my-first-eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "156a062f-014b-42e0-a558-e57a10d21773",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "94d04ba0-c08f-4942-9a5c-2b80fed5eb0c",
   "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>Rank</th>\n",
       "      <th>CCA3</th>\n",
       "      <th>Country</th>\n",
       "      <th>Capital</th>\n",
       "      <th>Continent</th>\n",
       "      <th>2022 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1970 Population</th>\n",
       "      <th>Area (km²)</th>\n",
       "      <th>Density (per km²)</th>\n",
       "      <th>Growth Rate</th>\n",
       "      <th>World Population Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Kabul</td>\n",
       "      <td>Asia</td>\n",
       "      <td>41128771.0</td>\n",
       "      <td>38972230.0</td>\n",
       "      <td>33753499.0</td>\n",
       "      <td>28189672.0</td>\n",
       "      <td>19542982.0</td>\n",
       "      <td>10694796.0</td>\n",
       "      <td>12486631.0</td>\n",
       "      <td>10752971.0</td>\n",
       "      <td>652230.0</td>\n",
       "      <td>63.0587</td>\n",
       "      <td>1.0257</td>\n",
       "      <td>0.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>138</td>\n",
       "      <td>ALB</td>\n",
       "      <td>Albania</td>\n",
       "      <td>Tirana</td>\n",
       "      <td>Europe</td>\n",
       "      <td>2842321.0</td>\n",
       "      <td>2866849.0</td>\n",
       "      <td>2882481.0</td>\n",
       "      <td>2913399.0</td>\n",
       "      <td>3182021.0</td>\n",
       "      <td>3295066.0</td>\n",
       "      <td>2941651.0</td>\n",
       "      <td>2324731.0</td>\n",
       "      <td>28748.0</td>\n",
       "      <td>98.8702</td>\n",
       "      <td>0.9957</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34</td>\n",
       "      <td>DZA</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>Algiers</td>\n",
       "      <td>Africa</td>\n",
       "      <td>44903225.0</td>\n",
       "      <td>43451666.0</td>\n",
       "      <td>39543154.0</td>\n",
       "      <td>35856344.0</td>\n",
       "      <td>30774621.0</td>\n",
       "      <td>25518074.0</td>\n",
       "      <td>18739378.0</td>\n",
       "      <td>13795915.0</td>\n",
       "      <td>2381741.0</td>\n",
       "      <td>18.8531</td>\n",
       "      <td>1.0164</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>213</td>\n",
       "      <td>ASM</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>Pago Pago</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>44273.0</td>\n",
       "      <td>46189.0</td>\n",
       "      <td>51368.0</td>\n",
       "      <td>54849.0</td>\n",
       "      <td>58230.0</td>\n",
       "      <td>47818.0</td>\n",
       "      <td>32886.0</td>\n",
       "      <td>27075.0</td>\n",
       "      <td>199.0</td>\n",
       "      <td>222.4774</td>\n",
       "      <td>0.9831</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>203</td>\n",
       "      <td>AND</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>Andorra la Vella</td>\n",
       "      <td>Europe</td>\n",
       "      <td>79824.0</td>\n",
       "      <td>77700.0</td>\n",
       "      <td>71746.0</td>\n",
       "      <td>71519.0</td>\n",
       "      <td>66097.0</td>\n",
       "      <td>53569.0</td>\n",
       "      <td>35611.0</td>\n",
       "      <td>19860.0</td>\n",
       "      <td>468.0</td>\n",
       "      <td>170.5641</td>\n",
       "      <td>1.0100</td>\n",
       "      <td>0.00</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>226</td>\n",
       "      <td>WLF</td>\n",
       "      <td>Wallis and Futuna</td>\n",
       "      <td>Mata-Utu</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>11572.0</td>\n",
       "      <td>11655.0</td>\n",
       "      <td>12182.0</td>\n",
       "      <td>13142.0</td>\n",
       "      <td>14723.0</td>\n",
       "      <td>13454.0</td>\n",
       "      <td>11315.0</td>\n",
       "      <td>9377.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>81.4930</td>\n",
       "      <td>0.9953</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>172</td>\n",
       "      <td>ESH</td>\n",
       "      <td>Western Sahara</td>\n",
       "      <td>El Aaiún</td>\n",
       "      <td>Africa</td>\n",
       "      <td>575986.0</td>\n",
       "      <td>556048.0</td>\n",
       "      <td>491824.0</td>\n",
       "      <td>413296.0</td>\n",
       "      <td>270375.0</td>\n",
       "      <td>178529.0</td>\n",
       "      <td>116775.0</td>\n",
       "      <td>76371.0</td>\n",
       "      <td>266000.0</td>\n",
       "      <td>2.1654</td>\n",
       "      <td>1.0184</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>46</td>\n",
       "      <td>YEM</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>Sanaa</td>\n",
       "      <td>Asia</td>\n",
       "      <td>33696614.0</td>\n",
       "      <td>32284046.0</td>\n",
       "      <td>28516545.0</td>\n",
       "      <td>24743946.0</td>\n",
       "      <td>18628700.0</td>\n",
       "      <td>13375121.0</td>\n",
       "      <td>9204938.0</td>\n",
       "      <td>6843607.0</td>\n",
       "      <td>527968.0</td>\n",
       "      <td>63.8232</td>\n",
       "      <td>1.0217</td>\n",
       "      <td>0.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>63</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>Lusaka</td>\n",
       "      <td>Africa</td>\n",
       "      <td>20017675.0</td>\n",
       "      <td>18927715.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13792086.0</td>\n",
       "      <td>9891136.0</td>\n",
       "      <td>7686401.0</td>\n",
       "      <td>5720438.0</td>\n",
       "      <td>4281671.0</td>\n",
       "      <td>752612.0</td>\n",
       "      <td>26.5976</td>\n",
       "      <td>1.0280</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>74</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>Harare</td>\n",
       "      <td>Africa</td>\n",
       "      <td>16320537.0</td>\n",
       "      <td>15669666.0</td>\n",
       "      <td>14154937.0</td>\n",
       "      <td>12839771.0</td>\n",
       "      <td>11834676.0</td>\n",
       "      <td>10113893.0</td>\n",
       "      <td>7049926.0</td>\n",
       "      <td>5202918.0</td>\n",
       "      <td>390757.0</td>\n",
       "      <td>41.7665</td>\n",
       "      <td>1.0204</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>234 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Rank CCA3            Country           Capital Continent  \\\n",
       "0      36  AFG        Afghanistan             Kabul      Asia   \n",
       "1     138  ALB            Albania            Tirana    Europe   \n",
       "2      34  DZA            Algeria           Algiers    Africa   \n",
       "3     213  ASM     American Samoa         Pago Pago   Oceania   \n",
       "4     203  AND            Andorra  Andorra la Vella    Europe   \n",
       "..    ...  ...                ...               ...       ...   \n",
       "229   226  WLF  Wallis and Futuna          Mata-Utu   Oceania   \n",
       "230   172  ESH     Western Sahara          El Aaiún    Africa   \n",
       "231    46  YEM              Yemen             Sanaa      Asia   \n",
       "232    63  ZMB             Zambia            Lusaka    Africa   \n",
       "233    74  ZWE           Zimbabwe            Harare    Africa   \n",
       "\n",
       "     2022 Population  2020 Population  2015 Population  2010 Population  \\\n",
       "0         41128771.0       38972230.0       33753499.0       28189672.0   \n",
       "1          2842321.0        2866849.0        2882481.0        2913399.0   \n",
       "2         44903225.0       43451666.0       39543154.0       35856344.0   \n",
       "3            44273.0          46189.0          51368.0          54849.0   \n",
       "4            79824.0          77700.0          71746.0          71519.0   \n",
       "..               ...              ...              ...              ...   \n",
       "229          11572.0          11655.0          12182.0          13142.0   \n",
       "230         575986.0         556048.0         491824.0         413296.0   \n",
       "231       33696614.0       32284046.0       28516545.0       24743946.0   \n",
       "232       20017675.0       18927715.0              NaN       13792086.0   \n",
       "233       16320537.0       15669666.0       14154937.0       12839771.0   \n",
       "\n",
       "     2000 Population  1990 Population  1980 Population  1970 Population  \\\n",
       "0         19542982.0       10694796.0       12486631.0       10752971.0   \n",
       "1          3182021.0        3295066.0        2941651.0        2324731.0   \n",
       "2         30774621.0       25518074.0       18739378.0       13795915.0   \n",
       "3            58230.0          47818.0          32886.0          27075.0   \n",
       "4            66097.0          53569.0          35611.0          19860.0   \n",
       "..               ...              ...              ...              ...   \n",
       "229          14723.0          13454.0          11315.0           9377.0   \n",
       "230         270375.0         178529.0         116775.0          76371.0   \n",
       "231       18628700.0       13375121.0        9204938.0        6843607.0   \n",
       "232        9891136.0        7686401.0        5720438.0        4281671.0   \n",
       "233       11834676.0       10113893.0        7049926.0        5202918.0   \n",
       "\n",
       "     Area (km²)  Density (per km²)  Growth Rate  World Population Percentage  \n",
       "0      652230.0            63.0587       1.0257                         0.52  \n",
       "1       28748.0            98.8702       0.9957                         0.04  \n",
       "2     2381741.0            18.8531       1.0164                         0.56  \n",
       "3         199.0           222.4774       0.9831                         0.00  \n",
       "4         468.0           170.5641       1.0100                         0.00  \n",
       "..          ...                ...          ...                          ...  \n",
       "229       142.0            81.4930       0.9953                         0.00  \n",
       "230    266000.0             2.1654       1.0184                         0.01  \n",
       "231    527968.0            63.8232       1.0217                         0.42  \n",
       "232    752612.0            26.5976       1.0280                         0.25  \n",
       "233    390757.0            41.7665       1.0204                         0.20  \n",
       "\n",
       "[234 rows x 17 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(r'world_population.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c71358c8-7f09-4621-a305-6c6cead0c707",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Первый взгляд:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0f9c898-4d08-4c62-9c6f-df810bff271a",
   "metadata": {},
   "source": [
    "**Получим название, количество строк  и тип колонок в таблице:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "211d753f-e618-4673-8c3f-e72fc3d963cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 234 entries, 0 to 233\n",
      "Data columns (total 17 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   Rank                         234 non-null    int64  \n",
      " 1   CCA3                         234 non-null    object \n",
      " 2   Country                      234 non-null    object \n",
      " 3   Capital                      234 non-null    object \n",
      " 4   Continent                    234 non-null    object \n",
      " 5   2022 Population              230 non-null    float64\n",
      " 6   2020 Population              233 non-null    float64\n",
      " 7   2015 Population              230 non-null    float64\n",
      " 8   2010 Population              227 non-null    float64\n",
      " 9   2000 Population              227 non-null    float64\n",
      " 10  1990 Population              229 non-null    float64\n",
      " 11  1980 Population              229 non-null    float64\n",
      " 12  1970 Population              230 non-null    float64\n",
      " 13  Area (km²)                   232 non-null    float64\n",
      " 14  Density (per km²)            230 non-null    float64\n",
      " 15  Growth Rate                  232 non-null    float64\n",
      " 16  World Population Percentage  234 non-null    float64\n",
      "dtypes: float64(12), int64(1), object(4)\n",
      "memory usage: 31.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87382662-a8ca-4e8e-a418-6d7fb40568e8",
   "metadata": {},
   "source": [
    "**Общие статистические данные**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c62e8a30-3a86-4d19-bfb1-397665736d82",
   "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>Rank</th>\n",
       "      <th>2022 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1970 Population</th>\n",
       "      <th>Area (km²)</th>\n",
       "      <th>Density (per km²)</th>\n",
       "      <th>Growth Rate</th>\n",
       "      <th>World Population Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>234.000000</td>\n",
       "      <td>2.300000e+02</td>\n",
       "      <td>2.330000e+02</td>\n",
       "      <td>2.300000e+02</td>\n",
       "      <td>2.270000e+02</td>\n",
       "      <td>2.270000e+02</td>\n",
       "      <td>2.290000e+02</td>\n",
       "      <td>2.290000e+02</td>\n",
       "      <td>2.300000e+02</td>\n",
       "      <td>2.320000e+02</td>\n",
       "      <td>230.000000</td>\n",
       "      <td>232.000000</td>\n",
       "      <td>234.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>117.500000</td>\n",
       "      <td>3.463225e+07</td>\n",
       "      <td>3.360071e+07</td>\n",
       "      <td>3.206600e+07</td>\n",
       "      <td>3.027016e+07</td>\n",
       "      <td>2.684050e+07</td>\n",
       "      <td>1.933046e+07</td>\n",
       "      <td>1.628288e+07</td>\n",
       "      <td>1.586650e+07</td>\n",
       "      <td>5.816637e+05</td>\n",
       "      <td>456.811652</td>\n",
       "      <td>1.009553</td>\n",
       "      <td>0.427051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>67.694165</td>\n",
       "      <td>1.378892e+08</td>\n",
       "      <td>1.358732e+08</td>\n",
       "      <td>1.315071e+08</td>\n",
       "      <td>1.260742e+08</td>\n",
       "      <td>1.133525e+08</td>\n",
       "      <td>8.130962e+07</td>\n",
       "      <td>6.934547e+07</td>\n",
       "      <td>6.835586e+07</td>\n",
       "      <td>1.769133e+06</td>\n",
       "      <td>2083.740364</td>\n",
       "      <td>0.013390</td>\n",
       "      <td>1.714977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.100000e+02</td>\n",
       "      <td>5.200000e+02</td>\n",
       "      <td>5.640000e+02</td>\n",
       "      <td>5.960000e+02</td>\n",
       "      <td>6.510000e+02</td>\n",
       "      <td>7.000000e+02</td>\n",
       "      <td>7.330000e+02</td>\n",
       "      <td>7.520000e+02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.026100</td>\n",
       "      <td>0.912000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>59.250000</td>\n",
       "      <td>4.197385e+05</td>\n",
       "      <td>4.064710e+05</td>\n",
       "      <td>3.942950e+05</td>\n",
       "      <td>3.827265e+05</td>\n",
       "      <td>3.294700e+05</td>\n",
       "      <td>2.619280e+05</td>\n",
       "      <td>2.237520e+05</td>\n",
       "      <td>1.458805e+05</td>\n",
       "      <td>2.567250e+03</td>\n",
       "      <td>36.598125</td>\n",
       "      <td>1.001925</td>\n",
       "      <td>0.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>117.500000</td>\n",
       "      <td>5.762857e+06</td>\n",
       "      <td>5.456681e+06</td>\n",
       "      <td>5.244415e+06</td>\n",
       "      <td>4.889741e+06</td>\n",
       "      <td>4.491202e+06</td>\n",
       "      <td>3.785847e+06</td>\n",
       "      <td>3.135123e+06</td>\n",
       "      <td>2.511718e+06</td>\n",
       "      <td>7.714100e+04</td>\n",
       "      <td>95.346750</td>\n",
       "      <td>1.007900</td>\n",
       "      <td>0.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>175.750000</td>\n",
       "      <td>2.265372e+07</td>\n",
       "      <td>2.152263e+07</td>\n",
       "      <td>1.973085e+07</td>\n",
       "      <td>1.682585e+07</td>\n",
       "      <td>1.562547e+07</td>\n",
       "      <td>1.188276e+07</td>\n",
       "      <td>9.817257e+06</td>\n",
       "      <td>8.817329e+06</td>\n",
       "      <td>4.146432e+05</td>\n",
       "      <td>236.884000</td>\n",
       "      <td>1.016650</td>\n",
       "      <td>0.280000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>234.000000</td>\n",
       "      <td>1.425887e+09</td>\n",
       "      <td>1.424930e+09</td>\n",
       "      <td>1.393715e+09</td>\n",
       "      <td>1.348191e+09</td>\n",
       "      <td>1.264099e+09</td>\n",
       "      <td>1.153704e+09</td>\n",
       "      <td>9.823725e+08</td>\n",
       "      <td>8.225344e+08</td>\n",
       "      <td>1.709824e+07</td>\n",
       "      <td>23172.266700</td>\n",
       "      <td>1.069100</td>\n",
       "      <td>17.880000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Rank  2022 Population  2020 Population  2015 Population  \\\n",
       "count  234.000000     2.300000e+02     2.330000e+02     2.300000e+02   \n",
       "mean   117.500000     3.463225e+07     3.360071e+07     3.206600e+07   \n",
       "std     67.694165     1.378892e+08     1.358732e+08     1.315071e+08   \n",
       "min      1.000000     5.100000e+02     5.200000e+02     5.640000e+02   \n",
       "25%     59.250000     4.197385e+05     4.064710e+05     3.942950e+05   \n",
       "50%    117.500000     5.762857e+06     5.456681e+06     5.244415e+06   \n",
       "75%    175.750000     2.265372e+07     2.152263e+07     1.973085e+07   \n",
       "max    234.000000     1.425887e+09     1.424930e+09     1.393715e+09   \n",
       "\n",
       "       2010 Population  2000 Population  1990 Population  1980 Population  \\\n",
       "count     2.270000e+02     2.270000e+02     2.290000e+02     2.290000e+02   \n",
       "mean      3.027016e+07     2.684050e+07     1.933046e+07     1.628288e+07   \n",
       "std       1.260742e+08     1.133525e+08     8.130962e+07     6.934547e+07   \n",
       "min       5.960000e+02     6.510000e+02     7.000000e+02     7.330000e+02   \n",
       "25%       3.827265e+05     3.294700e+05     2.619280e+05     2.237520e+05   \n",
       "50%       4.889741e+06     4.491202e+06     3.785847e+06     3.135123e+06   \n",
       "75%       1.682585e+07     1.562547e+07     1.188276e+07     9.817257e+06   \n",
       "max       1.348191e+09     1.264099e+09     1.153704e+09     9.823725e+08   \n",
       "\n",
       "       1970 Population    Area (km²)  Density (per km²)  Growth Rate  \\\n",
       "count     2.300000e+02  2.320000e+02         230.000000   232.000000   \n",
       "mean      1.586650e+07  5.816637e+05         456.811652     1.009553   \n",
       "std       6.835586e+07  1.769133e+06        2083.740364     0.013390   \n",
       "min       7.520000e+02  1.000000e+00           0.026100     0.912000   \n",
       "25%       1.458805e+05  2.567250e+03          36.598125     1.001925   \n",
       "50%       2.511718e+06  7.714100e+04          95.346750     1.007900   \n",
       "75%       8.817329e+06  4.146432e+05         236.884000     1.016650   \n",
       "max       8.225344e+08  1.709824e+07       23172.266700     1.069100   \n",
       "\n",
       "       World Population Percentage  \n",
       "count                   234.000000  \n",
       "mean                      0.427051  \n",
       "std                       1.714977  \n",
       "min                       0.000000  \n",
       "25%                       0.010000  \n",
       "50%                       0.070000  \n",
       "75%                       0.280000  \n",
       "max                      17.880000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c75b6f2d-f674-4c04-b630-0a378490055d",
   "metadata": {},
   "source": [
    "**Количество нулевых значений, которые нужно будет представить(заменить на медиану, макс, мин, пустоту,удалить)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bef1e627-2d28-46df-880e-69ec9f466c0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank                           0\n",
       "CCA3                           0\n",
       "Country                        0\n",
       "Capital                        0\n",
       "Continent                      0\n",
       "2022 Population                4\n",
       "2020 Population                1\n",
       "2015 Population                4\n",
       "2010 Population                7\n",
       "2000 Population                7\n",
       "1990 Population                5\n",
       "1980 Population                5\n",
       "1970 Population                4\n",
       "Area (km²)                     2\n",
       "Density (per km²)              4\n",
       "Growth Rate                    2\n",
       "World Population Percentage    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "005c89ae-5b6c-466f-9e1f-2f93bc9ea69d",
   "metadata": {},
   "source": [
    "**Количество уникальных значений:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "999e2895-2053-465c-bd2a-9362103c087e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank                           234\n",
       "CCA3                           234\n",
       "Country                        234\n",
       "Capital                        234\n",
       "Continent                        6\n",
       "2022 Population                230\n",
       "2020 Population                233\n",
       "2015 Population                230\n",
       "2010 Population                227\n",
       "2000 Population                227\n",
       "1990 Population                229\n",
       "1980 Population                229\n",
       "1970 Population                230\n",
       "Area (km²)                     231\n",
       "Density (per km²)              230\n",
       "Growth Rate                    178\n",
       "World Population Percentage     70\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e5092df-b53d-40e2-bd82-6eb8be1edc0c",
   "metadata": {},
   "source": [
    "**Выведем самые населённые страны:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1b888ae1-03ba-44c7-9c04-ff3c597c5111",
   "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>Rank</th>\n",
       "      <th>CCA3</th>\n",
       "      <th>Country</th>\n",
       "      <th>Capital</th>\n",
       "      <th>Continent</th>\n",
       "      <th>2022 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1970 Population</th>\n",
       "      <th>Area (km²)</th>\n",
       "      <th>Density (per km²)</th>\n",
       "      <th>Growth Rate</th>\n",
       "      <th>World Population Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.425887e+09</td>\n",
       "      <td>1.424930e+09</td>\n",
       "      <td>1.393715e+09</td>\n",
       "      <td>1.348191e+09</td>\n",
       "      <td>1.264099e+09</td>\n",
       "      <td>1.153704e+09</td>\n",
       "      <td>982372466.0</td>\n",
       "      <td>822534450.0</td>\n",
       "      <td>9706961.0</td>\n",
       "      <td>146.8933</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>17.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2</td>\n",
       "      <td>IND</td>\n",
       "      <td>India</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.417173e+09</td>\n",
       "      <td>1.396387e+09</td>\n",
       "      <td>1.322867e+09</td>\n",
       "      <td>1.240614e+09</td>\n",
       "      <td>1.059634e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>557501301.0</td>\n",
       "      <td>3287590.0</td>\n",
       "      <td>431.0675</td>\n",
       "      <td>1.0068</td>\n",
       "      <td>17.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>3</td>\n",
       "      <td>USA</td>\n",
       "      <td>United States</td>\n",
       "      <td>Washington, D.C.</td>\n",
       "      <td>North America</td>\n",
       "      <td>3.382899e+08</td>\n",
       "      <td>3.359420e+08</td>\n",
       "      <td>3.246078e+08</td>\n",
       "      <td>3.111828e+08</td>\n",
       "      <td>2.823986e+08</td>\n",
       "      <td>2.480837e+08</td>\n",
       "      <td>223140018.0</td>\n",
       "      <td>200328340.0</td>\n",
       "      <td>9372610.0</td>\n",
       "      <td>36.0935</td>\n",
       "      <td>1.0038</td>\n",
       "      <td>4.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>4</td>\n",
       "      <td>IDN</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>Jakarta</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.755013e+08</td>\n",
       "      <td>2.718580e+08</td>\n",
       "      <td>2.590920e+08</td>\n",
       "      <td>2.440162e+08</td>\n",
       "      <td>2.140724e+08</td>\n",
       "      <td>1.821599e+08</td>\n",
       "      <td>148177096.0</td>\n",
       "      <td>115228394.0</td>\n",
       "      <td>1904569.0</td>\n",
       "      <td>144.6529</td>\n",
       "      <td>1.0064</td>\n",
       "      <td>3.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>5</td>\n",
       "      <td>PAK</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>Islamabad</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.358249e+08</td>\n",
       "      <td>2.271967e+08</td>\n",
       "      <td>2.109693e+08</td>\n",
       "      <td>1.944545e+08</td>\n",
       "      <td>1.543699e+08</td>\n",
       "      <td>1.154141e+08</td>\n",
       "      <td>80624057.0</td>\n",
       "      <td>59290872.0</td>\n",
       "      <td>881912.0</td>\n",
       "      <td>267.4018</td>\n",
       "      <td>1.0191</td>\n",
       "      <td>2.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>6</td>\n",
       "      <td>NGA</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>Abuja</td>\n",
       "      <td>Africa</td>\n",
       "      <td>2.185412e+08</td>\n",
       "      <td>2.083274e+08</td>\n",
       "      <td>1.839958e+08</td>\n",
       "      <td>1.609529e+08</td>\n",
       "      <td>1.228520e+08</td>\n",
       "      <td>9.521426e+07</td>\n",
       "      <td>72951439.0</td>\n",
       "      <td>55569264.0</td>\n",
       "      <td>923768.0</td>\n",
       "      <td>236.5759</td>\n",
       "      <td>1.0241</td>\n",
       "      <td>2.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>Brasilia</td>\n",
       "      <td>South America</td>\n",
       "      <td>2.153135e+08</td>\n",
       "      <td>2.131963e+08</td>\n",
       "      <td>2.051882e+08</td>\n",
       "      <td>1.963535e+08</td>\n",
       "      <td>1.758737e+08</td>\n",
       "      <td>1.507064e+08</td>\n",
       "      <td>122288383.0</td>\n",
       "      <td>96369875.0</td>\n",
       "      <td>8515767.0</td>\n",
       "      <td>25.2841</td>\n",
       "      <td>1.0046</td>\n",
       "      <td>2.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8</td>\n",
       "      <td>BGD</td>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>Dhaka</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.711864e+08</td>\n",
       "      <td>1.674210e+08</td>\n",
       "      <td>1.578300e+08</td>\n",
       "      <td>1.483911e+08</td>\n",
       "      <td>1.291933e+08</td>\n",
       "      <td>1.071477e+08</td>\n",
       "      <td>83929765.0</td>\n",
       "      <td>67541860.0</td>\n",
       "      <td>147570.0</td>\n",
       "      <td>1160.0350</td>\n",
       "      <td>1.0108</td>\n",
       "      <td>2.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>9</td>\n",
       "      <td>RUS</td>\n",
       "      <td>Russia</td>\n",
       "      <td>Moscow</td>\n",
       "      <td>Europe</td>\n",
       "      <td>1.447133e+08</td>\n",
       "      <td>1.456173e+08</td>\n",
       "      <td>1.446684e+08</td>\n",
       "      <td>1.432426e+08</td>\n",
       "      <td>1.468448e+08</td>\n",
       "      <td>1.480057e+08</td>\n",
       "      <td>138257420.0</td>\n",
       "      <td>130093010.0</td>\n",
       "      <td>17098242.0</td>\n",
       "      <td>8.4636</td>\n",
       "      <td>0.9973</td>\n",
       "      <td>1.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>10</td>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>Mexico City</td>\n",
       "      <td>North America</td>\n",
       "      <td>1.275041e+08</td>\n",
       "      <td>1.259983e+08</td>\n",
       "      <td>1.201499e+08</td>\n",
       "      <td>1.125324e+08</td>\n",
       "      <td>9.787344e+07</td>\n",
       "      <td>8.172043e+07</td>\n",
       "      <td>67705186.0</td>\n",
       "      <td>50289306.0</td>\n",
       "      <td>1964375.0</td>\n",
       "      <td>64.9082</td>\n",
       "      <td>1.0063</td>\n",
       "      <td>1.60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Rank CCA3        Country           Capital      Continent  \\\n",
       "41      1  CHN          China           Beijing           Asia   \n",
       "92      2  IND          India         New Delhi           Asia   \n",
       "221     3  USA  United States  Washington, D.C.  North America   \n",
       "93      4  IDN      Indonesia           Jakarta           Asia   \n",
       "156     5  PAK       Pakistan         Islamabad           Asia   \n",
       "149     6  NGA        Nigeria             Abuja         Africa   \n",
       "27      7  BRA         Brazil          Brasilia  South America   \n",
       "16      8  BGD     Bangladesh             Dhaka           Asia   \n",
       "171     9  RUS         Russia            Moscow         Europe   \n",
       "131    10  MEX         Mexico       Mexico City  North America   \n",
       "\n",
       "     2022 Population  2020 Population  2015 Population  2010 Population  \\\n",
       "41      1.425887e+09     1.424930e+09     1.393715e+09     1.348191e+09   \n",
       "92      1.417173e+09     1.396387e+09     1.322867e+09     1.240614e+09   \n",
       "221     3.382899e+08     3.359420e+08     3.246078e+08     3.111828e+08   \n",
       "93      2.755013e+08     2.718580e+08     2.590920e+08     2.440162e+08   \n",
       "156     2.358249e+08     2.271967e+08     2.109693e+08     1.944545e+08   \n",
       "149     2.185412e+08     2.083274e+08     1.839958e+08     1.609529e+08   \n",
       "27      2.153135e+08     2.131963e+08     2.051882e+08     1.963535e+08   \n",
       "16      1.711864e+08     1.674210e+08     1.578300e+08     1.483911e+08   \n",
       "171     1.447133e+08     1.456173e+08     1.446684e+08     1.432426e+08   \n",
       "131     1.275041e+08     1.259983e+08     1.201499e+08     1.125324e+08   \n",
       "\n",
       "     2000 Population  1990 Population  1980 Population  1970 Population  \\\n",
       "41      1.264099e+09     1.153704e+09      982372466.0      822534450.0   \n",
       "92      1.059634e+09              NaN              NaN      557501301.0   \n",
       "221     2.823986e+08     2.480837e+08      223140018.0      200328340.0   \n",
       "93      2.140724e+08     1.821599e+08      148177096.0      115228394.0   \n",
       "156     1.543699e+08     1.154141e+08       80624057.0       59290872.0   \n",
       "149     1.228520e+08     9.521426e+07       72951439.0       55569264.0   \n",
       "27      1.758737e+08     1.507064e+08      122288383.0       96369875.0   \n",
       "16      1.291933e+08     1.071477e+08       83929765.0       67541860.0   \n",
       "171     1.468448e+08     1.480057e+08      138257420.0      130093010.0   \n",
       "131     9.787344e+07     8.172043e+07       67705186.0       50289306.0   \n",
       "\n",
       "     Area (km²)  Density (per km²)  Growth Rate  World Population Percentage  \n",
       "41    9706961.0           146.8933       1.0000                        17.88  \n",
       "92    3287590.0           431.0675       1.0068                        17.77  \n",
       "221   9372610.0            36.0935       1.0038                         4.24  \n",
       "93    1904569.0           144.6529       1.0064                         3.45  \n",
       "156    881912.0           267.4018       1.0191                         2.96  \n",
       "149    923768.0           236.5759       1.0241                         2.74  \n",
       "27    8515767.0            25.2841       1.0046                         2.70  \n",
       "16     147570.0          1160.0350       1.0108                         2.15  \n",
       "171  17098242.0             8.4636       0.9973                         1.81  \n",
       "131   1964375.0            64.9082       1.0063                         1.60  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=\"World Population Percentage\", ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5310124-9e71-4d80-b014-3d77cb6812e7",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Корреляция между данными:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ab198c0-9bf1-46b1-bcba-724aa6206cf3",
   "metadata": {},
   "source": [
    "**Даёт сходу понять, на что можно обратить внимание**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c1792eee-ce61-49ea-a7ee-29ddeb7f1fe3",
   "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>Rank</th>\n",
       "      <th>2022 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1970 Population</th>\n",
       "      <th>Area (km²)</th>\n",
       "      <th>Density (per km²)</th>\n",
       "      <th>Growth Rate</th>\n",
       "      <th>World Population Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Rank</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.357989</td>\n",
       "      <td>-0.356283</td>\n",
       "      <td>-0.352850</td>\n",
       "      <td>-0.350009</td>\n",
       "      <td>-0.342095</td>\n",
       "      <td>-0.333014</td>\n",
       "      <td>-0.328620</td>\n",
       "      <td>-0.335737</td>\n",
       "      <td>-0.384854</td>\n",
       "      <td>0.128994</td>\n",
       "      <td>-0.220197</td>\n",
       "      <td>-0.358464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022 Population</th>\n",
       "      <td>-0.357989</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999946</td>\n",
       "      <td>0.999492</td>\n",
       "      <td>0.998633</td>\n",
       "      <td>0.994602</td>\n",
       "      <td>0.991124</td>\n",
       "      <td>0.986675</td>\n",
       "      <td>0.973135</td>\n",
       "      <td>0.452812</td>\n",
       "      <td>-0.028761</td>\n",
       "      <td>-0.022059</td>\n",
       "      <td>0.999999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020 Population</th>\n",
       "      <td>-0.356283</td>\n",
       "      <td>0.999946</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999764</td>\n",
       "      <td>0.999108</td>\n",
       "      <td>0.995582</td>\n",
       "      <td>0.992557</td>\n",
       "      <td>0.988392</td>\n",
       "      <td>0.975245</td>\n",
       "      <td>0.454902</td>\n",
       "      <td>-0.027802</td>\n",
       "      <td>-0.025976</td>\n",
       "      <td>0.999944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015 Population</th>\n",
       "      <td>-0.352850</td>\n",
       "      <td>0.999492</td>\n",
       "      <td>0.999764</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999784</td>\n",
       "      <td>0.997343</td>\n",
       "      <td>0.994968</td>\n",
       "      <td>0.991346</td>\n",
       "      <td>0.979413</td>\n",
       "      <td>0.458101</td>\n",
       "      <td>-0.027740</td>\n",
       "      <td>-0.031150</td>\n",
       "      <td>0.999489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010 Population</th>\n",
       "      <td>-0.350009</td>\n",
       "      <td>0.998633</td>\n",
       "      <td>0.999108</td>\n",
       "      <td>0.999784</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.998595</td>\n",
       "      <td>0.996716</td>\n",
       "      <td>0.993628</td>\n",
       "      <td>0.983050</td>\n",
       "      <td>0.461498</td>\n",
       "      <td>-0.026635</td>\n",
       "      <td>-0.038262</td>\n",
       "      <td>0.998630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000 Population</th>\n",
       "      <td>-0.342095</td>\n",
       "      <td>0.994602</td>\n",
       "      <td>0.995582</td>\n",
       "      <td>0.997343</td>\n",
       "      <td>0.998595</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999192</td>\n",
       "      <td>0.997247</td>\n",
       "      <td>0.990959</td>\n",
       "      <td>0.473137</td>\n",
       "      <td>-0.026341</td>\n",
       "      <td>-0.052041</td>\n",
       "      <td>0.994598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990 Population</th>\n",
       "      <td>-0.333014</td>\n",
       "      <td>0.991124</td>\n",
       "      <td>0.992557</td>\n",
       "      <td>0.994968</td>\n",
       "      <td>0.996716</td>\n",
       "      <td>0.999192</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999257</td>\n",
       "      <td>0.997158</td>\n",
       "      <td>0.524392</td>\n",
       "      <td>-0.032348</td>\n",
       "      <td>-0.066718</td>\n",
       "      <td>0.991102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980 Population</th>\n",
       "      <td>-0.328620</td>\n",
       "      <td>0.986675</td>\n",
       "      <td>0.988392</td>\n",
       "      <td>0.991346</td>\n",
       "      <td>0.993628</td>\n",
       "      <td>0.997247</td>\n",
       "      <td>0.999257</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999251</td>\n",
       "      <td>0.530726</td>\n",
       "      <td>-0.032167</td>\n",
       "      <td>-0.077794</td>\n",
       "      <td>0.986652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970 Population</th>\n",
       "      <td>-0.335737</td>\n",
       "      <td>0.973135</td>\n",
       "      <td>0.975245</td>\n",
       "      <td>0.979413</td>\n",
       "      <td>0.983050</td>\n",
       "      <td>0.990959</td>\n",
       "      <td>0.997158</td>\n",
       "      <td>0.999251</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.509942</td>\n",
       "      <td>-0.027523</td>\n",
       "      <td>-0.080020</td>\n",
       "      <td>0.973143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area (km²)</th>\n",
       "      <td>-0.384854</td>\n",
       "      <td>0.452812</td>\n",
       "      <td>0.454902</td>\n",
       "      <td>0.458101</td>\n",
       "      <td>0.461498</td>\n",
       "      <td>0.473137</td>\n",
       "      <td>0.524392</td>\n",
       "      <td>0.530726</td>\n",
       "      <td>0.509942</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.063545</td>\n",
       "      <td>-0.012829</td>\n",
       "      <td>0.453305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Density (per km²)</th>\n",
       "      <td>0.128994</td>\n",
       "      <td>-0.028761</td>\n",
       "      <td>-0.027802</td>\n",
       "      <td>-0.027740</td>\n",
       "      <td>-0.026635</td>\n",
       "      <td>-0.026341</td>\n",
       "      <td>-0.032348</td>\n",
       "      <td>-0.032167</td>\n",
       "      <td>-0.027523</td>\n",
       "      <td>-0.063545</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.068923</td>\n",
       "      <td>-0.027957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Growth Rate</th>\n",
       "      <td>-0.220197</td>\n",
       "      <td>-0.022059</td>\n",
       "      <td>-0.025976</td>\n",
       "      <td>-0.031150</td>\n",
       "      <td>-0.038262</td>\n",
       "      <td>-0.052041</td>\n",
       "      <td>-0.066718</td>\n",
       "      <td>-0.077794</td>\n",
       "      <td>-0.080020</td>\n",
       "      <td>-0.012829</td>\n",
       "      <td>-0.068923</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.021495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>World Population Percentage</th>\n",
       "      <td>-0.358464</td>\n",
       "      <td>0.999999</td>\n",
       "      <td>0.999944</td>\n",
       "      <td>0.999489</td>\n",
       "      <td>0.998630</td>\n",
       "      <td>0.994598</td>\n",
       "      <td>0.991102</td>\n",
       "      <td>0.986652</td>\n",
       "      <td>0.973143</td>\n",
       "      <td>0.453305</td>\n",
       "      <td>-0.027957</td>\n",
       "      <td>-0.021495</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Rank  2022 Population  2020 Population  \\\n",
       "Rank                         1.000000        -0.357989        -0.356283   \n",
       "2022 Population             -0.357989         1.000000         0.999946   \n",
       "2020 Population             -0.356283         0.999946         1.000000   \n",
       "2015 Population             -0.352850         0.999492         0.999764   \n",
       "2010 Population             -0.350009         0.998633         0.999108   \n",
       "2000 Population             -0.342095         0.994602         0.995582   \n",
       "1990 Population             -0.333014         0.991124         0.992557   \n",
       "1980 Population             -0.328620         0.986675         0.988392   \n",
       "1970 Population             -0.335737         0.973135         0.975245   \n",
       "Area (km²)                  -0.384854         0.452812         0.454902   \n",
       "Density (per km²)            0.128994        -0.028761        -0.027802   \n",
       "Growth Rate                 -0.220197        -0.022059        -0.025976   \n",
       "World Population Percentage -0.358464         0.999999         0.999944   \n",
       "\n",
       "                             2015 Population  2010 Population  \\\n",
       "Rank                               -0.352850        -0.350009   \n",
       "2022 Population                     0.999492         0.998633   \n",
       "2020 Population                     0.999764         0.999108   \n",
       "2015 Population                     1.000000         0.999784   \n",
       "2010 Population                     0.999784         1.000000   \n",
       "2000 Population                     0.997343         0.998595   \n",
       "1990 Population                     0.994968         0.996716   \n",
       "1980 Population                     0.991346         0.993628   \n",
       "1970 Population                     0.979413         0.983050   \n",
       "Area (km²)                          0.458101         0.461498   \n",
       "Density (per km²)                  -0.027740        -0.026635   \n",
       "Growth Rate                        -0.031150        -0.038262   \n",
       "World Population Percentage         0.999489         0.998630   \n",
       "\n",
       "                             2000 Population  1990 Population  \\\n",
       "Rank                               -0.342095        -0.333014   \n",
       "2022 Population                     0.994602         0.991124   \n",
       "2020 Population                     0.995582         0.992557   \n",
       "2015 Population                     0.997343         0.994968   \n",
       "2010 Population                     0.998595         0.996716   \n",
       "2000 Population                     1.000000         0.999192   \n",
       "1990 Population                     0.999192         1.000000   \n",
       "1980 Population                     0.997247         0.999257   \n",
       "1970 Population                     0.990959         0.997158   \n",
       "Area (km²)                          0.473137         0.524392   \n",
       "Density (per km²)                  -0.026341        -0.032348   \n",
       "Growth Rate                        -0.052041        -0.066718   \n",
       "World Population Percentage         0.994598         0.991102   \n",
       "\n",
       "                             1980 Population  1970 Population  Area (km²)  \\\n",
       "Rank                               -0.328620        -0.335737   -0.384854   \n",
       "2022 Population                     0.986675         0.973135    0.452812   \n",
       "2020 Population                     0.988392         0.975245    0.454902   \n",
       "2015 Population                     0.991346         0.979413    0.458101   \n",
       "2010 Population                     0.993628         0.983050    0.461498   \n",
       "2000 Population                     0.997247         0.990959    0.473137   \n",
       "1990 Population                     0.999257         0.997158    0.524392   \n",
       "1980 Population                     1.000000         0.999251    0.530726   \n",
       "1970 Population                     0.999251         1.000000    0.509942   \n",
       "Area (km²)                          0.530726         0.509942    1.000000   \n",
       "Density (per km²)                  -0.032167        -0.027523   -0.063545   \n",
       "Growth Rate                        -0.077794        -0.080020   -0.012829   \n",
       "World Population Percentage         0.986652         0.973143    0.453305   \n",
       "\n",
       "                             Density (per km²)  Growth Rate  \\\n",
       "Rank                                  0.128994    -0.220197   \n",
       "2022 Population                      -0.028761    -0.022059   \n",
       "2020 Population                      -0.027802    -0.025976   \n",
       "2015 Population                      -0.027740    -0.031150   \n",
       "2010 Population                      -0.026635    -0.038262   \n",
       "2000 Population                      -0.026341    -0.052041   \n",
       "1990 Population                      -0.032348    -0.066718   \n",
       "1980 Population                      -0.032167    -0.077794   \n",
       "1970 Population                      -0.027523    -0.080020   \n",
       "Area (km²)                           -0.063545    -0.012829   \n",
       "Density (per km²)                     1.000000    -0.068923   \n",
       "Growth Rate                          -0.068923     1.000000   \n",
       "World Population Percentage          -0.027957    -0.021495   \n",
       "\n",
       "                             World Population Percentage  \n",
       "Rank                                           -0.358464  \n",
       "2022 Population                                 0.999999  \n",
       "2020 Population                                 0.999944  \n",
       "2015 Population                                 0.999489  \n",
       "2010 Population                                 0.998630  \n",
       "2000 Population                                 0.994598  \n",
       "1990 Population                                 0.991102  \n",
       "1980 Population                                 0.986652  \n",
       "1970 Population                                 0.973143  \n",
       "Area (km²)                                      0.453305  \n",
       "Density (per km²)                              -0.027957  \n",
       "Growth Rate                                    -0.021495  \n",
       "World Population Percentage                     1.000000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select_dtypes(include=[float, int]).corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be3f4582-a5a2-4e10-98bc-2c1010b7c66d",
   "metadata": {},
   "source": [
    "**Визуализируем это:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3195237d-70f1-458c-be49-3cf8640b241b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "da5be236-a832-4680-a38b-5ba8ee0f2ccf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.select_dtypes(include=[float, int]).corr(), annot = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9b62d98-9da6-46bc-8918-f176e5b2faff",
   "metadata": {},
   "source": [
    "**очевидно, наибольшая корреляция между значениями населения по годам и процентом от общего населения**\n",
    "<br>*кстати если быть оптимистами можно сказать, что есть какая-то корреляция между площадью страны и её популяцией, а остальное вообще никак не связано*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbf8987e-ee7e-4d57-b5d8-3597fb2e973e",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Анализ 1(Где покупать недвижимость)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de7a4456-7531-410b-ab2b-1923646189f6",
   "metadata": {},
   "source": [
    "**Сгруппируем данные из фрейма по континентам и отсортируем их в порядке густонаселённости на 2022 год, чтобы оценить темпы роста и найти самый быстрорастущий:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0139625a-9e82-47ba-b05f-388629e497f5",
   "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>Rank</th>\n",
       "      <th>2022 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1970 Population</th>\n",
       "      <th>Area (km²)</th>\n",
       "      <th>Density (per km²)</th>\n",
       "      <th>Growth Rate</th>\n",
       "      <th>World Population Percentage</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Continent</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Asia</th>\n",
       "      <td>77.560000</td>\n",
       "      <td>9.632739e+07</td>\n",
       "      <td>9.495513e+07</td>\n",
       "      <td>8.916500e+07</td>\n",
       "      <td>8.908777e+07</td>\n",
       "      <td>8.058084e+07</td>\n",
       "      <td>4.864000e+07</td>\n",
       "      <td>4.027833e+07</td>\n",
       "      <td>4.383988e+07</td>\n",
       "      <td>6.427628e+05</td>\n",
       "      <td>1025.024136</td>\n",
       "      <td>1.009384</td>\n",
       "      <td>1.183800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South America</th>\n",
       "      <td>97.571429</td>\n",
       "      <td>3.120119e+07</td>\n",
       "      <td>3.082357e+07</td>\n",
       "      <td>2.950960e+07</td>\n",
       "      <td>2.678940e+07</td>\n",
       "      <td>2.501589e+07</td>\n",
       "      <td>2.122474e+07</td>\n",
       "      <td>1.727064e+07</td>\n",
       "      <td>1.378194e+07</td>\n",
       "      <td>1.301303e+06</td>\n",
       "      <td>20.971979</td>\n",
       "      <td>1.007957</td>\n",
       "      <td>0.391429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Africa</th>\n",
       "      <td>92.157895</td>\n",
       "      <td>2.545588e+07</td>\n",
       "      <td>2.387144e+07</td>\n",
       "      <td>2.141970e+07</td>\n",
       "      <td>1.889820e+07</td>\n",
       "      <td>1.459837e+07</td>\n",
       "      <td>1.137696e+07</td>\n",
       "      <td>8.586032e+06</td>\n",
       "      <td>6.567175e+06</td>\n",
       "      <td>5.378793e+05</td>\n",
       "      <td>126.406569</td>\n",
       "      <td>1.021180</td>\n",
       "      <td>0.313509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Europe</th>\n",
       "      <td>124.500000</td>\n",
       "      <td>1.505537e+07</td>\n",
       "      <td>1.491584e+07</td>\n",
       "      <td>1.502745e+07</td>\n",
       "      <td>1.471228e+07</td>\n",
       "      <td>1.481769e+07</td>\n",
       "      <td>1.478520e+07</td>\n",
       "      <td>1.420000e+07</td>\n",
       "      <td>1.311848e+07</td>\n",
       "      <td>4.602082e+05</td>\n",
       "      <td>663.324742</td>\n",
       "      <td>1.002256</td>\n",
       "      <td>0.186600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North America</th>\n",
       "      <td>160.925000</td>\n",
       "      <td>1.500740e+07</td>\n",
       "      <td>1.485591e+07</td>\n",
       "      <td>1.425960e+07</td>\n",
       "      <td>1.356802e+07</td>\n",
       "      <td>1.215174e+07</td>\n",
       "      <td>1.053166e+07</td>\n",
       "      <td>9.207334e+06</td>\n",
       "      <td>7.885865e+06</td>\n",
       "      <td>6.061044e+05</td>\n",
       "      <td>272.494118</td>\n",
       "      <td>1.004285</td>\n",
       "      <td>0.187750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oceania</th>\n",
       "      <td>188.521739</td>\n",
       "      <td>2.046386e+06</td>\n",
       "      <td>1.910149e+06</td>\n",
       "      <td>1.756664e+06</td>\n",
       "      <td>1.613164e+06</td>\n",
       "      <td>1.357512e+06</td>\n",
       "      <td>1.162775e+06</td>\n",
       "      <td>9.965322e+05</td>\n",
       "      <td>8.469683e+05</td>\n",
       "      <td>3.702209e+05</td>\n",
       "      <td>132.543065</td>\n",
       "      <td>1.007383</td>\n",
       "      <td>0.023913</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Rank  2022 Population  2020 Population  2015 Population  \\\n",
       "Continent                                                                      \n",
       "Asia            77.560000     9.632739e+07     9.495513e+07     8.916500e+07   \n",
       "South America   97.571429     3.120119e+07     3.082357e+07     2.950960e+07   \n",
       "Africa          92.157895     2.545588e+07     2.387144e+07     2.141970e+07   \n",
       "Europe         124.500000     1.505537e+07     1.491584e+07     1.502745e+07   \n",
       "North America  160.925000     1.500740e+07     1.485591e+07     1.425960e+07   \n",
       "Oceania        188.521739     2.046386e+06     1.910149e+06     1.756664e+06   \n",
       "\n",
       "               2010 Population  2000 Population  1990 Population  \\\n",
       "Continent                                                          \n",
       "Asia              8.908777e+07     8.058084e+07     4.864000e+07   \n",
       "South America     2.678940e+07     2.501589e+07     2.122474e+07   \n",
       "Africa            1.889820e+07     1.459837e+07     1.137696e+07   \n",
       "Europe            1.471228e+07     1.481769e+07     1.478520e+07   \n",
       "North America     1.356802e+07     1.215174e+07     1.053166e+07   \n",
       "Oceania           1.613164e+06     1.357512e+06     1.162775e+06   \n",
       "\n",
       "               1980 Population  1970 Population    Area (km²)  \\\n",
       "Continent                                                       \n",
       "Asia              4.027833e+07     4.383988e+07  6.427628e+05   \n",
       "South America     1.727064e+07     1.378194e+07  1.301303e+06   \n",
       "Africa            8.586032e+06     6.567175e+06  5.378793e+05   \n",
       "Europe            1.420000e+07     1.311848e+07  4.602082e+05   \n",
       "North America     9.207334e+06     7.885865e+06  6.061044e+05   \n",
       "Oceania           9.965322e+05     8.469683e+05  3.702209e+05   \n",
       "\n",
       "               Density (per km²)  Growth Rate  World Population Percentage  \n",
       "Continent                                                                   \n",
       "Asia                 1025.024136     1.009384                     1.183800  \n",
       "South America          20.971979     1.007957                     0.391429  \n",
       "Africa                126.406569     1.021180                     0.313509  \n",
       "Europe                663.324742     1.002256                     0.186600  \n",
       "North America         272.494118     1.004285                     0.187750  \n",
       "Oceania               132.543065     1.007383                     0.023913  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Continent').mean(numeric_only=True).sort_values(by=\"2022 Population\",ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7222610e-ee72-402a-b049-68d5175b3a8e",
   "metadata": {},
   "source": [
    "* **Самый быстрорастущий континент - Африка, пока он на третьей позиции, но с сохранением тенденций сможет обогнать Южную Америку, до Азии вряд ли кто-то дотянется**\n",
    "* **В противоположность Азии, Южная Америка имеет наименьшую плотность населения(вероятно из-за джунглей), однако занимает второе место по численности. Значит там ещё полно места).**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1c05c3e-1672-4dff-a4d3-021774e79b23",
   "metadata": {},
   "source": [
    "**Проверим в какой стране Южной Америки лучше накупить земли на будущее:**\n",
    "<br>*также уберём всякие острова и страны менее 1млн км площади*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "87103b32-597b-4b66-83df-19f1052e5865",
   "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>Rank</th>\n",
       "      <th>CCA3</th>\n",
       "      <th>Country</th>\n",
       "      <th>Capital</th>\n",
       "      <th>Continent</th>\n",
       "      <th>2022 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1970 Population</th>\n",
       "      <th>Area (km²)</th>\n",
       "      <th>Density (per km²)</th>\n",
       "      <th>Growth Rate</th>\n",
       "      <th>World Population Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>80</td>\n",
       "      <td>BOL</td>\n",
       "      <td>Bolivia</td>\n",
       "      <td>Sucre</td>\n",
       "      <td>South America</td>\n",
       "      <td>12224110.0</td>\n",
       "      <td>11936162.0</td>\n",
       "      <td>11090085.0</td>\n",
       "      <td>10223270.0</td>\n",
       "      <td>8592656.0</td>\n",
       "      <td>7096194.0</td>\n",
       "      <td>5736088.0</td>\n",
       "      <td>4585693.0</td>\n",
       "      <td>1098581.0</td>\n",
       "      <td>11.1272</td>\n",
       "      <td>1.0120</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>33</td>\n",
       "      <td>ARG</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>South America</td>\n",
       "      <td>45510318.0</td>\n",
       "      <td>45036032.0</td>\n",
       "      <td>43257065.0</td>\n",
       "      <td>41100123.0</td>\n",
       "      <td>37070774.0</td>\n",
       "      <td>32637657.0</td>\n",
       "      <td>28024803.0</td>\n",
       "      <td>23842803.0</td>\n",
       "      <td>2780400.0</td>\n",
       "      <td>16.3683</td>\n",
       "      <td>1.0052</td>\n",
       "      <td>0.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>Brasilia</td>\n",
       "      <td>South America</td>\n",
       "      <td>215313498.0</td>\n",
       "      <td>213196304.0</td>\n",
       "      <td>205188205.0</td>\n",
       "      <td>196353492.0</td>\n",
       "      <td>175873720.0</td>\n",
       "      <td>150706446.0</td>\n",
       "      <td>122288383.0</td>\n",
       "      <td>96369875.0</td>\n",
       "      <td>8515767.0</td>\n",
       "      <td>25.2841</td>\n",
       "      <td>1.0046</td>\n",
       "      <td>2.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>44</td>\n",
       "      <td>PER</td>\n",
       "      <td>Peru</td>\n",
       "      <td>Lima</td>\n",
       "      <td>South America</td>\n",
       "      <td>34049588.0</td>\n",
       "      <td>33304756.0</td>\n",
       "      <td>30711863.0</td>\n",
       "      <td>29229572.0</td>\n",
       "      <td>26654439.0</td>\n",
       "      <td>22109099.0</td>\n",
       "      <td>17492406.0</td>\n",
       "      <td>13562371.0</td>\n",
       "      <td>1285216.0</td>\n",
       "      <td>26.4933</td>\n",
       "      <td>1.0099</td>\n",
       "      <td>0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>28</td>\n",
       "      <td>COL</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>Bogota</td>\n",
       "      <td>South America</td>\n",
       "      <td>51874024.0</td>\n",
       "      <td>50930662.0</td>\n",
       "      <td>47119728.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39215135.0</td>\n",
       "      <td>32601393.0</td>\n",
       "      <td>26176195.0</td>\n",
       "      <td>20905254.0</td>\n",
       "      <td>1141748.0</td>\n",
       "      <td>45.4339</td>\n",
       "      <td>1.0069</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Rank CCA3    Country       Capital      Continent  2022 Population  \\\n",
       "24     80  BOL    Bolivia         Sucre  South America       12224110.0   \n",
       "8      33  ARG  Argentina  Buenos Aires  South America       45510318.0   \n",
       "27      7  BRA     Brazil      Brasilia  South America      215313498.0   \n",
       "162    44  PER       Peru          Lima  South America       34049588.0   \n",
       "42     28  COL   Colombia        Bogota  South America       51874024.0   \n",
       "\n",
       "     2020 Population  2015 Population  2010 Population  2000 Population  \\\n",
       "24        11936162.0       11090085.0       10223270.0        8592656.0   \n",
       "8         45036032.0       43257065.0       41100123.0       37070774.0   \n",
       "27       213196304.0      205188205.0      196353492.0      175873720.0   \n",
       "162       33304756.0       30711863.0       29229572.0       26654439.0   \n",
       "42        50930662.0       47119728.0              NaN       39215135.0   \n",
       "\n",
       "     1990 Population  1980 Population  1970 Population  Area (km²)  \\\n",
       "24         7096194.0        5736088.0        4585693.0   1098581.0   \n",
       "8         32637657.0       28024803.0       23842803.0   2780400.0   \n",
       "27       150706446.0      122288383.0       96369875.0   8515767.0   \n",
       "162       22109099.0       17492406.0       13562371.0   1285216.0   \n",
       "42        32601393.0       26176195.0       20905254.0   1141748.0   \n",
       "\n",
       "     Density (per km²)  Growth Rate  World Population Percentage  \n",
       "24             11.1272       1.0120                         0.15  \n",
       "8              16.3683       1.0052                         0.57  \n",
       "27             25.2841       1.0046                         2.70  \n",
       "162            26.4933       1.0099                         0.43  \n",
       "42             45.4339       1.0069                         0.65  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['Continent'].str.contains('South America')) & (df['Area (km²)'] > 1000000)].sort_values(by='Density (per km²)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27e27e32-4b86-4891-b7f2-d8ed6a1e25d5",
   "metadata": {},
   "source": [
    "**Вывод: Скупаем дома в Боливии, несмотря на политику, преступность и прочие \"мелочи\"**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fa4f4ec-a9b1-404c-adf8-b029c50d25cc",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## Анализ 2(Где не стоит строить \"единорога\", по-крайней мере Хартманн не стал бы(а может и стал бы, он же умный))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f20766f4-3cbf-4a7f-af8e-bdbedafb9c31",
   "metadata": {},
   "source": [
    "**Теперь хочется наглядно посмотреть на рост населения в странах Азии**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9902615e-252d-4cef-8f91-9872b2f2d56b",
   "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>Rank</th>\n",
       "      <th>CCA3</th>\n",
       "      <th>Country</th>\n",
       "      <th>Capital</th>\n",
       "      <th>Continent</th>\n",
       "      <th>2022 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1970 Population</th>\n",
       "      <th>Area (km²)</th>\n",
       "      <th>Density (per km²)</th>\n",
       "      <th>Growth Rate</th>\n",
       "      <th>World Population Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Kabul</td>\n",
       "      <td>Asia</td>\n",
       "      <td>4.112877e+07</td>\n",
       "      <td>3.897223e+07</td>\n",
       "      <td>3.375350e+07</td>\n",
       "      <td>2.818967e+07</td>\n",
       "      <td>1.954298e+07</td>\n",
       "      <td>1.069480e+07</td>\n",
       "      <td>12486631.0</td>\n",
       "      <td>10752971.0</td>\n",
       "      <td>652230.0</td>\n",
       "      <td>63.0587</td>\n",
       "      <td>1.0257</td>\n",
       "      <td>0.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>140</td>\n",
       "      <td>ARM</td>\n",
       "      <td>Armenia</td>\n",
       "      <td>Yerevan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.780469e+06</td>\n",
       "      <td>2.805608e+06</td>\n",
       "      <td>2.878595e+06</td>\n",
       "      <td>2.946293e+06</td>\n",
       "      <td>3.168523e+06</td>\n",
       "      <td>3.556539e+06</td>\n",
       "      <td>3135123.0</td>\n",
       "      <td>2534377.0</td>\n",
       "      <td>29743.0</td>\n",
       "      <td>93.4831</td>\n",
       "      <td>0.9962</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>91</td>\n",
       "      <td>AZE</td>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>Baku</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.035807e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.863480e+06</td>\n",
       "      <td>9.237202e+06</td>\n",
       "      <td>8.190337e+06</td>\n",
       "      <td>7.427836e+06</td>\n",
       "      <td>6383060.0</td>\n",
       "      <td>5425317.0</td>\n",
       "      <td>86600.0</td>\n",
       "      <td>119.6082</td>\n",
       "      <td>1.0044</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>154</td>\n",
       "      <td>BHR</td>\n",
       "      <td>Bahrain</td>\n",
       "      <td>Manama</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.472233e+06</td>\n",
       "      <td>1.477469e+06</td>\n",
       "      <td>1.362142e+06</td>\n",
       "      <td>1.213645e+06</td>\n",
       "      <td>7.114420e+05</td>\n",
       "      <td>5.174180e+05</td>\n",
       "      <td>362595.0</td>\n",
       "      <td>222555.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>1924.4876</td>\n",
       "      <td>1.0061</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8</td>\n",
       "      <td>BGD</td>\n",
       "      <td>Bangladesh</td>\n",
       "      <td>Dhaka</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.711864e+08</td>\n",
       "      <td>1.674210e+08</td>\n",
       "      <td>1.578300e+08</td>\n",
       "      <td>1.483911e+08</td>\n",
       "      <td>1.291933e+08</td>\n",
       "      <td>1.071477e+08</td>\n",
       "      <td>83929765.0</td>\n",
       "      <td>67541860.0</td>\n",
       "      <td>147570.0</td>\n",
       "      <td>1160.0350</td>\n",
       "      <td>1.0108</td>\n",
       "      <td>2.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>165</td>\n",
       "      <td>BTN</td>\n",
       "      <td>Bhutan</td>\n",
       "      <td>Thimphu</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.824550e+05</td>\n",
       "      <td>7.725060e+05</td>\n",
       "      <td>7.432740e+05</td>\n",
       "      <td>7.055160e+05</td>\n",
       "      <td>5.872070e+05</td>\n",
       "      <td>5.584420e+05</td>\n",
       "      <td>415257.0</td>\n",
       "      <td>298894.0</td>\n",
       "      <td>38394.0</td>\n",
       "      <td>20.3796</td>\n",
       "      <td>1.0064</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>175</td>\n",
       "      <td>BRN</td>\n",
       "      <td>Brunei</td>\n",
       "      <td>Bandar Seri Begawan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>4.490020e+05</td>\n",
       "      <td>4.417250e+05</td>\n",
       "      <td>4.214370e+05</td>\n",
       "      <td>3.960530e+05</td>\n",
       "      <td>3.339260e+05</td>\n",
       "      <td>2.619280e+05</td>\n",
       "      <td>187921.0</td>\n",
       "      <td>133343.0</td>\n",
       "      <td>5765.0</td>\n",
       "      <td>77.8841</td>\n",
       "      <td>1.0081</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>73</td>\n",
       "      <td>KHM</td>\n",
       "      <td>Cambodia</td>\n",
       "      <td>Phnom Penh</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.676784e+07</td>\n",
       "      <td>1.639686e+07</td>\n",
       "      <td>1.541752e+07</td>\n",
       "      <td>1.436353e+07</td>\n",
       "      <td>1.211884e+07</td>\n",
       "      <td>8.910808e+06</td>\n",
       "      <td>6198959.0</td>\n",
       "      <td>6708525.0</td>\n",
       "      <td>181035.0</td>\n",
       "      <td>92.6221</td>\n",
       "      <td>1.0108</td>\n",
       "      <td>0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.425887e+09</td>\n",
       "      <td>1.424930e+09</td>\n",
       "      <td>1.393715e+09</td>\n",
       "      <td>1.348191e+09</td>\n",
       "      <td>1.264099e+09</td>\n",
       "      <td>1.153704e+09</td>\n",
       "      <td>982372466.0</td>\n",
       "      <td>822534450.0</td>\n",
       "      <td>9706961.0</td>\n",
       "      <td>146.8933</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>17.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>131</td>\n",
       "      <td>GEO</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Tbilisi</td>\n",
       "      <td>Asia</td>\n",
       "      <td>3.744385e+06</td>\n",
       "      <td>3.765912e+06</td>\n",
       "      <td>3.771132e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69700.0</td>\n",
       "      <td>53.7214</td>\n",
       "      <td>0.9964</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>104</td>\n",
       "      <td>HKG</td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.488865e+06</td>\n",
       "      <td>7.500958e+06</td>\n",
       "      <td>7.399838e+06</td>\n",
       "      <td>7.132438e+06</td>\n",
       "      <td>6.731195e+06</td>\n",
       "      <td>5.838574e+06</td>\n",
       "      <td>4978544.0</td>\n",
       "      <td>3955072.0</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>6783.3922</td>\n",
       "      <td>0.9992</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2</td>\n",
       "      <td>IND</td>\n",
       "      <td>India</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.417173e+09</td>\n",
       "      <td>1.396387e+09</td>\n",
       "      <td>1.322867e+09</td>\n",
       "      <td>1.240614e+09</td>\n",
       "      <td>1.059634e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>557501301.0</td>\n",
       "      <td>3287590.0</td>\n",
       "      <td>431.0675</td>\n",
       "      <td>1.0068</td>\n",
       "      <td>17.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>4</td>\n",
       "      <td>IDN</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>Jakarta</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.755013e+08</td>\n",
       "      <td>2.718580e+08</td>\n",
       "      <td>2.590920e+08</td>\n",
       "      <td>2.440162e+08</td>\n",
       "      <td>2.140724e+08</td>\n",
       "      <td>1.821599e+08</td>\n",
       "      <td>148177096.0</td>\n",
       "      <td>115228394.0</td>\n",
       "      <td>1904569.0</td>\n",
       "      <td>144.6529</td>\n",
       "      <td>1.0064</td>\n",
       "      <td>3.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>17</td>\n",
       "      <td>IRN</td>\n",
       "      <td>Iran</td>\n",
       "      <td>Tehran</td>\n",
       "      <td>Asia</td>\n",
       "      <td>8.855057e+07</td>\n",
       "      <td>8.729019e+07</td>\n",
       "      <td>8.179084e+07</td>\n",
       "      <td>7.537386e+07</td>\n",
       "      <td>6.554438e+07</td>\n",
       "      <td>5.579363e+07</td>\n",
       "      <td>38520664.0</td>\n",
       "      <td>28449705.0</td>\n",
       "      <td>1648195.0</td>\n",
       "      <td>53.7258</td>\n",
       "      <td>1.0071</td>\n",
       "      <td>1.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>35</td>\n",
       "      <td>IRQ</td>\n",
       "      <td>Iraq</td>\n",
       "      <td>Baghdad</td>\n",
       "      <td>Asia</td>\n",
       "      <td>4.449612e+07</td>\n",
       "      <td>4.255698e+07</td>\n",
       "      <td>3.775781e+07</td>\n",
       "      <td>3.126488e+07</td>\n",
       "      <td>2.462886e+07</td>\n",
       "      <td>1.765838e+07</td>\n",
       "      <td>13653369.0</td>\n",
       "      <td>9811347.0</td>\n",
       "      <td>438317.0</td>\n",
       "      <td>101.5158</td>\n",
       "      <td>1.0221</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>98</td>\n",
       "      <td>ISR</td>\n",
       "      <td>Israel</td>\n",
       "      <td>Jerusalem</td>\n",
       "      <td>Asia</td>\n",
       "      <td>9.038309e+06</td>\n",
       "      <td>8.757489e+06</td>\n",
       "      <td>8.007778e+06</td>\n",
       "      <td>7.328445e+06</td>\n",
       "      <td>6.116958e+06</td>\n",
       "      <td>4.803254e+06</td>\n",
       "      <td>3744608.0</td>\n",
       "      <td>2907307.0</td>\n",
       "      <td>20770.0</td>\n",
       "      <td>435.1617</td>\n",
       "      <td>1.0155</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>11</td>\n",
       "      <td>JPN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Tokyo</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.239517e+08</td>\n",
       "      <td>1.252448e+08</td>\n",
       "      <td>1.272509e+08</td>\n",
       "      <td>1.281054e+08</td>\n",
       "      <td>1.268039e+08</td>\n",
       "      <td>1.236863e+08</td>\n",
       "      <td>117624196.0</td>\n",
       "      <td>105416839.0</td>\n",
       "      <td>377930.0</td>\n",
       "      <td>327.9753</td>\n",
       "      <td>0.9947</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>83</td>\n",
       "      <td>JOR</td>\n",
       "      <td>Jordan</td>\n",
       "      <td>Amman</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.128587e+07</td>\n",
       "      <td>1.092872e+07</td>\n",
       "      <td>9.494246e+06</td>\n",
       "      <td>6.931258e+06</td>\n",
       "      <td>5.056174e+06</td>\n",
       "      <td>3.480587e+06</td>\n",
       "      <td>2216903.0</td>\n",
       "      <td>1557374.0</td>\n",
       "      <td>89342.0</td>\n",
       "      <td>126.3221</td>\n",
       "      <td>1.0123</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>66</td>\n",
       "      <td>KAZ</td>\n",
       "      <td>Kazakhstan</td>\n",
       "      <td>Nursultan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.939800e+07</td>\n",
       "      <td>1.897924e+07</td>\n",
       "      <td>1.783591e+07</td>\n",
       "      <td>1.662784e+07</td>\n",
       "      <td>1.523625e+07</td>\n",
       "      <td>1.686656e+07</td>\n",
       "      <td>14172710.0</td>\n",
       "      <td>12265305.0</td>\n",
       "      <td>2724900.0</td>\n",
       "      <td>7.1188</td>\n",
       "      <td>1.0105</td>\n",
       "      <td>0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>129</td>\n",
       "      <td>KWT</td>\n",
       "      <td>Kuwait</td>\n",
       "      <td>Kuwait City</td>\n",
       "      <td>Asia</td>\n",
       "      <td>4.268873e+06</td>\n",
       "      <td>4.360444e+06</td>\n",
       "      <td>3.908743e+06</td>\n",
       "      <td>2.943356e+06</td>\n",
       "      <td>1.934901e+06</td>\n",
       "      <td>1.674938e+06</td>\n",
       "      <td>1493870.0</td>\n",
       "      <td>802786.0</td>\n",
       "      <td>17818.0</td>\n",
       "      <td>239.5821</td>\n",
       "      <td>1.0044</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>110</td>\n",
       "      <td>KGZ</td>\n",
       "      <td>Kyrgyzstan</td>\n",
       "      <td>Bishkek</td>\n",
       "      <td>Asia</td>\n",
       "      <td>6.630623e+06</td>\n",
       "      <td>6.424874e+06</td>\n",
       "      <td>5.914980e+06</td>\n",
       "      <td>5.483774e+06</td>\n",
       "      <td>4.935182e+06</td>\n",
       "      <td>4.394734e+06</td>\n",
       "      <td>3691209.0</td>\n",
       "      <td>3016384.0</td>\n",
       "      <td>199951.0</td>\n",
       "      <td>33.1612</td>\n",
       "      <td>1.0158</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>103</td>\n",
       "      <td>LAO</td>\n",
       "      <td>Laos</td>\n",
       "      <td>Vientiane</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.529475e+06</td>\n",
       "      <td>7.319399e+06</td>\n",
       "      <td>6.787419e+06</td>\n",
       "      <td>6.323418e+06</td>\n",
       "      <td>5.430853e+06</td>\n",
       "      <td>4.314443e+06</td>\n",
       "      <td>3297519.0</td>\n",
       "      <td>2675283.0</td>\n",
       "      <td>236800.0</td>\n",
       "      <td>31.7968</td>\n",
       "      <td>1.0141</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>119</td>\n",
       "      <td>LBN</td>\n",
       "      <td>Lebanon</td>\n",
       "      <td>Beirut</td>\n",
       "      <td>Asia</td>\n",
       "      <td>5.489739e+06</td>\n",
       "      <td>5.662923e+06</td>\n",
       "      <td>6.398940e+06</td>\n",
       "      <td>4.995800e+06</td>\n",
       "      <td>4.320642e+06</td>\n",
       "      <td>3.593700e+06</td>\n",
       "      <td>2963702.0</td>\n",
       "      <td>2381791.0</td>\n",
       "      <td>10452.0</td>\n",
       "      <td>525.2334</td>\n",
       "      <td>0.9816</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>167</td>\n",
       "      <td>MAC</td>\n",
       "      <td>Macau</td>\n",
       "      <td>Concelho de Macau</td>\n",
       "      <td>Asia</td>\n",
       "      <td>6.951680e+05</td>\n",
       "      <td>6.762830e+05</td>\n",
       "      <td>6.152390e+05</td>\n",
       "      <td>5.572970e+05</td>\n",
       "      <td>4.318960e+05</td>\n",
       "      <td>3.502270e+05</td>\n",
       "      <td>245332.0</td>\n",
       "      <td>247284.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>23172.2667</td>\n",
       "      <td>1.0125</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>45</td>\n",
       "      <td>MYS</td>\n",
       "      <td>Malaysia</td>\n",
       "      <td>Kuala Lumpur</td>\n",
       "      <td>Asia</td>\n",
       "      <td>3.393822e+07</td>\n",
       "      <td>3.319999e+07</td>\n",
       "      <td>3.106883e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.751705e+07</td>\n",
       "      <td>13215707.0</td>\n",
       "      <td>10306508.0</td>\n",
       "      <td>330803.0</td>\n",
       "      <td>102.5934</td>\n",
       "      <td>1.0109</td>\n",
       "      <td>0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>174</td>\n",
       "      <td>MDV</td>\n",
       "      <td>Maldives</td>\n",
       "      <td>Malé</td>\n",
       "      <td>Asia</td>\n",
       "      <td>5.237870e+05</td>\n",
       "      <td>5.144380e+05</td>\n",
       "      <td>4.355820e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.249570e+05</td>\n",
       "      <td>164887.0</td>\n",
       "      <td>123243.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>1745.9567</td>\n",
       "      <td>1.0045</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>134</td>\n",
       "      <td>MNG</td>\n",
       "      <td>Mongolia</td>\n",
       "      <td>Ulaanbaatar</td>\n",
       "      <td>Asia</td>\n",
       "      <td>3.398366e+06</td>\n",
       "      <td>3.294335e+06</td>\n",
       "      <td>2.964749e+06</td>\n",
       "      <td>2.702520e+06</td>\n",
       "      <td>2.450979e+06</td>\n",
       "      <td>2.161433e+06</td>\n",
       "      <td>1697780.0</td>\n",
       "      <td>1293880.0</td>\n",
       "      <td>1564110.0</td>\n",
       "      <td>2.1727</td>\n",
       "      <td>1.0151</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>26</td>\n",
       "      <td>MMR</td>\n",
       "      <td>Myanmar</td>\n",
       "      <td>Nay Pyi Taw</td>\n",
       "      <td>Asia</td>\n",
       "      <td>5.417931e+07</td>\n",
       "      <td>5.342320e+07</td>\n",
       "      <td>5.148395e+07</td>\n",
       "      <td>4.939099e+07</td>\n",
       "      <td>4.553833e+07</td>\n",
       "      <td>4.009955e+07</td>\n",
       "      <td>33465781.0</td>\n",
       "      <td>27284112.0</td>\n",
       "      <td>676578.0</td>\n",
       "      <td>80.0784</td>\n",
       "      <td>1.0071</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>49</td>\n",
       "      <td>NPL</td>\n",
       "      <td>Nepal</td>\n",
       "      <td>Kathmandu</td>\n",
       "      <td>Asia</td>\n",
       "      <td>3.054758e+07</td>\n",
       "      <td>2.934863e+07</td>\n",
       "      <td>2.761032e+07</td>\n",
       "      <td>2.716157e+07</td>\n",
       "      <td>2.455950e+07</td>\n",
       "      <td>1.961653e+07</td>\n",
       "      <td>15600442.0</td>\n",
       "      <td>12501285.0</td>\n",
       "      <td>147181.0</td>\n",
       "      <td>207.5511</td>\n",
       "      <td>1.0171</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>56</td>\n",
       "      <td>PRK</td>\n",
       "      <td>North Korea</td>\n",
       "      <td>Pyongyang</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.606942e+07</td>\n",
       "      <td>2.586747e+07</td>\n",
       "      <td>2.525802e+07</td>\n",
       "      <td>2.468644e+07</td>\n",
       "      <td>2.336706e+07</td>\n",
       "      <td>2.079952e+07</td>\n",
       "      <td>17973650.0</td>\n",
       "      <td>14996879.0</td>\n",
       "      <td>120538.0</td>\n",
       "      <td>216.2755</td>\n",
       "      <td>1.0038</td>\n",
       "      <td>0.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>127</td>\n",
       "      <td>OMN</td>\n",
       "      <td>Oman</td>\n",
       "      <td>Muscat</td>\n",
       "      <td>Asia</td>\n",
       "      <td>4.576298e+06</td>\n",
       "      <td>4.543399e+06</td>\n",
       "      <td>4.191776e+06</td>\n",
       "      <td>2.881914e+06</td>\n",
       "      <td>2.344253e+06</td>\n",
       "      <td>1.804524e+06</td>\n",
       "      <td>1017462.0</td>\n",
       "      <td>670693.0</td>\n",
       "      <td>309500.0</td>\n",
       "      <td>14.7861</td>\n",
       "      <td>1.0123</td>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>5</td>\n",
       "      <td>PAK</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>Islamabad</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.358249e+08</td>\n",
       "      <td>2.271967e+08</td>\n",
       "      <td>2.109693e+08</td>\n",
       "      <td>1.944545e+08</td>\n",
       "      <td>1.543699e+08</td>\n",
       "      <td>1.154141e+08</td>\n",
       "      <td>80624057.0</td>\n",
       "      <td>59290872.0</td>\n",
       "      <td>881912.0</td>\n",
       "      <td>267.4018</td>\n",
       "      <td>1.0191</td>\n",
       "      <td>2.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>122</td>\n",
       "      <td>PSE</td>\n",
       "      <td>Palestine</td>\n",
       "      <td>Ramallah</td>\n",
       "      <td>Asia</td>\n",
       "      <td>5.250072e+06</td>\n",
       "      <td>5.019401e+06</td>\n",
       "      <td>4.484614e+06</td>\n",
       "      <td>3.992278e+06</td>\n",
       "      <td>3.139954e+06</td>\n",
       "      <td>2.124609e+06</td>\n",
       "      <td>1453620.0</td>\n",
       "      <td>1118241.0</td>\n",
       "      <td>6220.0</td>\n",
       "      <td>844.0630</td>\n",
       "      <td>1.0227</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>13</td>\n",
       "      <td>PHL</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>Manila</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1.155590e+08</td>\n",
       "      <td>1.121910e+08</td>\n",
       "      <td>1.030314e+08</td>\n",
       "      <td>9.463670e+07</td>\n",
       "      <td>7.795822e+07</td>\n",
       "      <td>6.155890e+07</td>\n",
       "      <td>48419546.0</td>\n",
       "      <td>37435586.0</td>\n",
       "      <td>342353.0</td>\n",
       "      <td>337.5434</td>\n",
       "      <td>1.0147</td>\n",
       "      <td>1.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>143</td>\n",
       "      <td>QAT</td>\n",
       "      <td>Qatar</td>\n",
       "      <td>Doha</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.695122e+06</td>\n",
       "      <td>2.760385e+06</td>\n",
       "      <td>2.414573e+06</td>\n",
       "      <td>1.713504e+06</td>\n",
       "      <td>6.459370e+05</td>\n",
       "      <td>4.416750e+05</td>\n",
       "      <td>277450.0</td>\n",
       "      <td>118007.0</td>\n",
       "      <td>11586.0</td>\n",
       "      <td>232.6189</td>\n",
       "      <td>1.0026</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>41</td>\n",
       "      <td>SAU</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>Riyadh</td>\n",
       "      <td>Asia</td>\n",
       "      <td>3.640882e+07</td>\n",
       "      <td>3.599711e+07</td>\n",
       "      <td>3.274985e+07</td>\n",
       "      <td>2.941193e+07</td>\n",
       "      <td>2.154739e+07</td>\n",
       "      <td>1.600476e+07</td>\n",
       "      <td>10171710.0</td>\n",
       "      <td>6106191.0</td>\n",
       "      <td>2149690.0</td>\n",
       "      <td>16.9368</td>\n",
       "      <td>1.0128</td>\n",
       "      <td>0.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>113</td>\n",
       "      <td>SGP</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>Asia</td>\n",
       "      <td>5.975689e+06</td>\n",
       "      <td>5.909869e+06</td>\n",
       "      <td>5.650018e+06</td>\n",
       "      <td>5.163590e+06</td>\n",
       "      <td>4.053602e+06</td>\n",
       "      <td>3.022209e+06</td>\n",
       "      <td>2400729.0</td>\n",
       "      <td>2061831.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>8416.4634</td>\n",
       "      <td>1.0058</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>29</td>\n",
       "      <td>KOR</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Seoul</td>\n",
       "      <td>Asia</td>\n",
       "      <td>5.181581e+07</td>\n",
       "      <td>5.184469e+07</td>\n",
       "      <td>5.099440e+07</td>\n",
       "      <td>4.881304e+07</td>\n",
       "      <td>4.678859e+07</td>\n",
       "      <td>4.412004e+07</td>\n",
       "      <td>38170501.0</td>\n",
       "      <td>32601143.0</td>\n",
       "      <td>100210.0</td>\n",
       "      <td>517.0722</td>\n",
       "      <td>0.9997</td>\n",
       "      <td>0.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>61</td>\n",
       "      <td>LKA</td>\n",
       "      <td>Sri Lanka</td>\n",
       "      <td>Colombo</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.183214e+07</td>\n",
       "      <td>2.171508e+07</td>\n",
       "      <td>2.133670e+07</td>\n",
       "      <td>2.066856e+07</td>\n",
       "      <td>1.877637e+07</td>\n",
       "      <td>1.720409e+07</td>\n",
       "      <td>14943645.0</td>\n",
       "      <td>12388769.0</td>\n",
       "      <td>65610.0</td>\n",
       "      <td>332.7563</td>\n",
       "      <td>1.0027</td>\n",
       "      <td>0.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>60</td>\n",
       "      <td>SYR</td>\n",
       "      <td>Syria</td>\n",
       "      <td>Damascus</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.212525e+07</td>\n",
       "      <td>2.077260e+07</td>\n",
       "      <td>1.920518e+07</td>\n",
       "      <td>2.233756e+07</td>\n",
       "      <td>1.630765e+07</td>\n",
       "      <td>1.240900e+07</td>\n",
       "      <td>8898954.0</td>\n",
       "      <td>6319199.0</td>\n",
       "      <td>185180.0</td>\n",
       "      <td>119.4797</td>\n",
       "      <td>1.0376</td>\n",
       "      <td>0.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>57</td>\n",
       "      <td>TWN</td>\n",
       "      <td>Taiwan</td>\n",
       "      <td>Taipei</td>\n",
       "      <td>Asia</td>\n",
       "      <td>2.389339e+07</td>\n",
       "      <td>2.382146e+07</td>\n",
       "      <td>2.351214e+07</td>\n",
       "      <td>2.308308e+07</td>\n",
       "      <td>2.219473e+07</td>\n",
       "      <td>2.058617e+07</td>\n",
       "      <td>18100281.0</td>\n",
       "      <td>14957870.0</td>\n",
       "      <td>36193.0</td>\n",
       "      <td>660.1662</td>\n",
       "      <td>1.0014</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>95</td>\n",
       "      <td>TJK</td>\n",
       "      <td>Tajikistan</td>\n",
       "      <td>Dushanbe</td>\n",
       "      <td>Asia</td>\n",
       "      <td>9.952787e+06</td>\n",
       "      <td>9.543207e+06</td>\n",
       "      <td>8.524063e+06</td>\n",
       "      <td>7.621779e+06</td>\n",
       "      <td>6.272998e+06</td>\n",
       "      <td>5.417860e+06</td>\n",
       "      <td>4045965.0</td>\n",
       "      <td>2993019.0</td>\n",
       "      <td>143100.0</td>\n",
       "      <td>69.5513</td>\n",
       "      <td>1.0208</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>20</td>\n",
       "      <td>THA</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>Bangkok</td>\n",
       "      <td>Asia</td>\n",
       "      <td>7.169703e+07</td>\n",
       "      <td>7.147566e+07</td>\n",
       "      <td>7.029440e+07</td>\n",
       "      <td>6.827049e+07</td>\n",
       "      <td>6.306660e+07</td>\n",
       "      <td>5.522841e+07</td>\n",
       "      <td>45737753.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>513120.0</td>\n",
       "      <td>139.7276</td>\n",
       "      <td>1.0013</td>\n",
       "      <td>0.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>155</td>\n",
       "      <td>TLS</td>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>Dili</td>\n",
       "      <td>Asia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.299995e+06</td>\n",
       "      <td>1.205813e+06</td>\n",
       "      <td>1.088486e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.581060e+05</td>\n",
       "      <td>642224.0</td>\n",
       "      <td>554021.0</td>\n",
       "      <td>14874.0</td>\n",
       "      <td>90.1772</td>\n",
       "      <td>1.0154</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>18</td>\n",
       "      <td>TUR</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>Ankara</td>\n",
       "      <td>Asia</td>\n",
       "      <td>8.534124e+07</td>\n",
       "      <td>8.413543e+07</td>\n",
       "      <td>7.964618e+07</td>\n",
       "      <td>7.319534e+07</td>\n",
       "      <td>6.411355e+07</td>\n",
       "      <td>5.432414e+07</td>\n",
       "      <td>44089069.0</td>\n",
       "      <td>35540990.0</td>\n",
       "      <td>783562.0</td>\n",
       "      <td>108.9145</td>\n",
       "      <td>1.0067</td>\n",
       "      <td>1.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>111</td>\n",
       "      <td>TKM</td>\n",
       "      <td>Turkmenistan</td>\n",
       "      <td>Ashgabat</td>\n",
       "      <td>Asia</td>\n",
       "      <td>6.430770e+06</td>\n",
       "      <td>6.250438e+06</td>\n",
       "      <td>5.766431e+06</td>\n",
       "      <td>5.267970e+06</td>\n",
       "      <td>4.569132e+06</td>\n",
       "      <td>3.720278e+06</td>\n",
       "      <td>2862903.0</td>\n",
       "      <td>2201432.0</td>\n",
       "      <td>488100.0</td>\n",
       "      <td>13.1751</td>\n",
       "      <td>1.0140</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>97</td>\n",
       "      <td>ARE</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>Asia</td>\n",
       "      <td>9.441129e+06</td>\n",
       "      <td>9.287289e+06</td>\n",
       "      <td>8.916899e+06</td>\n",
       "      <td>8.481771e+06</td>\n",
       "      <td>3.275333e+06</td>\n",
       "      <td>1.900151e+06</td>\n",
       "      <td>1014048.0</td>\n",
       "      <td>298084.0</td>\n",
       "      <td>83600.0</td>\n",
       "      <td>112.9322</td>\n",
       "      <td>1.0081</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>43</td>\n",
       "      <td>UZB</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>Tashkent</td>\n",
       "      <td>Asia</td>\n",
       "      <td>3.462765e+07</td>\n",
       "      <td>3.352666e+07</td>\n",
       "      <td>3.094942e+07</td>\n",
       "      <td>2.861423e+07</td>\n",
       "      <td>2.492555e+07</td>\n",
       "      <td>2.057910e+07</td>\n",
       "      <td>15947129.0</td>\n",
       "      <td>12011361.0</td>\n",
       "      <td>447400.0</td>\n",
       "      <td>77.3975</td>\n",
       "      <td>1.0160</td>\n",
       "      <td>0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>16</td>\n",
       "      <td>VNM</td>\n",
       "      <td>Vietnam</td>\n",
       "      <td>Hanoi</td>\n",
       "      <td>Asia</td>\n",
       "      <td>9.818686e+07</td>\n",
       "      <td>9.664868e+07</td>\n",
       "      <td>9.219140e+07</td>\n",
       "      <td>8.741101e+07</td>\n",
       "      <td>7.900114e+07</td>\n",
       "      <td>6.691261e+07</td>\n",
       "      <td>52968270.0</td>\n",
       "      <td>41928849.0</td>\n",
       "      <td>331212.0</td>\n",
       "      <td>296.4472</td>\n",
       "      <td>1.0074</td>\n",
       "      <td>1.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>46</td>\n",
       "      <td>YEM</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>Sanaa</td>\n",
       "      <td>Asia</td>\n",
       "      <td>3.369661e+07</td>\n",
       "      <td>3.228405e+07</td>\n",
       "      <td>2.851654e+07</td>\n",
       "      <td>2.474395e+07</td>\n",
       "      <td>1.862870e+07</td>\n",
       "      <td>1.337512e+07</td>\n",
       "      <td>9204938.0</td>\n",
       "      <td>6843607.0</td>\n",
       "      <td>527968.0</td>\n",
       "      <td>63.8232</td>\n",
       "      <td>1.0217</td>\n",
       "      <td>0.42</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Rank CCA3               Country              Capital Continent  \\\n",
       "0      36  AFG           Afghanistan                Kabul      Asia   \n",
       "9     140  ARM               Armenia              Yerevan      Asia   \n",
       "13     91  AZE            Azerbaijan                 Baku      Asia   \n",
       "15    154  BHR               Bahrain               Manama      Asia   \n",
       "16      8  BGD            Bangladesh                Dhaka      Asia   \n",
       "23    165  BTN                Bhutan              Thimphu      Asia   \n",
       "29    175  BRN                Brunei  Bandar Seri Begawan      Asia   \n",
       "33     73  KHM              Cambodia           Phnom Penh      Asia   \n",
       "41      1  CHN                 China              Beijing      Asia   \n",
       "73    131  GEO               Georgia              Tbilisi      Asia   \n",
       "89    104  HKG             Hong Kong            Hong Kong      Asia   \n",
       "92      2  IND                 India            New Delhi      Asia   \n",
       "93      4  IDN             Indonesia              Jakarta      Asia   \n",
       "94     17  IRN                  Iran               Tehran      Asia   \n",
       "95     35  IRQ                  Iraq              Baghdad      Asia   \n",
       "98     98  ISR                Israel            Jerusalem      Asia   \n",
       "102    11  JPN                 Japan                Tokyo      Asia   \n",
       "104    83  JOR                Jordan                Amman      Asia   \n",
       "105    66  KAZ            Kazakhstan            Nursultan      Asia   \n",
       "108   129  KWT                Kuwait          Kuwait City      Asia   \n",
       "109   110  KGZ            Kyrgyzstan              Bishkek      Asia   \n",
       "110   103  LAO                  Laos            Vientiane      Asia   \n",
       "112   119  LBN               Lebanon               Beirut      Asia   \n",
       "119   167  MAC                 Macau    Concelho de Macau      Asia   \n",
       "122    45  MYS              Malaysia         Kuala Lumpur      Asia   \n",
       "123   174  MDV              Maldives                 Malé      Asia   \n",
       "135   134  MNG              Mongolia          Ulaanbaatar      Asia   \n",
       "140    26  MMR               Myanmar          Nay Pyi Taw      Asia   \n",
       "143    49  NPL                 Nepal            Kathmandu      Asia   \n",
       "151    56  PRK           North Korea            Pyongyang      Asia   \n",
       "155   127  OMN                  Oman               Muscat      Asia   \n",
       "156     5  PAK              Pakistan            Islamabad      Asia   \n",
       "158   122  PSE             Palestine             Ramallah      Asia   \n",
       "163    13  PHL           Philippines               Manila      Asia   \n",
       "167   143  QAT                 Qatar                 Doha      Asia   \n",
       "182    41  SAU          Saudi Arabia               Riyadh      Asia   \n",
       "187   113  SGP             Singapore            Singapore      Asia   \n",
       "194    29  KOR           South Korea                Seoul      Asia   \n",
       "197    61  LKA             Sri Lanka              Colombo      Asia   \n",
       "202    60  SYR                 Syria             Damascus      Asia   \n",
       "203    57  TWN                Taiwan               Taipei      Asia   \n",
       "204    95  TJK            Tajikistan             Dushanbe      Asia   \n",
       "206    20  THA              Thailand              Bangkok      Asia   \n",
       "207   155  TLS           Timor-Leste                 Dili      Asia   \n",
       "213    18  TUR                Turkey               Ankara      Asia   \n",
       "214   111  TKM          Turkmenistan             Ashgabat      Asia   \n",
       "219    97  ARE  United Arab Emirates            Abu Dhabi      Asia   \n",
       "224    43  UZB            Uzbekistan             Tashkent      Asia   \n",
       "228    16  VNM               Vietnam                Hanoi      Asia   \n",
       "231    46  YEM                 Yemen                Sanaa      Asia   \n",
       "\n",
       "     2022 Population  2020 Population  2015 Population  2010 Population  \\\n",
       "0       4.112877e+07     3.897223e+07     3.375350e+07     2.818967e+07   \n",
       "9       2.780469e+06     2.805608e+06     2.878595e+06     2.946293e+06   \n",
       "13      1.035807e+07              NaN     9.863480e+06     9.237202e+06   \n",
       "15      1.472233e+06     1.477469e+06     1.362142e+06     1.213645e+06   \n",
       "16      1.711864e+08     1.674210e+08     1.578300e+08     1.483911e+08   \n",
       "23      7.824550e+05     7.725060e+05     7.432740e+05     7.055160e+05   \n",
       "29      4.490020e+05     4.417250e+05     4.214370e+05     3.960530e+05   \n",
       "33      1.676784e+07     1.639686e+07     1.541752e+07     1.436353e+07   \n",
       "41      1.425887e+09     1.424930e+09     1.393715e+09     1.348191e+09   \n",
       "73      3.744385e+06     3.765912e+06     3.771132e+06              NaN   \n",
       "89      7.488865e+06     7.500958e+06     7.399838e+06     7.132438e+06   \n",
       "92      1.417173e+09     1.396387e+09     1.322867e+09     1.240614e+09   \n",
       "93      2.755013e+08     2.718580e+08     2.590920e+08     2.440162e+08   \n",
       "94      8.855057e+07     8.729019e+07     8.179084e+07     7.537386e+07   \n",
       "95      4.449612e+07     4.255698e+07     3.775781e+07     3.126488e+07   \n",
       "98      9.038309e+06     8.757489e+06     8.007778e+06     7.328445e+06   \n",
       "102     1.239517e+08     1.252448e+08     1.272509e+08     1.281054e+08   \n",
       "104     1.128587e+07     1.092872e+07     9.494246e+06     6.931258e+06   \n",
       "105     1.939800e+07     1.897924e+07     1.783591e+07     1.662784e+07   \n",
       "108     4.268873e+06     4.360444e+06     3.908743e+06     2.943356e+06   \n",
       "109     6.630623e+06     6.424874e+06     5.914980e+06     5.483774e+06   \n",
       "110     7.529475e+06     7.319399e+06     6.787419e+06     6.323418e+06   \n",
       "112     5.489739e+06     5.662923e+06     6.398940e+06     4.995800e+06   \n",
       "119     6.951680e+05     6.762830e+05     6.152390e+05     5.572970e+05   \n",
       "122     3.393822e+07     3.319999e+07     3.106883e+07              NaN   \n",
       "123     5.237870e+05     5.144380e+05     4.355820e+05              NaN   \n",
       "135     3.398366e+06     3.294335e+06     2.964749e+06     2.702520e+06   \n",
       "140     5.417931e+07     5.342320e+07     5.148395e+07     4.939099e+07   \n",
       "143     3.054758e+07     2.934863e+07     2.761032e+07     2.716157e+07   \n",
       "151     2.606942e+07     2.586747e+07     2.525802e+07     2.468644e+07   \n",
       "155     4.576298e+06     4.543399e+06     4.191776e+06     2.881914e+06   \n",
       "156     2.358249e+08     2.271967e+08     2.109693e+08     1.944545e+08   \n",
       "158     5.250072e+06     5.019401e+06     4.484614e+06     3.992278e+06   \n",
       "163     1.155590e+08     1.121910e+08     1.030314e+08     9.463670e+07   \n",
       "167     2.695122e+06     2.760385e+06     2.414573e+06     1.713504e+06   \n",
       "182     3.640882e+07     3.599711e+07     3.274985e+07     2.941193e+07   \n",
       "187     5.975689e+06     5.909869e+06     5.650018e+06     5.163590e+06   \n",
       "194     5.181581e+07     5.184469e+07     5.099440e+07     4.881304e+07   \n",
       "197     2.183214e+07     2.171508e+07     2.133670e+07     2.066856e+07   \n",
       "202     2.212525e+07     2.077260e+07     1.920518e+07     2.233756e+07   \n",
       "203     2.389339e+07     2.382146e+07     2.351214e+07     2.308308e+07   \n",
       "204     9.952787e+06     9.543207e+06     8.524063e+06     7.621779e+06   \n",
       "206     7.169703e+07     7.147566e+07     7.029440e+07     6.827049e+07   \n",
       "207              NaN     1.299995e+06     1.205813e+06     1.088486e+06   \n",
       "213     8.534124e+07     8.413543e+07     7.964618e+07     7.319534e+07   \n",
       "214     6.430770e+06     6.250438e+06     5.766431e+06     5.267970e+06   \n",
       "219     9.441129e+06     9.287289e+06     8.916899e+06     8.481771e+06   \n",
       "224     3.462765e+07     3.352666e+07     3.094942e+07     2.861423e+07   \n",
       "228     9.818686e+07     9.664868e+07     9.219140e+07     8.741101e+07   \n",
       "231     3.369661e+07     3.228405e+07     2.851654e+07     2.474395e+07   \n",
       "\n",
       "     2000 Population  1990 Population  1980 Population  1970 Population  \\\n",
       "0       1.954298e+07     1.069480e+07       12486631.0       10752971.0   \n",
       "9       3.168523e+06     3.556539e+06        3135123.0        2534377.0   \n",
       "13      8.190337e+06     7.427836e+06        6383060.0        5425317.0   \n",
       "15      7.114420e+05     5.174180e+05         362595.0         222555.0   \n",
       "16      1.291933e+08     1.071477e+08       83929765.0       67541860.0   \n",
       "23      5.872070e+05     5.584420e+05         415257.0         298894.0   \n",
       "29      3.339260e+05     2.619280e+05         187921.0         133343.0   \n",
       "33      1.211884e+07     8.910808e+06        6198959.0        6708525.0   \n",
       "41      1.264099e+09     1.153704e+09      982372466.0      822534450.0   \n",
       "73               NaN              NaN              NaN              NaN   \n",
       "89      6.731195e+06     5.838574e+06        4978544.0        3955072.0   \n",
       "92      1.059634e+09              NaN              NaN      557501301.0   \n",
       "93      2.140724e+08     1.821599e+08      148177096.0      115228394.0   \n",
       "94      6.554438e+07     5.579363e+07       38520664.0       28449705.0   \n",
       "95      2.462886e+07     1.765838e+07       13653369.0        9811347.0   \n",
       "98      6.116958e+06     4.803254e+06        3744608.0        2907307.0   \n",
       "102     1.268039e+08     1.236863e+08      117624196.0      105416839.0   \n",
       "104     5.056174e+06     3.480587e+06        2216903.0        1557374.0   \n",
       "105     1.523625e+07     1.686656e+07       14172710.0       12265305.0   \n",
       "108     1.934901e+06     1.674938e+06        1493870.0         802786.0   \n",
       "109     4.935182e+06     4.394734e+06        3691209.0        3016384.0   \n",
       "110     5.430853e+06     4.314443e+06        3297519.0        2675283.0   \n",
       "112     4.320642e+06     3.593700e+06        2963702.0        2381791.0   \n",
       "119     4.318960e+05     3.502270e+05         245332.0         247284.0   \n",
       "122              NaN     1.751705e+07       13215707.0       10306508.0   \n",
       "123              NaN     2.249570e+05         164887.0         123243.0   \n",
       "135     2.450979e+06     2.161433e+06        1697780.0        1293880.0   \n",
       "140     4.553833e+07     4.009955e+07       33465781.0       27284112.0   \n",
       "143     2.455950e+07     1.961653e+07       15600442.0       12501285.0   \n",
       "151     2.336706e+07     2.079952e+07       17973650.0       14996879.0   \n",
       "155     2.344253e+06     1.804524e+06        1017462.0         670693.0   \n",
       "156     1.543699e+08     1.154141e+08       80624057.0       59290872.0   \n",
       "158     3.139954e+06     2.124609e+06        1453620.0        1118241.0   \n",
       "163     7.795822e+07     6.155890e+07       48419546.0       37435586.0   \n",
       "167     6.459370e+05     4.416750e+05         277450.0         118007.0   \n",
       "182     2.154739e+07     1.600476e+07       10171710.0        6106191.0   \n",
       "187     4.053602e+06     3.022209e+06        2400729.0        2061831.0   \n",
       "194     4.678859e+07     4.412004e+07       38170501.0       32601143.0   \n",
       "197     1.877637e+07     1.720409e+07       14943645.0       12388769.0   \n",
       "202     1.630765e+07     1.240900e+07        8898954.0        6319199.0   \n",
       "203     2.219473e+07     2.058617e+07       18100281.0       14957870.0   \n",
       "204     6.272998e+06     5.417860e+06        4045965.0        2993019.0   \n",
       "206     6.306660e+07     5.522841e+07       45737753.0              NaN   \n",
       "207              NaN     7.581060e+05         642224.0         554021.0   \n",
       "213     6.411355e+07     5.432414e+07       44089069.0       35540990.0   \n",
       "214     4.569132e+06     3.720278e+06        2862903.0        2201432.0   \n",
       "219     3.275333e+06     1.900151e+06        1014048.0         298084.0   \n",
       "224     2.492555e+07     2.057910e+07       15947129.0       12011361.0   \n",
       "228     7.900114e+07     6.691261e+07       52968270.0       41928849.0   \n",
       "231     1.862870e+07     1.337512e+07        9204938.0        6843607.0   \n",
       "\n",
       "     Area (km²)  Density (per km²)  Growth Rate  World Population Percentage  \n",
       "0      652230.0            63.0587       1.0257                         0.52  \n",
       "9       29743.0            93.4831       0.9962                         0.03  \n",
       "13      86600.0           119.6082       1.0044                         0.13  \n",
       "15        765.0          1924.4876       1.0061                         0.02  \n",
       "16     147570.0          1160.0350       1.0108                         2.15  \n",
       "23      38394.0            20.3796       1.0064                         0.01  \n",
       "29       5765.0            77.8841       1.0081                         0.01  \n",
       "33     181035.0            92.6221       1.0108                         0.21  \n",
       "41    9706961.0           146.8933       1.0000                        17.88  \n",
       "73      69700.0            53.7214       0.9964                         0.05  \n",
       "89       1104.0          6783.3922       0.9992                         0.09  \n",
       "92    3287590.0           431.0675       1.0068                        17.77  \n",
       "93    1904569.0           144.6529       1.0064                         3.45  \n",
       "94    1648195.0            53.7258       1.0071                         1.11  \n",
       "95     438317.0           101.5158       1.0221                         0.56  \n",
       "98      20770.0           435.1617       1.0155                         0.11  \n",
       "102    377930.0           327.9753       0.9947                         1.55  \n",
       "104     89342.0           126.3221       1.0123                         0.14  \n",
       "105   2724900.0             7.1188       1.0105                         0.24  \n",
       "108     17818.0           239.5821       1.0044                         0.05  \n",
       "109    199951.0            33.1612       1.0158                         0.08  \n",
       "110    236800.0            31.7968       1.0141                         0.09  \n",
       "112     10452.0           525.2334       0.9816                         0.07  \n",
       "119        30.0         23172.2667       1.0125                         0.01  \n",
       "122    330803.0           102.5934       1.0109                         0.43  \n",
       "123       300.0          1745.9567       1.0045                         0.01  \n",
       "135   1564110.0             2.1727       1.0151                         0.04  \n",
       "140    676578.0            80.0784       1.0071                         0.68  \n",
       "143    147181.0           207.5511       1.0171                         0.38  \n",
       "151    120538.0           216.2755       1.0038                         0.33  \n",
       "155    309500.0            14.7861       1.0123                         0.06  \n",
       "156    881912.0           267.4018       1.0191                         2.96  \n",
       "158      6220.0           844.0630       1.0227                         0.07  \n",
       "163    342353.0           337.5434       1.0147                         1.45  \n",
       "167     11586.0           232.6189       1.0026                         0.03  \n",
       "182   2149690.0            16.9368       1.0128                         0.46  \n",
       "187       710.0          8416.4634       1.0058                         0.07  \n",
       "194    100210.0           517.0722       0.9997                         0.65  \n",
       "197     65610.0           332.7563       1.0027                         0.27  \n",
       "202    185180.0           119.4797       1.0376                         0.28  \n",
       "203     36193.0           660.1662       1.0014                         0.30  \n",
       "204    143100.0            69.5513       1.0208                         0.12  \n",
       "206    513120.0           139.7276       1.0013                         0.90  \n",
       "207     14874.0            90.1772       1.0154                         0.02  \n",
       "213    783562.0           108.9145       1.0067                         1.07  \n",
       "214    488100.0            13.1751       1.0140                         0.08  \n",
       "219     83600.0           112.9322       1.0081                         0.12  \n",
       "224    447400.0            77.3975       1.0160                         0.43  \n",
       "228    331212.0           296.4472       1.0074                         1.23  \n",
       "231    527968.0            63.8232       1.0217                         0.42  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## создадим субфрейм для стран Азии, для лучшей читабельности\n",
    "df_asia = df.loc[df['Continent'] == 'Asia'] # df[df['Continent'] == 'Asia'] - тоже подошло бы\n",
    "df_asia"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a71150c-71ea-46ae-9c5e-bfe88d1fed11",
   "metadata": {},
   "source": [
    "**Оставим только интересующие нас столбцы**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3c5f8620-686b-4c4b-97e5-9d0c84cc2aa5",
   "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>1970 Population</th>\n",
       "      <th>1980 Population</th>\n",
       "      <th>1990 Population</th>\n",
       "      <th>2000 Population</th>\n",
       "      <th>2010 Population</th>\n",
       "      <th>2015 Population</th>\n",
       "      <th>2020 Population</th>\n",
       "      <th>2022 Population</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>822534450.0</td>\n",
       "      <td>982372466.0</td>\n",
       "      <td>1.153704e+09</td>\n",
       "      <td>1.264099e+09</td>\n",
       "      <td>1.348191e+09</td>\n",
       "      <td>1.393715e+09</td>\n",
       "      <td>1.424930e+09</td>\n",
       "      <td>1.425887e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>557501301.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.059634e+09</td>\n",
       "      <td>1.240614e+09</td>\n",
       "      <td>1.322867e+09</td>\n",
       "      <td>1.396387e+09</td>\n",
       "      <td>1.417173e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>115228394.0</td>\n",
       "      <td>148177096.0</td>\n",
       "      <td>1.821599e+08</td>\n",
       "      <td>2.140724e+08</td>\n",
       "      <td>2.440162e+08</td>\n",
       "      <td>2.590920e+08</td>\n",
       "      <td>2.718580e+08</td>\n",
       "      <td>2.755013e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pakistan</th>\n",
       "      <td>59290872.0</td>\n",
       "      <td>80624057.0</td>\n",
       "      <td>1.154141e+08</td>\n",
       "      <td>1.543699e+08</td>\n",
       "      <td>1.944545e+08</td>\n",
       "      <td>2.109693e+08</td>\n",
       "      <td>2.271967e+08</td>\n",
       "      <td>2.358249e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bangladesh</th>\n",
       "      <td>67541860.0</td>\n",
       "      <td>83929765.0</td>\n",
       "      <td>1.071477e+08</td>\n",
       "      <td>1.291933e+08</td>\n",
       "      <td>1.483911e+08</td>\n",
       "      <td>1.578300e+08</td>\n",
       "      <td>1.674210e+08</td>\n",
       "      <td>1.711864e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>105416839.0</td>\n",
       "      <td>117624196.0</td>\n",
       "      <td>1.236863e+08</td>\n",
       "      <td>1.268039e+08</td>\n",
       "      <td>1.281054e+08</td>\n",
       "      <td>1.272509e+08</td>\n",
       "      <td>1.252448e+08</td>\n",
       "      <td>1.239517e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philippines</th>\n",
       "      <td>37435586.0</td>\n",
       "      <td>48419546.0</td>\n",
       "      <td>6.155890e+07</td>\n",
       "      <td>7.795822e+07</td>\n",
       "      <td>9.463670e+07</td>\n",
       "      <td>1.030314e+08</td>\n",
       "      <td>1.121910e+08</td>\n",
       "      <td>1.155590e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vietnam</th>\n",
       "      <td>41928849.0</td>\n",
       "      <td>52968270.0</td>\n",
       "      <td>6.691261e+07</td>\n",
       "      <td>7.900114e+07</td>\n",
       "      <td>8.741101e+07</td>\n",
       "      <td>9.219140e+07</td>\n",
       "      <td>9.664868e+07</td>\n",
       "      <td>9.818686e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iran</th>\n",
       "      <td>28449705.0</td>\n",
       "      <td>38520664.0</td>\n",
       "      <td>5.579363e+07</td>\n",
       "      <td>6.554438e+07</td>\n",
       "      <td>7.537386e+07</td>\n",
       "      <td>8.179084e+07</td>\n",
       "      <td>8.729019e+07</td>\n",
       "      <td>8.855057e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>35540990.0</td>\n",
       "      <td>44089069.0</td>\n",
       "      <td>5.432414e+07</td>\n",
       "      <td>6.411355e+07</td>\n",
       "      <td>7.319534e+07</td>\n",
       "      <td>7.964618e+07</td>\n",
       "      <td>8.413543e+07</td>\n",
       "      <td>8.534124e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thailand</th>\n",
       "      <td>NaN</td>\n",
       "      <td>45737753.0</td>\n",
       "      <td>5.522841e+07</td>\n",
       "      <td>6.306660e+07</td>\n",
       "      <td>6.827049e+07</td>\n",
       "      <td>7.029440e+07</td>\n",
       "      <td>7.147566e+07</td>\n",
       "      <td>7.169703e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Myanmar</th>\n",
       "      <td>27284112.0</td>\n",
       "      <td>33465781.0</td>\n",
       "      <td>4.009955e+07</td>\n",
       "      <td>4.553833e+07</td>\n",
       "      <td>4.939099e+07</td>\n",
       "      <td>5.148395e+07</td>\n",
       "      <td>5.342320e+07</td>\n",
       "      <td>5.417931e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Korea</th>\n",
       "      <td>32601143.0</td>\n",
       "      <td>38170501.0</td>\n",
       "      <td>4.412004e+07</td>\n",
       "      <td>4.678859e+07</td>\n",
       "      <td>4.881304e+07</td>\n",
       "      <td>5.099440e+07</td>\n",
       "      <td>5.184469e+07</td>\n",
       "      <td>5.181581e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iraq</th>\n",
       "      <td>9811347.0</td>\n",
       "      <td>13653369.0</td>\n",
       "      <td>1.765838e+07</td>\n",
       "      <td>2.462886e+07</td>\n",
       "      <td>3.126488e+07</td>\n",
       "      <td>3.775781e+07</td>\n",
       "      <td>4.255698e+07</td>\n",
       "      <td>4.449612e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>10752971.0</td>\n",
       "      <td>12486631.0</td>\n",
       "      <td>1.069480e+07</td>\n",
       "      <td>1.954298e+07</td>\n",
       "      <td>2.818967e+07</td>\n",
       "      <td>3.375350e+07</td>\n",
       "      <td>3.897223e+07</td>\n",
       "      <td>4.112877e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>6106191.0</td>\n",
       "      <td>10171710.0</td>\n",
       "      <td>1.600476e+07</td>\n",
       "      <td>2.154739e+07</td>\n",
       "      <td>2.941193e+07</td>\n",
       "      <td>3.274985e+07</td>\n",
       "      <td>3.599711e+07</td>\n",
       "      <td>3.640882e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uzbekistan</th>\n",
       "      <td>12011361.0</td>\n",
       "      <td>15947129.0</td>\n",
       "      <td>2.057910e+07</td>\n",
       "      <td>2.492555e+07</td>\n",
       "      <td>2.861423e+07</td>\n",
       "      <td>3.094942e+07</td>\n",
       "      <td>3.352666e+07</td>\n",
       "      <td>3.462765e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malaysia</th>\n",
       "      <td>10306508.0</td>\n",
       "      <td>13215707.0</td>\n",
       "      <td>1.751705e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.106883e+07</td>\n",
       "      <td>3.319999e+07</td>\n",
       "      <td>3.393822e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\n",
       "      <td>6843607.0</td>\n",
       "      <td>9204938.0</td>\n",
       "      <td>1.337512e+07</td>\n",
       "      <td>1.862870e+07</td>\n",
       "      <td>2.474395e+07</td>\n",
       "      <td>2.851654e+07</td>\n",
       "      <td>3.228405e+07</td>\n",
       "      <td>3.369661e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nepal</th>\n",
       "      <td>12501285.0</td>\n",
       "      <td>15600442.0</td>\n",
       "      <td>1.961653e+07</td>\n",
       "      <td>2.455950e+07</td>\n",
       "      <td>2.716157e+07</td>\n",
       "      <td>2.761032e+07</td>\n",
       "      <td>2.934863e+07</td>\n",
       "      <td>3.054758e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Korea</th>\n",
       "      <td>14996879.0</td>\n",
       "      <td>17973650.0</td>\n",
       "      <td>2.079952e+07</td>\n",
       "      <td>2.336706e+07</td>\n",
       "      <td>2.468644e+07</td>\n",
       "      <td>2.525802e+07</td>\n",
       "      <td>2.586747e+07</td>\n",
       "      <td>2.606942e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan</th>\n",
       "      <td>14957870.0</td>\n",
       "      <td>18100281.0</td>\n",
       "      <td>2.058617e+07</td>\n",
       "      <td>2.219473e+07</td>\n",
       "      <td>2.308308e+07</td>\n",
       "      <td>2.351214e+07</td>\n",
       "      <td>2.382146e+07</td>\n",
       "      <td>2.389339e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Syria</th>\n",
       "      <td>6319199.0</td>\n",
       "      <td>8898954.0</td>\n",
       "      <td>1.240900e+07</td>\n",
       "      <td>1.630765e+07</td>\n",
       "      <td>2.233756e+07</td>\n",
       "      <td>1.920518e+07</td>\n",
       "      <td>2.077260e+07</td>\n",
       "      <td>2.212525e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sri Lanka</th>\n",
       "      <td>12388769.0</td>\n",
       "      <td>14943645.0</td>\n",
       "      <td>1.720409e+07</td>\n",
       "      <td>1.877637e+07</td>\n",
       "      <td>2.066856e+07</td>\n",
       "      <td>2.133670e+07</td>\n",
       "      <td>2.171508e+07</td>\n",
       "      <td>2.183214e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kazakhstan</th>\n",
       "      <td>12265305.0</td>\n",
       "      <td>14172710.0</td>\n",
       "      <td>1.686656e+07</td>\n",
       "      <td>1.523625e+07</td>\n",
       "      <td>1.662784e+07</td>\n",
       "      <td>1.783591e+07</td>\n",
       "      <td>1.897924e+07</td>\n",
       "      <td>1.939800e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cambodia</th>\n",
       "      <td>6708525.0</td>\n",
       "      <td>6198959.0</td>\n",
       "      <td>8.910808e+06</td>\n",
       "      <td>1.211884e+07</td>\n",
       "      <td>1.436353e+07</td>\n",
       "      <td>1.541752e+07</td>\n",
       "      <td>1.639686e+07</td>\n",
       "      <td>1.676784e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jordan</th>\n",
       "      <td>1557374.0</td>\n",
       "      <td>2216903.0</td>\n",
       "      <td>3.480587e+06</td>\n",
       "      <td>5.056174e+06</td>\n",
       "      <td>6.931258e+06</td>\n",
       "      <td>9.494246e+06</td>\n",
       "      <td>1.092872e+07</td>\n",
       "      <td>1.128587e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Azerbaijan</th>\n",
       "      <td>5425317.0</td>\n",
       "      <td>6383060.0</td>\n",
       "      <td>7.427836e+06</td>\n",
       "      <td>8.190337e+06</td>\n",
       "      <td>9.237202e+06</td>\n",
       "      <td>9.863480e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.035807e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tajikistan</th>\n",
       "      <td>2993019.0</td>\n",
       "      <td>4045965.0</td>\n",
       "      <td>5.417860e+06</td>\n",
       "      <td>6.272998e+06</td>\n",
       "      <td>7.621779e+06</td>\n",
       "      <td>8.524063e+06</td>\n",
       "      <td>9.543207e+06</td>\n",
       "      <td>9.952787e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Arab Emirates</th>\n",
       "      <td>298084.0</td>\n",
       "      <td>1014048.0</td>\n",
       "      <td>1.900151e+06</td>\n",
       "      <td>3.275333e+06</td>\n",
       "      <td>8.481771e+06</td>\n",
       "      <td>8.916899e+06</td>\n",
       "      <td>9.287289e+06</td>\n",
       "      <td>9.441129e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>2907307.0</td>\n",
       "      <td>3744608.0</td>\n",
       "      <td>4.803254e+06</td>\n",
       "      <td>6.116958e+06</td>\n",
       "      <td>7.328445e+06</td>\n",
       "      <td>8.007778e+06</td>\n",
       "      <td>8.757489e+06</td>\n",
       "      <td>9.038309e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Laos</th>\n",
       "      <td>2675283.0</td>\n",
       "      <td>3297519.0</td>\n",
       "      <td>4.314443e+06</td>\n",
       "      <td>5.430853e+06</td>\n",
       "      <td>6.323418e+06</td>\n",
       "      <td>6.787419e+06</td>\n",
       "      <td>7.319399e+06</td>\n",
       "      <td>7.529475e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hong Kong</th>\n",
       "      <td>3955072.0</td>\n",
       "      <td>4978544.0</td>\n",
       "      <td>5.838574e+06</td>\n",
       "      <td>6.731195e+06</td>\n",
       "      <td>7.132438e+06</td>\n",
       "      <td>7.399838e+06</td>\n",
       "      <td>7.500958e+06</td>\n",
       "      <td>7.488865e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kyrgyzstan</th>\n",
       "      <td>3016384.0</td>\n",
       "      <td>3691209.0</td>\n",
       "      <td>4.394734e+06</td>\n",
       "      <td>4.935182e+06</td>\n",
       "      <td>5.483774e+06</td>\n",
       "      <td>5.914980e+06</td>\n",
       "      <td>6.424874e+06</td>\n",
       "      <td>6.630623e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkmenistan</th>\n",
       "      <td>2201432.0</td>\n",
       "      <td>2862903.0</td>\n",
       "      <td>3.720278e+06</td>\n",
       "      <td>4.569132e+06</td>\n",
       "      <td>5.267970e+06</td>\n",
       "      <td>5.766431e+06</td>\n",
       "      <td>6.250438e+06</td>\n",
       "      <td>6.430770e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <td>2061831.0</td>\n",
       "      <td>2400729.0</td>\n",
       "      <td>3.022209e+06</td>\n",
       "      <td>4.053602e+06</td>\n",
       "      <td>5.163590e+06</td>\n",
       "      <td>5.650018e+06</td>\n",
       "      <td>5.909869e+06</td>\n",
       "      <td>5.975689e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lebanon</th>\n",
       "      <td>2381791.0</td>\n",
       "      <td>2963702.0</td>\n",
       "      <td>3.593700e+06</td>\n",
       "      <td>4.320642e+06</td>\n",
       "      <td>4.995800e+06</td>\n",
       "      <td>6.398940e+06</td>\n",
       "      <td>5.662923e+06</td>\n",
       "      <td>5.489739e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Palestine</th>\n",
       "      <td>1118241.0</td>\n",
       "      <td>1453620.0</td>\n",
       "      <td>2.124609e+06</td>\n",
       "      <td>3.139954e+06</td>\n",
       "      <td>3.992278e+06</td>\n",
       "      <td>4.484614e+06</td>\n",
       "      <td>5.019401e+06</td>\n",
       "      <td>5.250072e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oman</th>\n",
       "      <td>670693.0</td>\n",
       "      <td>1017462.0</td>\n",
       "      <td>1.804524e+06</td>\n",
       "      <td>2.344253e+06</td>\n",
       "      <td>2.881914e+06</td>\n",
       "      <td>4.191776e+06</td>\n",
       "      <td>4.543399e+06</td>\n",
       "      <td>4.576298e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kuwait</th>\n",
       "      <td>802786.0</td>\n",
       "      <td>1493870.0</td>\n",
       "      <td>1.674938e+06</td>\n",
       "      <td>1.934901e+06</td>\n",
       "      <td>2.943356e+06</td>\n",
       "      <td>3.908743e+06</td>\n",
       "      <td>4.360444e+06</td>\n",
       "      <td>4.268873e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.771132e+06</td>\n",
       "      <td>3.765912e+06</td>\n",
       "      <td>3.744385e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mongolia</th>\n",
       "      <td>1293880.0</td>\n",
       "      <td>1697780.0</td>\n",
       "      <td>2.161433e+06</td>\n",
       "      <td>2.450979e+06</td>\n",
       "      <td>2.702520e+06</td>\n",
       "      <td>2.964749e+06</td>\n",
       "      <td>3.294335e+06</td>\n",
       "      <td>3.398366e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Armenia</th>\n",
       "      <td>2534377.0</td>\n",
       "      <td>3135123.0</td>\n",
       "      <td>3.556539e+06</td>\n",
       "      <td>3.168523e+06</td>\n",
       "      <td>2.946293e+06</td>\n",
       "      <td>2.878595e+06</td>\n",
       "      <td>2.805608e+06</td>\n",
       "      <td>2.780469e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Qatar</th>\n",
       "      <td>118007.0</td>\n",
       "      <td>277450.0</td>\n",
       "      <td>4.416750e+05</td>\n",
       "      <td>6.459370e+05</td>\n",
       "      <td>1.713504e+06</td>\n",
       "      <td>2.414573e+06</td>\n",
       "      <td>2.760385e+06</td>\n",
       "      <td>2.695122e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bahrain</th>\n",
       "      <td>222555.0</td>\n",
       "      <td>362595.0</td>\n",
       "      <td>5.174180e+05</td>\n",
       "      <td>7.114420e+05</td>\n",
       "      <td>1.213645e+06</td>\n",
       "      <td>1.362142e+06</td>\n",
       "      <td>1.477469e+06</td>\n",
       "      <td>1.472233e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bhutan</th>\n",
       "      <td>298894.0</td>\n",
       "      <td>415257.0</td>\n",
       "      <td>5.584420e+05</td>\n",
       "      <td>5.872070e+05</td>\n",
       "      <td>7.055160e+05</td>\n",
       "      <td>7.432740e+05</td>\n",
       "      <td>7.725060e+05</td>\n",
       "      <td>7.824550e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macau</th>\n",
       "      <td>247284.0</td>\n",
       "      <td>245332.0</td>\n",
       "      <td>3.502270e+05</td>\n",
       "      <td>4.318960e+05</td>\n",
       "      <td>5.572970e+05</td>\n",
       "      <td>6.152390e+05</td>\n",
       "      <td>6.762830e+05</td>\n",
       "      <td>6.951680e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maldives</th>\n",
       "      <td>123243.0</td>\n",
       "      <td>164887.0</td>\n",
       "      <td>2.249570e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.355820e+05</td>\n",
       "      <td>5.144380e+05</td>\n",
       "      <td>5.237870e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brunei</th>\n",
       "      <td>133343.0</td>\n",
       "      <td>187921.0</td>\n",
       "      <td>2.619280e+05</td>\n",
       "      <td>3.339260e+05</td>\n",
       "      <td>3.960530e+05</td>\n",
       "      <td>4.214370e+05</td>\n",
       "      <td>4.417250e+05</td>\n",
       "      <td>4.490020e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timor-Leste</th>\n",
       "      <td>554021.0</td>\n",
       "      <td>642224.0</td>\n",
       "      <td>7.581060e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.088486e+06</td>\n",
       "      <td>1.205813e+06</td>\n",
       "      <td>1.299995e+06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      1970 Population  1980 Population  1990 Population  \\\n",
       "Country                                                                   \n",
       "China                     822534450.0      982372466.0     1.153704e+09   \n",
       "India                     557501301.0              NaN              NaN   \n",
       "Indonesia                 115228394.0      148177096.0     1.821599e+08   \n",
       "Pakistan                   59290872.0       80624057.0     1.154141e+08   \n",
       "Bangladesh                 67541860.0       83929765.0     1.071477e+08   \n",
       "Japan                     105416839.0      117624196.0     1.236863e+08   \n",
       "Philippines                37435586.0       48419546.0     6.155890e+07   \n",
       "Vietnam                    41928849.0       52968270.0     6.691261e+07   \n",
       "Iran                       28449705.0       38520664.0     5.579363e+07   \n",
       "Turkey                     35540990.0       44089069.0     5.432414e+07   \n",
       "Thailand                          NaN       45737753.0     5.522841e+07   \n",
       "Myanmar                    27284112.0       33465781.0     4.009955e+07   \n",
       "South Korea                32601143.0       38170501.0     4.412004e+07   \n",
       "Iraq                        9811347.0       13653369.0     1.765838e+07   \n",
       "Afghanistan                10752971.0       12486631.0     1.069480e+07   \n",
       "Saudi Arabia                6106191.0       10171710.0     1.600476e+07   \n",
       "Uzbekistan                 12011361.0       15947129.0     2.057910e+07   \n",
       "Malaysia                   10306508.0       13215707.0     1.751705e+07   \n",
       "Yemen                       6843607.0        9204938.0     1.337512e+07   \n",
       "Nepal                      12501285.0       15600442.0     1.961653e+07   \n",
       "North Korea                14996879.0       17973650.0     2.079952e+07   \n",
       "Taiwan                     14957870.0       18100281.0     2.058617e+07   \n",
       "Syria                       6319199.0        8898954.0     1.240900e+07   \n",
       "Sri Lanka                  12388769.0       14943645.0     1.720409e+07   \n",
       "Kazakhstan                 12265305.0       14172710.0     1.686656e+07   \n",
       "Cambodia                    6708525.0        6198959.0     8.910808e+06   \n",
       "Jordan                      1557374.0        2216903.0     3.480587e+06   \n",
       "Azerbaijan                  5425317.0        6383060.0     7.427836e+06   \n",
       "Tajikistan                  2993019.0        4045965.0     5.417860e+06   \n",
       "United Arab Emirates         298084.0        1014048.0     1.900151e+06   \n",
       "Israel                      2907307.0        3744608.0     4.803254e+06   \n",
       "Laos                        2675283.0        3297519.0     4.314443e+06   \n",
       "Hong Kong                   3955072.0        4978544.0     5.838574e+06   \n",
       "Kyrgyzstan                  3016384.0        3691209.0     4.394734e+06   \n",
       "Turkmenistan                2201432.0        2862903.0     3.720278e+06   \n",
       "Singapore                   2061831.0        2400729.0     3.022209e+06   \n",
       "Lebanon                     2381791.0        2963702.0     3.593700e+06   \n",
       "Palestine                   1118241.0        1453620.0     2.124609e+06   \n",
       "Oman                         670693.0        1017462.0     1.804524e+06   \n",
       "Kuwait                       802786.0        1493870.0     1.674938e+06   \n",
       "Georgia                           NaN              NaN              NaN   \n",
       "Mongolia                    1293880.0        1697780.0     2.161433e+06   \n",
       "Armenia                     2534377.0        3135123.0     3.556539e+06   \n",
       "Qatar                        118007.0         277450.0     4.416750e+05   \n",
       "Bahrain                      222555.0         362595.0     5.174180e+05   \n",
       "Bhutan                       298894.0         415257.0     5.584420e+05   \n",
       "Macau                        247284.0         245332.0     3.502270e+05   \n",
       "Maldives                     123243.0         164887.0     2.249570e+05   \n",
       "Brunei                       133343.0         187921.0     2.619280e+05   \n",
       "Timor-Leste                  554021.0         642224.0     7.581060e+05   \n",
       "\n",
       "                      2000 Population  2010 Population  2015 Population  \\\n",
       "Country                                                                   \n",
       "China                    1.264099e+09     1.348191e+09     1.393715e+09   \n",
       "India                    1.059634e+09     1.240614e+09     1.322867e+09   \n",
       "Indonesia                2.140724e+08     2.440162e+08     2.590920e+08   \n",
       "Pakistan                 1.543699e+08     1.944545e+08     2.109693e+08   \n",
       "Bangladesh               1.291933e+08     1.483911e+08     1.578300e+08   \n",
       "Japan                    1.268039e+08     1.281054e+08     1.272509e+08   \n",
       "Philippines              7.795822e+07     9.463670e+07     1.030314e+08   \n",
       "Vietnam                  7.900114e+07     8.741101e+07     9.219140e+07   \n",
       "Iran                     6.554438e+07     7.537386e+07     8.179084e+07   \n",
       "Turkey                   6.411355e+07     7.319534e+07     7.964618e+07   \n",
       "Thailand                 6.306660e+07     6.827049e+07     7.029440e+07   \n",
       "Myanmar                  4.553833e+07     4.939099e+07     5.148395e+07   \n",
       "South Korea              4.678859e+07     4.881304e+07     5.099440e+07   \n",
       "Iraq                     2.462886e+07     3.126488e+07     3.775781e+07   \n",
       "Afghanistan              1.954298e+07     2.818967e+07     3.375350e+07   \n",
       "Saudi Arabia             2.154739e+07     2.941193e+07     3.274985e+07   \n",
       "Uzbekistan               2.492555e+07     2.861423e+07     3.094942e+07   \n",
       "Malaysia                          NaN              NaN     3.106883e+07   \n",
       "Yemen                    1.862870e+07     2.474395e+07     2.851654e+07   \n",
       "Nepal                    2.455950e+07     2.716157e+07     2.761032e+07   \n",
       "North Korea              2.336706e+07     2.468644e+07     2.525802e+07   \n",
       "Taiwan                   2.219473e+07     2.308308e+07     2.351214e+07   \n",
       "Syria                    1.630765e+07     2.233756e+07     1.920518e+07   \n",
       "Sri Lanka                1.877637e+07     2.066856e+07     2.133670e+07   \n",
       "Kazakhstan               1.523625e+07     1.662784e+07     1.783591e+07   \n",
       "Cambodia                 1.211884e+07     1.436353e+07     1.541752e+07   \n",
       "Jordan                   5.056174e+06     6.931258e+06     9.494246e+06   \n",
       "Azerbaijan               8.190337e+06     9.237202e+06     9.863480e+06   \n",
       "Tajikistan               6.272998e+06     7.621779e+06     8.524063e+06   \n",
       "United Arab Emirates     3.275333e+06     8.481771e+06     8.916899e+06   \n",
       "Israel                   6.116958e+06     7.328445e+06     8.007778e+06   \n",
       "Laos                     5.430853e+06     6.323418e+06     6.787419e+06   \n",
       "Hong Kong                6.731195e+06     7.132438e+06     7.399838e+06   \n",
       "Kyrgyzstan               4.935182e+06     5.483774e+06     5.914980e+06   \n",
       "Turkmenistan             4.569132e+06     5.267970e+06     5.766431e+06   \n",
       "Singapore                4.053602e+06     5.163590e+06     5.650018e+06   \n",
       "Lebanon                  4.320642e+06     4.995800e+06     6.398940e+06   \n",
       "Palestine                3.139954e+06     3.992278e+06     4.484614e+06   \n",
       "Oman                     2.344253e+06     2.881914e+06     4.191776e+06   \n",
       "Kuwait                   1.934901e+06     2.943356e+06     3.908743e+06   \n",
       "Georgia                           NaN              NaN     3.771132e+06   \n",
       "Mongolia                 2.450979e+06     2.702520e+06     2.964749e+06   \n",
       "Armenia                  3.168523e+06     2.946293e+06     2.878595e+06   \n",
       "Qatar                    6.459370e+05     1.713504e+06     2.414573e+06   \n",
       "Bahrain                  7.114420e+05     1.213645e+06     1.362142e+06   \n",
       "Bhutan                   5.872070e+05     7.055160e+05     7.432740e+05   \n",
       "Macau                    4.318960e+05     5.572970e+05     6.152390e+05   \n",
       "Maldives                          NaN              NaN     4.355820e+05   \n",
       "Brunei                   3.339260e+05     3.960530e+05     4.214370e+05   \n",
       "Timor-Leste                       NaN     1.088486e+06     1.205813e+06   \n",
       "\n",
       "                      2020 Population  2022 Population  \n",
       "Country                                                 \n",
       "China                    1.424930e+09     1.425887e+09  \n",
       "India                    1.396387e+09     1.417173e+09  \n",
       "Indonesia                2.718580e+08     2.755013e+08  \n",
       "Pakistan                 2.271967e+08     2.358249e+08  \n",
       "Bangladesh               1.674210e+08     1.711864e+08  \n",
       "Japan                    1.252448e+08     1.239517e+08  \n",
       "Philippines              1.121910e+08     1.155590e+08  \n",
       "Vietnam                  9.664868e+07     9.818686e+07  \n",
       "Iran                     8.729019e+07     8.855057e+07  \n",
       "Turkey                   8.413543e+07     8.534124e+07  \n",
       "Thailand                 7.147566e+07     7.169703e+07  \n",
       "Myanmar                  5.342320e+07     5.417931e+07  \n",
       "South Korea              5.184469e+07     5.181581e+07  \n",
       "Iraq                     4.255698e+07     4.449612e+07  \n",
       "Afghanistan              3.897223e+07     4.112877e+07  \n",
       "Saudi Arabia             3.599711e+07     3.640882e+07  \n",
       "Uzbekistan               3.352666e+07     3.462765e+07  \n",
       "Malaysia                 3.319999e+07     3.393822e+07  \n",
       "Yemen                    3.228405e+07     3.369661e+07  \n",
       "Nepal                    2.934863e+07     3.054758e+07  \n",
       "North Korea              2.586747e+07     2.606942e+07  \n",
       "Taiwan                   2.382146e+07     2.389339e+07  \n",
       "Syria                    2.077260e+07     2.212525e+07  \n",
       "Sri Lanka                2.171508e+07     2.183214e+07  \n",
       "Kazakhstan               1.897924e+07     1.939800e+07  \n",
       "Cambodia                 1.639686e+07     1.676784e+07  \n",
       "Jordan                   1.092872e+07     1.128587e+07  \n",
       "Azerbaijan                        NaN     1.035807e+07  \n",
       "Tajikistan               9.543207e+06     9.952787e+06  \n",
       "United Arab Emirates     9.287289e+06     9.441129e+06  \n",
       "Israel                   8.757489e+06     9.038309e+06  \n",
       "Laos                     7.319399e+06     7.529475e+06  \n",
       "Hong Kong                7.500958e+06     7.488865e+06  \n",
       "Kyrgyzstan               6.424874e+06     6.630623e+06  \n",
       "Turkmenistan             6.250438e+06     6.430770e+06  \n",
       "Singapore                5.909869e+06     5.975689e+06  \n",
       "Lebanon                  5.662923e+06     5.489739e+06  \n",
       "Palestine                5.019401e+06     5.250072e+06  \n",
       "Oman                     4.543399e+06     4.576298e+06  \n",
       "Kuwait                   4.360444e+06     4.268873e+06  \n",
       "Georgia                  3.765912e+06     3.744385e+06  \n",
       "Mongolia                 3.294335e+06     3.398366e+06  \n",
       "Armenia                  2.805608e+06     2.780469e+06  \n",
       "Qatar                    2.760385e+06     2.695122e+06  \n",
       "Bahrain                  1.477469e+06     1.472233e+06  \n",
       "Bhutan                   7.725060e+05     7.824550e+05  \n",
       "Macau                    6.762830e+05     6.951680e+05  \n",
       "Maldives                 5.144380e+05     5.237870e+05  \n",
       "Brunei                   4.417250e+05     4.490020e+05  \n",
       "Timor-Leste              1.299995e+06              NaN  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df_asia[['Country'] + list(df.columns[12:4:-1])].sort_values(by=\"2022 Population\",ascending=False)\n",
    "df2.set_index('Country', inplace = True)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "62118199-5ee3-4647-95ad-1b6eabc5b989",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABMEAAAG7CAYAAADKVYINAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAADND0lEQVR4nOzdeXxU5d0+/mvO7JN9nySELGQjCQHcKrgBZQkodaHWqq3yuPSngtbHWp+qrUqrRWtxq9Z+a1tw59FW1EdlE1lcUREkISRhSQhL9kz2zHrO748zc2YmeyDJZLnerxevzFnnnogkc83n/twqSZIkEBERERERERERjWNCoAdAREREREREREQ03BiCERERERERERHRuMcQjIiIiIiIiIiIxj2GYERERERERERENO4xBCMiIiIiIiIionGPIRgREREREREREY17DMGIiIiIiIiIiGjcYwhGRERERERERETjHkMwIiIiIiIiIiIa9xiCERERERERERHRuDemQrBdu3Zh6dKlSEhIgEqlwrvvvjvoe2zevBnnn38+QkJCEBMTg2XLlqGiomLIx0pERERERERERKPHmArB2tvbMX36dLzwwgundX15eTkuv/xyzJs3D/v27cPmzZtRX1+Pq666aohHSkREREREREREo4lKkiQp0IM4HSqVChs2bMAVV1yh7LPZbHjwwQfx5ptvoqmpCXl5eXjiiScwZ84cAMC///1vXHvttbDZbBAEOf/7v//7P1x++eWw2WzQarUBeCVERERERERERDTcxlQlWH9WrlyJL7/8EuvXr8f+/ftx9dVXo6CgAIcOHQIAnH322RAEAWvXroXL5UJzczNeffVVzJ8/nwEYEREREREREdE4Nm4qwSorK5GWlobKykokJCQo582fPx/nnXce/vjHPwIAdu7ciZ/85CdoaGiAy+XCrFmz8NFHHyE8PDwAr4KIiIiIiIiIiEbCuKkEKywshMvlQmZmJoKDg5U/O3fuxJEjRwAA1dXVuPXWW3HjjTfim2++wc6dO6HT6fDjH/8YYzQLJCIiIiIiIiKiAdAEegBDpa2tDWq1Gnv27IFarfY7FhwcDAB44YUXEBYWhj/96U/Ksddeew1JSUnYvXs3zj///BEdMxERERERERERjYxxE4LNnDkTLpcLtbW1uOiii3o8p6OjQ2mI7+EJzERRHPYxEhERERERERFRYIyp6ZBtbW3Yt28f9u3bBwAoLy/Hvn37UFlZiczMTFx//fW44YYb8M4776C8vBxff/01Vq9ejQ8//BAAcOmll+Kbb77B73//exw6dAjfffcd/uu//gvJycmYOXNmAF8ZERERERERERENpzHVGH/Hjh2YO3dut/033ngj1q1bB4fDgUcffRSvvPIKTp48iejoaJx//vlYtWoVpk2bBgBYv349/vSnP6GsrAwmkwmzZs3CE088gezs7JF+OURERERERERENELGVAhGRERERERERER0OsbUdEgiIiIiIiIiIqLTMSYa44uiiFOnTiEkJAQqlSrQwyEiIiIiIiIiogCRJAmtra1ISEjotgBiX8ZECHbq1CkkJSUFehhERERERERERDRKHD9+HJMmTRrw+WMiBAsJCQEgv7jQ0NAAj4aIiIiIiIiIiAKlpaUFSUlJSl40UGMiBPNMgQwNDWUIRkREREREREREg26Zxcb4REREREREREQ07jEEIyIiIiIiIiKicY8hGBERERERERERjXtjoifYQIiiCLvdHuhhUADpdLpBLY1KRERERERERBPHuAjB7HY7ysvLIYpioIdCASQIAlJTU6HT6QI9FCIiIiIiIiIaZcZ8CCZJEqqqqqBWq5GUlMRKoAlKFEWcOnUKVVVVmDx58qBXiCAiIiIiIiKi8W3Mh2BOpxMdHR1ISEiAyWQK9HAogGJiYnDq1Ck4nU5otdpAD4eIiIiIiIiIRpExXzblcrkAgFPgSPk74Pk7QURERERERETkMeZDMA9OfyP+HSAiIiIiIiKi3oybEIyIiIiIiIiIiKg3DMGIiIiIiIiIiGjcYwhGRERERERERETjHkOwEVJdXY0777wTaWlp0Ov1SEpKwtKlS7Ft27YRHYdKpcK77747os9JRERERERERBRomkAPYCKoqKjABRdcgPDwcDz55JOYNm0aHA4HNm/ejBUrVqCkpCTQQ/Rjt9u52iYRERERERHRGCFJEhwuCVanC1a7C1aHKD92uB87XJgSG4zEcGOghxpQDMFGwB133AGVSoWvv/4aQUFByv7c3FzcdNNNAIDKykrceeed2LZtGwRBQEFBAf7yl78gLi4OALB8+XI0NTX5VXHdfffd2LdvH3bs2AEAmDNnDvLz82EwGPCPf/wDOp0Ot912Gx555BEAQEpKCgDgyiuvBAAkJyejoqICjzzyCN59912sXLkSjz32GI4dO4Z169bhv//7v3Hq1Cno9XrlOa+44gqEhITg1VdfHabvFhEREREREdHYJkkSbE4Rth7CqE6Hd9vW5VjX8MrW5Xz5mLzf6nDB6vRc54Io9T2mP1yei5/PShmR1z9aMQQbZo2Njdi0aRMee+wxvwDMIzw8HKIo4vLLL0dwcDB27twJp9OJFStW4JprrlECroF6+eWXcc8992D37t348ssvsXz5clxwwQVYsGABvvnmG8TGxmLt2rUoKCiAWq1Wrjt8+DD+85//4J133oFarUZGRgbuuusuvP/++7j66qsBALW1tfjwww+xZcuWM/qeEBEREREREY0kUZRDKTk48g2dvOGSzf3YL3Ryn2/r4Xz/8Mp/v80pQuonlBouKhVg0Khh0AowaNUwaNXQawSEGrWBGdAowhBsmB0+fBiSJCE7O7vXc7Zt24bCwkKUl5cjKSkJAPDKK68gNzcX33zzDc4999wBP19+fj4efvhhAEBGRgaef/55bNu2DQsWLEBMTAwAOXgzm81+19ntdrzyyivKOQBw3XXXYe3atUoI9tprr2Hy5MmYM2fOgMdDRERERERE1JUoylP3Ou3+1UxKlZOzS3WUZ18P5/tWRNm6hFGe+9udYsBeq1pQwaDxCaS0QreQyuDZp1N3Oeb+qnFf5znffT+jz/l69/k6tQCVShWw1zuaMQQbZtIAot+DBw8iKSlJCcAAICcnB+Hh4Th48OCgQzBf8fHxqK2t7fe65ORkvwAMAG699Vace+65OHnyJBITE7Fu3TosX76c/zMRERERERGNM06X2HO41DWE8tlv63J+n9P8fK61OUTYXYELpTSCCkatWgmN/EIorU+g1CWMMiohltov1PINqjyPPYGVUauGVs01CUcLhmDDLCMjAyqV6oyb3wuC0C1Qczgc3c7Tav3LG1UqFUSx/39cepqqOXPmTEyfPh2vvPIKFi5ciAMHDuDDDz8c5MiJiIiIiIhoMPyanDt8p+L5T8PzhE62XoOq3qb5+QZV8rnO/hpKDSOdWvCpcpLDKE+FU0/VT12n+XnCJkOXUEuv6bpPvoeGodSExRBsmEVGRmLRokV44YUXcNddd3ULm5qamjB16lQcP34cx48fV6rBiouL0dTUhJycHABATEwMioqK/K7dt29ft9CrP1qtFi6Xa8Dn33LLLXjmmWdw8uRJzJ8/369ajYiIiIiIiAanudOBk5ZOnLB04ISl0/2nAyebOlHTYkWHfWBNzoeTvmvY5DfdTg1jj5VP3aupugdQ3acA6jVqqAXONqKRwRBsBLzwwgu44IILcN555+H3v/898vPz4XQ6sXXrVrz44osoLi7GtGnTcP311+OZZ56B0+nEHXfcgUsuuQTnnHMOAGDevHl48skn8corr2DWrFl47bXXUFRUhJkzZw5qLCkpKdi2bRsuuOAC6PV6RERE9Hn+ddddh3vvvRcvvfQSXnnlldP+HhAREREREY13kiShpdOJ4+6A62RT97Cr1eoc1D17a3Le2zS87lP0uoROXc7vWkGlUwsQGErROMUQbASkpaXhu+++w2OPPYZf/epXqKqqQkxMDM4++2y8+OKLUKlUeO+993DnnXfi4osvhiAIKCgowF/+8hflHosWLcLvfvc73HfffbBarbjppptwww03oLCwcFBjWbNmDe655x689NJLSExMREVFRZ/nh4WFYdmyZfjwww9xxRVXnMarJyIiIiIiGh8kSUJzp0MJtLzhlruay9KJVlv/IVdUkA6TIoyYFGFCYoTR/dgIc6gRQXpv1ZReK0CvYZNzoqGikgbSuT3AWlpaEBYWhubmZoSGhvods1qtKC8vR2pqKgwGQ4BGOL798Ic/RG5uLp577rlAD6VP/LtARERERERnQpIkWDq6Tlf0hl0nmzrRNoCQKzpYh8QIkxJuTYowYVK4/DgxwgiTjvUoRGeir5yoL/w/j3plsViwY8cO7NixA3/9618DPRwiIiIiIqIzIkkSGtvtPqGW/1TFE5ZOdNj776EcE6JHYrhPwOUTdiWGG2HUqUfg1RDRYDEEo17NnDkTFosFTzzxBLKysgI9HCIiIiIioj5JkoQGJeTq8Jum6Am7Oh39h1yxIXq/gCvR93G4EQYtQy6isYghGPWqv35hREREREREI0mSJNS12eQqri4VXJ4VFq0Osc97qFSekKvLdEV3wJXAkIto3GIIRkRERERERKOCKEqob7PhuE+4Ja+w6K3osjn7D7nMoQa/6Ym+QVd8uAF6DUMuoomIIRgRERERERGNCFH0VHJ178V10tKJE02dsPcTcglKyNWlF5f7cXyYETqNMEKviIjGEoZgRERERERENCRcooTaVqvPdEX/sOtUkxV2V/8hV3yYUQm1fMOupAgTzGEGaNUMuYho8BiCERERERER0YC4RAk1LdYeKrjkx6eaOuFwSX3eQy2oEB/W+3RFhlxENFwYghEREREREREAwOkSUd1i9VtNUanmaupAVZMVTrHvkEsjqBAfbsCkcFO3Sq7ECCPMoQZoGHIRUQAwBCMiIiIiIpognC4RVc1Wv9UUfYOuqmYrXP2EXFq1Cgme6q1wU7dpi3GhBqgF1Qi9IiKigWMINoapVCps2LABV1xxRaCHAgDYsWMH5s6dC4vFgvDw8EAPh4iIiIhownG4RFQ3W3G8Sy8uT2VXdcvAQi55imLPjedjQxhyEdHYxBAsQJYvX46mpia8++67gR7KkJk9ezaqqqoQFhYW6KEQEREREY1LdqeIqubOXhvPV7dY0U/GBZ1GwKTwnhvPT4owISZYD4EhFxGNQwzBaMjodDqYzeZAD4OIiIiIaMyyOV2oaurSeL7J+7i6xQppICGXT7jl23g+KcKIaIZcRDRBjbsQTJIkdDpcAXluo1YNlWrwP0zmzJmD/Px8GAwG/OMf/4BOp8Ntt92GRx55RDnn0KFDuPnmm/H1118jLS0Nzz77bLf7FBYW4pe//CW+/PJLmEwmLFu2DE899RSCg4MBeKvPLrzwQqxZswZ2ux0//elP8cwzz0Cr1QIAbDYbHnzwQbz55ptoampCXl4ennjiCcyZMwcAcOzYMaxcuRKfffYZ7HY7UlJS8OSTT2LJkiXdpkM2NDRg5cqV2LVrFywWC6ZMmYIHHngA11577eC/uURERERE44DV4cKpps5uvbg8lV01rf2HXPouIZcSdrmruaKDGHIREfVk3IVgnQ4Xch7aHJDnLv79Iph0p/ctffnll3HPPfdg9+7d+PLLL7F8+XJccMEFWLBgAURRxFVXXYW4uDjs3r0bzc3NuPvuu/2ub29vx6JFizBr1ix88803qK2txS233IKVK1di3bp1ynnbt29HfHw8tm/fjsOHD+Oaa67BjBkzcOuttwIAVq5cieLiYqxfvx4JCQnYsGEDCgoKUFhYiIyMDKxYsQJ2ux27du1CUFAQiouLlZCtK6vVirPPPhv/8z//g9DQUHz44Yf4+c9/jilTpuC88847re8TEREREdFoZnW4/AKuk11WWKxttfV7D6NW7beaYtewKypId1ofvhMRTXTjLgQbq/Lz8/Hwww8DADIyMvD8889j27ZtWLBgAT7++GOUlJRg8+bNSEhIAAD88Y9/xOLFi5Xr33jjDVitVrzyyisICgoCADz//PNYunQpnnjiCcTFxQEAIiIi8Pzzz0OtViM7OxuXXnoptm3bhltvvRWVlZVYu3YtKisrlee59957sWnTJqxduxZ//OMfUVlZiWXLlmHatGkAgLS0tF5fU2JiIu69915l+84778TmzZvx1ltvMQQjIiIiojHJ5nTheGP3Xlye4KtuACGXSafu1osrMdz7OJIhFxHRsBh3IZhRq0bx7xcF7LlPV35+vt92fHw8amtrAQAHDx5EUlKSEkwBwKxZs/zOP3jwIKZPn64EYABwwQUXQBRFlJaWKiFYbm4u1GrvOOPj41FYWAhAnk7pcrmQmZnpd2+bzYaoqCgAwF133YXbb78dW7Zswfz587Fs2bJuY/dwuVz44x//iLfeegsnT56E3W6HzWaDyWQa1PeGiIiIiGgkuUQJJy2dOFrfhvL6dlTUt+NofTsqGtpx0tLZb+P5IJ0aSZEmv15cvl/DTVqGXEREATDuQjCVSnXaUxIDydOTy0OlUkEUxRF9nra2NqjVauzZs8cvKAOgTHm85ZZbsGjRInz44YfYsmULVq9ejTVr1uDOO+/s9lxPPvkknn32WTzzzDOYNm0agoKCcPfdd8Nutw/56yIiIiIiGgxJklDTYvMLusrdfyobO+Bw9Z50Bes1Payq6N0OMzLkIiIajcZeWjQBTZ06FcePH0dVVRXi4+MBAF999VW3c9atW4f29nalGuzzzz+HIAjIysoa0PPMnDkTLpcLtbW1uOiii3o9LykpCbfddhtuu+023H///XjppZd6DME+//xzXH755fjZz34GABBFEWVlZcjJyRnQeIiIiIiIzoQkSbB0OFBe34ajdXIllxx0daCivr3PBbV0GgGpUUFIjQ5CSnQQ0txfU6ODEB3M6YpERGMRQ7AxYP78+cjMzMSNN96IJ598Ei0tLXjwwQf9zrn++uvx8MMP48Ybb8QjjzyCuro63Hnnnfj5z3+uTIXsT2ZmJq6//nrccMMNWLNmDWbOnIm6ujps27YN+fn5uPTSS3H33Xdj8eLFyMzMhMViwfbt2zF16tQe75eRkYF///vf+OKLLxAREYGnnnoKNTU1DMGIiIiIaEi1Wh2oqO9AeUM7yuvaUV7fhvKGDpTXtaHF6uz1OrWgwuRIkxx0RQUhNSZIDr5ighAfauAKi0RE4wxDsDFAEARs2LABN998M8477zykpKTgueeeQ0FBgXKOyWTC5s2b8ctf/hLnnnsuTCYTli1bhqeeempQz7V27Vo8+uij+NWvfoWTJ08iOjoa559/Pi677DIAcp+vFStW4MSJEwgNDUVBQQGefvrpHu/129/+FkePHsWiRYtgMpnwi1/8AldccQWam5tP/5tBRERERBOS1eHCsYYOZcpieX0bKuo7cLS+HfVtfTejTww3uiu6TEiNDkaq++ukCCO0amGEXgEREQWaSpKkfto6Bl5LSwvCwsLQ3NyM0NBQv2NWqxXl5eVITU2FwWAI0AhpNODfBSIiIqKxzeESccLSqTSi9wRd5fXtONXcib7euUQH693hVpBf0JUcZYLhDBawIiKi0aevnKgvrAQjIiIiIqIRI4oSqlqs3qDLp1fX8cYOOPtYejHEoEFatLdPV2p0ENKig5ESbUKIQdvrdURERABDMCIiIiIiGmKSJKG+zS6HW3XtPr265MDL5ux9FXSDVkBKVBDSYtx9uqK9jyOD2JCeiIhOH0MwIiIiIiI6Lc2dDlQoPbq8fyrq29Fq670hvVatQlKkSV5x0dOQ3l3ZFRfChvRERDQ8GIIREREREVGvOu0uZbqib8hVXt+OhnZ7r9epVN6G9Kk+UxjTooOQGG6Ehg3piYhohDEEIyIiIiKa4OxOEcctHUp/rqM+QVdVs7XPa2ND9D0GXUmRbEhPRESjy6BCsNWrV+Odd95BSUkJjEYjZs+ejSeeeAJZWVm9XrNu3Tr813/9l98+vV4Pq7XvH6ZERERERDR0XKKEU02dSl+uoz4N6U9YOuHqoyF9mFGLtJggpEb5N6VPiQ5CsJ6fqxMR0dgwqJ9YO3fuxIoVK3DuuefC6XTigQcewMKFC1FcXIygoKBerwsNDUVpaamyzWaWRERERERDT5Ik1LXa/Cq5PH+ONXbA3kdDepNOrfTn8uvVFRWEiCDdCL4KIiKi4TGoEGzTpk1+2+vWrUNsbCz27NmDiy++uNfrVCoVzGbzgJ/HZrPBZrMp2y0tLYMZJhERERHRuNbUYe/WjN7Tq6vd7ur1Op1awOQok9/0Rc+f2BA9P6wmIqJx7Yxql5ubmwEAkZGRfZ7X1taG5ORkiKKIs846C3/84x+Rm5vb6/mrV6/GqlWrzmRoRERERERjWrvN6W1IX9eO8gZv0GXpcPR6naACJkX0HHQlhBuh5sqLREQ0QakkSep98n8fRFHEj370IzQ1NeGzzz7r9bwvv/wShw4dQn5+Ppqbm/HnP/8Zu3btwoEDBzBp0qQer+mpEiwpKQnNzc0IDQ31O9dqtaK8vBypqakwGAyn81LGnHXr1uHuu+9GU1NTj8d37NiBuXPnwmKxIDw8fETHFkgT8e8CERERjW02pwvHGztwtK69W6+umhZbn9eaQw1+jeg9fbomR5qg03DlRSIiGr9aWloQFhbWY07Ul9OuBFuxYgWKior6DMAAYNasWZg1a5ayPXv2bEydOhX/7//9P/zhD3/o8Rq9Xg+9Xn+6QxsTli9fjpdffhkAoNVqMXnyZNxwww144IEHoNGcWXPR2bNno6qqCmFhYf2eO1EDMyIiIqKR4hIlnLR04mh9m9Kn66g78Dpp6UQf/egRGaSTg66oIKTFuPt0RQchJdoEk44N6YmIiAbjtH5yrly5Eh988AF27drVazVXb7RaLWbOnInDhw+fzlOPKwUFBVi7di1sNhs++ugjrFixAlqtFvfff/8Z3Ven0w2qBxsRERERnRlJklDTYnMHXR0or29T+nRVNnbA4eo96QrWa/xWXEyNNiE1OhipUUEIM2lH8FUQERGNb4MKwSRJwp133okNGzZgx44dSE1NHfQTulwuFBYWYsmSJYO+dkAkCXB0DM+9+6M1AYNoJqrX65Ww6vbbb8eGDRvw/vvvQ6/XY+3atTh69CgiIyOxdOlS/OlPf0JwcHCP96mrq8PixYuRlJSE9evX48svv/Sr7jp27BhWrlyJzz77DHa7HSkpKXjyySeRk5ODuXPnAgAiIiIAADfeeCPWrVuHTZs24dFHH0VRURHUajVmzZqFZ599FlOmTAEAVFRUIDU1Ff/5z3/wl7/8Bbt370ZGRgb+9re/+VX+EREREY0XkiTB0uFwB1xy0FVR36GsxNjp6KMhvUZAitKQPlgJulKiTYgJZkN6IiKikTCoEGzFihV444038N577yEkJATV1dUAgLCwMBiNRgDADTfcgMTERKxevRoA8Pvf/x7nn38+0tPT0dTUhCeffBLHjh3DLbfcMsQvxc3RAfwxYXju3Z8HTgG6oNO+3Gg0oqGhAYIg4LnnnkNqaiqOHj2KO+64A/fddx/++te/drvm+PHjWLBgAc4//3z885//hFqt7nbOihUrYLfbsWvXLgQFBaG4uBjBwcFISkrCf/7zHyxbtgylpaUIDQ1V/ju2t7fjnnvuQX5+Ptra2vDQQw/hyiuvxL59+yAI3h4TDz74IP785z8jIyMDDz74IK699locPnz4jKd0EhEREQVKq9UhV3M1yA3pKxrk6YvldW1osTp7vU4tqJAUYewx6EoIM0JgQ3oiIqKAGlRS8eKLLwIA5syZ47d/7dq1WL58OQCgsrLSLySxWCy49dZbUV1djYiICJx99tn44osvkJOTc2YjH0ckScK2bduwefNm3Hnnnbj77ruVYykpKXj00Udx2223dQvBSktLsWDBAlx55ZV45plnev0EsbKyEsuWLcO0adMAAGlpacoxz8qesbGxfj3Bli1b5nePf/3rX4iJiUFxcTHy8vKU/ffeey8uvfRSAMCqVauQm5uLw4cPIzs7e/DfCCIiIqIRYnW4cKyhQ5my6OnVVd7QjrrWvhvSJ4QZkOrTn8vTqysp0gStmg3piYiIRqtBT4fsz44dO/y2n376aTz99NODGtQZ0ZrkiqxA0JoGdfoHH3yA4OBgOBwOiKKI6667Do888gg+/vhjrF69GiUlJWhpaYHT6YTVakVHRwdMJvk5Ojs7cdFFF+G6667DM8880+fz3HXXXbj99tuxZcsWzJ8/H8uWLUN+fn6f1xw6dAgPPfQQdu/ejfr6eoiiCEAO1HxDMN/7xMfHAwBqa2sZghEREVHAOVwiTlg6UeFpRO8Juurbcaq5E339ahsd7G1InxoThFT31+TIIBh13SvviYiIaPQbf3PWVKozmpI4kubOnYsXX3wROp0OCQkJ0Gg0qKiowGWXXYbbb78djz32GCIjI/HZZ5/h5ptvht1uV0IwvV6P+fPn44MPPsCvf/1rJCYm9vo8t9xyCxYtWoQPP/wQW7ZswerVq7FmzRrceeedvV6zdOlSJCcn46WXXkJCQgJEUUReXh7sdrvfeVqtt1mrpxLNE5gRERERjSRJknCkrg3bS+rwSUktvj3W2GdD+hCDBml+DemDlAb1oQY2pCciIhpvxl8INoYEBQUhPT3db9+ePXsgiiLWrFmjTCt96623ul0rCAJeffVVXHfddZg7dy527NiBhITee6ElJSXhtttuw2233Yb7778fL730Eu68807odDoA8oIFHg0NDSgtLcVLL72Eiy66CADw2WefnfHrJSIiIhpqVocLXx5twI6SWnxSWovjjZ1+xw1aQZm26Am40tyPI4N0bEhPREQ0gTAEG2XS09PhcDjwl7/8BUuXLsXnn3+Ov/3tbz2eq1ar8frrr+Paa6/FvHnzsGPHDmW1SV933303Fi9ejMzMTFgsFmzfvh1Tp04FACQnJ0OlUuGDDz7AkiVLYDQaERERgaioKPz9739HfHw8Kisr8Zvf/GZYXzcRERHRQJ1s6sQnJbXYXlKLL47Uw+rwVqHr1AJ+kBaJedmxuCQzBilRQWxIT0RERAAYgo0606dPx1NPPYUnnngC999/Py6++GKsXr0aN9xwQ4/nazQavPnmm7jmmmuUIKwrl8uFFStW4MSJEwgNDUVBQYHSpy0xMRGrVq3Cb37zG/zXf/0XbrjhBqxbtw7r16/HXXfdhby8PGRlZeG5557rtiACERER0UhwuER8d8yCT0rl4Kusps3veHyYAXOyYjEvOxYXpEfBpOOvuERERNSdShpIt/sAa2lpQVhYGJqbmxEaGup3zGq1ory8HKmpqTAYDAEaIY0G/LtAREQ0ftS32bCztA6flNZiV1kdWq1O5ZigAs5OjlCCr2xzCKc1EhERTSB95UR94cdkRERERBRwoiih6FSz3NS+tBb7TzT5rd4YYdJiTlYs5mbH4uKMaISbdIEbLBEREY1JDMGIiIiIKCBarA58dqgen5TUYkdpHerbbH7HcxNCMS9bDr6mTwqHmr29iIiI6AwwBCMiIiKiESFJEo7UteGTklp8UlKLbysscIrecq8gnRoXZkRjXnYs5mTFIi6U7Q2IiIho6DAEIyIiIqJhY3W48OXRBmwvqcX20locb+z0O54WE4S57t5e56ZEQqcRAjRSIiIiGu8YghERERHRkDph6cD20jpsL6nFF0fqYXWIyjGdRsD5aVGYlxWDudmxSI4KCuBIiYiIaCJhCEZEREREZ8ThErHnmAXbS2uxvaQWZTVtfsfjwwyYmx2LeVmxmJ0eBZOOv4ISERHRyONvIEREREQ0aPVtNuworcP20lrsKqtDq9WpHBNUwNnJEXLwlR2LrLgQqFRsak9ERBRQkgRM8J/HDMGIiIiIqF+iKKHoVDM+KanF9tI67D/RBMnb0x6RQTpckilPcbwkIwZhJm3gBktERDQROG1Aez3QUQ+01wHtDfLXHrfrgcV/AmZeH+hRBxRDMEJKSgruvvtu3H333ad9j3Xr1uHuu+9GU1PTqBkTERERnZkWqwOfHarHJyW12FFah/o2m9/xvMRQzMuKxZzsWEyfFA61MLE/XSYiIjojLsfgQi1by+Du3143POMeQxiCBcjy5cvx8ssvK9uRkZE499xz8ac//Qn5+fkBHBkRERFNVJIk4XBtG7aX1uKTklp8W2GBU/SWewXp1LgoIwZzs2MwJysWcaGGAI6WiIholHM5gY4GnxCrvkvI1WXb2jz45xA0gCkaCIoBgqLkr6ZoIMjzx2c7xDz0r3GMYQgWQAUFBVi7di0AoLq6Gr/97W9x2WWXobKyMsAjIyIioonC6nDhyyMNSvB1wtLpdzwtJgjzsmIxNzsW56ZEQqcRAjRSIiKiABNdQEfjwEOtTsvgn0Ml+IdYSsDVNdRyh16G8Anf52swGIIFkF6vh9ksJ7Fmsxm/+c1vcNFFF6Gurg4xMTH4n//5H2zYsAEnTpyA2WzG9ddfj4ceeghardxj45FHHsG7776LX/3qV/jd734Hi8WCxYsX46WXXkJISAgAoLW1FbfddhveffddhIaG4r777sN7772HGTNm4JlnnulxXE899RTWrl2Lo0ePIjIyEkuXLsWf/vQnBAcHK+esW7cODz30EOrr67Fo0SJceOGF3e7z3nvvYdWqVSguLkZCQgJuvPFGPPjgg9BoNJAkCatWrcK//vUv1NTUICoqCj/+8Y/x3HPPKdd3dHTgpptuwttvv42IiAj89re/xS9+8Yuh+vYTERFNWCcsHdju7u31xZF6WB2ickynEXB+WhTmZcn9vZKjggI4UiIiomEkinJQ5Rdi1cnVWz2FWh2NAKR+b+tPBZiifAKsKP9Qyy/kipFDLYEfOA2XcReCSZKETmdn/ycOA6PGeNorH7W1teG1115Deno6oqKiAAAhISFYt24dEhISUFhYiFtvvRUhISG47777lOuOHDmCd999Fx988AEsFgt+8pOf4PHHH8djjz0GALjnnnvw+eef4/3330dcXBweeughfPfdd5gxY0avYxEEAc899xxSU1Nx9OhR3HHHHbjvvvvw17/+FQCwe/du3HzzzVi9ejWuuOIKbNq0CQ8//LDfPT799FPccMMNeO6553DRRRfhyJEjSoD18MMP4z//+Q+efvpprF+/Hrm5uaiursb333/vd481a9bgD3/4Ax544AH8+9//xu23345LLrkEWVlZp/U9JiIimqgcLhF7jlmwvUSu9jpU2+Z3PD7MIK/kmBWL2elRMOnG3a+IREQ0EUgSYG3yhle+/bN6Crk6GgHJNfjnMUb2Emr1sG2MAAT1kL9UOj3j7jecTmcnfvDGDwLy3Luv2w2T1jTg8z/44AOluqq9vR3x8fH44IMPILhT39/+9rfKuSkpKbj33nuxfv16vxBMFEWsW7dOqfz6+c9/jm3btuGxxx5Da2srXn75Zbzxxhv44Q9/CABYu3YtEhIS+hyXbzP6lJQUPProo7jtttuUEOzZZ59FQUGBMo7MzEx88cUX2LRpk3LdqlWr8Jvf/AY33ngjACAtLQ1/+MMfcN999+Hhhx9GZWUlzGYz5s+fD61Wi8mTJ+O8887zG8eSJUtwxx13AAD+53/+B08//TS2b9/OEIyIiGgA6tts2FFah+0ltdh1qA6tVqdyTC2ocPbkCMzJjsG87FhkxYWc9gd5REREw0aS5Obv3UKtHprEeyq2RGf/9+3KED6IUCsSUI+7KGXC4H+5AJo7dy5efPFFAIDFYsFf//pXLF68GF9//TWSk5Pxv//7v3juuedw5MgRtLW1wel0IjQ01O8eKSkpSgAGAPHx8aitrQUAHD16FA6Hwy9cCgsL6zdE+vjjj7F69WqUlJSgpaUFTqcTVqsVHR0dMJlMOHjwIK688kq/a2bNmuUXgn3//ff4/PPPlYo0AHC5XMp9rr76ajzzzDNIS0tDQUEBlixZgqVLl0Kj8f6V9F0gQKVSwWw2K6+NiIiI/ImihKJTzfikpBbbS2qx/2QzJJ8ZG5FBOszJjMGc7FhckhGDMJM2cIMlIqKJSZIAe9sAVj702RYdg38efWiXqYaeIKunpvFRgJo/EyeKcReCGTVG7L5ud8CeezCCgoKQnp6ubP/jH/9AWFgYXnrpJVx66aW4/vrrsWrVKixatAhhYWFYv3491qxZ43cPT38wD5VKBVEUcboqKipw2WWX4fbbb8djjz2GyMhIfPbZZ7j55ptht9thMg2s0q2trQ2rVq3CVVdd1e2YwWBAUlISSktL8fHHH2Pr1q2444478OSTT2Lnzp3Kaxrq10ZERDTetFgd+LSsHttLa7GjtA71bTa/43mJoZiXFYs52bGYPikcaoHVXkRENMTs7b2EWF2bxruPu2z937MrXXDPoVZvqyJq9EP/OmlcGHchmEqlGtSUxNFEpVJBEAR0dnbiiy++QHJyMh588EHl+LFjxwZ1v7S0NGi1WnzzzTeYPHkyAKC5uRllZWW4+OKLe7xmz549EEURa9asUaZlvvXWW37nTJ06Fbt3+weNX331ld/2WWedhdLSUr+Qryuj0YilS5di6dKlWLFiBbKzs1FYWIizzjprUK+TiIhoopAkCYdr2+Rqr9JafFthgVP0lnsF6zW4MD0a87JjMScrBrGhhgCOloiIxiRH58BWPvSEWqfTk1tr6nnlwx63owHt4ApOiHoz7kKwscRms6G6uhqAPB3y+eefR1tbG5YuXYqWlhZUVlZi/fr1OPfcc/Hhhx9iw4YNg7p/SEgIbrzxRvz6179GZGQkYmNj8fDDD0MQhF77fqSnp8PhcOAvf/kLli5dis8//xx/+9vf/M656667cMEFF+DPf/4zLr/8cmzevNlvKiQAPPTQQ7jsssswefJk/PjHP4YgCPj+++9RVFSERx99FOvWrYPL5cIPfvADmEwmvPbaazAajUhOTh7UayQiIhrvrA4XvjzSoARfJyz+bzamxARhblYs5mXH4pyUSOg0XFGKiIh8OKzd+2b1FXI52gf/HBrDAFY+9Am1dFx5mAKDIVgAbdq0CfHx8QDkwCo7Oxtvv/025syZAwD47//+b6xcuRI2mw2XXnopfve73+GRRx4Z1HM89dRTuO2223DZZZchNDQU9913H44fPw6DoedPhqdPn46nnnoKTzzxBO6//35cfPHFWL16NW644QblnPPPPx8vvfQSHn74YTz00EOYP38+fvvb3+IPf/iDcs6iRYvwwQcf4Pe//z2eeOIJaLVaZGdn45ZbbgEAhIeH4/HHH8c999wDl8uFadOm4f/+7/+UlTGJiIgmshOWDmUlxy+ONMDm9LYD0GkEzEqLwtysGMzLjsPkqLFZAU9ERKfJafdf8dCz0mGP2/WAvXXwz6HW+fTO6qNJvGdbFwRwgRUaA1SS5NsydXRqaWlBWFgYmpubuzWGt1qtKC8vR2pqaq/BDnm1t7cjMTERa9aswc033xzo4Qwp/l0gIqKxyuES8W2FBTtK5eDrUG2b3/GEMAPmZsdiblYsZqdHwaTj55hEROOKKAItJ4DGoz2shNilUsvWPPj7C5re+2cpgZbPtj6UoRaNan3lRH3hb1Dj3N69e1FSUoLzzjsPzc3N+P3vfw8AuPzyywM8MiIioomtrtWGHe6G9rsO1aHV6l3SXS2ocPbkCMzNlqc5ZsYF99rKgIiIxhCnDWg4AtSXAvWHgLpSoL4MaDgMODoGfh+V2qcqq68m8e5tQzhDLSIwBJsQ/vznP6O0tBQ6nQ5nn302Pv30U0RHRwd6WERERBOKKEooPNmMT0pqsaO0Ft+f8P8kPzJIhzmZMZibHYuLM2IQZuJy7UREY1anBagrkwMu38Cr6Rgg9bLivaAFIlOB4Lh+VkKMlkMtgT0giQaLIdg4N3PmTOzZsyfQwyAiIpqQWqwOfFpWj09KarGzrBb1bXa/49MSwzA3Sw6+8ieFQy3wU3oiojHDM4Wxvswn8Dokh17tdb1fpw8FojOBmCwgOgOIzpK3I1IANd+iEw0n/h9GRERENEQkScKh2jalqf2eYxY4RW/71WC9BhdlRGNudizmZMYgNpQ9LImIRj1lCmOZ909daf9TGEMT5XArOhOIyfQ+Do7j1ESiAGEIRkRERHQGrA4XvjzSgE/cwdfJpk6/41NigjAvOxZzs2NxTnIkdBpOXyEiGpU6Lf59ujx/LBV9TGHUAJFTfEIuT3VXBqAPGdHhE1H/GIIRERERDdLxxg5lJccvjjTA5vS+OdJpBMxKi5KDr6xYTI4yBXCkRETkRxSBlpNdqrrcX9tre7/OM4XRr6orC4hIBtTs4Ug0VjAEIyIiIuqHwyXi2wqLEnwdqm3zO54QZlBWcpw9JRpGnTpAIyUiIgDyFMbGo+6qLnefrvoyoP4w4Gjv/brQRHcll8/0xZgsTmEkGicYghERERH1oK7Vhh2ltdheWotPy+rRanMqx9SCCmcnRyjVXplxwVDxzRER0cjrbOq5qstSAUiunq/xTGGMznA3p/cEXpzCSDTeMQQjIiIiAiCKEgpPNuOTEjn42n+i2e94VJAOl2TFYF52LC5Kj0GYidNfiIhGhCTJUxj9qrrcvbv6msKoC3FPXczyVnfFZLlXYeS/4UQTEUMwIiIimrCaOx347FA9Pimpxc6yWtS32f2OT0sMU6Y55ieGQRBY7UVENGycdqDxiH9FV32ZHHj1NYUxJKGHqq5MIMTMKYxE5IchWIAsX74cTU1NePfddwM9FCIioglDkiQcqm3DdvdKjt8es8AlSsrxYL0GF2VEY252LOZkxSA2xBDA0RIRjVOdTe6KrjL/qq5+pzCm+ffpis4AojIAQ+hIjp6IxjCGYERERDSuddpd+PKoXO21vaQOJ5s6/Y6nxwZjblYM5mbH4pzkSOg0QoBGSkQ0jnimMHar6ioD2mp6v04X4lPVleGeypgJRKZyCiMRnTGGYKPApk2b8Oijj6KoqAhqtRqzZs3Cs88+iylTpgAAKioqkJqaijfffBPPPfccvvvuO6Snp+OFF17AJZdcAgBwuVz4xS9+gU8++QTV1dWYPHky7rjjDvzyl79UnsdTfXbhhRdizZo1sNvt+OlPf4pnnnkGWi1/oBAR0fhxvLED290rOX55pAE2p6gc02kEzJ4ShblZclP7yVGmAI6UiGiMc9rlVRi7VnX1O4UxvntVV3QWpzAS0bAadyGYJEmQOjv7P3EYqIzG01oZqr29Hffccw/y8/PR1taGhx56CFdeeSX27dsHQfB+Gv3rX/8azzzzDHJycvDUU09h6dKlKC8vR1RUFERRxKRJk/D2228jKioKX3zxBX7xi18gPj4eP/nJT5R7bN++HfHx8di+fTsOHz6Ma665BjNmzMCtt946JN8DIiKiQHC4RHxbYVGCr8O1bX7HE8ONmJsdg7lZsZg9JRpGnTpAIyUiGqOszT4Bl09VV2P5AKcw+lR1RXMKIxEFxvgLwTo7UXrW2QF57qzv9kBlGvynycuWLfPb/te//oWYmBgUFxcjLy9P2b9y5Url3BdffBGbNm3CP//5T9x3333QarVYtWqVcm5qaiq+/PJLvPXWW34hWEREBJ5//nmo1WpkZ2fj0ksvxbZt2xiCERHRmFPbasXO0jpsL63Fp2X1aLU5lWNqQYWzkyMwL1uu9sqMCz6tD6qIiCYUSQJaTnkruurLvFVdbdW9X+eZwhid6V6N0b0iY0QKoNGN2PCJiPoz7kKwsejQoUN46KGHsHv3btTX10MU5SkblZWVfiHYrFmzlMcajQbnnHMODh48qOx74YUX8K9//QuVlZXo7OyE3W7HjBkz/J4rNzcXarX30+/4+HgUFhYO0ysjIiIaOqIoYf/JZmwvqcX20lrsP9HsdzwqSIdLsmIwLzsWF2XEIMzIqf5ERD1y2gFLefeqrvpDgL2t9+tC4rtXdMVkyfv5QQMRjQHjLgRTGY3I+m5PwJ77dCxduhTJycl46aWXkJCQAFEUkZeXB7vd3v/FbuvXr8e9996LNWvWYNasWQgJCcGTTz6J3bt3+53XtfeXSqVSQjciIqLRprnTgU8P1WF7SR12ltWivs3/Z2P+pDDMyYrFvOxY5CeGQRD4JoyISOGZwuhb0VVfJvfw6m0Ko0rtncLoW9UVnQ4YwkZ2/EREQ2z8hWAq1WlNSQyUhoYGlJaW4qWXXsJFF10EAPjss896PPerr77CxRdfDABwOp3Ys2cPVq5cCQD4/PPPMXv2bNxxxx3K+UeOHBnm0RMREQ0tSZJwqLbNvZJjLb49ZoFLlJTjIXoNLsqMxpysWMzJikFsiCGAoyUiGgUkCWit8gm5Sr0rMvY5hTHYp6rLsxpjJhCRyimMRDRujbsQbKyJiIhAVFQU/v73vyM+Ph6VlZX4zW9+0+O5L7zwAjIyMjB16lQ8/fTTsFgsuOmmmwAAGRkZeOWVV7B582akpqbi1VdfxTfffIPU1NSRfDlERESD1ml34cuj9e7gqw4nm/wXuEmPDca8bDn0OjclElq10MudiIjGMZfDuwqjX+DVzxTGYLN/yOX5E5rAKYxENOEwBAsQURSh0WggCALWr1+Pu+66C3l5ecjKysJzzz2HOXPmdLvm8ccfx+OPP459+/YhPT0d77//PqKjowEA/9//9/9h7969uOaaa6BSqXDttdfijjvuwMaNG0f4lREREfWvvs2GbQdrsLW4Bp8eqofN6Z2ar9cImDUlSmlqnxQ5diq8iYjOmLXFO23RE3LVlco9vERnz9eo1EBkaveqrugMTmEkIvKhkiRJ6v+0wGppaUFYWBiam5sRGuq/lK7VakV5eTlSU1NhMIydKREFBQVIT0/H888/3++5FRUVSE1Nxd69e7s1uievsfp3gYhooiivb8fW4mpsOVCDPZUW+P4GkhhuxNxsuan9rLRoGHXq3m9ERDTWeaYweqYt+gZerVW9X6dMYcz0b1AfmcYpjEQ0ofSVE/WFlWAjzGKx4PPPP8eOHTtw2223BXo4REREw8azmuOWA9XYWlyDQ7X+03WmJYZhYU4cFuTGISsuBCpOyyGi8cblABrLvX26PFVd9YcAe2vv1wXHeactxmR5Ay9OYSQiOiMMwUbYTTfdhG+++Qa/+tWvcPnllwd6OEREREPK7hTx5dEGJfiqbbUpxzSCCrOmRGFBThzmT41DQvjprapMRDTqWFuAhkM+VV1l3lUY+53C2KWqKzoDMIaP6PCJiCYKhmAjbMOGDYO+JiUlBWNg1ioREU1QLVYHtpfUYmtxDXaU1qHN5n3DF6zX4JKsGCzMicOcrFiEGbUBHCkR0RmQJKCtxl3JVeb9Wn8IaD3V+3XaIO8UxhhPY/osOQDT6Edu/ERExBCMiIiIBq+quRMfF9dgS3ENvjraAIfL+2FNbIgeC3LisCAnDrOmREGvYX8vIhpDRBFoOuYNuupK5emMdWWArbn363ynMHoqumKygJAEQOCqtkREowFDMCIiIuqXJEkoq2mTG9sX12D/Cf83gumxwViYE4eFuWbkJ4ZBENizhohGOacdaDziU9lVIgddDYcAp7Xna1QCEJEiV3L5VnVFpwPGiBEdPhERDR5DMCIiIuqRS5Sw55hF7u91sAbHGjqUYyoVcPbkCKXiKy0mOIAjJSLqg63N26PLt7KrsRyQXD1fo9YBURnuoMsdeMVkA5FTAC1XISciGqsYghEREZGi0+7CZ4frseVANbaV1KKx3a4c02kEXJQejYW5cZiXHYeYEPayIaJRpL3BPW2xS2VXy4ner9GF+Add0VnyFMaIFEDgVG4iovGGIRgREdEE19hux7aDNdhaXINdh+pgdYjKsTCjFj/MjsXC3DhclBGDID1/dSCiAJIkoOWkf3N6T2VXR0Pv1wXFdAm63JVdIfFyaSsREU0I/E2WiIhoAqps6MAWd3+vbysaIfosQpwYbsTCXHma43kpkdCo2dCZiEaYywlYKrpUdrm/2tt6vy5scs+VXabIERs6ERGNXgzBRqF169bh7rvvRlNTU6/nLF++HE1NTXj33XcBAHPmzMGMGTPwzDPPAABSUlJw99134+677x6yce3YsQNz586FxWJBeHj4kN2XiIiGnyRJKDrZgi3F1dhaXIOS6la/4znxoUrwlRMfChUrI4hoJDisciP6rkFXw2HAZe/5GkEDRKbJTeljsvyb1OuCRnb8REQ0pjAEC5Dly5fj5ZdfBgBotVpMnjwZN9xwAx544IEBXf/ss89CkqRej3/zzTcIChraXwJmz56NqqoqhIWFDel9iYhoeDhcInYfbVSCr6pm72pnakGFH6RGKo3tJ0WYAjhSIhr3rM1yf66ulV2WCgC9/E6rMQLRGV2Criw5ANPoRnL0REQ0TjAEC6CCggKsXbsWNpsNH330EVasWAGtVov4+Ph+r+0viIqJiRmqYSp0Oh3MZvOQ35eIiIZOq9WBnWV12Fpcg09KatFqdSrHTDo1LsmMwcLcOMzNikW4iW8iiWgISRLQXuduSN+lsqu1qvfrDGFyf66ulV1hkwGB07GJiGjo8KdKAOn1epjNZiQnJ+P222/H/Pnz8f777yvHN2/ejKlTpyI4OBgFBQWoqvL+8rB8+XJcccUVvd47JSVFmRoJACqVCi+++CIWL14Mo9GItLQ0/Pvf/1aOV1RUQKVSYf369Zg9ezYMBgPy8vKwc+dO5ZwdO3ZApVIp0zTXrVuH8PDwPscJAP/4xz8wdepUGAwGZGdn469//atyzG63Y+XKlYiPj4fBYEBycjJWr1492G8lEdGEVttixeu7j2H52q9x9h8+xso39uK9fafQanUiOliHn56bhH8tPwff/W4BXvzZ2bhy5iQGYER0+kQRsBwDyrYAX/wFeG8l8M+FwBMpwJ8zgJeXAh/dC3z9d6B8pzcACzYDqZcA5/0CWPJn4Mb/A35VBvzPMeDmLcDlzwOz7wQyF7pXZ+RbFSIiGlrjrhJMkiQ47WL/Jw4DjU44ox4qRqMRDQ3yqjYdHR3485//jFdffRWCIOBnP/sZ7r33Xrz++uunff/f/e53ePzxx/Hss8/i1VdfxU9/+lMUFhZi6tSpyjm//vWv8cwzzyAnJwdPPfUUli5divLyckRFRfV4z/7G+frrr+Ohhx7C888/j5kzZ2Lv3r249dZbERQUhBtvvBHPPfcc3n//fbz11luYPHkyjh8/juPHj5/2ayQimggkScKRujZsKa7BlgM12He8ye94WnQQFuTGYWFOHGYkRUAtsL8XEZ0GlwNoPOqu7PKZythwGHB09HKRCohI7l7ZFZ0BGMNHcvRERETdjLsQzGkX8fdf7uz/xGHwi2cvgVavHvR1kiRh27Zt2Lx5M+68804AgMPhwN/+9jdMmTIFALBy5Ur8/ve/P6PxXX311bjlllsAAH/4wx+wdetW/OUvf/GrzFq5ciWWLVsGAHjxxRexadMm/POf/8R9993X4z37G+fDDz+MNWvW4KqrrgIApKamori4GP/v//0/3HjjjaisrERGRgYuvPBCqFQqJCcnn9FrJCIar1yihH3HLdhyoAZbi2twtL7d7/iMpHAszI3Dwhwz0mODAzRKIhqT7O1Avac5vU/PrsajgOjs+RpBC0SlyyFXTJY38IpKB7TGkR0/ERHRAI27EGws+eCDDxAcHAyHwwFRFHHdddfhkUcewdtvvw2TyaQESwAQHx+P2traM3q+WbNmddvet29fr+doNBqcc845OHjwYK/37Guc7e3tOHLkCG6++WbceuutyjlOp1PpabZ8+XIsWLAAWVlZKCgowGWXXYaFCxee9mskIhpPrA4XPj9cj63FNfj4YA3q27wrpenUAmanR8mN7afGITbUEMCREtGY0NHo7tPlW9lVBjRX9n6NLtjdnL5LZVdECqDmWwkiIhpbBvWTa/Xq1XjnnXdQUlICo9GI2bNn44knnkBWVlaf17399tv43e9+h4qKCmRkZOCJJ57AkiVLzmjgvdHoBPzi2UuG5d4Dee7BmDt3Ll588UXodDokJCRAo/H+59BqtX7nqlSqPleDDJS+xtnW1gYAeOmll/CDH/zA7zy1Wq6YO+uss1BeXo6NGzfi448/xk9+8hPMnz/fr18ZEdFE0tRhxycltdhaXIOdZXXosLuUYyEGDeZlx2JhjhmXZMUgWM83oETUhSTJPbjqSn0qu9yBV3td79eZotwN6btUdoUmAmfQ7oOIiGg0GdRvzzt37sSKFStw7rnnwul04oEHHsDChQtRXFyMoKCgHq/54osvcO2112L16tW47LLL8MYbb+CKK67Ad999h7y8vCF5Eb5UKtVpTUkMhKCgIKSnp4/Y83311Ve44YYb/LZnzpzZ7ZyLL74YgFyxtWfPHqxcufK0ni8uLg4JCQk4evQorr/++l7PCw0NxTXXXINrrrkGP/7xj1FQUIDGxkZERkae1vMSEY01Jywd2Oru7/V1RSNcovdDj/gwAxbkyNMcz0uNhE7DRtFEBEB0AZYK7wqMnsCr/hBga+n9utBJ8sqLXSu7gnru/0pERDSeDCoE27Rpk9/2unXrEBsbiz179ijBSVfPPvssCgoK8Otf/xqAtxfV888/j7/97W+nOWw6HW+//TbOOeccXHjhhXj99dfx9ddf45///KffOS+88AIyMjIwdepUPP3007BYLLjppptO+zlXrVqFu+66C2FhYSgoKIDNZsO3334Li8WCe+65B0899RTi4+Mxc+ZMCIKAt99+G2azGeHh4Wf4aomIRi9JklBc1aIEX8VV/m9Ys80hWJgThwU5ZuQlhp7RoitENMY5bXIjek+fLs9UxobDgMvW8zUqNRCZ6q7s8gm8ojMBPXsGEhHRxHVG8yiam5sBoM+KnS+//BL33HOP375Fixbh3Xff7fUam80Gm837Q72lpY9Ps2jAVq1ahfXr1+OOO+5AfHw83nzzTeTk5Pid8/jjj+Pxxx/Hvn37kJ6ejvfffx/R0dGn/Zy33HILTCYTnnzySfz6179GUFAQpk2bhrvvvhsAEBISgj/96U84dOgQ1Go1zj33XHz00UcQuCQ2EY0zTpeIrysalcb2J5s6lWOCCjg3JVKp+JocZQrgSIkoIKwtchWXpzG9p7LLUgFIvax8rjEAURly0OU7lTEyDdDoR3T4REREY4FKOs1GU6Io4kc/+hGamprw2Wef9XqeTqfDyy+/jGuvvVbZ99e//hWrVq1CTU1Nj9c88sgjWLVqVbf9zc3NCA0N9dtntVpRXl6O1NRUGAxsCtwblUqFDRs24IorrujxeEVFBVJTU7F3717MmDFjRMc2VPh3gYhGm3abE7vK6rC1uAbbSmrR3OlQjhm0Ai7OiMHCXDPmZcciMkgXwJES0YiQJKC93n8FRk9lV+up3q/Th/kEXT6VXeGTAWFstAEhIiIaSi0tLQgLC+sxJ+rLaVeCrVixAkVFRX0GYKfr/vvv96sea2lpQVJS0pA/DxER0VCra7Vh28EabCmuwWeH62F3eis4IoN0+GF2LBbmmnFhejSMOr55JRqXRBFoOeGzAqNP4NVp6f264Dhvny7fnl3BcWxOT0RENAROKwRbuXIlPvjgA+zatQuTJk3q81yz2dyt4qumpgZms7nXa/R6PfR6lnATEdHYcLSuTe7vVVyD7yot8K2xTo4yKf29zk6OgFrgG1miccPlABrLuwRd7q+Ojl4uUskVXMoKjNnuxxmAMWJEh09ERDTRDCoEkyQJd955JzZs2IAdO3YgNTW132tmzZqFbdu2KT2gAGDr1q2YNWvWoAdLp6+/Wa8pKSn9nkNERDJRlPD9iSZsKZb7ex2ubfM7nj8pTAm+MuOC2dieaKyzdwANh7pXdjUcAURHz9cIWiBqSvfKrqh0QMe+f0RERIEwqBBsxYoVeOONN/Dee+8hJCQE1dXVAICwsDAYjUYAwA033IDExESsXr0aAPDLX/4Sl1xyCdasWYNLL70U69evx7fffou///3vQ/xSiIiIho/N6cKXRxqwpbgGHxfXoLbVu4CLRlBh1pQoLMyJw/ycOMSHGQM4UiI6bZ2WHqYwlgJNlQB6+bBQGyRXcSmVXe7AKyIFUGtHcvRERETUj0GFYC+++CIAYM6cOX77165di+XLlwMAKisr/Vb2mz17Nt544w389re/xQMPPICMjAy8++67yMvLO7ORd8EqJuLfASIaas2dDuworcWW4hrsLK1Dm82pHAvWazAnKwYLcuIwJysWYUa+2SUaEyQJaK12B11dAq+2nhdtAgAYI/2DLs9qjKGJAFe1JiIiGhMGPR2yPzt27Oi27+qrr8bVV189mKcaMLVabipst9uVajSamOx2OwDv3wkiotNxqqkTHx+swZYDNfjqaAOcovdnX1yoHvOnxmFhrhnnp0VCr+G/N0SjliQBTceA2pIugVcZYGvu/brQRJ+gy6eyKyh65MZOREREw+K0V4ccLTQaDUwmE+rq6qDVav2q0GjiEEURdXV1MJlM0GjG/F9rIhpBkiShtKYVWw/Ije0LT/q/Oc6IDcbCXLm/V35iGAQ2tica3ToagcK3ge9eAWqKej5HJQARqd0ru6IzAMPAl1knIiKisWXMpwUqlQrx8fEoLy/HsWPHAj0cCiBBEDB58mQ2oCaifjldIvYcsyiN7Ssbvau4qVTA2ZMjlOArNToogCMlogERReDYZ3LwVfw+4HL37BO0XYIu99fIKYDWENgxExER0Ygb8yEYAOh0OmRkZCjT4Whi0ul0rAQkol512l3YdagOW4trsO1gDSwd3hXddBoBF2dEY0FOHOZlxyEmRB/AkRLRgLVUAd+/AXz3KmAp9+6PmwacdQOQfzVgjAjc+IiIiGhUGRchGCBXARkM/ESPiIi8Gtps2FZSi63FNfj0UB2sDlE5Fm7SYl52LBbmmHFxZjRMunHzI5FofHM5gcNb5aqvss2A5JL360Lk0OusG4D4GXJZJxEREZEP/sZPRETjyrGGdmwtlhvbf3usET597TEpwogFOXFYmGPGuSkR0KhZPUo0ZjQeBfa+Bux9HWir9u6fPEsOvnIuB3ScvkxERES9YwhGRERjmiRJKDzZjC0H5P5epTWtfsdzE0KxMMeMBTlxmBofwr6BRGOJwwoc/D9g7ytA+S7vflM0MONaYOYNQExm4MZHREREYwpDMCIiGnPsThG7yxuw5UANPj5Yg6pmq3JMLajwg9RILMyJw/ycOEyKMAVwpER0WqqL5OmO+/8XsDa5d6qA9B/KVV+ZiwGNLpAjJCIiojGIIRgREY0JrVYHdpTKje23l9Si1eZUjpl0aszJisGCnDjMzYpFuIlvjonGHGsLUPQfOfw69Z13f1gSMPNnwIzrgfCkwI2PiIiIxjyGYERENGrVtFjl/l7FNfjySD0cLm+Dr+hgPRbkyI3tZ02JgkGrDuBIiei0SBJw/Gs5+DrwDuDokPcLWiD7UuCsnwNpcwGB/38TERHRmWMIRkREo4YkSThc24Yt7uDr++NNfsfTooOwIFdubD8zKRyCwP5eRGNSez3w/Xo5/Kov9e6PzgTOuhGY/lMgKDpw4yMiIqJxiSEYEREFlEuUsLfSgi3FcmP78vp2v+MzJ4crje3TY4MDNEoiOmOiCBzdDnz3MlDyESA65P1aE5B7ldzrK+k8gItXEBER0TBhCEZERCPO6nDhs0P12FosN7ZvaLcrx3RqARekR2FBjhnzp8YiNtQQwJES0RlrOg7sex3Y+zrQXOndn3CWHHzlLQMMoYEbHxEREU0YDMGIiGhEWNrt+KSkFluLa7CzrA6dDpdyLMSgwQ+zY7Egx4xLsmIQrOePJ6IxzWkHyjbK0x0PbwPg7udnCAPyfyr3+jJPC+gQiYiIaOLhuwwiIho2xxs73I3tq/FNhQUu0dvYPj7MgIU5cViYa8Z5qZHQqoUAjpSIhkRdGbD3FWDfm0BHvXd/ykVyr6+plwFaY+DGR0RERBMaQzAiIhoykiThwKkWZUXHg1UtfsezzSFK8JWbEAoVe/8QjX32dqD4Pbnqq/JL7/5gMzDzemDmz4DItMCNj4iIiMiNIRgREZ0Rh0vEN+WNSmP7k02dyjFBBZybEomFuWYszIlDUqQpgCMloiEjScCpvXLwVfQfwOYOvFVqIHOR3OsrfQGg5q+aRERENHrwNxMiIhq0dpsTO8vqsLW4BtsO1qDF6lSOGbQCLsmMwYIcM+ZlxyIySBfAkRLRkOq0APvflsOvmkLv/ogUOfiafh0QGh+w4RERERH1hSEYERENSG2rFdsO1mLLgWp8fqQBdqeoHIsM0mH+VLmx/YXp0TDq1AEcKRENKUkCKj6Tg6/i9wCXTd6v1gM5P5LDr+QLAYF9/YiIiGh0YwhGRES9qm62YmNRFTYWVuObY42QvH3tkRxlUvp7nTU5AmqB/b2IxpXWamDfG8DeV4HGo979sbnA2TcC064GTJGBGx8RERHRIDEEIyIiP1XNnfiosBobC6vw7TGL37Hpk8KwwB18ZcQGs7E90XjjcgKHP5arvso2AZJL3q8LAaYtk6u+Es4C+P8+ERERjUEMwYiICCebOrGxsAofFVbhu8omv2NnJ0dgybR4LM4zIyHcGJgBEtHwaiwH9r4G7HsdaK3y7k/6AXDWjUDuFYAuKGDDIyIiIhoKDMGIiCao440d2FRUjQ8Lq7DveJOyX6UCznEHXwV5ZsSHMfgiGpccVqDkA+C7l4HyXd79pihg+rVy1VdMVuDGR0RERDTEGIIREU0gxxs78JG74uv7E83KfpUKODclEkvyzFg8LR5xoYYAjpKIhlXNAXm64/frAWuTe6cKmDJPDr6ylgAarupKRERE4w9DMCKica6yoQMfuoOvwpPe4EtQAeelRsoVX7lmxDL4Ihq/bK1A0X/k8OvkHu/+0EnAzJ8BM68HwicHbnxEREREI4AhGBHROFRR364EXwdOtSj7BRVwfloUFruDr5gQfQBHSUTDSpKAE9/I0x2LNgCOdnm/oJGrvc66EZgyFxDUgR0nERER0QhhCEZENE4crWvDR4VV+LCwGger/IOvWVOisGRaPBblmhEdzOCLaFxrbwD2r5ervupKvPujM+Xpjvk/BYJjAjc+IiIiogBhCEZENIYdrm1TenyVVLcq+9WCCrPdwdfCnDhEMfgiGt9EETi6XQ6+Sj4ERIe8X2ME8q6Sw6+kH8gNAImIiIgmKIZgRERjzKGaVnxUWI2PCqtQWuMNvjSCCrPTo3HpNDMW5pgREcTG1kTjXvMJYO/rwN7XgOZK7/6EmXLwlbcMMIQFbnxEREREowhDMCKiUU6SJJTVeCu+DtW2Kcc0ggoXZkQrFV/hJgZfROOe0w6UbZKrvg5/DECS9xvCgPxrgJk/B+LzAzpEIiIiotGIIRgR0SgkSRJKa1rx0f4qfFhYhSN17coxrVqFizJisGRaPBZMjUOYSRvAkRLRiKk/JAdf378JtNd596dcJFd9TV0KaI2BGx8RERHRKMcQjIholJAkCQerWpWKr6P13uBLpxZwcWY0FufFY35OHMKMDL6IJgR7B1D8nhx+VX7h3R8cB8y4Tq76ipoSuPERERERjSEMwYiIAkiSJBw41YKPCquwsaga5b7Bl0bAJZkxWDLNjB9OjUOogcEX0YRxap8cfBW+Ddjcq72qBCBjIXDWjUDGAkDNfxOIiIiIBoMhGBHRCJMkCUUnW/BhYRU2FlXhWEOHckyvETAnS57qOC87FiEMvogmjk4LUPhv4LuXgepC7/7wZHm644zrgNCEwI2PiIiIaIxjCEZENAIkScL+E834qKgKGwurUdnoH3zNzYrFknw5+ArW859moglDkoBjn8tVX8XvAU6rvF+tA6b+SA6/Ui4CBCGw4yQiIiIaB/hOi4homEiShH3Hm7CxqBofFVbhhKVTOWbQCpiXHYsl0+IxNysWQQy+iCaW1hrg+zeA714FGo9498fmyNMd838CmCIDNz4iIiIaMZIkwSE60OnshM1lg81pQ6erEzanDVaXFVanFTaXTTludVphdVm9j51Wv/3Kdpdr//vs/8YV6VcE+uUGFN91ERENIVGUsPd4Eza6e3ydbPIGX0atGvOmxuLSafGYkxUDk47/BBNNKC4ncGSbXPVVuhGQXPJ+XTCQt0wOvxLPAlSqwI6TiIiIIEqiEkgNNIjyC6C6Hu/pmM+9JUjD/ppa7a3D/hyjHd+BERGdITn4suDD/dXYWFSFqmarcsykU+OHU+OwJM+MOVmxMOrUARwpEQVEYzmw9zVg3+tAa5V3f9IP5NUdc68E9MGBGx8REdEY4RJdvQZRnc7ulVMDDaJ6qrqyuWwBeY1qlRoGjQF6tR5GjRF6tR4GjQEGtcHvseccg8bnsc/+btdq9IgzxQXkNY0mDMGIiE6DKErYU2nBh/ursKmoGtUt3uArSKfG/Jw4LM6TK74MWgZfRBOOwwqUfCBXfZXv9O43RsoN7mf+HIjNDtz4iIiIhoAkSXCKzgEFUT0FUr7n9jaFz3d6oFN0BuR1agVtj0GUXuMfSvUZVLnPN6qN8nW9HNcKXBhrODEEIyIaIJco4duKRnzknupY2+r9dChEr3EHX2ZcnMngi2jCqimWg6/96+XVHgEAKmDKXLnJfdYSQKMP6BCJiGh8kyQJdtHuFyz1OoWva1g1yCl8NpcNLs/0/hHmCY0GVTE1gO2uQZVerYda4O/24wVDMCKiPrhECV+Xy8HXpgPVqOsSfC3IicOSafG4KDMaeg1/OBJNSLZWoOgdOfw6+a13f2giMPNnwIzrgYjkwI2PiIhGLafoRKO1EfWd9WjobIDFZkGno3NQU/j8Kqbc54xEf6muBJXgF0j5Pe6nAqqnbaXSSt3zdD8Ve2jSaWAIRkTUhdMl4uvyRnxYWIXNB6pR32ZXjoUaNFiQY8al+WZckM7gi2jCkiTgxLfAdy/LAZijXd4vaICsxXKT+ynzAH5yTEQ04UiShGZbM+o761FvlcMtT8hV31nvt99itQxrYKVRaXqsdOqxAsoTWvUXVPmEVAaN935aQctgikY9hmBERJCDr6+ONuKjoipsLqpGQ7s3+AozarEwJw5L8uNxwZRo6DRCAEdKRAHV3iBPdfzuVaDuoHd/VLo83XH6tUBwbODGR0REw6bD0aGEWA1Wb6DlF265jw2md5VapUakIRLRxmhEGCJg0pj6DKL660vlCarYX4qoO4ZgRDRhOVwivjzSgI1FVdh8oAaNPsFXuEmLRTlmLMmPx+wpUdCqGXwRTViiCJTvkKc7lnwIuNz/VmiMQO4VctXX5PMBfvpNRDTmOFwOJdDqKczy3e50dg7q3mH6MEQbohFtjEaUMQrRxmjlj2c7yhCFcH04e04RjRCGYEQ0oThcIr440oCP9ldhc3E1mjocyrEIkxYFeWYsmRaP89MYfBFNeM0ngX2vA3tfBZoqvfvjZwBn/RzI+zFgDA/U6IiIqBeiJMJitSjBVtcwSwm7rPVotjUP6t5GjdE/zDL0HG5FGiKhU+uG6RUS0eliCEZE457dKeLzI/X4aH8VthTXoLnTG3xFBemwKM+MJXnxOD8tEhoGX0QTm8sBlG2Sq74OfwxIorxfHwbk/0QOv+KnB3aMREQTkCRJaHO0+VVpdavccm83WhsHtWKhRqXptVKra9Bl0pqG8VUS0XBjCEZE45LdKeKzw3X4cH81thZXo8Xq7csQHayTK77y4nFeKoMvIgJQfxjY+wqw7w2gvc67P/lCuddXzo8ArTFw4yMiGqesTmu36Yg9NZCv76yHzWXr/4ZuKqgQYYiQwyxDD9MQffaH6kMhqPj7INFEwBCMiMYNm9OFT8vq8VFhFbYerEGrX/Clx2L3VMfzUiOhFti7h2jCs3cAB9+Xq76Ofe7dHxQLzLgOmPlzIDo9cOMjIhqjnKJTmY7o21urp8qtVkfroO4drA3uuceWIcpvX4Qhgk3hiagbhmBENKZZHS7sKqvDR4VV2HawFq02b/AVG+INvs5JYfBFRG6n9snBV+HbgK1F3qcSgPQFctVX5iJAzTdORES+JElCi72lx75aXcMti9UCCdKA760TdD1OQ+wabkUZo2DUsCqXiE4fQzAiGnOsDhd2lNZhY5EcfLX5BF/mUAMK8sy4ND8eZ0+OgMDgi4gAoLNJDr2+ewWo3u/dHz4ZmHmDXPkVlhiw4RERBUqHo0MOsXoIs7oGXQ7R0f8N3QSVgEhDZLeph92mJBqjEaINgYor7BLRCGAIRkRjQqfdhR2ltfioqBqfHKxBu93b7DQ+zIDFefG4NN+MmUkMvojITZKAY1/IwVfxu4DTKu9X64CpS+Wqr5SLAYF9YIhofHG4HH6N43tdHbGzHh3OjkHdO1QX2m/z+ChjFCL0EVAL6mF6hUREp4chGBGNWh12J3aU1uHDwipsL6lFh0/wlRhulKc65sdjxqRwBl9E5NVWKze4/+4VoPGId3/MVODsG4H8awBTZODGR0R0GkRJRJOtyS/I8q3U8g23mmxNg7q3QW3ocWXEniq4dGrd8LxAIqIRwBCMiEaVDrsTn5TU4qPCKmwvqUOnwz/4ujQ/HovzzJiRFM6yeSLyEl3A4W3Ady8DZZsA0T1NWhsETFsGnHUjkHg2wH83iGgUkSQJ7Y72ATWQb7A2wCW5+r+pm0alQaQxss/m8Z4/Jo2Jv1cR0YTAEIyIAq7d5sS2klp8tL8KO8pqYXWIyrGkSCOWTIvHkrx45E8K4y9oROTPUgHsfR3Y+xrQesq7f9K58nTH3CsBfUjAhkdEE5PNZfMLsvoKt6wu66DuHaGP6HdlxGhjNML0YRBUnO5NROSLIRgRBUSbzYltB2vw4f4q7Cyrg83pDb6So0xK8JWXGMrgi4j8OW1AyQfydMejO7z7jRHA9GuBmT8H4nICNjwiGp+cohMWq6XHQMvTWN6z3WpvHdS9g7RBPfbV8ntsiEakMRJagavXEhGdLoZgRDRiWqwObDtYg48Kq7GzrA52n+ArxRN8TYtHbgKDLyLqQU0xsPdV4Pv1QGejd3/aXOCsnwPZlwEafeDGR0RjjiiJ3YItz9RD33CrobMBFqsFEqQB31sraLv32DJEdeu9FWWIgklrGsZXSUREHgzBiGhYNXc68HFxDTYWVWFXWT3sLm/wlRYdpARfU+O5NDYR9cDWBhx4R676OvGNd39IAjDzZ8DM64GIlIANj4hGH0mS0Gxr7l6xZe0eclmslkH12RJUgjIdMcYYI4dYXZrHe8KtUB0/1CMiGm0YghHRkGvucGDrwRp8VFiFTw/VweHyfmo6JSYIl06Lx5L8eGTFMfgioh5IEnDiW2DvK0DRO4C9Td4vaIDMArnJffoPAUEd2HES0YiRJAmtjtbeq7V8+m41Whvh9CyOMUCeYKtrxZYn4PIci9BHQM1/e4iIxiyGYEQ0JJo67NhSLAdfnx+u9wu+MmKDsWRaPC7Nj0dmHBtUE1EvOhrlqY7fvQLUHfTuj5wiN7mffi0QEhe48RHRkJIkCR3Ojh6DrJ6CLrtoH9T9Q3WhPQZZXftuRRgi2GeLiGiCYAhGRKfN0m7HluJqfFhYjS8O18MpeoOvrLgQ91RHMzIYfBFRb0QRKN8pB18lHwAu95tcjQHIuUIOv5JnA6waJRozOp2dA6rYOp2VEYO1wYg2RiPSENlrv60oYxQiDZHQqXXD9AqJiGisYghGRIPS2G7H5gPV+KiwCl8caYDLJ/jKNofg0mnxWDwtHumxwQEcJRGNepYKYN8bwL43geZK735zvhx8TbsaMIYHanRE1IXNZVNCLd8gyzP90Dfk6nB2DOreJo3JL8jqbVpilCEKBo1hmF4hERFNBAzBiKhf9W02Jfj66mijX/CVEx+KJdPMWDItHmkxDL6IqA/2DuDg+8De14CKT7379WFA/tXAzJ8DCTMCNjyiicbhcqDBKldqKeFWL9MSWx2tg7q3Xq33C6+6TkvkyohERBQIDMGIqEd1rTZsOlCNjYVV+OpoA3xyL+QlhmJxnryqY2p0UOAGSUSjnyQBx78G9r0GFG0A7J430iog7RJgxs+AqZcBWmNAh0k0XjhFJyxWS7cgy7OtVHNZ69Fsax7UvbWCtluQ1du0xCBtEBe/ISKiUYchGBEpalut2FQkV3x9Xd7oF3xNSwxTenwlRzH4IqJ+tFQB378pT3lsOOTdH5ECzLhebnIfnhSw4RGNJS7RhSZbU/cgyzfocu+3WC2QIPV/UzeNSoNIQ6RfdVa3aYjuiq1QXSiDLSIiGtMGHYLt2rULTz75JPbs2YOqqips2LABV1xxRa/n79ixA3Pnzu22v6qqCmazebBPT0RDrKbFio2FVfioqBrfVDRC8vm9efokT/AVj6RITlUgon44bUDpRnm645FtgCTK+7Umucn9zOuBybMBQQjoMIlGA1ES0WJr6dZfq6eQq9HaCNHz/9MACCpBDrZ6CLK6TksM04dBUPH/SSIimhgGHYK1t7dj+vTpuOmmm3DVVVcN+LrS0lKEhoYq27GxsYN9aiIaItXNVmwsqsJHhVX49pjFL/iakRTubm5vxqQIBl9ENABV3wN7XwcK3wI6Ld79SefLwVfulYCeq8TS+CdJElodrX69tHqbltjY2Qin5BzwvVVQIcIQoUw/7NZfy6ehfIQ+AmpBPYyvlIiIaGwadAi2ePFiLF68eNBPFBsbi/Dw8AGda7PZYLPZlO2WlpZBPx8R+TvV1ImN7qmOe45Z/I6dNTkcS9yrOiaGsy8PEQ1Ae4Mceu19Hagp9O4PiZenOs64HohOD9z4iIaIJElod7T33V/LJ+hyiI5B3T9MH+at0OqyMqLvtMQIQwQ0AjuZEBERnYkR+0k6Y8YM2Gw25OXl4ZFHHsEFF1zQ67mrV6/GqlWrRmpoROPWyaZObCyswoeFVdhb2eR37JzkCCyZFo+CPDMSGHwR0UC4nMDhj+Um96WbAM+bfbUOyL5UbnI/ZS7AChQaAzocHb3313I3jvccs7qsg7p3iDbEL8zym4boG3YZoqBVa4fpFRIREVFXwx6CxcfH429/+xvOOecc2Gw2/OMf/8CcOXOwe/dunHXWWT1ec//99+Oee+5RtltaWpCUxOa5RANxvLEDG4uq8GFhNb4/3qTsV6mAc5MjsXiaGYvz4mEOMwRukEQ0ttSVycHX9+uBthrv/vjpcvA17ceAKTJw4yPqot3RjjJLGY40HfH22ups8Au5Opwdg7qnSWPyC7J6nZZojIJerR+mV0ZERERnYthDsKysLGRlZSnbs2fPxpEjR/D000/j1Vdf7fEavV4PvZ6/PBAN1OHaNmw+UI1NRdUoPOld7lylAs5LiVQqvuJCGXwR0QBZm4Gid4B9rwMnvvHuN0UB+dfI0x3NeYEbHxHkqYo1HTUobSxFqaUUJY0lKG0sRWVr5YCuN6gN3ootQ98rI5q07JNJREQ01gWkscB5552Hzz77LBBPTTQuSJKEA6dasPlANTYWVeNwbZtyTFAB56VG4tJp8ViUZ0ZsCIMvIhogUQQqdsl9vg7+H+DslPer1EDGQrnJfcYiQKML7DhpQnKIDlQ0VyhBV4lF/tpka+rx/FhTLDIiMmA2mf1WRvSt5jJpTFCpVCP7QoiIiChgAhKC7du3D/Hx8YF4aqIxSxQlfFdpwaaiamw6UI0Tlk7lmFatwgXp0SjINWN+Thyig1lJSUSDYKkA9r0J7HsDaPapoInOAmb+TK78CokL2PBo4mm1t6LMUuYNvBpLcKTpCOyivdu5apUaqWGpyIrMQnZENrIis5AVmYVIA6foEhERkb9Bh2BtbW04fPiwsl1eXo59+/YhMjISkydPxv3334+TJ0/ilVdeAQA888wzSE1NRW5uLqxWK/7xj3/gk08+wZYtW4buVRCNUw6XiK+ONmBTUTW2FNegrtW7aqpBK2BOZiwK8syYNzUWoQY21iWiQbB3AAffB/a+BlR86t2vDwXylsnhV+LZ8rxqomEiSRKq26tR0liiVHaVNpbiRNuJHs8P0gYhK0IOubIj5cArPTydPbiIiIhoQAYdgn377beYO3eusu1pYH/jjTdi3bp1qKqqQmWl91Nku92OX/3qVzh58iRMJhPy8/Px8ccf+92DiLysDhc+PVSPTUXV+PhgDZo7vUuthxg0mD81DotyzbgkMwZGHVdgI6JBkCTg+Ndyk/uiDYC91X1ABaRdIje5n3oZoOWKsTT0HC4HjjYflau7LKVKhVeLvaXH881BZqWyKzsyG1kRWUgMSYSgEkZ45ERERDReqCRJkgI9iP60tLQgLCwMzc3NCA0NDfRwiIZcm82JT0pqsbmoGttLa9FhdynHooJ0WJgbh4K8eMxKi4JOw1/+iWiQWqqA/evlXl8Nh7z7w5Pliq/pPwXCJwdufDTutNhblKouT+h1uOkwnKKz27kalQZp4WlK0JUVmYWsiCyEG8JHfuBEREQ0JpxuThSQnmBEBFja7dh6sAabi6rx6aF62F2iciwhzIBFeWYU5JpxTkok1AKnIxHRIDltQOlGeXXHwx8DkvvfGK0JyLlcXt0x+QJAYLBOp0+SJJxqP+XXu6u0sRSn2k/1eH6INkTp2ZUVIVd4TQmfAp2aiy0QERHR8GMIRjSCqput2FJcjU1F1dhd3giX6C3ETIsOQkGeGQV5ZkxLDONqVUR0eqq+lyu+Ct8COi3e/Unny6s75l4J6EMCNz4as+wuO440HfGbzljaWIpWR2uP5ycEJfj17sqOzEZCUAJ/vhEREVHAMAQjGmbHGtqx+YAcfH1X2eR3LCc+VAm+MmKD+caAiE5Pe4Mceu19Hagp9O4PiQemXytXfUWnB258NOY0WZtQapEruzyrNB5tOgqn1MN0RkGD9PB0pbIrKzILmRGZCNOHBWDkRERERL1jCEY0xCRJQllNGzYVVWPTgWocrPJv+Ht2cgQKcs1YlGvG5ChTgEZJRGOeywkc2Sav7li6ERDdi2iodUDWErnX15R5gMAFNKh3oiTiZOtJJfAqbSxFiaUE1e3VPZ4fqgtVgi5P6JUWlgatmisUExER0ejHEIxoCEiShP0nmrGxqBqbD1SjvL5dOaYWVDg/LRIFuWYszDUjLtQQwJES0ZhXVyav7vj9/wJtPkFF/HR5dcdpPwZMkYEbH41aNpcNh5sO+/XuKrWUot3R3uP5k4InITsyG5mRmciOyEZ2ZDbMQWZWLRMREdGYxRCM6DS5RAnfVDRikzv4qmq2Ksd0GgEXZ0RjUa4Z86fGISKIDX+J6AxYW4AD78hVXye+8e43RQH518jTHc15gRsfjToWq8Wvsqu0sRTlzeVwSa5u52oFLdLD0/16d2VGZCJEx95xRERENL4wBCMaBLtTxOdH6rG5qBpbi2vQ0G5Xjpl0aszNjkVBrhlzs2MRrOf/XkR0BkQRqPhUXt2x+H3A2SnvV6mBjAXydMeMRYCGIftEJkoijrce96vsKmksQW1HbY/nh+vD5aArwht4pYSlQCtwOiMRERGNf3yXTtSPDrsTu8rqsKmoGtsO1qLV5m0KHGbUYkFOHApyzbgwIxoGLXvvENEZshwD9r0BfP8G0FTp3R+dJa/umP9TICQucOOjgLE6rTjcdBgljSV+oVenJyDtYnLIZCXo8lR3xZniOJ2RiIiIJiyGYEQ9aO504JOSGmwqqsbOsjpYHaJyLDZEj0W58oqO56VGQqsWAjhSIhoX7B3Awffl6Y4Vn3r360OBvGVy1Vfi2QDDiwmjobNBmcroCbwqWiogSmK3c/VqPTLCM+Rm9T7TGYO0QQEYOREREdHoxRCMyK2+zYatxXLw9cWRejhcknIsKdKIAnfwNTMpAoLAN6JEdIYkSe7vtfc1oOgdwN7qPqACUi+Wg6/sywAdV5Edz1yiC5WtlUqz+hJLCcoay1DXWdfj+ZGGSGVVRk/glRyaDI3AX+mIiIiI+sPfmGhCO9nUic1F1dh0oBrfVjRC9OZeyIgNxuI8MxblmZETH8rpI0Q0NFqqgP3r5SmP9WXe/eHJcoP7GdcC4ZMDNz4aNh2ODhxqOiRPY3RXeR2yHOpxOqMKKiSHJitBlyf4ijZG8+cRERER0WliCEYTztG6Nmx0r+i4/0Sz37H8SWFYlGvGolwz0mODAzRCIhp3nDagdKPc5P7wx4BnSpvWBORcLodfyRcAAqdXjweSJKG+s16exmgpVaq8jrUcgwSp2/kGtQGZEZnewCsyCxnhGTBpWQVIRERENJQYgtG4J0kSiqtalIqvspo25ZhKBZybEomCXDMW5sZhUgTfcBDREKraLwdf+98COhu9+5POl5vc51wBGEIDNjw6cy7RhWMtx5SpjJ7Aq9Ha2OP50cZov9UZsyKzkBySDLXAhVWIiIiIhhtDMBqXRFHC3uNN2FRUhU0HqnG80TvVRCOoMDs9GgW5ZizIiUNMiD6AIyWicae9ASh8G9j3GlBd6N0fEg9M/6lc9RWdEbjx0WnrcHSgzFLmtzrj4abDsLqs3c4VVAJSQlOQFZHlV+EVbYwOwMiJiIiICGAIRuOIwyXi6/JGbHJPdaxttSnHDFoBl2TGoCDPjHnZcQgzagM4UiIad1xO4Mg2ucl96UZAdMj71Toga4nc5H7KPIDVPmOCJEmo7ahFqaVUCbtKLaWobKnscTqjUWNEZkSmt1l9RDbSI9Jh1BgDMHoiIiIi6g1DMBrTrA4XPjtUj00HqvHxwRo0dTiUYyF6DX44NRYFeWZcnBkDk45/3YloiNUfkoOv79cDbdXe/eZ8YObPgWk/BkyRgRsf9cspOlHeXO7Xu6u0sRQWm6XH82ONsX6VXdmR2UgKSYKgYj83IiIiotGOqQCNOW02J3aU1mJTUTW2l9Si3e5SjkUG6bAwJw6L8syYPSUKeg2rLohoiFlbgAPvAHtfB0587d1vigKm/UTu9WWeFrjxUa/a7G3KdEZPlddhy2HYRXu3c9UqNVLDUpXKrszITGRFZCHKGBWAkRMRERHRUGAIRmOCpd2Ojw/WYPOBauw6VA+7U1SOmUMNKMgzoyDPjHOSI6BR89N4IhpioghUfCo3uS9+H3C6+wyq1EDGArnPV2YBoNEFdpwEQJ7OWNNR49e7q6SxBCfaTvR4fpA2SOndlRUhV3dNCZ8Cg8YwwiMnIiIiouHEEIxGrdoWKzYX12BTURW+OtoIl+jtw5ISZUJBXjwK8szITwyDIKgCOFIiGrcsx4B9bwDfvwE0VXr3R2fJFV/51wAh5sCNj+AQHTjadFSp7CprLEOJpQTNtuYez48zxflNZcyOyEZiSCKnMxIRERFNAAzBaFSpbOjA5gPV2HSgGt9VWiD59B+eGh+Kgly54iszLhgqFYMvIhoG9g7g4P/JqzuW7/Lu14cCecvkJveJZwP8N2jEtdhbUNpY6p3S6F6d0SE6up2rUWmQGp6K7Ahv4JUVkYVwQ/jID5yIiIiIRgWGYBRQkiThcG0bNhZVY1NRNYqrWvyOz5wcjoJcMxblmpESHRSgURLRuCdJwIlv5Cb3BzYANp9/i1IvkYOv7MsAnSlwY5xAJElCVXuV31TGUkspTrad7PH8YG2wX9Dlmc6oU3N6KhERERF5MQSjESdJEgpPNmNTkVzxdbSuXTmmFlT4QWokCvLMWJhjhjmM/ViIaBi1VgPfvylPeawv8+4PT5b7fM24FgifHLjxTQAO0YEjTUe6BV6t9tYez08ISpB7d7kb1mdFZiExOJHVwURERETUL4ZgNCJcooRvKxqx6UA1thyowcmmTuWYTi3gwoxoFOSaMT8nDpFB/OSeiIaR0w6UbZRXdzz8MSC5V5jVGIGcy+Wqr+QLAIE9ooaap8Jrf/1+FNYVorC+EMUNxbC5bN3O1QgaTAmb4u3dFZmNzIhMhOnDAjByIiIiIhoPGILRsLE7RXx5tAGbiqqxtbga9W3eJehNOjXmZsViUZ4Zc7NiEGLQBnCkRDQhVO2XV3fc/xbQ2ejdn/QDueor90rAEBq48Y1DrfZWHGg4gMK6QiX4arA2dDsvRBuC7CjvVMbsyGykhaVBq+bPhtFEkiR5pVSXC5LLBcklAqL8GH7bIuByDmpbcjkBUXTfayDbLu+9RBckZy/bogSVoAJUAiAIfo8hqKAS1O6vQvdz1ILPflX3x92u9Xk8gGtVgkoeh0rwewxBBZVa3W2/8ri3awVBrojseq1nv+9jIiKiCYohGA2pTrsLO8vqsPlANT4+WINWq1M5FmrQYH5OHBbnxeOijGgYtOoAjpSIJoSORjn02vcaUF3o3R8SD0z/qRx+RWcEbnzjiFN04pDlEArrC7G/bj8K6wtR3lwOCZLfeRqVBpmRmZgWPQ35MfmYFj0NyaHJI7Y6o1+QI4o+4YlLDll6C1MGuu1yKUGNX8DjEiGJPoGO37bPGLoGPJ779TMG5V6iC+hx2/ua4XQObtvl/f7QONA1EOsSoPnug6CCSgkHhZ6vU0JDdff7CV2v9d7P77Fa6Hm/ElT2fq1K3UOA6XuOXyDpf4732tMIM9Vq+TVrtFBpNFBpNVBpNIBGI+9zbyv7tFplW9nHQJKIaMQxBKMz1mJ1YHtJLTYWVmNHWS2sDu8vydHBeizKjUNBnhnnp0VBq+b0IiIaZi4ncOQTOfgq3Qi43FWoah2QtUSe7pg2F1DzR+BgSZIEOJ0QbTZUN53AwarvUVZzAEdqD6Ky4Qgkux1apwStE4h2AfFOIFYdgWRDPCbp45Cgi0a0EAZ1rQuizQ7J/h0k25eostu9QY9PgNN7wOMJaE4j4HG5Av1tHL8EwRsMCO5QZLDbggBo1HLwoRbkr122VRq1XA2ldldFdd323NMTcEgSIImQRHcA6nnsckGSRMC93/cxJNEdMoq9niOJrp73ex67XN7QVRS7PBbdf8e77vd57P7a2zm+x/2W0+6PJI8NLpdfRD2IO9BQ8QnFVBoNoNV4Q7XT2qfxC+W89+9ln19w11N457/d6z6tloEeEY0ZfAdAp6WhzYatxTXYdKAanx+uh8Pl/dUpMdyIxXlmFOSZMXNyBNQCfygS0QioPySv7vj9eqCt2rvfnC8HX9OuBkyRgRvfEJCcTkg2G0S7HZLdDslmk7dtdkh2m7JPtNkg2dzn2PvYtsnXiPY+tt3P57J1AjYHVD5vthPdf+b2OeoG958iAEDTcH1zhspQBDlqnwBHLUCl1vhvDzbIEXzuqVb7bws++9Vqv23PuV23e33Ofsfk8/rc257n5TS7wJIkSQ63fIMylzwdFJJPqOYJ0Fyiz/4ezul2bZdzxJ72+zx2ecJGdyDY5Rw59Ja6naM8Fl097/c87uH+3mt9xtjn/buEon0EpH7neO7vmRbsdEJyOgCH0/3Y+wcOh/dxT5WUnnNH/q/M0FOruwdjviGf1h2gddvXJdAbyL6uVXcDqcQbSMDnGTN7ghKNawzBaMBONXVi84FqbCqqxjcVjRB9fmKnxwajIFcOvnITQvmLMBGNDGsLcOAducn9ia+9+42RQP41wMzrAfO0IXkqyemUAyKbN2xStn1CKP+AybOv67b3HFEJr3re9g29AlnF1NO/6k61CpJWDZVeD43BBK3eCEGvh8r9R9DroNLqlG2VXgdBp4NK57Ot10Ol1brDFU238MgTwAxZkKNRe4Mu97YnvGKQQ2OVSqXyTnNEz/+/UmDJ06/9gzHJ6YTkcAJOh9+25HR4A7Ke9imBWx/7/EK5ge5zj6Xrvi5j7vFnkScUtHVf6GTMEYTew7yBVuedaZjn8/NvwD/P/D6o8PmZqfY9T/AGfUr1LYM/mlgYglGfyuvbsamoGpsOVOP7401+x/ISQ7E4Lx6LcuOQHhsSmAES0YTg+cVastshWq2Qjn4O6ft3IJbtgOSwQXKpIIlGiHEzIE2aDSlyKqRmF6TN30G0feUTWrmroOwO/22bt7JKqYJStuWvo24anVYLQavtEjDpodLpet/W6+UASqeDSi+HUW0qG07aanHcVo0K6ymUW0+gXWWHQw04NCrYNYBDA0QGxyHdPBVZcdOQmzADWXF5MOmCAv1dICIaE1SCAJVOB+jG/iroylTzvsK8PgI+OWxz77M7Rl+gJ4ruyml792PjWddQbMAVzz1PZfeEdr19uCWHdj2Eff1WQgvdKp+7bQs+Vdg+231VNve4LfiMsddtNT9AG2MYgpEfSZJQUt2KjUXV2FxUjdKaVuWYSgWckxyBRblmLMo1IynSFMCREtFIkpxOiO3tEK02SA7faXjuwMjRzzS8gUy7U67x3l8+xw44nb2MrOtqjsfcf4aZRiNXNOm9IZPgDpW6hVB6b+jUbdsTSun1UOm03ioqXZdt9zV+z6ke/OIi7Y52HKg/oKzUWFhfiLrOOkALINh7XrA2FLnRuciPlhvXT4uZhmhj9NB9/4iIaMxSCQKg08mh3hgnSVL/1XkDDfS67vMJ83rd120arcO7uEl/PS+VhVj62FZW1R3A4iae6x2O8TFFdyT1EBoqVeaeUPCMemT20jOzp5YLXavou1QRmmbNgjE3N9DfsYBiCEYQRQn7TjRhs7vi61hDh3JMI6gwa0oUCvLMWJATh9gQQwBHSkSnQ3I6Iba1wdXWBrG1Fa7WVojK4zaIba1wtbTK222tEFvdx9q8X6WOjv6faKSoJKjUkAMhUzBUxmD/gMk3UOoaMPlOw1MCJb27Kso3lPI89p4juM9R6XTyVIVRziW6cLjpMArrC5UVG482H4Uo+f8SrFapkRGRIYdd7hUbU8NSR2y1RiIiokBRqVTjJtDrj7Kohico81nV2H9bBFzOvreHanVk0eUT3vlu97RCcR+rJvvcu9fnHsjqyX0Ei33y9Av0fK+H/b/m6Yt78EGGYIEeAAWG0yXi6/JGbDpQjc0HqlHT4p2/r9cIuDgzBgW5ZsyfGocwkzaAIyWa2CSXSw6w3GGVX3DV2uoNtZR9bd3CLHEoAyxBgMpg6DYNT65S6n1bCZR0Pr2ieuoN5QmZmo5AOLoJqiNboXK1QqWWIKgB1ZSLoDr750D2ZYCO1ai+atpr5LDLXeV1oOEAOp2d3c4zB5nlsCs6H9NipmFq5FSYtPxeEhERjWcqlcpbcUSD1ldVnrL4RZfwTHJX4HmDRp9tUfQJErtuDz6Q7H9lbXlbPyUt0N/KgGMINoHYnC58frgem4qqsbW4BpYOh3IsWK/BvOxYFOSZcUlmDIL0/KtBdKYkUfRWXHWpwnK1tPQeXHn2tbQMaYCl0ushhIRAHRIifw0OhhASAiEkGOpg99eQEAjBIVCHyl+VfSEhUAcFDe8npa3V8sqO374O1JfJ+/QAwicDM64Hpl8LRCQP3/OPIR2ODhxoOCBXedXJwVdtR22380waE/Ki85QpjfnR+YgxxQRgxERERERjl0oQ5A+DAUCvD/Rw6Aww6Rjn2m1O7Citw6YD1dheUos2m7evToRJi4U58oqOs9OjoNfwUwEiD0kU5R5Y/VZeyY/9phG6zxPb24dsPCqdDkJoqBJcqUOCvSFVcIh3X0iof5gVEqwEXqOy1N9pB8o2yqs7Hv4YkNzl5hojkHO5vLpj8oXKimcTkUt04UjzEaWH1/76/TjSdKTbtEZBJSAjPEMJu/Ki85AWlga1wH/biYiIiIgAhmDjUlOHHR8frMWmomrsOlQHu9P7RskcasCi3DgsyjPjvJRIaNQT940ljV+SKELs6Bh45ZWnUqulRanYEtvbAWloZvSrtFq/AKtbcNVT5ZVPgCWEhEAYjQHWmagulIOv/f8LdDZ69yf9QK76yr0SMHRtej8x1HbUKtVdhfWFOFB/AB3O7hWBcaY45MfkK728cqJyOK2RiIiIiKgPDMHGidpWK7YcqMHmA9X48kgDnKL3zXtylAkFeWYU5JoxfVI4BIFLuNLoJUkSxPYOn/5XPfXB6hJmtXZp6t7WNrQBVi/BlRxY9Vx5JQR7pxEKLJmWdTQChW8De18Dqvd794fEA9N/Kodf0RmBG18AdDg6UNxQ7Ne8vqajptt5Ro1Rmdbo6eUVa4oNwIiJiIiIiMYuhmBj2PHGDmw+UI1NRdXYU2nxe8+fbQ7Bolx5qmO2OURuhEg0zCRJgtTR4a2q6iu4amuF2NJDNVZbW/9LOA+UVuudPthjFVZPoZZ/mKXS6/n/z5lwOYEjnwD7XgNKNwIuu7xfrQOyFgMzfgZMmQeox/+PI5foQnlzuV/z+sNNh+GS/FccElQCpoRPkcMudy+vKWFTOK2RiIiIiOgMjf93HePM4dpWbCqqxqYD1Sg62eJ3bEZSOAryzFiUa0ZqdFCARkhjlSRJkDo7/fteKc3cu/S/am3xD658A6z+lhAeKI2m5+AqOFieWthHcCUEB0MdGsoAK5DqD8kVX/v/F2it8u435wMzfwZMuxowRQZufCOgvrMe++v2K83rixqK0O7o3icu1hiLaTHylMb8mHzkRuVyWiMRERER0TBgCDbKSZKEopMt2HSgCpuKqnGkzvsGSlAB56VGoiDXjIW5ZiSEGwM4UhoNxI4OOKprILY0dw+u3JVX/tVY7v5X7sdDFmCp1T4BVohPM/eQ3lcj9Ol/pQ4JgcpgYIA11lhbgAMbgH2vA8d3e/cbI4H8a+Qm9+ZpgRvfMOp0dsrTGt3N6wvrC1HVXtXtPKPGiNyoXKV5/bToaYgLigvAiImIiIiIJh6GYKOQS5TwXaVFrvgqqsbJpk7lmFatwoXp0SjIM2P+1DhEBbPX0EQhSRJc9fVwVFXBcaoKjlOn3I9PwVF1Cs6Tp+Bqbj7zJxIE/+BqEJVXnn0qo5EB1kQhisCxz+Qm98XvAU73v1cqAUhfIAdfmYsBzfhp7C9KIsqby71VXvWFOGQ51G1aowoqeVqjT/P6KeFToBH4o5eIiIiIKBD4m/go4XCJ+PJIAzYdqMaWAzWob7Mpx4xaNeZkxaAgz4y52bEINWgDOFIaLqLdDmdVlRxsnfQPuBynTsFZVQ3Jbu/3PkJQENRhYd6KK0/j9h6buod4VyZ0B14qk4kBFvWvqRLY96Zc9dV0zLs/OlNucD/9p0CIOXDjG0L1nfVKhdf++v04UH8AbY62bufFGGOUHl750fnIjc5FkJZT04mIiIiIRguGYAFkdbiwq6wOm4qq8fHBGrRYncqxEIMGC6bGYVGeGRdnxMCoY0PksUySJIjNzT7VW90ruVx19f3fSKWCJjYW2vh4aBMSoE2IhyYhwb2dCG1CPNQhIcP/gmhisncAJR/Ivb7KdwFwr8ahDwXyrpKb3E86BxjDIarVacXBxoN+vbxOtZ/qdp5RY8TUyKlKlVd+TD7iTHEMkImIiIhoVJAkCaJTgtMpwml3weUQoQ/SQm+c2DHQxH71AbKjtBZvfXsc20vq0OnwTp+JDtZhQY4Zi/PMOD8tCjqNEMBR0mBITiecNTXeUOtUVZdKripIHR393kdlMPgFXNqEBGiU7QRoY2Oh0o2faWU0BrgcwNEdQNE7cgBm81mQI/USucl99mWAbuw1chclERXNFcqUxv11+3HIcghOyel3ngoqpIWl+TWvTw9P57RGIiIiIuqXKEpwOUQ4HS73V9Hnq6vLtu/X7sd6u0/Xe7kcIpxOUfnM2uOS67KQd3FiYL4RowR/gw+A7yqb8FFhNQAgMdyIRblmFOSZcXZyBNQCqwhGI1dbO5zuaYl+0xXdQZezpkbujdQPdVSUHHJ1q+RKgDYxAerwcFaSUOC5nEDFLm/w1WnxHguf7J7ueC0QkRy4MZ6Ghs4GJewqrC/EgfoDaHW0djsv2hithF3ToqchNyoXwbrgAIyYiIiIiIaCUhXVa+jUZb9ThNPeJXRyinDZPV9d/uf5fvUNqewiRFHqf4DDTQVoNAKk0TCWAGMIFgBL8+PhdIlYnBePvMRQhh4BJokinPX1cPpOT/SdrlhVBXEgDee1WmjNZjncio/vXskVHw/BYBj+F0R0OkQXcOxzeXXH4veBDp/puUGxQM7l8pTHpPMBYfRXqVqdVpQ0lvg1rz/ZdrLbeQa1ATlROX69vMxBZv67TERERDQMulVFKcGRN4jy7BvuqqhAENQqqLUCNFrB/VWtbHfd53+e+7FGDY3O/5haI0CjU/ud69mn1grQaAQIGhV/v3VjCBYAGXEhuK8gO9DDmDBEm83dWL7ngMtZVQXJ4ej3PkJoqE/A5Z6uGO8JuhKgiYmGagyEA0QKUQSO7wYOvCOv7NhW4z1migKm/kgOvpIvAITR25dQlEQcaznmV+VV1ljWbVojAHlao0+VV3pEOrQCFxshIiKiiWPQVVFdwqjxUhWl1skBkVrrDow0ghwwaTwBkztY8j2vh/Cqv/2+oZbAmV8BxxCMxjRJkuBqanKHW+6gy29lxSq4Ghr6v5EgQBMX5w244uOhTZS/eiq51MGcDkXjgCQBJ76Vg68D7wKtPk3fDeHA1KVA7pVyvy/16PwR0WhtRFF9kV+VV6u9+7TGSEMk8qPzlV5eedF5CNFx4QgiIiIafUSXiM42B6xtjtOqivKETeOtKsqvoslznhJWeaui/AIsT1VUl32siiKAIRiNcpLDAUdNTZ+VXFJnZ7/3URmN3ubyPVVyxcZCpWU1CI1TkgSc2usNvpqPe4/pQ+XG9rlXAmlzAM3oWnjB5rLhYMNBOfSq34/CukKcaDvR7Ty9Wo+pkVOVKY3TYqYhISiBv+AQERFRwLgcIjpa7ehstaOjRf7jedzZYkdHq0PZtrY7AhZMdatm8lRF+e1X91D1xKooGnsYglFAuVpb3aHWSWVqom8ll7O2Vn4D3w91dLR/wNWlkosN52nCkSSgutAdfG0ALBXeY7pgIGsxkHsVkP5DQKMP2DB9SZLUbVpjqaUUTrH7tMbUsFR5WqM78MqIyOC0RiIiIhp2dqsTnT7hlV+wpXx1oKPFDntn999h+qQCDCYtNPohrIrqYaqfJ+hiVRRNRAzBaNhILhec9fXuUKvnSi6xtfsUpq5UWi00CfHyCopdK7kSEqAxmyHoR8ebeKKAqyn2Bl8Nh737tSYgc5EcfGUsALTGwI3RzWK1KNMZC+vkry32lm7nRRoi5cb17ub1edF5CNWFBmDERERENN5IkgR7p9MnxHJ4H7e6K7Z8Ai6nvf8V4X0JahWMIToYQ7QwhepgCtHBGKqDKVQHY4j/tiFYy+ooomHGEIxOm9jZ6a7Y8qnk8p2qWF0NOPv/9EMdFgZNYoIccnUJuLTx8VBHRbHhPFFf6srk0OvAO0BdiXe/xiAHXrlXyQGYLihgQ7S77ChpLPGr8jreerzbeTpBh6lRU/2a1ycGJ/ITSiIiIhowSZRgbZfDLP8gy9E92Gq1Q3QObh6iWiv4hVemEG2vwZbepOHvMUSjCEMw6pEkSXA1NvpUbfk0nnfvc1ks/d9IrYY2Lk6u5ErwCbrcUxW18fEQggL3xpxozGo44g6+NgA1Rd79ah2QPl8OvrIKAP3IN4KXJAnHW48rPbwK6wtR0lgCh9h9FdaU0BSlwis/Oh+ZEZnQqjmtkYiIiPy5XCKsrT7Bll9vLU+wJU9T7GxzQBrkKoRagxqmEHeQ5Vux5Qm4fIItrV7NYItojGIINkFJdrvccF7pv9W9kkuy2fq9j2AyQZuYAI1nmqJnyqJnqmJMDFQa/jUjGhKWY96Kr6rvvfsFDTBlntzcPmsJYAwf0WE1WZuUaY376/ejqL4IzbbmbudF6COUlRo9qzWG6cNGdKxEREQ0ejgdLneQ5VCqsroFW60OdHoaxw+SPkjTPdjqFnRpYQrRQaNTD8MrJKLRhunEOCRJEsTW1i79t9yVXKfkFRWddXUDajiviYmRwyzfSi6fqYpCaCg/BSEaTs0n5BUdD7wDnNzj3a9SA2mXyMFX9mWAKXJEhuNwOVDSWCJXebl7eVW2VnY7TytoMTVqqty43l3pNSl4Ev+9ICIiGsckSYLD5lKmHnrCLL9gy2fbbnUN6v4qFWBwTzc0hcoVWkZl2xtsmUJ1MIRooVazpQoR+WMINgZJTiecdXVyBVe3Si45+BLb2/u9j0qvd/fgivdWciUkeveZzRB0uhF4RUTkp7XaHXxtAI5/5d2vEoDkC4C8q4CpPwKCood9KDXtNfi+7nvsq9uH72u/x8HGgz1Oa0wOTVYqvPJj8pEVkcVpjUREROOAJEmwdTh7Xg3RU6nls+10DL5xvKeXltEdbim9tbpUcLFxPBGdKYZgo5DY0eFtLt9TJVdNDeDq/1MTdUSE0n9LE+9bySVXc6kjI1mVQTRatNUBB98DijYAxz4H4KnUVAGTZ3mDr5C4YRuCQ3SgzFKGfbVy4LWvbh+q2qu6nRemD5PDruh8ZXojpzUSERGNHaIowdrm6DnYavX21vJsi67B9dfS6IQuwZbOP9gK8QZdbBxPRCOJIVgAuJqaYK+s9Am4vEGX8+QpuJq799LpRqOBNi5OCbT8KrkS3A3njcbhfzFEdPo6GoGD7wNF7wAVnwKSzyenk86Tg6+cy4HQhGF5+iZrE/bX78e+2n3YV7cPRfVF6HR2+p0jqARkRmRiesx05U9SSBJ/WSUiIhplXC7R21ury+qHnV2CLmubYyCdUfzojBolvPJtEu+/GqIWxhAddAa+zSSi0Yn/OgVAwz//hYaXXurzHCEkRFk9sVslV2ICNNHRUKnZvJFozPn/27vz8CjLc3/g39nXTPZkAoQAshhAEkXUoP4s5wioHBX1KHq0olas2zkqVtGWqthjtUWrXBW1i5b2HFdatQtWDxWoFdEqJgECRoEACtkg+ySz378/ZuadeTMzYQLZ+X6uiyuZyfu+8ww8ZCbf3M/9dDUDX6wLBV97NwESU9U56rRQj69plwEZhX36sEEJoqa1Rgm8KhoqsK9tX9xxacY0lOSWoDS3FKV5pZieMx02A3dwJSIiGgx+byC6G6ISZPkSBlueTn+vr2+2GZTwKnmwFarc0hv4swcRDX8MwQaBYcwY6CNVXIl6co0qgC4tbbCHSUR9xd0GVL8TCr72bABie2o5Z0SDr6zxffaQLp8L2w9vV5Y1VjZWot3bHnfcOMc4lOaVKqHX+PTx0GrYRJaIiKg/iAh8bnWwpVRuRRrJxzSQ9/W2cbxWA4vdoIRXkSArYQWX3QAtG8cT0QlGI9LbQtiB19bWhvT0dLS2tsLhcAz2cIiIjs7TAXz5bij42v03IOCJfi1vWjT4ypl43A8lIjjYcVCp8KpsrMSXzV8iKOrGtBa9BdNzpiuB14ycGcgwZxz34xMREZ3IRAQel18VXql2Q+xWwRXobeN4vUa1+6F6N0R1BZfZaoCGjeOJ6ARwrDkRK8GIiPqKtxP46v+AqjeBL/8PiO2vlTMZmHZ5KPjKO/m4HsYT8GDXkV2hXRvDyxsPdx2OO67AVoDS3FKU5JWgNK8UkzMnw6Dljo1EREQ9ERF4u/zoavehK9w83t3hQ1eHF10dPrjbQ59Hgq6udh+CwV42jjfpYI1pDh/ZATFR83ijhY3jiYj6CkMwIqLj4XOHKr2q3gSq3wV8rujXsiZEg6/8acAxvoFt7GxUBV47j+yEL3ZJJQC9Vo+pWVNDgVduKUpyS5Bv67+dJImIiIaLYFDgcfnCoVYk0AqFW6FQyxu+Hf16b3dDBACTVR/eDTFJ8/iYjwYT+2sREQ2GXodgH3zwAVauXImtW7eitrYWb731FhYuXNjjOZs2bcLSpUtRVVWFwsJCLF++HDfccMMxDpmIaJD5vaHeXlVvAl+8A8T22soYGw2+Ckp6HXz5g37sbtmtamB/sONg3HFZ5qxQA/twP6+p2VNh1puP95kRERENeYFAMBRkRUKr8MdI5VY01Ap99Lh6vxMiEKrWstgNoT9poR5a5vBHS5pBHWylGaEzsL8WEdFQ1+sQzOVyoaSkBDfddBMuv/zyox5fU1ODBQsW4NZbb8XLL7+M999/HzfffDMKCgowf/78Yxo0EdGAC/iAvX8PB19/Adyt0a85Rod7fF0OjD6tV8FXq6cV2xq3hZrXN1Ri2+Ft6IpdRglAAw0mZU5SenmV5JagMK2QSyOIiGhE8HsDPVZmdbX74I4Jubxdvd8FEQhVapntBljsoWotdahlDH8tGnjpjazWIiIaaXodgl144YW48MILUz7+hRdewPjx4/HUU08BAIqLi/Hhhx/i6aefZghGRENbwA/s+0co+Nr1Z6CrOfo1uxOYtjAUfI2ZBWiP/ttfEUFNWw0qGyqV5Y17WvfEHWc32DEjd4bSz2tGzgzYjfY+fGJERET9I7L7YWxlltJTKybccof7a3V1+OD39G4HRCD0+yaz3QCzPaYyy26EOfwxFHBFAy+z3QAdd0IkIjrh9XtPsC1btuD8889X3Td//nzcfffdSc/xeDzweKI7qbW1tfXX8IiI1IIBYP9HQNVbwM4/Ap0xDedtucDUS0PB19iyowZfnb5OVB2pUpY2VjZWotXTGndckaNItbRxQvoE6LT87TMREQ0+CQo8nf6YUCu+MksJtMJfD/p7v/ZQq9PEVWZFwq3YoMscDrVMVgO03AWRiIh6qd9DsLq6OuTnq5sz5+fno62tDV1dXbBYLHHnPP7441ixYkV/D42IKCQYBL75J7DjzVDw1VEX/ZolC5h6SSj4Kjob0CX+tikiqHXVoqIhFHZVNFaguqkaAVH/dtukM2Fa9jQl8CrJK0GWOas/nx0REZEiGAiGg6sklVmqz71wu/yQXu58CAB6ozamCitm+aEq4DIqt41mHZf5ExFRvxuSu0M++OCDWLp0qXK7ra0NhYWFgzgiIhpxRICDW8PB19tAW0zzeXM6UHxxqM/X+PMAnSHudF/Ah11Nu6JVXg2VaOhqiDsuz5qHU/NOVfp5TcmcAkOC6xERER0Lvy8QDq5iq7RiAy71boiezmPrp2W06OOqsSz22M+jyw4taUYY2E+LiIiGoH4PwZxOJ+rr61X31dfXw+FwJKwCAwCTyQSTydTfQyOiE40IUFsRCr6q3gZaD0S/ZnIAJy8IBV8T5gB6o+rUw12HUdlYqfTz2nF4B7xBr+oYvUaPk7NORkleiRJ6OW3O/n9eREQ0IogIfJ6AaufDuB0QY6u12n3wHUM/LWgAs63broeqyqzY5vGh+3R69tMiIqLhr99DsLKyMrzzzjuq+9avX4+ysrL+fmgiolDwVb8jHHy9BTTXRL9msAFTLgSmXw6c9K+AwQwACAQD2N1UrTSvr2iswNftX8ddOsOUoSxpLM0txbScabDoE4f7RER04hEJ9dPqXpkV2gExNtSKVmsFfMFeP45Wq4lrAm/poVrLZGM/LSIiOjH1OgTr6OjA7t27lds1NTWoqKhAVlYWxo4diwcffBAHDx7E7373OwDArbfeimeffRb3338/brrpJmzYsAFvvPEG1q1b13fPgoiou4ZdodBrx5vAka+i9+stwOT5oeBr0jzAYEG7tx3bGrYqyxq3Hd4Gl8+lupwGGpyUcZKqgX2Ro4j9S4iITiDBoCjLDt0xOx+GQq3IbofRJYnuDh+Cx9JPy6BNusthpDIrtnG80aLn6xEREVEKeh2CffbZZ5gzZ45yO9K7a/HixVizZg1qa2tx4EB0idH48eOxbt063HPPPVi1ahXGjBmDX//615g/f34fDJ+IKMbh3UDVm6Hgq3FX9H6dCZg0F5h+OWTiPBzwNoUqvD77KSoaKrCnZQ8E6h9SrHorZuTOUAKvU3JPgcPoGOAnRERE/SngD8YvN4zcjumjFVme6O70Ab3PtGA066K7HsbugNitj1ZkeaLBxH5aRERE/UEjIsfwUj6w2trakJ6ejtbWVjgc/CGUiGI07Q1XfL0F1G+P3q81ABPPR9fUi1GVVYiK1i+Vfl7Nnua4yxSmFSp9vEpySzAxYyJ0Wv4QQkQ0HHm6/GiudaG1oROdMf2zuldued3H2E/LalD1zjKHlx2qqrViKrl0BvbTIiIi6kvHmhMNyd0hiYh61HIgutSxtiJ6v1aPuvHnoGLMKag0GVHRtAtfbHsSflHvhGXUGjEtZ5rSz6sktwQ5lpyBfQ5ERHTcutq9aKp1obmuM/Qx/MfV6j36yWEarSbcQyumIXxstVaaekmi2aaHVsdQi4iIaDhiCEZEw0PrQWDn26Hw65tPAQA+ANUmMypGFaPCkYNKXzPquvYCB/aqTs215CoVXqV5pSjOKoZRZ4x/DCIiGnJEBK4WD5prQ0FXU10k7OqE2+VLep4tw4SMfCts6UZ1tVZMuGW2G2Cysp8WERHRiYIhGBENXe11wM4/hoKvA1vQrNWi0mRCRWYGKtJzUaUNwC1+AEeAtiMAAJ1Gh8mZk5VeXqV5pSiwFfAHHCKiIS4YFLQfcaM5Juhqqu1Ec50LvmTLFjWAI9uMzAIbspw2ZBZYkVlgQ6bTBpOFb3OJiIhIje8OiGho6WgEdv0Jwao3sefgP1FhNqDCZELlmALsNxhiDvQAAjiMDlXgNS17GqwG66ANn4iIehYIBNHa0IXmbkFXc10nAr5gwnO0Wg3S8yzhgMuKrAIbMgtsyMi3wmBk/0YiIiJKDUMwIhp8nU3o2PF7bN+1FhXNX6LSZMA2kwntY5xxh05In6CEXiV5JRjnGAethr1ZiIiGGr83gJaGSK+uznDg5UJrQxeCwcT7Mun0WmQ4rchyRiu6sgpsSM+zQKfn93oiIiI6PgzBiGjAiQi+ObwTFdv/FxXf/AMVnsP4yqCHaDRAZnRnD4vOjBm5JUrz+pLcEqSb0gdx5ERE1J3X7Vf6dSnVXXWdaDvcBSTZg9xg0qkqujILbMgqsCIt2wKtlsvXiYiIqH8wBCOifucJeLDzyE5UHPoYFfveR0XrbjQhpr+LMbTMcbTejpL801A65hyU5pZiUuYk6LX8NkVENBS4O3xK0BXZkbG51oWOZk/Sc0w2fSjoCld0ZYYrvOyZJvZqJCIiogHHny6JqM81dDagoqECFY0VqKz/HDubdsEv6j4vBhFMDepQmnkySif+G0pOugC51txBGjEREQGhSt3OVq9qB8ZI8NXVnnwnRmu6URV0RSq8LGkGhl1EREQ0ZDAEI6Lj4g/6Ud1cjcqGylDo1VCJQ65Dccdl+wMo9XhQqktDadEcFJfcAFNBySCMmIiIJChob3KrKrpCFV6d8Hb5k56XlmUOL18MBV2R0MtkNSQ9h4iIiGioYAhGRL3S4m7BtsPblEqvHYd3oMvfpTpGK4LJXh9KPB6Uuj0oNedhdPG/QzP9ciB/OsCqACKiAREMBNHa2IXmutieXaHdGP3exDsxajRAep5VWbqoLGN02mAwcSdGIiIiGr4YghFRUkEJYl/rPlQ0ViihV01rTdxxadBhhtuN0i4XSt0enOLxwuYoBKYvAqZdBhSUMvgiIupHAV8wZifGUEVXc50LLQ2dCPoTd6fX6jXIyLOqenVlFdiQkWeFzsCdGImIiGjkYQhGRIpOXye2H94e7efVWIl2b3vcceMseSj1a1DaWIPSjhaM9/mhBYC0UUDpt4HplwOjZzL4IiLqY163Hy31nUrQFanuamvsgiTZiVFv1CLTGV3CGOnd5cgxQ6tj2EVEREQnDoZgRCcoEcHBjoNKH6/KxkpUN1cj2K2BvVlnxvScaSg1ZqG0uR4z9nyEzM4D0QPs+cCpC0PB15gzAC1/oCIiOl5ul0/p1RW7I2NHU/KdGI0WPbIKQhVdSpP6AivSMs3QaPlLCSIiIiKGYEQnCG/Ai51HdqKysVKp9DrcdTjuuAJbAUpzS1GSOwOlAS0m7/8Uhu1/BlyN0YOsOcDUS0PB19gyQMseMUREvSUi6Gr3KUsYm2td4V0ZO9HZ5k16niXNoFR0hZYwhoIvq8PInRiJiIiIesAQjGiEOtx1GBUNFUroVXWkCr6gent7vVaPqVlTUZJXgpLcEpRkz4Cz+QBQ9Sbwzo+AjrrowZZMoPiSUPBVdA6g47cPIqJUiAg6mj3Rqq7wjoxNtS54OpPvxGjPNIVCrvBSxsjnZjt3YiQiIiI6FvwplmiY8wf9+Lr9a+xt3Yua1hp81fwVKhsrcbDjYNyxWeYslOSWoDSvFKW5pZiaPRVmnQk4+Hko+KpaCrR9Ez3BnA6cfHGouf2E8wAdf/AiIkomGBS0He6KWcLYqQRePk8g8UkawJFjUZrTh5Ywhj43mvk2jYiIiKgv8d0V0TDR6evEvrZ9SthV01qDvS17sb99P/zB+EoCDTSYlDlJFXoVphWGlsqIALWVwMYfA1VvAS0xPb6MacDJC0LB10n/AuiNA/gsiYiGvoA/tBNjc3gHxlB1Vyda6jsR8AcTnqPVapCeb0VWeBfGSJP6jDwr9EYuKSciIiIaCAzBiIaYZnezEnTtbd0b+rylBodch5KeY9FbMM4xDhMyJmBC+gRMz5mOU3JOQZoxLXqQCFBfFa74egto2hv9msEGTLkAmHY5MPF8wGDux2dIRDQ8+LwBtISXLcYuYWxt7IIEE2/FqDNokem0hhvTh5cwFtjgyLVAx50YiYiIiAYVQzCiQRCUIOpcdeqwqyX0ebOnOel5maZMjE8fjwkZEzDeMV4JvZw2J7SaJD9cNXwRCr2q3gQOfxm9X28BJs8LBV+T5gFGax8/SyKi4cHT5U+whNGFtiNuIHHWBYNZpyxhjPbtsiEt2wwtd2IkIiIiGpIYghH1I1/AhwPtB1RVXXtb9mJf2z50+buSnjfKNgrjM8ZjQvqEUOiVHgq7Ms2ZqT3wkT3AjjdDwVfDzuj9OhMwaW5oqePkCwCT/TifIRHR8NHV7lWCrtgdGV2tyXdiNNsMytLF2LDLlsGdGImIiIiGG4ZgRH3A5XNhX+s+VdC1t3Uvvmn/Bn5JvPOXXqtHUVoRJmRMUC1lHOcYB6uhF1VZwSDQtCfU3P7Q58C+zUD99ujXtQZg4r+Ggq8pFwFmx3E+WyKioUtE4GrxoLk2HHTF9Oxyu3xJz7OlG8O9ukLLF7MKQksaLWnsi0hEREQ0UjAEI0qRiKDJ3RS3hHFv617Ud9YnPc+qt0YrujKilV1j0sbAoO3lbosiQNvBUOB1cGso9DpUCXha1cdp9cCEb4WCr5MXAJYUK8iIiIaJYFDQfsQdWsZY5wovZww1qve5k+zECMCRY0amMxJ2WZXPTRa+JSIiIiIa6fiOj6iboARxqONQwrCrzduW9Lxsc3Z06WJM2JVvzT/2JTOuI6GgK1LldfBzwNUQf5zeDDhnAKNnAqNPCzW3t2Yd22MSEQ0hgUAQrQ1daO4WdDXXdSLgS7wTo0arQXquRd2zq8CGDKcVBu7ESERERHTCYghGJyxvwIv9bftVOzDubQ316/IEPAnP0UCD0fbRqrArUuWVbko/vgF5OoDaCnXg1bI/wSB0QP5UYNRpocBr1GlAXjGg62VVGRHREOL3BtDS0KksXYw0qm9t6EIw2U6Mei0y8q3Rnl1OGzILrMjIs0Kn506MRERERKTGEIxGvHZvu6oxfU1LDWraavB1+9cISuIqAoPWgCJHkSrompA+AUWOIpj15uMflN8D1O8IB17loY+Hq4FE48meqA68nKdwJ0ciGrY8nb5oY/q6TrTUudBU14m2w11Jd2LUm3TICld0ZTqjTeodORbuxEhEREREKWMIRiOCiOBw12FVY/qathrUtNSgoSvB8sEwu8Gu6tcVCbtG20dDp+2jJTPBAHD4S3WFV/0OIJBgNzLHaGDUqdHAa9SpgCWjb8ZBRDRAQs3pvcqyxdDHUIVXZ1vynRhNVr1qCWNkGaM9wwQNwy4iIiIiOk4MwWhYCQQDONhxMFrVFa7wqmmpQbuvPel5uZbchGFXjiWnb7e4FwktYVQCr/LQEkdvR/yxlkx1hdfo04A0Z9+NhYionwUDQbQddkfDrtpQVVdLnQveHprTKzsxOtU9uyxphr79nkxEREREFIMhGA1Jbr9b6dcVu5Rxf+t+eIOJqwi0Gi3G2MeEwq6M8UrQNS59HBxGR/8MtKMhJvDaGlra2Hkk/jiDDSgoCQVdkdArcxzAH/aIaBjwewNoru9UqrkioVdLQyeC/sRrGDUawJFrQaYzZhdGZ6g5PXdiJCIiIqLBwHehNKhaPa2oaa1RBV17W/biYMdBSJLmMCadCeMc41Rh1/j08ShyFMGkM/XfYN2twKGKaOB1sBxo+yb+OK0ByJ8W3alx1GlA7hSgr5ZXEhH1E7fLh+Zwr66mOhdawksZ2464k/frMmiR4bRGq7rCHzPyrNAZ2JyeiIiIiIYOhmDU70QE9Z310aWLkcCrZS+OuBNUTYU5jI64HRjHp4/HKNuovuvXlYzPDdRtD1d3hft4HfkqwYEaIGeyOvByTgf0/RjGEREdh1C/Lg+aa0NBV2QZY3OdC13tvqTnmax6ZffFSNCVVWBDWpaZ/bqIiIiIaFhgCEZ9xh/045v2b9T9usIN6l0+V9Lz8q35CcOubHP2wPSGCfiBxi/UgVfDTiDojz82Y6y6j1dBCWDup6WWRETHIRgIorWxK9qYPmYZo8+TvF+XPdMUregqiFZ3sV8XEREREQ13DMGo17r8XdjXui8u7Nrfvh/+RMERAJ1Gh8K0QiXsGp8eXcZoM9gGbvAiQNNe9U6NtZWAvyv+WFtufON6W87AjZWIKAU+TwAt9Z1oCldztdR1oqmuE60NnQgGkvTr0mqQnmuJNqUPf8zIt8Jo5lsDIiIiIhqZ+E6Xkmpxt0T7dEUCr5YaHHIdSnqORW8J9evKmIDxjuhOjGPTxsKgMwzg6MPaatUVXofKAXdL/HHGNGBUaUzgNRNIH8PG9UQ0ZHR1eFXVXJHqrvYmd9Jz9EZtTK+uaHP69DwLdHr26yIiIiKiEwtDsBOciKDOVacOu1r2Yl/bPjS5m5Kel2nKDFVzdQu7nDYntJpB+sGqsykUch36PNS0/tDnQHtt/HE6E+A8RR14ZU8EtPyBkIgGl4igo9mjak4f+dzdkbxfl9lmUPXqiixjTMtkvy4iIiIiogiGYCcIX9CHr9u+Vld1hXdl7Eq0FDBslG0UxmeMVwVdE9InINOcOYCjT8DrAmq3xVR4fR5a5tidRgvkFgOjT40GXnlTAb1x4MdMRBQWCATR2tAV16urub4T/p76dWWZkBWu5lJCrwIrLHZ+TyMiIiIiOhqGYCNMp68zuvtizE6MX7d9Db8k7tel1+pRlFakNKSPhF3jHONgNVgH+BkkEPAB9VXRwOvg50DjLkCC8cdmjg9VeI2eGW5cPwMwDmDPMSKiGF63Hy31nUo1V2QZY2tDF4LBxP26tFoN0vMsqqb0mU4r+3URERERER0nvpsehkQETe4mVTVXJPSqc9UlPc+qtyoN6WOb049JGwODdhD6dSUSDAJHdscEXluBuu1AwBN/rN0ZCrsiVV6jTgWsWQM/ZiI6oYkIutp9aKl3oSm2qqvWhY7mBN+7wvQmHbKcVmSEg66scFWXI9cCnY7Ls4mIiIiI+hpDsCEsKEEc6jiUMOxq9bQmPS/bnJ0w7Mq35g+t7e1FgNZvwoHX1uhOjZ62+GPN6fE7NTpGDfyYieiEJUFBe5M7pil9tG+Xx5W40hYALGmGmOb00WWM9kzT0PqeTEREREQ0wjEEGwK8AS/2t+2PW8a4r3Uf3IHEu35poMEo+yilR1dkCeP49PFIN6UP8DNIkeuIOvA69Dngaow/Tm8BCkrUgVfWBO7USEQDIuAPoqWhM24nxpb6Tvi9CZZhA4AGSMsyKyFXVkzoZbYPkUpbIiIiIqITHEOwQfBZ3Wf4x8F/KGHXN+3fICCJGyEbtAYUOYpUQdeE9AkochTBrDcP8Mh7wdMequqKDbxaDsQfp9WHGtXHBl65xYCOU5OI+pfX7Q8FXfXq5vStjV2QZP26dBpk5FtVvboynTZkOK0wGHUD/AyIiIiIiKg3mDQMgk/rPsVLO15S3Wc32JVKrtiwa5R9FPTaIf7P5PcAdTvUOzU2VgNI8ENk9qSYwGsm4JwOGCwDPmQiOjFE+nWFli660FQXbVLvakner8tg1sWEXOGeXQU2OHLM0LJfFxERERHRsDTE05WR6XTn6bjafbVqCWOuJXd49IYJBkIBV2zgVbcDCPrij3WMiTatHz0TGFUa6u1FRNTHgkFB+xF3uFdXpKorFHZ5Onvo1+UwIqtbr65Mpw22DOPw+J5MREREREQpYwg2CGY5Z2GWc9ZgD+PoRIDmfTGBVzlwqALwueKPtWSFKrxGz4wua7TnDfSIiWiEC/hC/bqaakM9upprQ9VdLfWdCPiS9+tyZJuRWWBTqruyCmzIyLfCbGO/LiIiIiKiEwVDMIpqr1dXeB38HOhqij/OYAtVdcX28cooYuN6Iuozni5/t6quUODVdrgLkrhdF3R6LTLyLUqPrqxwdVdGnhV69usiIiIiIjrhMQQ7UblbQ5VdB8O7NR4qB9oOxh+nNYT6dsVWeOVMBrT8gZKIjo+IoLPNq/ToilR1Nde50NnqTXqe0awLV3VFljGGPnfkWKDVMownIiIiIqLEGIKdCHxdQN32mMDrc+DI7gQHaoDck8MVXqeGPuZPB/SmAR8yEY0cwaCg7XCXEnQplV11nfB2Je/XZU03hhrSO63R0KvABquD/bqIiIiIiKj3GIKNNAE/0LhLHXg17AKCCX7QzChSL2ksKAFMaQM/ZiIaEfzeAFoaOmPCrlBVV0t9FwL+xP26NBrAkWNRV3aFd2Q0Wdmvi4iIiIiI+g5DsOFMBGjaGwq7In28arcB/q74Y2156sBr1GmALXvgx0xEw56n04fmulBz+kjQ1VzrQtsRN5CsX5dBi4x8K7KcVmTENKdPz7NAb+DyaiIiIiIi6n8MwYaTtkPqwOtQeai3V3cmR6hx/ajwbo2jTwMco9m4nohSIsFQr662I260He5C+5EutB0Ofd5U14mutuT9ukxWfUxFV6gxfabThrRsM/t1ERERERHRoGIINlR1NoV3aCyP7tTYURd/nM4EFMxQB15ZJwFa7cCPmYiGBRGB2+VD+xG3Em61HXErYVf7EXfS5YsRtgyT0qMrK6ZBvSXNwH5dREREREQ0JDEEGwq8LqC2MlrhdfBzoLkm/jiNDsgrVi9rzJsK6Ng3h4jUvF3+mEqu+KDL5wn0eL5GA9gzzXDkmJGWbYYjxwJHthkZ+aGljEYLXz6IiIiIiGh44U8xg+HwV0DNB9HAq/ELQBJUXWRNCFV3RQIv5wzAaB348RLRkOP3BtDelLiSq+1IFzyu5LsuRljTjXBkW8IhVzToSsu2wJ5lgk7HilIiIiIiIho5GIINhvL/ATavUt+XNipc4XVq9KMlc3DGR0SDLhAIoqPJg7YjXWhPEHR19tCXK8JsM0QrubItoc8jQVeWGXojG9ITEREREdGJgyHYYCg6G6jbrt6p0VEw2KMiogEUDAo6Wz1K5VaoF1e0ksvV7IEk2WkxwmDWqSu5IkFXdijo4pJFIiIiIiKiKP6ENBgmzw/9IaIRS0TQ1e6LVnIdCVdyHQ4HXk1uBAM9p1w6gza8PDEUcKXFBF2ObAtMNj2b0BMREREREaWIIRgR0THydPqUyi1lp8WYqi6/t+cdFrVaDexZplDlVvdKrhwzrGlGaLQMuYiIiIiIiPoCQzAioiR8nkBMJZdbVdXVfsQNT+dRms9rAFu6SQm4QpVc0c/tGSZo2XyeiIiIiIhoQDAEI6ITVsAXDO2wmKSSq6vdd9RrWNIMqkqu2P5caVlm6AwMuYiIiIiIiIYChmBENGIFg4KOZnfSSq6OFg9wlObzRos+aSWXI9sCg4k7LBIREREREQ0HDMGIaNgSEXS2eeN2Vozc7mjyIBjsOeXSG7RIy0lcyeXIMcNkNQzQsyEiIiIiIqL+xBCMiIYsEYHH5VeCre6VXG1H3Aj4jtJ8XqdBWlYo2ErLscRVclnSDNxhkYiIiIiI6ATAEIyIBpXX7U9SyRX63OcO9Hi+RgPYMk2hyq1sc1xVly3DBC13WCQiIiIiIjrhMQQjon7l9wWUqq32wzEVXeFG9G7X0ZvPWx3GUCVXOOhy5ET7c9kzzdDp2XyeiIiIiIiIenZMIdjq1auxcuVK1NXVoaSkBD//+c9xxhlnJDx2zZo1uPHGG1X3mUwmuN3uY3loIhpiAoEgOpo8oUquI260HVZXcnW2eo96DZNNr67kigRd2aGgS29k83kiIiIiIiI6Pr0OwV5//XUsXboUL7zwAs4880w888wzmD9/Pqqrq5GXl5fwHIfDgerqauU2++8QDR8SFLhaPdFKrnDQFank6mjxQI7SfN5g0sVXcsU0oDdaWJRKRERERERE/avXP3n+7Gc/w5IlS5TqrhdeeAHr1q3DSy+9hAceeCDhORqNBk6nM+XH8Hg88Hg8yu22trbeDpOIUiQi6Gr3KZVbbeGgqz0SdjW5EfT3HHLp9FqlaiuukivHDLONzeeJiIiIiIhocPUqBPN6vdi6dSsefPBB5T6tVovzzz8fW7ZsSXpeR0cHioqKEAwGcdppp+HHP/4xpk2blvT4xx9/HCtWrOjN0IioB54ufyjQUjWeD1d1HXHD7zlK83mtBmlZpnDQZYmr6rI6jNCw+TwRERERERENYb0KwQ4fPoxAIID8/HzV/fn5+fjiiy8SnjNlyhS89NJLmDFjBlpbW/Hkk09i9uzZqKqqwpgxYxKe8+CDD2Lp0qXK7ba2NhQWFvZmqEQnjGBQ0NXuhavFg47m0J/Y/lztR9zwdPp7vogGsKWbwpVc8UGXPdMErY7N54mIiIiIiGj46vdGPGVlZSgrK1Nuz549G8XFxfjFL36BH/3oRwnPMZlMMJlM/T00oiHP7wvA1eIJBVzhkMvV4oGrOXTb1eKBq9V71J5cAGC2G5TKrbj+XFlm6AwMuYiIiIiIiGjk6lUIlpOTA51Oh/r6etX99fX1Kff8MhgMOPXUU7F79+7ePDTRiCIi8HT6lXBLCbqao4GXq9kDt8uX0vU0GsDqMMKWYYI904y0bHO4H1d4x8VsM4xmNp8nIiIiIiKiE1evfio2Go2YOXMm3n//fSxcuBAAEAwG8f777+POO+9M6RqBQADbt2/HRRdd1OvBEg0HwaCgq80bE2i5VcFWJPTye4MpXU9n0MKeYYIt/Mee2e1jhglWh5HLFYmIiIiIiIh60OvSkKVLl2Lx4sU4/fTTccYZZ+CZZ56By+VSdou8/vrrMXr0aDz++OMAgEcffRRnnXUWJk6ciJaWFqxcuRL79+/HzTff3LfPhGgA+L0BJcRSlibGVHN1NHvQ2Zba8kQAMNn04YDLDHtGtJIrNuQyWfXcWZGIiIiIiIjoOPU6BFu0aBEaGxvx0EMPoa6uDqWlpXj33XeVZvkHDhyAVhutSGlubsaSJUtQV1eHzMxMzJw5Ex999BGmTp3ad8+C6DhFlieqgq3mSAWXF64WNzpaPPC4jtJgPkyjAazp0SArUrEVG27ZMkwwGHX9/MyIiIiIiIiICAA0IpJaycogamtrQ3p6OlpbW+FwOAZ7ODTMBANBdLZ54yq4uldyBXypLU/UG7SwZYZDrcyYcCsjWsFlcRih1bJ6i4iIiIiIiKivHWtOxE7ZNKz5vAH1TolxzeXdoeWJKUa9ZpshYd+t2EouLk8kIiIiIiIiGn4YgtGQJCLwuPzoaHGrQ61uzeU9nSkuT9RqYEs3RsOsmJBLaTqfboKeyxOJiIiIiIiIRiSGYDTggoEgXK3eHprLu+Fq9aa+PNGojTaTT9B3y55pgiWNyxOJiIiIiIiITmQMwahP+TwBpaF8dEliTMDVEto9EakuT7Qbemwub88wwWjh8kQiIiIiIiIi6hlDMEqJiMDd4YtvLt+tF5e3K7XliVqtBtYMYzjUMseHW5mh5Yk6g/boFyMiIiIiIiIiOgqGYIRAIIjOVq96aWK4misacnkR8Ke2PNFg0sVVa9m6hVzWNCM0XJ5IRERERERERAOEIdgI53X7Ey9LjAm8OttTX55oSTPENJc3w54RaTZvVkIuo4XTioiIiIiIiIiGFqYVw5QEBV0dvviG8t1CLq87kNL1tDoNbOkJliTG9uLi8kQiIiIiIiIiGqYYgg1BAX8wfsfEyLLEmGquYCC18i2DWRftuZVhgi0ztpIrdL/FbuDyRCIiIiIiIiIasRiCDYKOZg+a61xJmsu70dXuS/laFodRHXAlqODi8kQiIiIiIiIiOtExHRkEOz74Blv/ur/HY7T60PLExM3lzbBlGEPLE/VcnkhEREREREREdDQMwQZBeq4VmQW2UFP5mCWJsZVcZhuXJxIRERERERER9RWGYIOgeHYBimcXDPYwiIiIiIiIiIhOGFxLR0REREREREREIx5DMCIiIiIiIiIiGvEYghERERERERER0YjHEIyIiIiIiIiIiEY8hmBERERERERERDTiMQQjIiIiIiIiIqIRjyEYERERERERERGNeAzBiIiIiIiIiIhoxGMIRkREREREREREIx5DMCIiIiIiIiIiGvEYghERERERERER0YjHEIyIiIiIiIiIiEY8hmBERERERERERDTiMQQjIiIiIiIiIqIRTz/YA0iFiAAA2traBnkkREREREREREQ0mCL5UCQvStWwCMHa29sBAIWFhYM8EiIiIiIiIiIiGgra29uRnp6e8vEa6W1sNgiCwSAOHTqEtLQ0aDSawR5On2hra0NhYSG+/vprOByOwR4OjSCcW9RfOLeoP3BeUX/h3KL+wrlF/YVzi/rLSJxbIoL29naMGjUKWm3qnb6GRSWYVqvFmDFjBnsY/cLhcIyYSUhDC+cW9RfOLeoPnFfUXzi3qL9wblF/4dyi/jLS5lZvKsAi2BifiIiIiIiIiIhGPIZgREREREREREQ04jEEGyQmkwkPP/wwTCbTYA+FRhjOLeovnFvUHzivqL9wblF/4dyi/sK5Rf2FcytqWDTGJyIiIiIiIiIiOh6sBCMiIiIiIiIiohGPIRgREREREREREY14DMGIiIiIiIiIiGjEYwhGREREREREREQjHkOwYW7fvn3QaDSoqKgYEtehkUWj0eDtt98eMtehkYNzi/rDmjVrkJGRMWSuQyPHpk2boNFo0NLSMiSuQyMH5xb1F74mUn8Z7nNrSIdgH3zwAS6++GKMGjUq6Q869fX1uOGGGzBq1ChYrVZccMEF+Oqrr5SvR8KdRH/Wrl2rHHfgwAEsWLAAVqsVeXl5uO++++D3+3scX+y10tPTcfbZZ2PDhg199vz7yw033ICFCxeq7issLERtbS2mT58+OIMaYH0xtwCgrq4O3/72t+F0OmGz2XDaaafhD3/4g+qYpqYmXHvttXA4HMjIyMB3vvMddHR09Di+cePGKXMrct3Y+TpUPfLIIygtLY27v7a2FhdeeOHAD2gQ9NXc2rNnDy677DLk5ubC4XDgqquuQn19veoYzq0Ta249/vjjmDVrFtLS0pCXl4eFCxeiurpadYzb7cYdd9yB7Oxs2O12XHHFFXHzJpXXu02bNuG0006DyWTCxIkTsWbNmh7HFvnhK/InPz8fV1xxBfbu3dsnz70/jRs3Ds8884zqvkWLFuHLL78cnAENgr6aW//1X/+FmTNnwmQyJfz/CgDbtm3DueeeC7PZjMLCQvz0pz/tcWzd38dlZ2dj3rx5KC8vP67nPBC+9a1v4e6771bdN3v2bNTW1iI9PX1wBjXABmpuJXu///HHHycdG+fW8NYXc6uyshLXXHMNCgsLYbFYUFxcjFWrVsU9Fl8T+ZrYH3PrzTffxNy5c5X3+mVlZXjvvfd6HBvnVt8Y0iGYy+VCSUkJVq9enfDrIoKFCxdi7969+OMf/4jy8nIUFRXh/PPPh8vlAhANd2L/rFixAna7XfnBKRAIYMGCBfB6vfjoo4/w29/+FmvWrMFDDz101DH+5je/QW1tLTZv3oycnBz827/927CYhN3pdDo4nU7o9frBHsqA6Iu5BQDXX389qqur8ac//Qnbt2/H5Zdfjquuukr1Buraa69FVVUV1q9fj7/85S/44IMPcMsttxx1jI8++ihqa2tRXl6OWbNmYdGiRfjoo4+O/8kPAqfTCZPJNNjDGBB9MbdcLhfmzZsHjUaDDRs2YPPmzfB6vbj44osRDAaVa3FunVhz6+9//zvuuOMOfPzxx1i/fj18Ph/mzZun+p50zz334M9//jPWrl2Lv//97zh06BAuv/xy5eupvN7V1NRgwYIFmDNnDioqKnD33Xfj5ptvPuobMwCorq7GoUOHsHbtWlRVVeHiiy9GIBDo27+IAWCxWJCXlzfYwxgwfTG3Im666SYsWrQo4eO0tbVh3rx5KCoqwtatW7Fy5Uo88sgj+OUvf3nUMf7tb39DbW0t3nvvPXR0dODCCy8clhUvRqMRTqcTGo1msIcyIAZqbkVE5knkz8yZM486Rs6t4akv5tbWrVuRl5eH//3f/0VVVRV+8IMf4MEHH8Szzz6rHMPXRL4m9tfc+uCDDzB37ly888472Lp1K+bMmYOLL744pSCec+s4yTABQN566y3VfdXV1QJAduzYodwXCAQkNzdXfvWrXyW9Vmlpqdx0003K7XfeeUe0Wq3U1dUp9z3//PPicDjE4/GkPKaDBw8KAHnhhRdERGTTpk0ya9YsMRqN4nQ6ZdmyZeLz+ZTjzzvvPLnjjjvkjjvuEIfDIdnZ2bJ8+XIJBoM9Pu/09HT5zW9+IyIiNTU1AkDKy8tFRMTv98tNN90k48aNE7PZLJMnT5ZnnnlGOffhhx8WAKo/GzdujLtOquP/z//8T7nvvvskMzNT8vPz5eGHH0769zVUHc/cstls8rvf/U51blZWlnLMzp07BYB8+umnytf/+te/ikajkYMHDyYdU1FRkTz99NPKbZ/PJ1arVR544AEREdm2bZvMmTNHzGazZGVlyZIlS6S9vV05fvHixXLppZfKI488Ijk5OZKWlibf/e53VfO5+2OIiJSUlKj+Dbv/3dx///0yadIksVgsMn78eFm+fLl4vV4REfnNb34TN7ci87T7dVId/8qVK8XpdEpWVpbcfvvtymMNF8c6t9577z3RarXS2tqqHNPS0iIajUbWr18vIpxbJ/rcEhFpaGgQAPL3v/9dREJzxGAwyNq1a5Vjdu3aJQBky5YtIpLa6939998v06ZNUz3WokWLZP78+UnHsnHjRgEgzc3Nyn0vv/yyAJAvvvhCRESee+45mTBhghgMBpk8eXLc904A8txzz8kFF1wgZrNZxo8fr3ouiR6jvLxcAEhNTY2IhOZKenq68vXdu3fLJZdcInl5eWKz2eT0009X/g+JhF7Hus+tRNdJdfy/+tWvZOHChWKxWGTixInyxz/+Menf2VB2LHMr1sMPPywlJSVx9z/33HOSmZmp+n6xbNkymTJlStKxJHp/snnzZgEg7777roiI/P73v5epU6eK0WiUoqIiefLJJ1XXKCoqkkcffVSuvvpqsVqtMmrUKHn22Wd7fIzm5mblPZJI/Pw7fPiwXH311TJq1CixWCwyffp0eeWVV5TzFy9eHDe3ampqEs7jVMb/2GOPyY033ih2u10KCwvlF7/4RdK/s6Gsv+ZWon/Do+Hc4txK5Pbbb5c5c+Yot/mayNfE/ppbiUydOlVWrFiR9OucW30zt4Z0JdjReDweAIDZbFbu02q1MJlM+PDDDxOes3XrVlRUVOA73/mOct+WLVtwyimnID8/X7lv/vz5aGtrQ1VVVcrjsVgsAACv14uDBw/ioosuwqxZs1BZWYnnn38eL774Iv77v/9bdc5vf/tb6PV6/POf/8SqVavws5/9DL/+9a9TfszugsEgxowZg7Vr12Lnzp146KGH8P3vfx9vvPEGAOB73/serrrqKlxwwQXKb8lmz54dd53ejN9ms+GTTz7BT3/6Uzz66KNYv379MY9/qEh1bs2ePRuvv/46mpqaEAwG8dprr8HtduNb3/oWgNDcysjIwOmnn66cc/7550Or1eKTTz5JeTx6vR4GgwFerxculwvz589HZmYmPv30U6xduxZ/+9vfcOedd6rOef/997Fr1y5s2rQJr776Kt58802sWLHiWP46FGlpaVizZg127tyJVatW4Ve/+hWefvppAKFy1nvvvRfTpk1T5lai39imOv6NGzdiz5492Lhxo1KtcrTy8+Eglbnl8Xig0WhUFU5msxlarVY5hnOLc6u1tRUAkJWVBSD0+ubz+XD++ecrx5x88skYO3YstmzZAiC117stW7aorhE5JnKNVMW+Jr711lu46667cO+992LHjh347ne/ixtvvBEbN25UnfPDH/4QV1xxBSorK3Httdfi6quvxq5du3r1uLE6Ojpw0UUX4f3330d5eTkuuOACXHzxxThw4ACA0FKEMWPGKNWRtbW1Ca+T6vhXrFiBq666Ctu2bcNFF12Ea6+9Fk1NTcc8/sFyLHMrFVu2bMH/+3//D0ajUblv/vz5qK6uRnNzc8rXiZ1bW7duxVVXXYWrr74a27dvxyOPPIIf/vCHcf+nV65ciZKSEpSXl+OBBx7AXXfddVzvV9xuN2bOnIl169Zhx44duOWWW/Dtb38b//znPwEAq1atQllZGZYsWaLMrcLCwrjrpDr+p556CqeffjrKy8tx++2347bbbotbnjMc9NfcirjkkkuQl5eHc845B3/60596fT7nFudWa2urcg2Ar4mJ8DWxb+ZWd8FgEO3t7T0ekwjn1jHMrV5FZoMICSoqvF6vjB07Vq688kppamoSj8cjTzzxhACQefPmJbzObbfdJsXFxar7lixZEne8y+USAPLOO++kNCaXyyW333676HQ6qayslO9///syZcoUVVXX6tWrxW63SyAQEJFQIlpcXKw6ZtmyZarxJXrePVWCJXLHHXfIFVdcodyOVELE6n6dVMd/zjnnqK4za9YsWbZsWdKxDEXHM7eam5tl3rx5AkD0er04HA557733lK8/9thjMnny5LjHzM3Nleeeey7pmGIraTwej/z4xz8WAPKXv/xFfvnLX0pmZqZ0dHQox69bt05V3bF48WLJysoSl8ulHPP888+r/v2OpVqnu5UrV8rMmTOV28l+Qxt7nVTHX1RUJH6/XznmyiuvlEWLFiUdy1B0rHOroaFBHA6H3HXXXeJyuaSjo0PuvPNOASC33HKLiHBuJbrOiTS3AoGALFiwQM4++2zlvpdfflmMRmPcsbNmzZL7779fRFJ7vZs0aZL8+Mc/Vh2zbt06ASCdnZ0Jx9P9t4aHDh2S2bNny+jRo8Xj8cjs2bNlyZIlqnOuvPJKueiii5TbAOTWW29VHXPmmWfKbbfdlvAxRI7+m8lEpk2bJj//+c+V24nma/frpDr+5cuXK7c7OjoEgPz1r3/tcTxDzbHOrVjJ/r/OnTtX+R4WUVVVJQBk586dCcfT/f1Jc3OzXHbZZWK326Wurk7+4z/+Q+bOnas657777pOpU6cqt4uKiuSCCy5QHbNo0SK58MILEz5G5HHQQ7VOIgsWLJB7771XuX3eeefJXXfdpTqm+3VSHf91112n3A4Gg5KXlyfPP/980rEMRf05txobG+Wpp56Sjz/+WP75z3/KsmXLRKPR9FgdwLnFudXd5s2bRa/Xq97L8zWRr4n9Nbe6+8lPfiKZmZlSX1+f9BjOrb6ZW8O6EsxgMODNN9/El19+iaysLFitVmzcuBEXXnghtNr4p9bV1YVXXnlFVQV2vK655hrY7XakpaXhD3/4A1588UXMmDEDu3btQllZmWpd/tlnn42Ojg588803yn1nnXWW6piysjJ89dVXx7Wmd/Xq1Zg5cyZyc3Nht9vxy1/+UklhU5Xq+GfMmKE6r6CgAA0NDcc89qEi1bn1wx/+EC0tLfjb3/6Gzz77DEuXLsVVV12F7du3H/cYli1bBrvdDqvVip/85Cd44oknsGDBAuzatQslJSWw2WzKsWeffTaCwaDqN3clJSWwWq3K7bKyMnR0dODrr78+5jG9/vrrOPvss+F0OmG327F8+fJjmlupjH/atGnQ6XTK7RNpbuXm5mLt2rX485//DLvdjvT0dLS0tOC0005L+L2ttzi3hv/cuuOOO7Bjxw689tprgz0UlTFjxsBms2HUqFFwuVz4wx/+AKPRiF27duHss89WHXv22WfH/daxrKws7vbx/mbye9/7HoqLi5GRkQG73Y5du3Yd09xKZfyxr4k2mw0Oh4Nzq4/Mnj0bdrsdmZmZqKysxOuvv478/Pyk/zbd30v19dwKBAL40Y9+hFNOOQVZWVmw2+147733+mxudR9/7NzSaDRwOp2cWzFycnKwdOlSnHnmmZg1axaeeOIJXHfddVi5cuVRz+Xc4twCgB07duDSSy/Fww8/jHnz5vXJuPiayNdEILW59corr2DFihV44403UuqRxbl1fHNr2HdBnzlzJioqKtDa2gqv14vc3FyceeaZqiVCEb///e/R2dmJ66+/XnW/0+lUSowjIrs7OJ3OHh//6aefxvnnn4/09HTk5uYe57OJp9FoEAo8o3w+X9LjX3vtNXzve9/DU089hbKyMqSlpWHlypW9Wh7VGwaDIW68sY27h7Ojza09e/bg2WefxY4dOzBt2jQAoXDgH//4B1avXo0XXngh4RsJv9+Ppqamo86t++67DzfccAPsdjvy8/P7vNGpVqvt1dzasmULrr32WqxYsQLz589Heno6XnvtNTz11FN9Oq6IE3luAcC8efOwZ88eHD58GHq9HhkZGXA6nZgwYQIAcG4dh+E+t+68805lI4QxY8Yo9zudTni9XrS0tKi2m66vr1fmRCqvd06nM25ntvr6ejgcDqXkPpl//OMfcDgcyMvLQ1pa2jE/x0QiAXDs3OppXgGhFgDr16/Hk08+iYkTJ8JiseDf//3f4fV6+3RsESfy3EpFsrkV+VpPXn/9dUydOhXZ2dl9vp36scytlStXYtWqVXjmmWdwyimnwGaz4e677+bcSqK/51YiZ555ZkrLEjm3OLd27tyJf/3Xf8Utt9yC5cuXq77G18Rjx7nV89yKeO2113DzzTdj7dq1cUtvk+HcOr65NawrwWJFQqivvvoKn332GS699NK4Y1588UVccsklcWFVWVkZtm/frvqBcv369XA4HJg6dWqPj+t0OjFx4sS4axYXF2PLli2qybN582akpaWp/hN1D6c+/vhjTJo0SalSyM3NVa2Z/eqrr9DZ2Zl0PJs3b8bs2bNx++2349RTT8XEiROxZ88e1TFGo/GolWapjv9EkGxuRf4dulfm6HQ65T9hWVkZWlpasHXrVuXrGzZsQDAYxJlnntnj4+bk5GDixIlxO/0UFxejsrJStUPJ5s2bodVqMWXKFOW+yspKdHV1Kbc//vhj2O12pW9E97nV1taGmpqapOP56KOPUFRUhB/84Ac4/fTTMWnSJOzfv191TKpzK5XxnwhS+b6Vk5ODjIwMbNiwAQ0NDbjkkksAcG4lMtLnlojgzjvvxFtvvYUNGzZg/Pjxqq/PnDkTBoMB77//vnJfdXU1Dhw4oPzGL5XXu7KyMtU1Isd0/61hIuPHj8dJJ50U94asuLgYmzdvVt23efPmuNfYjz/+OO52cXExACivs7Fzq6KiosfxbN68GTfccAMuu+wynHLKKXA6ndi3b5/qmFTnVirjH676Ym6loqysDB988IHqzfT69esxZcoUZGZm9nhuYWEhTjrppLiQItm/zeTJk1UVn/0xty699FJcd911KCkpwYQJE+K2eT+eudV9/MPVQM2tRCoqKlBQUHDU4zi3hqe+mltVVVWYM2cOFi9ejMceeyzucfiaGI+viX0ztwDg1VdfxY033ohXX30VCxYsSHmMnFvHKeWFk4Ogvb1dysvLlTWoP/vZz6S8vFz279+vHPPGG2/Ixo0bZc+ePfL2229LUVGRXH755XHX+uqrr0Sj0SRcK+r3+2X69Okyb948qaiokHfffVdyc3PlwQcf7HF86KGnzTfffCNWq1XuuOMO2bVrl7z99tuSk5Oj6olz3nnnid1ul3vuuUe++OILeeWVV8Rmsym7S4qIXH311VJcXCyff/65fPrpp/Iv//IvYjAYkvYEW7VqlTgcDnn33Xelurpali9fLg6HQ9U/4bHHHpOxY8fKF198IY2NjeL1euOuk+r4u/cjuPTSS2Xx4sU9/r0NBX0xt7xer0ycOFHOPfdc+eSTT2T37t3y5JNPikajkXXr1inHXXDBBXLqqafKJ598Ih9++KFMmjRJrrnmmh7Hl2jNdITL5ZKCggK54oorZPv27bJhwwaZMGGC6u998eLFYrfb5ZprrpGqqipZt26d5OfnKzsAiog88MAD4nQ65YMPPpBt27bJwoULxW63J+3b9Mc//lH0er28+uqrsnv3blm1apVkZWWp1nG//PLLYrPZpLy8XBobG8XtdsddJ9Xxd+9bd9ddd8l5553X49/bUNBX37deeukl2bJli+zevVv+53/+R7KysmTp0qWqYzi3Tqy5ddttt0l6erps2rRJamtrlT+xPUluvfVWGTt2rGzYsEE+++wzKSsrk7KyMuXrqbze7d27V6xWq9x3332ya9cuWb16teh0OmW3tESO1tPmrbfeEoPBIM8995x8+eWX8tRTT4lOp1N64oiE/i1zcnLkxRdflOrqannooYdEq9VKVVWViIS+5xYWFsqVV14pX375pfzlL3+RKVOm9Nij4rLLLpPS0lIpLy+XiooKufjiiyUtLU312jV37ly55JJL5JtvvpHGxsaE10l1/D318BzK+mJuiYTea5WXl8t3v/tdmTx5svK9MLIbZEtLi+Tn58u3v/1t2bFjh7z22mtitVp73I3uaL1Pt27dKlqtVh599FGprq6WNWvWiMViUf29FxUVicPhkJ/85CdSXV0tzz77bNycPuuss+Tcc8+VnTt3yqZNm+SMM87osW/TPffcI4WFhbJ582bZuXOn3HzzzeJwOFTfX5YsWSKzZs2SmpoaaWxslEAgEHedVMd/tD6LQ9VAza01a9bIK6+8Irt27ZJdu3bJY489JlqtVl566aWkY+Pc4tzavn275ObmynXXXae6RkNDg3IMXxP5mthfc+vll18WvV4vq1evVh3T0tKSdGycW30zt4Z0CBb5R+7+J/YHmlWrVsmYMWPEYDDI2LFjZfny5aqttyMefPBBKSwsVBo3d7dv3z658MILxWKxSE5Ojtx7773i8/l6HF9PIZiIyKZNm2TWrFliNBrF6XTKsmXLVNc877zz5Pbbb5dbb71VHA6HZGZmyve//31VM/qDBw/KvHnzxGazyaRJk+Sdd97psTG+2+2WG264QdLT0yUjI0Nuu+02eeCBB1QhWENDg8ydO1fsdrvyIpzojUAq4x+uIVhfza0vv/xSLr/8csnLyxOr1SozZsyI28b1yJEjcs0114jdbheHwyE33nijtLe39zi+noIKEZFt27bJnDlzxGw2S1ZWlixZskR1zcgP+g899JBkZ2eL3W6XJUuWKMGBiEhra6ssWrRIHA6HFBYWypo1a47avPy+++5Trrdo0SJ5+umnVd+43G63XHHFFZKRkSEAlHna/Tqpjj/WcAkq+mpuLVu2TPLz88VgMMikSZPkqaeeUn1vEOHcSnSdkTy3Es2r2L8LEZGuri65/fbbJTMzU6xWq1x22WVSW1uruk4qr3cbN26U0tJSMRqNMmHChKO+sUilsXMqW16vXr1a5s6dKyaTScaNGyevv/666pgPP/xQTjnlFDGbzXLuuefK2rVre3xTVlNTI3PmzBGLxSKFhYXy7LPPxr12bdmyRWbMmCEmk0kivxs81i27h+sb/r6aW4m2QI/99xERqayslHPOOUdMJpOMHj1annjiiR7HlsoGQL///e9l6tSpyvfUlStXqr5eVFQkK1askCuvvFKsVqs4nU5ZtWqV6pidO3dKWVmZWCwWKS0tlf/7v//rMag4cuSIXHrppWK32yUvL0+WL18u119/ver7S3V1tZx11llisViUv4dE/1dSGf9wDSoGam6tWbNGiouLxWq1isPhkDPOOEPWrl3b49g4tzi3Hn744YTXKCoqUj0WXxP5mtgfcyvZ97Wefpbm3OqbuaUJX4gGwbe+9S2UlpbimWeeGeyh0Ahzww03oKWlBW+//fZgD4VGGM4t6i8ajQZvvfUWFi5cONhDoRFm3LhxuPvuu3H33XcP9lBohOHcov7C10TqL5xbI6gnGBERERERERERUTIMwYiIiIiIiIiIaMTjckgiIiIiIiIiIhrxWAlGREREREREREQjHkMwIiIiIiIiIiIa8RiCERERERERERHRiMcQjIiIiIiIiIiIRjyGYERERERERERENOIxBCMiIiIiIiIiohGPIRgREREREREREY14DMGIiIiIiIiIiGjE+/9wNZETJNHR7wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.iloc[2:7].transpose().plot(figsize=(15, 5))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58d0112b-ec4e-47b7-8737-188a44fe9c46",
   "metadata": {},
   "source": [
    "**Уберём из выборки больших ребят в лице Китая и Индии и заметим, что Япония теряет население**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e1db34f9-1607-4ec5-b20f-8acc02b26e36",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1970 Population    105416839.0\n",
       "1980 Population    117624196.0\n",
       "1990 Population    123686321.0\n",
       "2000 Population    126803861.0\n",
       "2010 Population    128105431.0\n",
       "2015 Population    127250933.0\n",
       "2020 Population    125244761.0\n",
       "2022 Population    123951692.0\n",
       "Name: Japan, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.loc['Japan']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d174d94-f3a5-4ae2-9f0e-da6b3ba5f814",
   "metadata": {},
   "source": [
    "**Как видим с 2010го население уменьшается**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d91b0f1c-b6e5-4117-9006-37b53d08db1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(-4153739.0)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_difference = df2.loc['Japan', '2022 Population'] - df2.loc['Japan', '2010 Population']\n",
    "population_difference"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec93f83b-aa62-4146-b975-7930e5806c69",
   "metadata": {},
   "source": [
    "**на 4 153 739 человек убыло население**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb5a0d73-cf30-4a6c-aaab-8911a7162110",
   "metadata": {},
   "source": [
    "*Табличка с Вики*\n",
    "\n",
    "<img src='https://i.imgur.com/NYxKvL5.png'>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9692e5b2-110a-47c7-9d18-bba7c45e032e",
   "metadata": {},
   "source": [
    "*Причины называют разные, но можно принять как факт*"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}