG5s+fj3nz5uHHH3+UlrG0tERiYiIuXryI9evXY9u2bfjTn/7UbC5JSUl49913sXr1auTm5uL999/H8uXLsX379jbtk6mpqZR7eHg4MjMzcfDgQZw6dQpCCDz//POyLxq3b9/G6tWr8be//Q3p6ekoKyvDq6++2qZtPqy2tharVq1CdnY2Dhw4gKtXr0pNvLOzMz777DMA939VKS4uxvr165tcT2vz//DDD7Fjxw4cP34chYWFiIyMfKL8iagJgoiISE8cO3ZMABDm5uay4eeffxY7duwQnp6eor6+Xoqvrq4WpqamIiUlRQghxKxZs4SLi4u4d++eFOPp6SlGjx4tjdfV1Qlzc3Oxc+fOZvNYt26d8PX1lcZjYmLEsGHDpPH+/fuLTz/9VLbMqlWrxKhRo5pd56xZs0RISIgQQoj6+npx+PBhoVKpRGRkpPj+++8FAJGeni7F//zzz8LU1FTs2bNHCCFEQkKCACC++eYbKSY3N1cAEBkZGY220WDx4sVi7Nix0vjYsWPF4sWLm83zzJkzAoCorKwUQvyvJqWlpbK4B9fTlvwvX74sxWzatEnY29s3mwsRPR5eg09ERHrnxIkTsLS0lMatra2RnZ2Ny5cvy6YDwN27d5Gfny+NDx48GEZG//uB2t7eHkOGDJHGe/TogV69ekmXoQDA7t27sWHDBuTn56Oqqgp1dXWyewAedOvWLeTn52P27NmYM2eONL2urg5qtbrF/Tp06BAsLCxQW1uL+vp6hIaGIjY2FqmpqejZsyf8/f2l2F69esHT0xO5ubnStJ49e8LPz08aHzhwIDQaDXJzczFy5MgWt92cs2fPIjY2FtnZ2SgtLUV9fT0AoLCwEIMGDWrVOnJzc1uVv5mZGfr37y+NOzg4yOpARO2DDT4REekdV1dXaDQa2bSqqir4+voiKSmpUbydnZ30t7GxsWyeQqFoclpDI3vq1CmEhYVhxYoV0Ol0UKvV2LVrFz766KMmc6uqqgIAbNu2TdbQAve/PLRk3Lhx2LJlC5RKJRwdHdGzZ/t+DBsZGUEIIZvW0r0Et27dgk6ng06nQ1JSEuzs7FBYWAidTie77Km9NFWHh/MloifHBp+IiLqF4cOHY/fu3ejdu3ezZ9cfx8mTJ+Hi4oJ33nlHmvbDDz80G29vbw9HR0dcuXIFYWFhbdqWubk53N3dG0338vJCXV0dMjIy8PTTTwMASkpKkJeXJzuLXldXh8zMTOlsfV5eHsrKyuDl5QXg/hednJwc2bqzsrIaNdYNvvvuO5SUlGDNmjVwdnYGAGRmZspilEolAODevXvN7ldr8yeizsGbbImIqFsICwuDra0tQkJCcOLECRQUFCAtLQ1vvvmm7IbZtvLw8EBhYSF27dqF/Px8bNiwAfv3729xmRUrViAuLg4bNmzA999/jwsXLiAhIQHx8fGPnUNISAjmzJmDr7/+GtnZ2ZgxYwacnJwQEhIixRkbG+ONN95ARkYGzp49i/DwcDz11FNSwx8YGIjMzEz87W9/w6VLlxATE9Oo4X9Q3759oVQqsXHjRly5cgUHDx5s9Gx7FxcXKBQKHDp0CD/99JP0C8bj5E9EnYMNPhERdQtmZmY4fvw4+vbti5deegleXl6YPXs27t69+0Rn9F988UX8/ve/x6JFi+Dj44OTJ09i+fLlLS7z+uuv45NPPkFCQgK8vb0xduxYJCYmwtXV9bHzSEhIgK+vL1544QWMGjUKQggkJyfLzr6bmZkhKioKoaGheOaZZ2BhYYHdu3dL83U6HZYvX463334bfn5+qKysxG9+85tmt2lnZ4fExETs3bsXgwYNwpo1a/Dhhx/KYpycnLBixQosXboU9vb2WLRo0WPnT0SdQyF48RsREZHeS0xMRERERKP/KEtE9DCewSciIiIiMiBs8ImIiIiIDAgv0SEiIiIiMiA8g09EREREZEDY4BMRERERGRA2+EREREREBoQNPhERERGRAWGDT0RERERkQNjgExEREREZEDb4REREREQGhA0+EREREZEB+f/6Nbof9qDmdwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plot for male lowest population\n",
    "plt.figure(figsize=(15, 10))\n",
    "plt.subplot(2, 2, 1)\n",
    "sns.barplot(x=\"2022\", y=\"Country Name\", data=male_lowest_pop, palette=\"viridis\")\n",
    "plt.xlabel(\"Male Population\")\n",
    "plt.ylabel(\"Country Name\")\n",
    "plt.title(\"Top countries with lowest male population (2022)\")\n",
    "plt.show()\n",
    "\n",
    "# Bar plot for female lowest population\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "plt.subplot(2, 2, 2)\n",
    "sns.barplot(\n",
    "    x=\"2022\", y=\"Country Name\", data=female_lowest_population, palette=\"viridis\"\n",
    ")\n",
    "plt.xlabel(\" Female Population\")\n",
    "plt.ylabel(\"Country Name\")\n",
    "plt.title(\"Top countries with lowest female population(2022)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Top countries with male and female population:_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Series Code_male</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>2022_male</th>\n",
       "      <th>2021_male</th>\n",
       "      <th>2020_male</th>\n",
       "      <th>2019_male</th>\n",
       "      <th>2018_male</th>\n",
       "      <th>2017_male</th>\n",
       "      <th>2016_male</th>\n",
       "      <th>2015_male</th>\n",
       "      <th>...</th>\n",
       "      <th>2010_female</th>\n",
       "      <th>2009_female</th>\n",
       "      <th>2008_female</th>\n",
       "      <th>2007_female</th>\n",
       "      <th>2006_female</th>\n",
       "      <th>2005_female</th>\n",
       "      <th>2004_female</th>\n",
       "      <th>2003_female</th>\n",
       "      <th>2002_female</th>\n",
       "      <th>2001_female</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>20766442.0</td>\n",
       "      <td>20254878.0</td>\n",
       "      <td>19692301.0</td>\n",
       "      <td>19090409.0</td>\n",
       "      <td>18549862.0</td>\n",
       "      <td>18028696.0</td>\n",
       "      <td>17520861.0</td>\n",
       "      <td>17071446.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13949295.0</td>\n",
       "      <td>13557331.0</td>\n",
       "      <td>13088192.0</td>\n",
       "      <td>12835340.0</td>\n",
       "      <td>12614497.0</td>\n",
       "      <td>12109086.0</td>\n",
       "      <td>11690825.0</td>\n",
       "      <td>11247647.0</td>\n",
       "      <td>10438055.0</td>\n",
       "      <td>9793166.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Albania</td>\n",
       "      <td>1384548.0</td>\n",
       "      <td>1404454.0</td>\n",
       "      <td>1419264.0</td>\n",
       "      <td>1428828.0</td>\n",
       "      <td>1435881.0</td>\n",
       "      <td>1440219.0</td>\n",
       "      <td>1442176.0</td>\n",
       "      <td>1444890.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1454108.0</td>\n",
       "      <td>1462978.0</td>\n",
       "      <td>1474838.0</td>\n",
       "      <td>1488396.0</td>\n",
       "      <td>1501918.0</td>\n",
       "      <td>1513578.0</td>\n",
       "      <td>1523393.0</td>\n",
       "      <td>1531532.0</td>\n",
       "      <td>1538490.0</td>\n",
       "      <td>1543533.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>22862237.0</td>\n",
       "      <td>22497244.0</td>\n",
       "      <td>22132899.0</td>\n",
       "      <td>21756903.0</td>\n",
       "      <td>21362603.0</td>\n",
       "      <td>20961313.0</td>\n",
       "      <td>20556314.0</td>\n",
       "      <td>20152232.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17573708.0</td>\n",
       "      <td>17249096.0</td>\n",
       "      <td>16941031.0</td>\n",
       "      <td>16653361.0</td>\n",
       "      <td>16384158.0</td>\n",
       "      <td>16150274.0</td>\n",
       "      <td>15932047.0</td>\n",
       "      <td>15709725.0</td>\n",
       "      <td>15497822.0</td>\n",
       "      <td>15288132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>21873.0</td>\n",
       "      <td>22289.0</td>\n",
       "      <td>22921.0</td>\n",
       "      <td>23535.0</td>\n",
       "      <td>24134.0</td>\n",
       "      <td>24701.0</td>\n",
       "      <td>25240.0</td>\n",
       "      <td>25739.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27189.0</td>\n",
       "      <td>27406.0</td>\n",
       "      <td>27626.0</td>\n",
       "      <td>27842.0</td>\n",
       "      <td>28044.0</td>\n",
       "      <td>28230.0</td>\n",
       "      <td>28392.0</td>\n",
       "      <td>28521.0</td>\n",
       "      <td>28608.0</td>\n",
       "      <td>28649.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>40786.0</td>\n",
       "      <td>40361.0</td>\n",
       "      <td>39615.0</td>\n",
       "      <td>38842.0</td>\n",
       "      <td>38071.0</td>\n",
       "      <td>37380.0</td>\n",
       "      <td>36628.0</td>\n",
       "      <td>36188.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35212.0</td>\n",
       "      <td>36065.0</td>\n",
       "      <td>36864.0</td>\n",
       "      <td>37633.0</td>\n",
       "      <td>38392.0</td>\n",
       "      <td>38147.0</td>\n",
       "      <td>36852.0</td>\n",
       "      <td>35478.0</td>\n",
       "      <td>34076.0</td>\n",
       "      <td>32669.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Series Code_male    Country Name   2022_male   2021_male   2020_male  \\\n",
       "0  SP.POP.TOTL.MA.IN     Afghanistan  20766442.0  20254878.0  19692301.0   \n",
       "1  SP.POP.TOTL.MA.IN         Albania   1384548.0   1404454.0   1419264.0   \n",
       "2  SP.POP.TOTL.MA.IN         Algeria  22862237.0  22497244.0  22132899.0   \n",
       "3  SP.POP.TOTL.MA.IN  American Samoa     21873.0     22289.0     22921.0   \n",
       "4  SP.POP.TOTL.MA.IN         Andorra     40786.0     40361.0     39615.0   \n",
       "\n",
       "    2019_male   2018_male   2017_male   2016_male   2015_male  ...  \\\n",
       "0  19090409.0  18549862.0  18028696.0  17520861.0  17071446.0  ...   \n",
       "1   1428828.0   1435881.0   1440219.0   1442176.0   1444890.0  ...   \n",
       "2  21756903.0  21362603.0  20961313.0  20556314.0  20152232.0  ...   \n",
       "3     23535.0     24134.0     24701.0     25240.0     25739.0  ...   \n",
       "4     38842.0     38071.0     37380.0     36628.0     36188.0  ...   \n",
       "\n",
       "   2010_female  2009_female  2008_female  2007_female  2006_female  \\\n",
       "0   13949295.0   13557331.0   13088192.0   12835340.0   12614497.0   \n",
       "1    1454108.0    1462978.0    1474838.0    1488396.0    1501918.0   \n",
       "2   17573708.0   17249096.0   16941031.0   16653361.0   16384158.0   \n",
       "3      27189.0      27406.0      27626.0      27842.0      28044.0   \n",
       "4      35212.0      36065.0      36864.0      37633.0      38392.0   \n",
       "\n",
       "   2005_female  2004_female  2003_female  2002_female  2001_female  \n",
       "0   12109086.0   11690825.0   11247647.0   10438055.0    9793166.0  \n",
       "1    1513578.0    1523393.0    1531532.0    1538490.0    1543533.0  \n",
       "2   16150274.0   15932047.0   15709725.0   15497822.0   15288132.0  \n",
       "3      28230.0      28392.0      28521.0      28608.0      28649.0  \n",
       "4      38147.0      36852.0      35478.0      34076.0      32669.0  \n",
       "\n",
       "[5 rows x 47 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_data = pd.merge(\n",
    "    male_population, female_population, on=\"Country Name\", suffixes=(\"_male\", \"_female\")\n",
    ")\n",
    "merge_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>Series Code_male</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>2022_male</th>\n",
       "      <th>2021_male</th>\n",
       "      <th>2020_male</th>\n",
       "      <th>2019_male</th>\n",
       "      <th>2018_male</th>\n",
       "      <th>2017_male</th>\n",
       "      <th>2016_male</th>\n",
       "      <th>2015_male</th>\n",
       "      <th>...</th>\n",
       "      <th>2010_female</th>\n",
       "      <th>2009_female</th>\n",
       "      <th>2008_female</th>\n",
       "      <th>2007_female</th>\n",
       "      <th>2006_female</th>\n",
       "      <th>2005_female</th>\n",
       "      <th>2004_female</th>\n",
       "      <th>2003_female</th>\n",
       "      <th>2002_female</th>\n",
       "      <th>2001_female</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Virgin Islands (U.S.)</td>\n",
       "      <td>49137.0</td>\n",
       "      <td>49510.0</td>\n",
       "      <td>49866.0</td>\n",
       "      <td>50196.0</td>\n",
       "      <td>50489.0</td>\n",
       "      <td>50759.0</td>\n",
       "      <td>50999.0</td>\n",
       "      <td>51208.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56560.0</td>\n",
       "      <td>56549.0</td>\n",
       "      <td>56507.0</td>\n",
       "      <td>56467.0</td>\n",
       "      <td>56492.0</td>\n",
       "      <td>56555.0</td>\n",
       "      <td>56593.0</td>\n",
       "      <td>56652.0</td>\n",
       "      <td>56692.0</td>\n",
       "      <td>56744.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>2516444.0</td>\n",
       "      <td>2455361.0</td>\n",
       "      <td>2394860.0</td>\n",
       "      <td>2334948.0</td>\n",
       "      <td>2275925.0</td>\n",
       "      <td>2217868.0</td>\n",
       "      <td>2173706.0</td>\n",
       "      <td>2125660.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1897763.0</td>\n",
       "      <td>1848287.0</td>\n",
       "      <td>1798811.0</td>\n",
       "      <td>1749079.0</td>\n",
       "      <td>1703735.0</td>\n",
       "      <td>1659247.0</td>\n",
       "      <td>1615402.0</td>\n",
       "      <td>1572199.0</td>\n",
       "      <td>1530053.0</td>\n",
       "      <td>1489250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>17023203.0</td>\n",
       "      <td>16668432.0</td>\n",
       "      <td>16320979.0</td>\n",
       "      <td>15953578.0</td>\n",
       "      <td>15578957.0</td>\n",
       "      <td>15202496.0</td>\n",
       "      <td>14820156.0</td>\n",
       "      <td>14439156.0</td>\n",
       "      <td>...</td>\n",
       "      <td>12224951.0</td>\n",
       "      <td>11874775.0</td>\n",
       "      <td>11531790.0</td>\n",
       "      <td>11195418.0</td>\n",
       "      <td>10864747.0</td>\n",
       "      <td>10548931.0</td>\n",
       "      <td>10262472.0</td>\n",
       "      <td>9997157.0</td>\n",
       "      <td>9739899.0</td>\n",
       "      <td>9488026.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>9877642.0</td>\n",
       "      <td>9609004.0</td>\n",
       "      <td>9338613.0</td>\n",
       "      <td>9066397.0</td>\n",
       "      <td>8794716.0</td>\n",
       "      <td>8525934.0</td>\n",
       "      <td>8260471.0</td>\n",
       "      <td>8000338.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7026189.0</td>\n",
       "      <td>6794701.0</td>\n",
       "      <td>6569350.0</td>\n",
       "      <td>6351748.0</td>\n",
       "      <td>6144175.0</td>\n",
       "      <td>5947650.0</td>\n",
       "      <td>5764425.0</td>\n",
       "      <td>5593084.0</td>\n",
       "      <td>5431354.0</td>\n",
       "      <td>5276383.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>7705601.0</td>\n",
       "      <td>7543690.0</td>\n",
       "      <td>7385220.0</td>\n",
       "      <td>7231989.0</td>\n",
       "      <td>7086002.0</td>\n",
       "      <td>6940631.0</td>\n",
       "      <td>6796658.0</td>\n",
       "      <td>6652836.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6805605.0</td>\n",
       "      <td>6714016.0</td>\n",
       "      <td>6638373.0</td>\n",
       "      <td>6578079.0</td>\n",
       "      <td>6511613.0</td>\n",
       "      <td>6450827.0</td>\n",
       "      <td>6405855.0</td>\n",
       "      <td>6353380.0</td>\n",
       "      <td>6300516.0</td>\n",
       "      <td>6257972.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Series Code_male           Country Name   2022_male   2021_male  \\\n",
       "212  SP.POP.TOTL.MA.IN  Virgin Islands (U.S.)     49137.0     49510.0   \n",
       "213  SP.POP.TOTL.MA.IN     West Bank and Gaza   2516444.0   2455361.0   \n",
       "214  SP.POP.TOTL.MA.IN            Yemen, Rep.  17023203.0  16668432.0   \n",
       "215  SP.POP.TOTL.MA.IN                 Zambia   9877642.0   9609004.0   \n",
       "216  SP.POP.TOTL.MA.IN               Zimbabwe   7705601.0   7543690.0   \n",
       "\n",
       "      2020_male   2019_male   2018_male   2017_male   2016_male   2015_male  \\\n",
       "212     49866.0     50196.0     50489.0     50759.0     50999.0     51208.0   \n",
       "213   2394860.0   2334948.0   2275925.0   2217868.0   2173706.0   2125660.0   \n",
       "214  16320979.0  15953578.0  15578957.0  15202496.0  14820156.0  14439156.0   \n",
       "215   9338613.0   9066397.0   8794716.0   8525934.0   8260471.0   8000338.0   \n",
       "216   7385220.0   7231989.0   7086002.0   6940631.0   6796658.0   6652836.0   \n",
       "\n",
       "     ...  2010_female  2009_female  2008_female  2007_female  2006_female  \\\n",
       "212  ...      56560.0      56549.0      56507.0      56467.0      56492.0   \n",
       "213  ...    1897763.0    1848287.0    1798811.0    1749079.0    1703735.0   \n",
       "214  ...   12224951.0   11874775.0   11531790.0   11195418.0   10864747.0   \n",
       "215  ...    7026189.0    6794701.0    6569350.0    6351748.0    6144175.0   \n",
       "216  ...    6805605.0    6714016.0    6638373.0    6578079.0    6511613.0   \n",
       "\n",
       "     2005_female  2004_female  2003_female  2002_female  2001_female  \n",
       "212      56555.0      56593.0      56652.0      56692.0      56744.0  \n",
       "213    1659247.0    1615402.0    1572199.0    1530053.0    1489250.0  \n",
       "214   10548931.0   10262472.0    9997157.0    9739899.0    9488026.0  \n",
       "215    5947650.0    5764425.0    5593084.0    5431354.0    5276383.0  \n",
       "216    6450827.0    6405855.0    6353380.0    6300516.0    6257972.0  \n",
       "\n",
       "[5 rows x 47 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "merge_data[\"Total population\"] = merge_data[\"2022_male\"] + merge_data[\"2022_female\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Series Code_male</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>2022_male</th>\n",
       "      <th>2021_male</th>\n",
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       "      <th>2016_male</th>\n",
       "      <th>2015_male</th>\n",
       "      <th>...</th>\n",
       "      <th>2009_female</th>\n",
       "      <th>2008_female</th>\n",
       "      <th>2007_female</th>\n",
       "      <th>2006_female</th>\n",
       "      <th>2005_female</th>\n",
       "      <th>2004_female</th>\n",
       "      <th>2003_female</th>\n",
       "      <th>2002_female</th>\n",
       "      <th>2001_female</th>\n",
       "      <th>Total population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>20766442.0</td>\n",
       "      <td>20254878.0</td>\n",
       "      <td>19692301.0</td>\n",
       "      <td>19090409.0</td>\n",
       "      <td>18549862.0</td>\n",
       "      <td>18028696.0</td>\n",
       "      <td>17520861.0</td>\n",
       "      <td>17071446.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13557331.0</td>\n",
       "      <td>13088192.0</td>\n",
       "      <td>12835340.0</td>\n",
       "      <td>12614497.0</td>\n",
       "      <td>12109086.0</td>\n",
       "      <td>11690825.0</td>\n",
       "      <td>11247647.0</td>\n",
       "      <td>10438055.0</td>\n",
       "      <td>9793166.0</td>\n",
       "      <td>41128771.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Albania</td>\n",
       "      <td>1384548.0</td>\n",
       "      <td>1404454.0</td>\n",
       "      <td>1419264.0</td>\n",
       "      <td>1428828.0</td>\n",
       "      <td>1435881.0</td>\n",
       "      <td>1440219.0</td>\n",
       "      <td>1442176.0</td>\n",
       "      <td>1444890.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1462978.0</td>\n",
       "      <td>1474838.0</td>\n",
       "      <td>1488396.0</td>\n",
       "      <td>1501918.0</td>\n",
       "      <td>1513578.0</td>\n",
       "      <td>1523393.0</td>\n",
       "      <td>1531532.0</td>\n",
       "      <td>1538490.0</td>\n",
       "      <td>1543533.0</td>\n",
       "      <td>2775633.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>22862237.0</td>\n",
       "      <td>22497244.0</td>\n",
       "      <td>22132899.0</td>\n",
       "      <td>21756903.0</td>\n",
       "      <td>21362603.0</td>\n",
       "      <td>20961313.0</td>\n",
       "      <td>20556314.0</td>\n",
       "      <td>20152232.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17249096.0</td>\n",
       "      <td>16941031.0</td>\n",
       "      <td>16653361.0</td>\n",
       "      <td>16384158.0</td>\n",
       "      <td>16150274.0</td>\n",
       "      <td>15932047.0</td>\n",
       "      <td>15709725.0</td>\n",
       "      <td>15497822.0</td>\n",
       "      <td>15288132.0</td>\n",
       "      <td>44903224.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>21873.0</td>\n",
       "      <td>22289.0</td>\n",
       "      <td>22921.0</td>\n",
       "      <td>23535.0</td>\n",
       "      <td>24134.0</td>\n",
       "      <td>24701.0</td>\n",
       "      <td>25240.0</td>\n",
       "      <td>25739.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27406.0</td>\n",
       "      <td>27626.0</td>\n",
       "      <td>27842.0</td>\n",
       "      <td>28044.0</td>\n",
       "      <td>28230.0</td>\n",
       "      <td>28392.0</td>\n",
       "      <td>28521.0</td>\n",
       "      <td>28608.0</td>\n",
       "      <td>28649.0</td>\n",
       "      <td>44272.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>40786.0</td>\n",
       "      <td>40361.0</td>\n",
       "      <td>39615.0</td>\n",
       "      <td>38842.0</td>\n",
       "      <td>38071.0</td>\n",
       "      <td>37380.0</td>\n",
       "      <td>36628.0</td>\n",
       "      <td>36188.0</td>\n",
       "      <td>...</td>\n",
       "      <td>36065.0</td>\n",
       "      <td>36864.0</td>\n",
       "      <td>37633.0</td>\n",
       "      <td>38392.0</td>\n",
       "      <td>38147.0</td>\n",
       "      <td>36852.0</td>\n",
       "      <td>35478.0</td>\n",
       "      <td>34076.0</td>\n",
       "      <td>32669.0</td>\n",
       "      <td>79824.0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Virgin Islands (U.S.)</td>\n",
       "      <td>49137.0</td>\n",
       "      <td>49510.0</td>\n",
       "      <td>49866.0</td>\n",
       "      <td>50196.0</td>\n",
       "      <td>50489.0</td>\n",
       "      <td>50759.0</td>\n",
       "      <td>50999.0</td>\n",
       "      <td>51208.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56549.0</td>\n",
       "      <td>56507.0</td>\n",
       "      <td>56467.0</td>\n",
       "      <td>56492.0</td>\n",
       "      <td>56555.0</td>\n",
       "      <td>56593.0</td>\n",
       "      <td>56652.0</td>\n",
       "      <td>56692.0</td>\n",
       "      <td>56744.0</td>\n",
       "      <td>105412.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>2516444.0</td>\n",
       "      <td>2455361.0</td>\n",
       "      <td>2394860.0</td>\n",
       "      <td>2334948.0</td>\n",
       "      <td>2275925.0</td>\n",
       "      <td>2217868.0</td>\n",
       "      <td>2173706.0</td>\n",
       "      <td>2125660.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1848287.0</td>\n",
       "      <td>1798811.0</td>\n",
       "      <td>1749079.0</td>\n",
       "      <td>1703735.0</td>\n",
       "      <td>1659247.0</td>\n",
       "      <td>1615402.0</td>\n",
       "      <td>1572199.0</td>\n",
       "      <td>1530053.0</td>\n",
       "      <td>1489250.0</td>\n",
       "      <td>5043613.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>17023203.0</td>\n",
       "      <td>16668432.0</td>\n",
       "      <td>16320979.0</td>\n",
       "      <td>15953578.0</td>\n",
       "      <td>15578957.0</td>\n",
       "      <td>15202496.0</td>\n",
       "      <td>14820156.0</td>\n",
       "      <td>14439156.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11874775.0</td>\n",
       "      <td>11531790.0</td>\n",
       "      <td>11195418.0</td>\n",
       "      <td>10864747.0</td>\n",
       "      <td>10548931.0</td>\n",
       "      <td>10262472.0</td>\n",
       "      <td>9997157.0</td>\n",
       "      <td>9739899.0</td>\n",
       "      <td>9488026.0</td>\n",
       "      <td>33696614.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>9877642.0</td>\n",
       "      <td>9609004.0</td>\n",
       "      <td>9338613.0</td>\n",
       "      <td>9066397.0</td>\n",
       "      <td>8794716.0</td>\n",
       "      <td>8525934.0</td>\n",
       "      <td>8260471.0</td>\n",
       "      <td>8000338.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6794701.0</td>\n",
       "      <td>6569350.0</td>\n",
       "      <td>6351748.0</td>\n",
       "      <td>6144175.0</td>\n",
       "      <td>5947650.0</td>\n",
       "      <td>5764425.0</td>\n",
       "      <td>5593084.0</td>\n",
       "      <td>5431354.0</td>\n",
       "      <td>5276383.0</td>\n",
       "      <td>20017675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>7705601.0</td>\n",
       "      <td>7543690.0</td>\n",
       "      <td>7385220.0</td>\n",
       "      <td>7231989.0</td>\n",
       "      <td>7086002.0</td>\n",
       "      <td>6940631.0</td>\n",
       "      <td>6796658.0</td>\n",
       "      <td>6652836.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6714016.0</td>\n",
       "      <td>6638373.0</td>\n",
       "      <td>6578079.0</td>\n",
       "      <td>6511613.0</td>\n",
       "      <td>6450827.0</td>\n",
       "      <td>6405855.0</td>\n",
       "      <td>6353380.0</td>\n",
       "      <td>6300516.0</td>\n",
       "      <td>6257972.0</td>\n",
       "      <td>16320536.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>217 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Series Code_male           Country Name   2022_male   2021_male  \\\n",
       "0    SP.POP.TOTL.MA.IN            Afghanistan  20766442.0  20254878.0   \n",
       "1    SP.POP.TOTL.MA.IN                Albania   1384548.0   1404454.0   \n",
       "2    SP.POP.TOTL.MA.IN                Algeria  22862237.0  22497244.0   \n",
       "3    SP.POP.TOTL.MA.IN         American Samoa     21873.0     22289.0   \n",
       "4    SP.POP.TOTL.MA.IN                Andorra     40786.0     40361.0   \n",
       "..                 ...                    ...         ...         ...   \n",
       "212  SP.POP.TOTL.MA.IN  Virgin Islands (U.S.)     49137.0     49510.0   \n",
       "213  SP.POP.TOTL.MA.IN     West Bank and Gaza   2516444.0   2455361.0   \n",
       "214  SP.POP.TOTL.MA.IN            Yemen, Rep.  17023203.0  16668432.0   \n",
       "215  SP.POP.TOTL.MA.IN                 Zambia   9877642.0   9609004.0   \n",
       "216  SP.POP.TOTL.MA.IN               Zimbabwe   7705601.0   7543690.0   \n",
       "\n",
       "      2020_male   2019_male   2018_male   2017_male   2016_male   2015_male  \\\n",
       "0    19692301.0  19090409.0  18549862.0  18028696.0  17520861.0  17071446.0   \n",
       "1     1419264.0   1428828.0   1435881.0   1440219.0   1442176.0   1444890.0   \n",
       "2    22132899.0  21756903.0  21362603.0  20961313.0  20556314.0  20152232.0   \n",
       "3       22921.0     23535.0     24134.0     24701.0     25240.0     25739.0   \n",
       "4       39615.0     38842.0     38071.0     37380.0     36628.0     36188.0   \n",
       "..          ...         ...         ...         ...         ...         ...   \n",
       "212     49866.0     50196.0     50489.0     50759.0     50999.0     51208.0   \n",
       "213   2394860.0   2334948.0   2275925.0   2217868.0   2173706.0   2125660.0   \n",
       "214  16320979.0  15953578.0  15578957.0  15202496.0  14820156.0  14439156.0   \n",
       "215   9338613.0   9066397.0   8794716.0   8525934.0   8260471.0   8000338.0   \n",
       "216   7385220.0   7231989.0   7086002.0   6940631.0   6796658.0   6652836.0   \n",
       "\n",
       "     ...  2009_female  2008_female  2007_female  2006_female  2005_female  \\\n",
       "0    ...   13557331.0   13088192.0   12835340.0   12614497.0   12109086.0   \n",
       "1    ...    1462978.0    1474838.0    1488396.0    1501918.0    1513578.0   \n",
       "2    ...   17249096.0   16941031.0   16653361.0   16384158.0   16150274.0   \n",
       "3    ...      27406.0      27626.0      27842.0      28044.0      28230.0   \n",
       "4    ...      36065.0      36864.0      37633.0      38392.0      38147.0   \n",
       "..   ...          ...          ...          ...          ...          ...   \n",
       "212  ...      56549.0      56507.0      56467.0      56492.0      56555.0   \n",
       "213  ...    1848287.0    1798811.0    1749079.0    1703735.0    1659247.0   \n",
       "214  ...   11874775.0   11531790.0   11195418.0   10864747.0   10548931.0   \n",
       "215  ...    6794701.0    6569350.0    6351748.0    6144175.0    5947650.0   \n",
       "216  ...    6714016.0    6638373.0    6578079.0    6511613.0    6450827.0   \n",
       "\n",
       "     2004_female  2003_female  2002_female  2001_female  Total population  \n",
       "0     11690825.0   11247647.0   10438055.0    9793166.0        41128771.0  \n",
       "1      1523393.0    1531532.0    1538490.0    1543533.0         2775633.0  \n",
       "2     15932047.0   15709725.0   15497822.0   15288132.0        44903224.0  \n",
       "3        28392.0      28521.0      28608.0      28649.0           44272.0  \n",
       "4        36852.0      35478.0      34076.0      32669.0           79824.0  \n",
       "..           ...          ...          ...          ...               ...  \n",
       "212      56593.0      56652.0      56692.0      56744.0          105412.0  \n",
       "213    1615402.0    1572199.0    1530053.0    1489250.0         5043613.0  \n",
       "214   10262472.0    9997157.0    9739899.0    9488026.0        33696614.0  \n",
       "215    5764425.0    5593084.0    5431354.0    5276383.0        20017675.0  \n",
       "216    6405855.0    6353380.0    6300516.0    6257972.0        16320536.0  \n",
       "\n",
       "[217 rows x 48 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Series Code_male</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>2022_male</th>\n",
       "      <th>2021_male</th>\n",
       "      <th>2020_male</th>\n",
       "      <th>2019_male</th>\n",
       "      <th>2018_male</th>\n",
       "      <th>2017_male</th>\n",
       "      <th>2016_male</th>\n",
       "      <th>2015_male</th>\n",
       "      <th>...</th>\n",
       "      <th>2009_female</th>\n",
       "      <th>2008_female</th>\n",
       "      <th>2007_female</th>\n",
       "      <th>2006_female</th>\n",
       "      <th>2005_female</th>\n",
       "      <th>2004_female</th>\n",
       "      <th>2003_female</th>\n",
       "      <th>2002_female</th>\n",
       "      <th>2001_female</th>\n",
       "      <th>Total population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>India</td>\n",
       "      <td>731180498.0</td>\n",
       "      <td>726503429.0</td>\n",
       "      <td>720997448.0</td>\n",
       "      <td>714325057.0</td>\n",
       "      <td>707149230.0</td>\n",
       "      <td>699587889.0</td>\n",
       "      <td>691623419.0</td>\n",
       "      <td>683543213.0</td>\n",
       "      <td>...</td>\n",
       "      <td>590747758.0</td>\n",
       "      <td>582492785.0</td>\n",
       "      <td>574185530.0</td>\n",
       "      <td>565762395.0</td>\n",
       "      <td>557161047.0</td>\n",
       "      <td>548274218.0</td>\n",
       "      <td>539178882.0</td>\n",
       "      <td>529978166.0</td>\n",
       "      <td>520679574.0</td>\n",
       "      <td>1.417173e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>China</td>\n",
       "      <td>720646499.0</td>\n",
       "      <td>721140373.0</td>\n",
       "      <td>720928153.0</td>\n",
       "      <td>719565010.0</td>\n",
       "      <td>717291023.0</td>\n",
       "      <td>714208198.0</td>\n",
       "      <td>710100087.0</td>\n",
       "      <td>706169297.0</td>\n",
       "      <td>...</td>\n",
       "      <td>649891191.0</td>\n",
       "      <td>646729218.0</td>\n",
       "      <td>643486317.0</td>\n",
       "      <td>640203444.0</td>\n",
       "      <td>636711861.0</td>\n",
       "      <td>633047012.0</td>\n",
       "      <td>629369651.0</td>\n",
       "      <td>625534993.0</td>\n",
       "      <td>621436557.0</td>\n",
       "      <td>1.412175e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>United States</td>\n",
       "      <td>165021339.0</td>\n",
       "      <td>164481553.0</td>\n",
       "      <td>164308503.0</td>\n",
       "      <td>162730147.0</td>\n",
       "      <td>161911851.0</td>\n",
       "      <td>160970309.0</td>\n",
       "      <td>159847727.0</td>\n",
       "      <td>158580581.0</td>\n",
       "      <td>...</td>\n",
       "      <td>155660194.0</td>\n",
       "      <td>154289840.0</td>\n",
       "      <td>152829130.0</td>\n",
       "      <td>151383683.0</td>\n",
       "      <td>149946323.0</td>\n",
       "      <td>148594732.0</td>\n",
       "      <td>147242226.0</td>\n",
       "      <td>145972802.0</td>\n",
       "      <td>144625822.0</td>\n",
       "      <td>3.332876e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>138703277.0</td>\n",
       "      <td>137852478.0</td>\n",
       "      <td>136927582.0</td>\n",
       "      <td>135798442.0</td>\n",
       "      <td>134536680.0</td>\n",
       "      <td>133245399.0</td>\n",
       "      <td>131909809.0</td>\n",
       "      <td>130517327.0</td>\n",
       "      <td>...</td>\n",
       "      <td>119636496.0</td>\n",
       "      <td>118134983.0</td>\n",
       "      <td>116621886.0</td>\n",
       "      <td>115112096.0</td>\n",
       "      <td>113637675.0</td>\n",
       "      <td>112236510.0</td>\n",
       "      <td>110834579.0</td>\n",
       "      <td>109376745.0</td>\n",
       "      <td>107901551.0</td>\n",
       "      <td>2.755013e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>118960880.0</td>\n",
       "      <td>116815852.0</td>\n",
       "      <td>114815641.0</td>\n",
       "      <td>113015042.0</td>\n",
       "      <td>111438323.0</td>\n",
       "      <td>110003086.0</td>\n",
       "      <td>108894512.0</td>\n",
       "      <td>107983708.0</td>\n",
       "      <td>...</td>\n",
       "      <td>92290019.0</td>\n",
       "      <td>90186327.0</td>\n",
       "      <td>88180519.0</td>\n",
       "      <td>86259841.0</td>\n",
       "      <td>84430090.0</td>\n",
       "      <td>82599094.0</td>\n",
       "      <td>80749416.0</td>\n",
       "      <td>78984415.0</td>\n",
       "      <td>77005059.0</td>\n",
       "      <td>2.358249e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Series Code_male   Country Name    2022_male    2021_male    2020_male  \\\n",
       "89   SP.POP.TOTL.MA.IN          India  731180498.0  726503429.0  720997448.0   \n",
       "41   SP.POP.TOTL.MA.IN          China  720646499.0  721140373.0  720928153.0   \n",
       "206  SP.POP.TOTL.MA.IN  United States  165021339.0  164481553.0  164308503.0   \n",
       "90   SP.POP.TOTL.MA.IN      Indonesia  138703277.0  137852478.0  136927582.0   \n",
       "149  SP.POP.TOTL.MA.IN       Pakistan  118960880.0  116815852.0  114815641.0   \n",
       "\n",
       "       2019_male    2018_male    2017_male    2016_male    2015_male  ...  \\\n",
       "89   714325057.0  707149230.0  699587889.0  691623419.0  683543213.0  ...   \n",
       "41   719565010.0  717291023.0  714208198.0  710100087.0  706169297.0  ...   \n",
       "206  162730147.0  161911851.0  160970309.0  159847727.0  158580581.0  ...   \n",
       "90   135798442.0  134536680.0  133245399.0  131909809.0  130517327.0  ...   \n",
       "149  113015042.0  111438323.0  110003086.0  108894512.0  107983708.0  ...   \n",
       "\n",
       "     2009_female  2008_female  2007_female  2006_female  2005_female  \\\n",
       "89   590747758.0  582492785.0  574185530.0  565762395.0  557161047.0   \n",
       "41   649891191.0  646729218.0  643486317.0  640203444.0  636711861.0   \n",
       "206  155660194.0  154289840.0  152829130.0  151383683.0  149946323.0   \n",
       "90   119636496.0  118134983.0  116621886.0  115112096.0  113637675.0   \n",
       "149   92290019.0   90186327.0   88180519.0   86259841.0   84430090.0   \n",
       "\n",
       "     2004_female  2003_female  2002_female  2001_female  Total population  \n",
       "89   548274218.0  539178882.0  529978166.0  520679574.0      1.417173e+09  \n",
       "41   633047012.0  629369651.0  625534993.0  621436557.0      1.412175e+09  \n",
       "206  148594732.0  147242226.0  145972802.0  144625822.0      3.332876e+08  \n",
       "90   112236510.0  110834579.0  109376745.0  107901551.0      2.755013e+08  \n",
       "149   82599094.0   80749416.0   78984415.0   77005059.0      2.358249e+08  \n",
       "\n",
       "[5 rows x 48 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_population_sorted = merge_data.sort_values(by=\"Total population\", ascending=False)\n",
    "total_population_sorted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Series Code_male</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>2022_male</th>\n",
       "      <th>2021_male</th>\n",
       "      <th>2020_male</th>\n",
       "      <th>2019_male</th>\n",
       "      <th>2018_male</th>\n",
       "      <th>2017_male</th>\n",
       "      <th>2016_male</th>\n",
       "      <th>2015_male</th>\n",
       "      <th>...</th>\n",
       "      <th>2009_female</th>\n",
       "      <th>2008_female</th>\n",
       "      <th>2007_female</th>\n",
       "      <th>2006_female</th>\n",
       "      <th>2005_female</th>\n",
       "      <th>2004_female</th>\n",
       "      <th>2003_female</th>\n",
       "      <th>2002_female</th>\n",
       "      <th>2001_female</th>\n",
       "      <th>Total population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>India</td>\n",
       "      <td>731180498.0</td>\n",
       "      <td>726503429.0</td>\n",
       "      <td>720997448.0</td>\n",
       "      <td>714325057.0</td>\n",
       "      <td>707149230.0</td>\n",
       "      <td>699587889.0</td>\n",
       "      <td>691623419.0</td>\n",
       "      <td>683543213.0</td>\n",
       "      <td>...</td>\n",
       "      <td>590747758.0</td>\n",
       "      <td>582492785.0</td>\n",
       "      <td>574185530.0</td>\n",
       "      <td>565762395.0</td>\n",
       "      <td>557161047.0</td>\n",
       "      <td>548274218.0</td>\n",
       "      <td>539178882.0</td>\n",
       "      <td>529978166.0</td>\n",
       "      <td>520679574.0</td>\n",
       "      <td>1.417173e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>China</td>\n",
       "      <td>720646499.0</td>\n",
       "      <td>721140373.0</td>\n",
       "      <td>720928153.0</td>\n",
       "      <td>719565010.0</td>\n",
       "      <td>717291023.0</td>\n",
       "      <td>714208198.0</td>\n",
       "      <td>710100087.0</td>\n",
       "      <td>706169297.0</td>\n",
       "      <td>...</td>\n",
       "      <td>649891191.0</td>\n",
       "      <td>646729218.0</td>\n",
       "      <td>643486317.0</td>\n",
       "      <td>640203444.0</td>\n",
       "      <td>636711861.0</td>\n",
       "      <td>633047012.0</td>\n",
       "      <td>629369651.0</td>\n",
       "      <td>625534993.0</td>\n",
       "      <td>621436557.0</td>\n",
       "      <td>1.412175e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>United States</td>\n",
       "      <td>165021339.0</td>\n",
       "      <td>164481553.0</td>\n",
       "      <td>164308503.0</td>\n",
       "      <td>162730147.0</td>\n",
       "      <td>161911851.0</td>\n",
       "      <td>160970309.0</td>\n",
       "      <td>159847727.0</td>\n",
       "      <td>158580581.0</td>\n",
       "      <td>...</td>\n",
       "      <td>155660194.0</td>\n",
       "      <td>154289840.0</td>\n",
       "      <td>152829130.0</td>\n",
       "      <td>151383683.0</td>\n",
       "      <td>149946323.0</td>\n",
       "      <td>148594732.0</td>\n",
       "      <td>147242226.0</td>\n",
       "      <td>145972802.0</td>\n",
       "      <td>144625822.0</td>\n",
       "      <td>3.332876e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>138703277.0</td>\n",
       "      <td>137852478.0</td>\n",
       "      <td>136927582.0</td>\n",
       "      <td>135798442.0</td>\n",
       "      <td>134536680.0</td>\n",
       "      <td>133245399.0</td>\n",
       "      <td>131909809.0</td>\n",
       "      <td>130517327.0</td>\n",
       "      <td>...</td>\n",
       "      <td>119636496.0</td>\n",
       "      <td>118134983.0</td>\n",
       "      <td>116621886.0</td>\n",
       "      <td>115112096.0</td>\n",
       "      <td>113637675.0</td>\n",
       "      <td>112236510.0</td>\n",
       "      <td>110834579.0</td>\n",
       "      <td>109376745.0</td>\n",
       "      <td>107901551.0</td>\n",
       "      <td>2.755013e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>118960880.0</td>\n",
       "      <td>116815852.0</td>\n",
       "      <td>114815641.0</td>\n",
       "      <td>113015042.0</td>\n",
       "      <td>111438323.0</td>\n",
       "      <td>110003086.0</td>\n",
       "      <td>108894512.0</td>\n",
       "      <td>107983708.0</td>\n",
       "      <td>...</td>\n",
       "      <td>92290019.0</td>\n",
       "      <td>90186327.0</td>\n",
       "      <td>88180519.0</td>\n",
       "      <td>86259841.0</td>\n",
       "      <td>84430090.0</td>\n",
       "      <td>82599094.0</td>\n",
       "      <td>80749416.0</td>\n",
       "      <td>78984415.0</td>\n",
       "      <td>77005059.0</td>\n",
       "      <td>2.358249e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>110448136.0</td>\n",
       "      <td>107827012.0</td>\n",
       "      <td>105243174.0</td>\n",
       "      <td>102680839.0</td>\n",
       "      <td>100165119.0</td>\n",
       "      <td>97662955.0</td>\n",
       "      <td>95191980.0</td>\n",
       "      <td>92803434.0</td>\n",
       "      <td>...</td>\n",
       "      <td>77749737.0</td>\n",
       "      <td>75683500.0</td>\n",
       "      <td>73673124.0</td>\n",
       "      <td>71718561.0</td>\n",
       "      <td>69820038.0</td>\n",
       "      <td>67971753.0</td>\n",
       "      <td>66172940.0</td>\n",
       "      <td>64424240.0</td>\n",
       "      <td>62731941.0</td>\n",
       "      <td>2.185412e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>105733027.0</td>\n",
       "      <td>105291292.0</td>\n",
       "      <td>104779288.0</td>\n",
       "      <td>104119798.0</td>\n",
       "      <td>103354449.0</td>\n",
       "      <td>102567011.0</td>\n",
       "      <td>101794390.0</td>\n",
       "      <td>101008689.0</td>\n",
       "      <td>...</td>\n",
       "      <td>98581682.0</td>\n",
       "      <td>97612571.0</td>\n",
       "      <td>96616434.0</td>\n",
       "      <td>95583318.0</td>\n",
       "      <td>94515633.0</td>\n",
       "      <td>93418462.0</td>\n",
       "      <td>92310671.0</td>\n",
       "      <td>91173105.0</td>\n",
       "      <td>89978663.0</td>\n",
       "      <td>2.153135e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>84859213.0</td>\n",
       "      <td>83998088.0</td>\n",
       "      <td>83063714.0</td>\n",
       "      <td>82164179.0</td>\n",
       "      <td>81314565.0</td>\n",
       "      <td>80422431.0</td>\n",
       "      <td>79459393.0</td>\n",
       "      <td>78535803.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73217854.0</td>\n",
       "      <td>72384496.0</td>\n",
       "      <td>71536401.0</td>\n",
       "      <td>70599279.0</td>\n",
       "      <td>69574712.0</td>\n",
       "      <td>68397392.0</td>\n",
       "      <td>67154861.0</td>\n",
       "      <td>65885157.0</td>\n",
       "      <td>64587346.0</td>\n",
       "      <td>1.711864e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>66670833.0</td>\n",
       "      <td>66624709.0</td>\n",
       "      <td>66925854.0</td>\n",
       "      <td>67076532.0</td>\n",
       "      <td>67084512.0</td>\n",
       "      <td>67064796.0</td>\n",
       "      <td>66964302.0</td>\n",
       "      <td>66823446.0</td>\n",
       "      <td>...</td>\n",
       "      <td>76775747.0</td>\n",
       "      <td>76745227.0</td>\n",
       "      <td>76754261.0</td>\n",
       "      <td>76829928.0</td>\n",
       "      <td>76976788.0</td>\n",
       "      <td>77146216.0</td>\n",
       "      <td>77339545.0</td>\n",
       "      <td>77591468.0</td>\n",
       "      <td>77868557.0</td>\n",
       "      <td>1.435557e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>62194954.0</td>\n",
       "      <td>61856137.0</td>\n",
       "      <td>61587451.0</td>\n",
       "      <td>61187228.0</td>\n",
       "      <td>60685164.0</td>\n",
       "      <td>60126616.0</td>\n",
       "      <td>59489629.0</td>\n",
       "      <td>58824776.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56685733.0</td>\n",
       "      <td>55985191.0</td>\n",
       "      <td>55278659.0</td>\n",
       "      <td>54557092.0</td>\n",
       "      <td>53823103.0</td>\n",
       "      <td>53064573.0</td>\n",
       "      <td>52296746.0</td>\n",
       "      <td>51530724.0</td>\n",
       "      <td>50758748.0</td>\n",
       "      <td>1.275041e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>60810077.0</td>\n",
       "      <td>61087180.0</td>\n",
       "      <td>61375600.0</td>\n",
       "      <td>61567714.0</td>\n",
       "      <td>61670382.0</td>\n",
       "      <td>61765051.0</td>\n",
       "      <td>61830297.0</td>\n",
       "      <td>61873910.0</td>\n",
       "      <td>...</td>\n",
       "      <td>65637199.0</td>\n",
       "      <td>65618491.0</td>\n",
       "      <td>65557955.0</td>\n",
       "      <td>65451729.0</td>\n",
       "      <td>65374871.0</td>\n",
       "      <td>65330634.0</td>\n",
       "      <td>65270637.0</td>\n",
       "      <td>65093948.0</td>\n",
       "      <td>64907199.0</td>\n",
       "      <td>1.251250e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Ethiopia</td>\n",
       "      <td>61980175.0</td>\n",
       "      <td>60443404.0</td>\n",
       "      <td>58906550.0</td>\n",
       "      <td>57375433.0</td>\n",
       "      <td>55882976.0</td>\n",
       "      <td>54418849.0</td>\n",
       "      <td>52968539.0</td>\n",
       "      <td>51560461.0</td>\n",
       "      <td>...</td>\n",
       "      <td>43088296.0</td>\n",
       "      <td>41898913.0</td>\n",
       "      <td>40732253.0</td>\n",
       "      <td>39597926.0</td>\n",
       "      <td>38508936.0</td>\n",
       "      <td>37448428.0</td>\n",
       "      <td>36408151.0</td>\n",
       "      <td>35386878.0</td>\n",
       "      <td>34388876.0</td>\n",
       "      <td>1.233799e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>58679278.0</td>\n",
       "      <td>57817463.0</td>\n",
       "      <td>56947945.0</td>\n",
       "      <td>56011134.0</td>\n",
       "      <td>55072020.0</td>\n",
       "      <td>54121554.0</td>\n",
       "      <td>53151806.0</td>\n",
       "      <td>52189304.0</td>\n",
       "      <td>...</td>\n",
       "      <td>45954012.0</td>\n",
       "      <td>45083466.0</td>\n",
       "      <td>44228376.0</td>\n",
       "      <td>43410285.0</td>\n",
       "      <td>42611126.0</td>\n",
       "      <td>41805071.0</td>\n",
       "      <td>40992524.0</td>\n",
       "      <td>40184410.0</td>\n",
       "      <td>39376849.0</td>\n",
       "      <td>1.155590e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Egypt, Arab Rep.</td>\n",
       "      <td>56124592.0</td>\n",
       "      <td>55260287.0</td>\n",
       "      <td>54357401.0</td>\n",
       "      <td>53429404.0</td>\n",
       "      <td>52490759.0</td>\n",
       "      <td>51515521.0</td>\n",
       "      <td>50509730.0</td>\n",
       "      <td>49472593.0</td>\n",
       "      <td>...</td>\n",
       "      <td>42205138.0</td>\n",
       "      <td>41378685.0</td>\n",
       "      <td>40568130.0</td>\n",
       "      <td>39776795.0</td>\n",
       "      <td>39003462.0</td>\n",
       "      <td>38236048.0</td>\n",
       "      <td>37471228.0</td>\n",
       "      <td>36706908.0</td>\n",
       "      <td>35958115.0</td>\n",
       "      <td>1.109901e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Congo, Dem. Rep.</td>\n",
       "      <td>49118035.0</td>\n",
       "      <td>47574851.0</td>\n",
       "      <td>46065978.0</td>\n",
       "      <td>44600412.0</td>\n",
       "      <td>43197045.0</td>\n",
       "      <td>41799533.0</td>\n",
       "      <td>40378425.0</td>\n",
       "      <td>38997298.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32441587.0</td>\n",
       "      <td>31428249.0</td>\n",
       "      <td>30446631.0</td>\n",
       "      <td>29491075.0</td>\n",
       "      <td>28573264.0</td>\n",
       "      <td>27703894.0</td>\n",
       "      <td>26895414.0</td>\n",
       "      <td>26117751.0</td>\n",
       "      <td>25333610.0</td>\n",
       "      <td>9.901021e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Series Code_male        Country Name    2022_male    2021_male  \\\n",
       "89   SP.POP.TOTL.MA.IN               India  731180498.0  726503429.0   \n",
       "41   SP.POP.TOTL.MA.IN               China  720646499.0  721140373.0   \n",
       "206  SP.POP.TOTL.MA.IN       United States  165021339.0  164481553.0   \n",
       "90   SP.POP.TOTL.MA.IN           Indonesia  138703277.0  137852478.0   \n",
       "149  SP.POP.TOTL.MA.IN            Pakistan  118960880.0  116815852.0   \n",
       "144  SP.POP.TOTL.MA.IN             Nigeria  110448136.0  107827012.0   \n",
       "26   SP.POP.TOTL.MA.IN              Brazil  105733027.0  105291292.0   \n",
       "15   SP.POP.TOTL.MA.IN          Bangladesh   84859213.0   83998088.0   \n",
       "161  SP.POP.TOTL.MA.IN  Russian Federation   66670833.0   66624709.0   \n",
       "127  SP.POP.TOTL.MA.IN              Mexico   62194954.0   61856137.0   \n",
       "98   SP.POP.TOTL.MA.IN               Japan   60810077.0   61087180.0   \n",
       "64   SP.POP.TOTL.MA.IN            Ethiopia   61980175.0   60443404.0   \n",
       "155  SP.POP.TOTL.MA.IN         Philippines   58679278.0   57817463.0   \n",
       "58   SP.POP.TOTL.MA.IN    Egypt, Arab Rep.   56124592.0   55260287.0   \n",
       "44   SP.POP.TOTL.MA.IN    Congo, Dem. Rep.   49118035.0   47574851.0   \n",
       "\n",
       "       2020_male    2019_male    2018_male    2017_male    2016_male  \\\n",
       "89   720997448.0  714325057.0  707149230.0  699587889.0  691623419.0   \n",
       "41   720928153.0  719565010.0  717291023.0  714208198.0  710100087.0   \n",
       "206  164308503.0  162730147.0  161911851.0  160970309.0  159847727.0   \n",
       "90   136927582.0  135798442.0  134536680.0  133245399.0  131909809.0   \n",
       "149  114815641.0  113015042.0  111438323.0  110003086.0  108894512.0   \n",
       "144  105243174.0  102680839.0  100165119.0   97662955.0   95191980.0   \n",
       "26   104779288.0  104119798.0  103354449.0  102567011.0  101794390.0   \n",
       "15    83063714.0   82164179.0   81314565.0   80422431.0   79459393.0   \n",
       "161   66925854.0   67076532.0   67084512.0   67064796.0   66964302.0   \n",
       "127   61587451.0   61187228.0   60685164.0   60126616.0   59489629.0   \n",
       "98    61375600.0   61567714.0   61670382.0   61765051.0   61830297.0   \n",
       "64    58906550.0   57375433.0   55882976.0   54418849.0   52968539.0   \n",
       "155   56947945.0   56011134.0   55072020.0   54121554.0   53151806.0   \n",
       "58    54357401.0   53429404.0   52490759.0   51515521.0   50509730.0   \n",
       "44    46065978.0   44600412.0   43197045.0   41799533.0   40378425.0   \n",
       "\n",
       "       2015_male  ...  2009_female  2008_female  2007_female  2006_female  \\\n",
       "89   683543213.0  ...  590747758.0  582492785.0  574185530.0  565762395.0   \n",
       "41   706169297.0  ...  649891191.0  646729218.0  643486317.0  640203444.0   \n",
       "206  158580581.0  ...  155660194.0  154289840.0  152829130.0  151383683.0   \n",
       "90   130517327.0  ...  119636496.0  118134983.0  116621886.0  115112096.0   \n",
       "149  107983708.0  ...   92290019.0   90186327.0   88180519.0   86259841.0   \n",
       "144   92803434.0  ...   77749737.0   75683500.0   73673124.0   71718561.0   \n",
       "26   101008689.0  ...   98581682.0   97612571.0   96616434.0   95583318.0   \n",
       "15    78535803.0  ...   73217854.0   72384496.0   71536401.0   70599279.0   \n",
       "161   66823446.0  ...   76775747.0   76745227.0   76754261.0   76829928.0   \n",
       "127   58824776.0  ...   56685733.0   55985191.0   55278659.0   54557092.0   \n",
       "98    61873910.0  ...   65637199.0   65618491.0   65557955.0   65451729.0   \n",
       "64    51560461.0  ...   43088296.0   41898913.0   40732253.0   39597926.0   \n",
       "155   52189304.0  ...   45954012.0   45083466.0   44228376.0   43410285.0   \n",
       "58    49472593.0  ...   42205138.0   41378685.0   40568130.0   39776795.0   \n",
       "44    38997298.0  ...   32441587.0   31428249.0   30446631.0   29491075.0   \n",
       "\n",
       "     2005_female  2004_female  2003_female  2002_female  2001_female  \\\n",
       "89   557161047.0  548274218.0  539178882.0  529978166.0  520679574.0   \n",
       "41   636711861.0  633047012.0  629369651.0  625534993.0  621436557.0   \n",
       "206  149946323.0  148594732.0  147242226.0  145972802.0  144625822.0   \n",
       "90   113637675.0  112236510.0  110834579.0  109376745.0  107901551.0   \n",
       "149   84430090.0   82599094.0   80749416.0   78984415.0   77005059.0   \n",
       "144   69820038.0   67971753.0   66172940.0   64424240.0   62731941.0   \n",
       "26    94515633.0   93418462.0   92310671.0   91173105.0   89978663.0   \n",
       "15    69574712.0   68397392.0   67154861.0   65885157.0   64587346.0   \n",
       "161   76976788.0   77146216.0   77339545.0   77591468.0   77868557.0   \n",
       "127   53823103.0   53064573.0   52296746.0   51530724.0   50758748.0   \n",
       "98    65374871.0   65330634.0   65270637.0   65093948.0   64907199.0   \n",
       "64    38508936.0   37448428.0   36408151.0   35386878.0   34388876.0   \n",
       "155   42611126.0   41805071.0   40992524.0   40184410.0   39376849.0   \n",
       "58    39003462.0   38236048.0   37471228.0   36706908.0   35958115.0   \n",
       "44    28573264.0   27703894.0   26895414.0   26117751.0   25333610.0   \n",
       "\n",
       "     Total population  \n",
       "89       1.417173e+09  \n",
       "41       1.412175e+09  \n",
       "206      3.332876e+08  \n",
       "90       2.755013e+08  \n",
       "149      2.358249e+08  \n",
       "144      2.185412e+08  \n",
       "26       2.153135e+08  \n",
       "15       1.711864e+08  \n",
       "161      1.435557e+08  \n",
       "127      1.275041e+08  \n",
       "98       1.251250e+08  \n",
       "64       1.233799e+08  \n",
       "155      1.155590e+08  \n",
       "58       1.109901e+08  \n",
       "44       9.901021e+07  \n",
       "\n",
       "[15 rows x 48 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_15_countries_totpop = total_population_sorted.head(15)\n",
    "top_15_countries_totpop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Series Code_male</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>2022_male</th>\n",
       "      <th>2021_male</th>\n",
       "      <th>2020_male</th>\n",
       "      <th>2019_male</th>\n",
       "      <th>2018_male</th>\n",
       "      <th>2017_male</th>\n",
       "      <th>2016_male</th>\n",
       "      <th>2015_male</th>\n",
       "      <th>...</th>\n",
       "      <th>2009_female</th>\n",
       "      <th>2008_female</th>\n",
       "      <th>2007_female</th>\n",
       "      <th>2006_female</th>\n",
       "      <th>2005_female</th>\n",
       "      <th>2004_female</th>\n",
       "      <th>2003_female</th>\n",
       "      <th>2002_female</th>\n",
       "      <th>2001_female</th>\n",
       "      <th>Total population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Northern Mariana Islands</td>\n",
       "      <td>26635.0</td>\n",
       "      <td>26597.0</td>\n",
       "      <td>26631.0</td>\n",
       "      <td>26731.0</td>\n",
       "      <td>26903.0</td>\n",
       "      <td>27059.0</td>\n",
       "      <td>27200.0</td>\n",
       "      <td>27325.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27779.0</td>\n",
       "      <td>29582.0</td>\n",
       "      <td>31397.0</td>\n",
       "      <td>33200.0</td>\n",
       "      <td>34982.0</td>\n",
       "      <td>36719.0</td>\n",
       "      <td>38389.0</td>\n",
       "      <td>39980.0</td>\n",
       "      <td>41471.0</td>\n",
       "      <td>49551.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>St. Kitts and Nevis</td>\n",
       "      <td>23011.0</td>\n",
       "      <td>23015.0</td>\n",
       "      <td>23072.0</td>\n",
       "      <td>23149.0</td>\n",
       "      <td>23216.0</td>\n",
       "      <td>23270.0</td>\n",
       "      <td>23316.0</td>\n",
       "      <td>23360.0</td>\n",
       "      <td>...</td>\n",
       "      <td>24005.0</td>\n",
       "      <td>23904.0</td>\n",
       "      <td>23800.0</td>\n",
       "      <td>23695.0</td>\n",
       "      <td>23587.0</td>\n",
       "      <td>23485.0</td>\n",
       "      <td>23381.0</td>\n",
       "      <td>23274.0</td>\n",
       "      <td>23130.0</td>\n",
       "      <td>47657.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Turks and Caicos Islands</td>\n",
       "      <td>23006.0</td>\n",
       "      <td>22729.0</td>\n",
       "      <td>22325.0</td>\n",
       "      <td>21739.0</td>\n",
       "      <td>20953.0</td>\n",
       "      <td>20137.0</td>\n",
       "      <td>19341.0</td>\n",
       "      <td>18491.0</td>\n",
       "      <td>...</td>\n",
       "      <td>14046.0</td>\n",
       "      <td>13463.0</td>\n",
       "      <td>12886.0</td>\n",
       "      <td>12316.0</td>\n",
       "      <td>11746.0</td>\n",
       "      <td>11177.0</td>\n",
       "      <td>10611.0</td>\n",
       "      <td>10039.0</td>\n",
       "      <td>9537.0</td>\n",
       "      <td>45703.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>21873.0</td>\n",
       "      <td>22289.0</td>\n",
       "      <td>22921.0</td>\n",
       "      <td>23535.0</td>\n",
       "      <td>24134.0</td>\n",
       "      <td>24701.0</td>\n",
       "      <td>25240.0</td>\n",
       "      <td>25739.0</td>\n",
       "      <td>...</td>\n",
       "      <td>27406.0</td>\n",
       "      <td>27626.0</td>\n",
       "      <td>27842.0</td>\n",
       "      <td>28044.0</td>\n",
       "      <td>28230.0</td>\n",
       "      <td>28392.0</td>\n",
       "      <td>28521.0</td>\n",
       "      <td>28608.0</td>\n",
       "      <td>28649.0</td>\n",
       "      <td>44272.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Sint Maarten (Dutch part)</td>\n",
       "      <td>23228.0</td>\n",
       "      <td>22932.0</td>\n",
       "      <td>22579.0</td>\n",
       "      <td>22120.0</td>\n",
       "      <td>21648.0</td>\n",
       "      <td>21459.0</td>\n",
       "      <td>21132.0</td>\n",
       "      <td>20431.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17964.0</td>\n",
       "      <td>17758.0</td>\n",
       "      <td>17620.0</td>\n",
       "      <td>17373.0</td>\n",
       "      <td>17097.0</td>\n",
       "      <td>16777.0</td>\n",
       "      <td>16209.0</td>\n",
       "      <td>15814.0</td>\n",
       "      <td>15692.0</td>\n",
       "      <td>43389.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Marshall Islands</td>\n",
       "      <td>21223.0</td>\n",
       "      <td>21483.0</td>\n",
       "      <td>22190.0</td>\n",
       "      <td>22874.0</td>\n",
       "      <td>23529.0</td>\n",
       "      <td>24146.0</td>\n",
       "      <td>24738.0</td>\n",
       "      <td>25299.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26162.0</td>\n",
       "      <td>26261.0</td>\n",
       "      <td>26360.0</td>\n",
       "      <td>26439.0</td>\n",
       "      <td>26494.0</td>\n",
       "      <td>26534.0</td>\n",
       "      <td>26555.0</td>\n",
       "      <td>26552.0</td>\n",
       "      <td>26508.0</td>\n",
       "      <td>41569.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Liechtenstein</td>\n",
       "      <td>19502.0</td>\n",
       "      <td>19354.0</td>\n",
       "      <td>19223.0</td>\n",
       "      <td>19102.0</td>\n",
       "      <td>18961.0</td>\n",
       "      <td>18816.0</td>\n",
       "      <td>18663.0</td>\n",
       "      <td>18521.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18047.0</td>\n",
       "      <td>17927.0</td>\n",
       "      <td>17814.0</td>\n",
       "      <td>17693.0</td>\n",
       "      <td>17552.0</td>\n",
       "      <td>17399.0</td>\n",
       "      <td>17257.0</td>\n",
       "      <td>17110.0</td>\n",
       "      <td>16951.0</td>\n",
       "      <td>39327.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Monaco</td>\n",
       "      <td>17872.0</td>\n",
       "      <td>17982.0</td>\n",
       "      <td>18095.0</td>\n",
       "      <td>18145.0</td>\n",
       "      <td>18142.0</td>\n",
       "      <td>18159.0</td>\n",
       "      <td>18187.0</td>\n",
       "      <td>18043.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16589.0</td>\n",
       "      <td>16320.0</td>\n",
       "      <td>16305.0</td>\n",
       "      <td>16407.0</td>\n",
       "      <td>16479.0</td>\n",
       "      <td>16532.0</td>\n",
       "      <td>16576.0</td>\n",
       "      <td>16617.0</td>\n",
       "      <td>16652.0</td>\n",
       "      <td>36468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>San Marino</td>\n",
       "      <td>16380.0</td>\n",
       "      <td>16419.0</td>\n",
       "      <td>16563.0</td>\n",
       "      <td>16650.0</td>\n",
       "      <td>16626.0</td>\n",
       "      <td>16564.0</td>\n",
       "      <td>16453.0</td>\n",
       "      <td>16328.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15838.0</td>\n",
       "      <td>15648.0</td>\n",
       "      <td>15473.0</td>\n",
       "      <td>15264.0</td>\n",
       "      <td>15049.0</td>\n",
       "      <td>14847.0</td>\n",
       "      <td>14603.0</td>\n",
       "      <td>14283.0</td>\n",
       "      <td>13957.0</td>\n",
       "      <td>33661.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Gibraltar</td>\n",
       "      <td>16308.0</td>\n",
       "      <td>16317.0</td>\n",
       "      <td>16337.0</td>\n",
       "      <td>16320.0</td>\n",
       "      <td>16297.0</td>\n",
       "      <td>16268.0</td>\n",
       "      <td>16244.0</td>\n",
       "      <td>16223.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15445.0</td>\n",
       "      <td>15241.0</td>\n",
       "      <td>15043.0</td>\n",
       "      <td>14838.0</td>\n",
       "      <td>14628.0</td>\n",
       "      <td>14416.0</td>\n",
       "      <td>14220.0</td>\n",
       "      <td>14030.0</td>\n",
       "      <td>13931.0</td>\n",
       "      <td>32649.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>St. Martin (French part)</td>\n",
       "      <td>15111.0</td>\n",
       "      <td>15188.0</td>\n",
       "      <td>15477.0</td>\n",
       "      <td>15749.0</td>\n",
       "      <td>16100.0</td>\n",
       "      <td>16412.0</td>\n",
       "      <td>16563.0</td>\n",
       "      <td>16659.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18985.0</td>\n",
       "      <td>18631.0</td>\n",
       "      <td>18241.0</td>\n",
       "      <td>17825.0</td>\n",
       "      <td>17390.0</td>\n",
       "      <td>16948.0</td>\n",
       "      <td>16503.0</td>\n",
       "      <td>16057.0</td>\n",
       "      <td>15610.0</td>\n",
       "      <td>31791.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>British Virgin Islands</td>\n",
       "      <td>15062.0</td>\n",
       "      <td>14976.0</td>\n",
       "      <td>14900.0</td>\n",
       "      <td>14786.0</td>\n",
       "      <td>14681.0</td>\n",
       "      <td>14578.0</td>\n",
       "      <td>14453.0</td>\n",
       "      <td>14303.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13714.0</td>\n",
       "      <td>13197.0</td>\n",
       "      <td>12679.0</td>\n",
       "      <td>12190.0</td>\n",
       "      <td>11724.0</td>\n",
       "      <td>11277.0</td>\n",
       "      <td>10849.0</td>\n",
       "      <td>10437.0</td>\n",
       "      <td>10069.0</td>\n",
       "      <td>31304.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Palau</td>\n",
       "      <td>9376.0</td>\n",
       "      <td>9380.0</td>\n",
       "      <td>9377.0</td>\n",
       "      <td>9379.0</td>\n",
       "      <td>9389.0</td>\n",
       "      <td>9409.0</td>\n",
       "      <td>9431.0</td>\n",
       "      <td>9454.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8813.0</td>\n",
       "      <td>8912.0</td>\n",
       "      <td>9008.0</td>\n",
       "      <td>9095.0</td>\n",
       "      <td>9165.0</td>\n",
       "      <td>9164.0</td>\n",
       "      <td>9113.0</td>\n",
       "      <td>9066.0</td>\n",
       "      <td>9024.0</td>\n",
       "      <td>18055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Nauru</td>\n",
       "      <td>6435.0</td>\n",
       "      <td>6361.0</td>\n",
       "      <td>6266.0</td>\n",
       "      <td>6177.0</td>\n",
       "      <td>6074.0</td>\n",
       "      <td>5953.0</td>\n",
       "      <td>5832.0</td>\n",
       "      <td>5706.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5016.0</td>\n",
       "      <td>5016.0</td>\n",
       "      <td>5019.0</td>\n",
       "      <td>5022.0</td>\n",
       "      <td>5020.0</td>\n",
       "      <td>5019.0</td>\n",
       "      <td>5016.0</td>\n",
       "      <td>5011.0</td>\n",
       "      <td>5013.0</td>\n",
       "      <td>12668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>SP.POP.TOTL.MA.IN</td>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>5799.0</td>\n",
       "      <td>5755.0</td>\n",
       "      <td>5702.0</td>\n",
       "      <td>5654.0</td>\n",
       "      <td>5613.0</td>\n",
       "      <td>5598.0</td>\n",
       "      <td>5609.0</td>\n",
       "      <td>5617.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5093.0</td>\n",
       "      <td>5045.0</td>\n",
       "      <td>5006.0</td>\n",
       "      <td>4965.0</td>\n",
       "      <td>4922.0</td>\n",
       "      <td>4878.0</td>\n",
       "      <td>4835.0</td>\n",
       "      <td>4822.0</td>\n",
       "      <td>4845.0</td>\n",
       "      <td>11312.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Series Code_male               Country Name  2022_male  2021_male  \\\n",
       "146  SP.POP.TOTL.MA.IN   Northern Mariana Islands    26635.0    26597.0   \n",
       "181  SP.POP.TOTL.MA.IN        St. Kitts and Nevis    23011.0    23015.0   \n",
       "200  SP.POP.TOTL.MA.IN   Turks and Caicos Islands    23006.0    22729.0   \n",
       "3    SP.POP.TOTL.MA.IN             American Samoa    21873.0    22289.0   \n",
       "172  SP.POP.TOTL.MA.IN  Sint Maarten (Dutch part)    23228.0    22932.0   \n",
       "124  SP.POP.TOTL.MA.IN           Marshall Islands    21223.0    21483.0   \n",
       "114  SP.POP.TOTL.MA.IN              Liechtenstein    19502.0    19354.0   \n",
       "130  SP.POP.TOTL.MA.IN                     Monaco    17872.0    17982.0   \n",
       "164  SP.POP.TOTL.MA.IN                 San Marino    16380.0    16419.0   \n",
       "75   SP.POP.TOTL.MA.IN                  Gibraltar    16308.0    16317.0   \n",
       "183  SP.POP.TOTL.MA.IN   St. Martin (French part)    15111.0    15188.0   \n",
       "27   SP.POP.TOTL.MA.IN     British Virgin Islands    15062.0    14976.0   \n",
       "150  SP.POP.TOTL.MA.IN                      Palau     9376.0     9380.0   \n",
       "137  SP.POP.TOTL.MA.IN                      Nauru     6435.0     6361.0   \n",
       "201  SP.POP.TOTL.MA.IN                     Tuvalu     5799.0     5755.0   \n",
       "\n",
       "     2020_male  2019_male  2018_male  2017_male  2016_male  2015_male  ...  \\\n",
       "146    26631.0    26731.0    26903.0    27059.0    27200.0    27325.0  ...   \n",
       "181    23072.0    23149.0    23216.0    23270.0    23316.0    23360.0  ...   \n",
       "200    22325.0    21739.0    20953.0    20137.0    19341.0    18491.0  ...   \n",
       "3      22921.0    23535.0    24134.0    24701.0    25240.0    25739.0  ...   \n",
       "172    22579.0    22120.0    21648.0    21459.0    21132.0    20431.0  ...   \n",
       "124    22190.0    22874.0    23529.0    24146.0    24738.0    25299.0  ...   \n",
       "114    19223.0    19102.0    18961.0    18816.0    18663.0    18521.0  ...   \n",
       "130    18095.0    18145.0    18142.0    18159.0    18187.0    18043.0  ...   \n",
       "164    16563.0    16650.0    16626.0    16564.0    16453.0    16328.0  ...   \n",
       "75     16337.0    16320.0    16297.0    16268.0    16244.0    16223.0  ...   \n",
       "183    15477.0    15749.0    16100.0    16412.0    16563.0    16659.0  ...   \n",
       "27     14900.0    14786.0    14681.0    14578.0    14453.0    14303.0  ...   \n",
       "150     9377.0     9379.0     9389.0     9409.0     9431.0     9454.0  ...   \n",
       "137     6266.0     6177.0     6074.0     5953.0     5832.0     5706.0  ...   \n",
       "201     5702.0     5654.0     5613.0     5598.0     5609.0     5617.0  ...   \n",
       "\n",
       "     2009_female  2008_female  2007_female  2006_female  2005_female  \\\n",
       "146      27779.0      29582.0      31397.0      33200.0      34982.0   \n",
       "181      24005.0      23904.0      23800.0      23695.0      23587.0   \n",
       "200      14046.0      13463.0      12886.0      12316.0      11746.0   \n",
       "3        27406.0      27626.0      27842.0      28044.0      28230.0   \n",
       "172      17964.0      17758.0      17620.0      17373.0      17097.0   \n",
       "124      26162.0      26261.0      26360.0      26439.0      26494.0   \n",
       "114      18047.0      17927.0      17814.0      17693.0      17552.0   \n",
       "130      16589.0      16320.0      16305.0      16407.0      16479.0   \n",
       "164      15838.0      15648.0      15473.0      15264.0      15049.0   \n",
       "75       15445.0      15241.0      15043.0      14838.0      14628.0   \n",
       "183      18985.0      18631.0      18241.0      17825.0      17390.0   \n",
       "27       13714.0      13197.0      12679.0      12190.0      11724.0   \n",
       "150       8813.0       8912.0       9008.0       9095.0       9165.0   \n",
       "137       5016.0       5016.0       5019.0       5022.0       5020.0   \n",
       "201       5093.0       5045.0       5006.0       4965.0       4922.0   \n",
       "\n",
       "     2004_female  2003_female  2002_female  2001_female  Total population  \n",
       "146      36719.0      38389.0      39980.0      41471.0           49551.0  \n",
       "181      23485.0      23381.0      23274.0      23130.0           47657.0  \n",
       "200      11177.0      10611.0      10039.0       9537.0           45703.0  \n",
       "3        28392.0      28521.0      28608.0      28649.0           44272.0  \n",
       "172      16777.0      16209.0      15814.0      15692.0           43389.0  \n",
       "124      26534.0      26555.0      26552.0      26508.0           41569.0  \n",
       "114      17399.0      17257.0      17110.0      16951.0           39327.0  \n",
       "130      16532.0      16576.0      16617.0      16652.0           36468.0  \n",
       "164      14847.0      14603.0      14283.0      13957.0           33661.0  \n",
       "75       14416.0      14220.0      14030.0      13931.0           32649.0  \n",
       "183      16948.0      16503.0      16057.0      15610.0           31791.0  \n",
       "27       11277.0      10849.0      10437.0      10069.0           31304.0  \n",
       "150       9164.0       9113.0       9066.0       9024.0           18055.0  \n",
       "137       5019.0       5016.0       5011.0       5013.0           12668.0  \n",
       "201       4878.0       4835.0       4822.0       4845.0           11312.0  \n",
       "\n",
       "[15 rows x 48 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bottom_15_countries_totpop = total_population_sorted.tail(15)\n",
    "bottom_15_countries_totpop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bar plot total population of world 2022\n",
    "\n",
    "plt.figure(figsize=(18, 8))\n",
    "sns.barplot(\n",
    "    x=\"Country Name\",\n",
    "    y=\"2022_female\",\n",
    "    data=top_15_countries_totpop,\n",
    "    bottom=top_15_countries_totpop[\"2022_male\"],\n",
    "    color=\"red\",\n",
    "    label=\"female population\",\n",
    "    width=0.75,\n",
    ")\n",
    "sns.barplot(\n",
    "    x=\"Country Name\",\n",
    "    y=\"2022_male\",\n",
    "    data=top_15_countries_totpop,\n",
    "    color=\"blue\",\n",
    "    label=\"Male population\",\n",
    "    width=0.75,\n",
    ")\n",
    "\n",
    "plt.title(\"Total population of top 15 contries (2022)\")\n",
    "plt.xlabel(\"Country Name\")\n",
    "plt.ylabel(\"Population\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# _Total populaiton of bottom 15 countries_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "sns.barplot(\n",
    "    x=\"Country Name\",\n",
    "    y=\"2022_male\",\n",
    "    data=bottom_15_countries_totpop,\n",
    "    bottom=bottom_15_countries_totpop[\"2022_female\"],\n",
    "    color=\"red\",\n",
    "    label=\"Male population\",\n",
    ")\n",
    "sns.barplot(\n",
    "    x=\"Country Name\",\n",
    "    y=\"2022_female\",\n",
    "    data=bottom_15_countries_totpop,\n",
    "    color=\"blue\",\n",
    "    label=\"Female population\",\n",
    ")\n",
    "plt.xlabel(\"Country Name\")\n",
    "plt.ylabel(\"population\")\n",
    "plt.title(\"Total population of bottom 15 countries (2022)\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}