PRODIGY_DS_01.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3baea0ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5a0904f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Indicator Name</th>\n",
       "      <th>Indicator Code</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>...</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>ABW</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>54608.0</td>\n",
       "      <td>55811.0</td>\n",
       "      <td>56682.0</td>\n",
       "      <td>57475.0</td>\n",
       "      <td>58178.0</td>\n",
       "      <td>58782.0</td>\n",
       "      <td>...</td>\n",
       "      <td>102880.0</td>\n",
       "      <td>103594.0</td>\n",
       "      <td>104257.0</td>\n",
       "      <td>104874.0</td>\n",
       "      <td>105439.0</td>\n",
       "      <td>105962.0</td>\n",
       "      <td>106442.0</td>\n",
       "      <td>106585.0</td>\n",
       "      <td>106537.0</td>\n",
       "      <td>106445.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Africa Eastern and Southern</td>\n",
       "      <td>AFE</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>130692579.0</td>\n",
       "      <td>134169237.0</td>\n",
       "      <td>137835590.0</td>\n",
       "      <td>141630546.0</td>\n",
       "      <td>145605995.0</td>\n",
       "      <td>149742351.0</td>\n",
       "      <td>...</td>\n",
       "      <td>567892149.0</td>\n",
       "      <td>583651101.0</td>\n",
       "      <td>600008424.0</td>\n",
       "      <td>616377605.0</td>\n",
       "      <td>632746570.0</td>\n",
       "      <td>649757148.0</td>\n",
       "      <td>667242986.0</td>\n",
       "      <td>685112979.0</td>\n",
       "      <td>702977106.0</td>\n",
       "      <td>720859132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>8622466.0</td>\n",
       "      <td>8790140.0</td>\n",
       "      <td>8969047.0</td>\n",
       "      <td>9157465.0</td>\n",
       "      <td>9355514.0</td>\n",
       "      <td>9565147.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31541209.0</td>\n",
       "      <td>32716210.0</td>\n",
       "      <td>33753499.0</td>\n",
       "      <td>34636207.0</td>\n",
       "      <td>35643418.0</td>\n",
       "      <td>36686784.0</td>\n",
       "      <td>37769499.0</td>\n",
       "      <td>38972230.0</td>\n",
       "      <td>40099462.0</td>\n",
       "      <td>41128771.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Africa Western and Central</td>\n",
       "      <td>AFW</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>97256290.0</td>\n",
       "      <td>99314028.0</td>\n",
       "      <td>101445032.0</td>\n",
       "      <td>103667517.0</td>\n",
       "      <td>105959979.0</td>\n",
       "      <td>108336203.0</td>\n",
       "      <td>...</td>\n",
       "      <td>387204553.0</td>\n",
       "      <td>397855507.0</td>\n",
       "      <td>408690375.0</td>\n",
       "      <td>419778384.0</td>\n",
       "      <td>431138704.0</td>\n",
       "      <td>442646825.0</td>\n",
       "      <td>454306063.0</td>\n",
       "      <td>466189102.0</td>\n",
       "      <td>478185907.0</td>\n",
       "      <td>490330870.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>AGO</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>5357195.0</td>\n",
       "      <td>5441333.0</td>\n",
       "      <td>5521400.0</td>\n",
       "      <td>5599827.0</td>\n",
       "      <td>5673199.0</td>\n",
       "      <td>5736582.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26147002.0</td>\n",
       "      <td>27128337.0</td>\n",
       "      <td>28127721.0</td>\n",
       "      <td>29154746.0</td>\n",
       "      <td>30208628.0</td>\n",
       "      <td>31273533.0</td>\n",
       "      <td>32353588.0</td>\n",
       "      <td>33428486.0</td>\n",
       "      <td>34503774.0</td>\n",
       "      <td>35588987.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>Kosovo</td>\n",
       "      <td>XKX</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>947000.0</td>\n",
       "      <td>966000.0</td>\n",
       "      <td>994000.0</td>\n",
       "      <td>1022000.0</td>\n",
       "      <td>1050000.0</td>\n",
       "      <td>1078000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1818117.0</td>\n",
       "      <td>1812771.0</td>\n",
       "      <td>1788196.0</td>\n",
       "      <td>1777557.0</td>\n",
       "      <td>1791003.0</td>\n",
       "      <td>1797085.0</td>\n",
       "      <td>1788878.0</td>\n",
       "      <td>1790133.0</td>\n",
       "      <td>1786038.0</td>\n",
       "      <td>1761985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>YEM</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>5542459.0</td>\n",
       "      <td>5646668.0</td>\n",
       "      <td>5753386.0</td>\n",
       "      <td>5860197.0</td>\n",
       "      <td>5973803.0</td>\n",
       "      <td>6097298.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26984002.0</td>\n",
       "      <td>27753304.0</td>\n",
       "      <td>28516545.0</td>\n",
       "      <td>29274002.0</td>\n",
       "      <td>30034389.0</td>\n",
       "      <td>30790513.0</td>\n",
       "      <td>31546691.0</td>\n",
       "      <td>32284046.0</td>\n",
       "      <td>32981641.0</td>\n",
       "      <td>33696614.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>ZAF</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>16520441.0</td>\n",
       "      <td>16989464.0</td>\n",
       "      <td>17503133.0</td>\n",
       "      <td>18042215.0</td>\n",
       "      <td>18603097.0</td>\n",
       "      <td>19187194.0</td>\n",
       "      <td>...</td>\n",
       "      <td>53873616.0</td>\n",
       "      <td>54729551.0</td>\n",
       "      <td>55876504.0</td>\n",
       "      <td>56422274.0</td>\n",
       "      <td>56641209.0</td>\n",
       "      <td>57339635.0</td>\n",
       "      <td>58087055.0</td>\n",
       "      <td>58801927.0</td>\n",
       "      <td>59392255.0</td>\n",
       "      <td>59893885.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>3119430.0</td>\n",
       "      <td>3219451.0</td>\n",
       "      <td>3323427.0</td>\n",
       "      <td>3431381.0</td>\n",
       "      <td>3542764.0</td>\n",
       "      <td>3658024.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15234976.0</td>\n",
       "      <td>15737793.0</td>\n",
       "      <td>16248230.0</td>\n",
       "      <td>16767761.0</td>\n",
       "      <td>17298054.0</td>\n",
       "      <td>17835893.0</td>\n",
       "      <td>18380477.0</td>\n",
       "      <td>18927715.0</td>\n",
       "      <td>19473125.0</td>\n",
       "      <td>20017675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>3806310.0</td>\n",
       "      <td>3925952.0</td>\n",
       "      <td>4049778.0</td>\n",
       "      <td>4177931.0</td>\n",
       "      <td>4310332.0</td>\n",
       "      <td>4447149.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13555422.0</td>\n",
       "      <td>13855753.0</td>\n",
       "      <td>14154937.0</td>\n",
       "      <td>14452704.0</td>\n",
       "      <td>14751101.0</td>\n",
       "      <td>15052184.0</td>\n",
       "      <td>15354608.0</td>\n",
       "      <td>15669666.0</td>\n",
       "      <td>15993524.0</td>\n",
       "      <td>16320537.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>266 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Country Name Country Code     Indicator Name  \\\n",
       "0                          Aruba          ABW  Population, total   \n",
       "1    Africa Eastern and Southern          AFE  Population, total   \n",
       "2                    Afghanistan          AFG  Population, total   \n",
       "3     Africa Western and Central          AFW  Population, total   \n",
       "4                         Angola          AGO  Population, total   \n",
       "..                           ...          ...                ...   \n",
       "261                       Kosovo          XKX  Population, total   \n",
       "262                  Yemen, Rep.          YEM  Population, total   \n",
       "263                 South Africa          ZAF  Population, total   \n",
       "264                       Zambia          ZMB  Population, total   \n",
       "265                     Zimbabwe          ZWE  Population, total   \n",
       "\n",
       "    Indicator Code         1960         1961         1962         1963  \\\n",
       "0      SP.POP.TOTL      54608.0      55811.0      56682.0      57475.0   \n",
       "1      SP.POP.TOTL  130692579.0  134169237.0  137835590.0  141630546.0   \n",
       "2      SP.POP.TOTL    8622466.0    8790140.0    8969047.0    9157465.0   \n",
       "3      SP.POP.TOTL   97256290.0   99314028.0  101445032.0  103667517.0   \n",
       "4      SP.POP.TOTL    5357195.0    5441333.0    5521400.0    5599827.0   \n",
       "..             ...          ...          ...          ...          ...   \n",
       "261    SP.POP.TOTL     947000.0     966000.0     994000.0    1022000.0   \n",
       "262    SP.POP.TOTL    5542459.0    5646668.0    5753386.0    5860197.0   \n",
       "263    SP.POP.TOTL   16520441.0   16989464.0   17503133.0   18042215.0   \n",
       "264    SP.POP.TOTL    3119430.0    3219451.0    3323427.0    3431381.0   \n",
       "265    SP.POP.TOTL    3806310.0    3925952.0    4049778.0    4177931.0   \n",
       "\n",
       "            1964         1965  ...         2013         2014         2015  \\\n",
       "0        58178.0      58782.0  ...     102880.0     103594.0     104257.0   \n",
       "1    145605995.0  149742351.0  ...  567892149.0  583651101.0  600008424.0   \n",
       "2      9355514.0    9565147.0  ...   31541209.0   32716210.0   33753499.0   \n",
       "3    105959979.0  108336203.0  ...  387204553.0  397855507.0  408690375.0   \n",
       "4      5673199.0    5736582.0  ...   26147002.0   27128337.0   28127721.0   \n",
       "..           ...          ...  ...          ...          ...          ...   \n",
       "261    1050000.0    1078000.0  ...    1818117.0    1812771.0    1788196.0   \n",
       "262    5973803.0    6097298.0  ...   26984002.0   27753304.0   28516545.0   \n",
       "263   18603097.0   19187194.0  ...   53873616.0   54729551.0   55876504.0   \n",
       "264    3542764.0    3658024.0  ...   15234976.0   15737793.0   16248230.0   \n",
       "265    4310332.0    4447149.0  ...   13555422.0   13855753.0   14154937.0   \n",
       "\n",
       "            2016         2017         2018         2019         2020  \\\n",
       "0       104874.0     105439.0     105962.0     106442.0     106585.0   \n",
       "1    616377605.0  632746570.0  649757148.0  667242986.0  685112979.0   \n",
       "2     34636207.0   35643418.0   36686784.0   37769499.0   38972230.0   \n",
       "3    419778384.0  431138704.0  442646825.0  454306063.0  466189102.0   \n",
       "4     29154746.0   30208628.0   31273533.0   32353588.0   33428486.0   \n",
       "..           ...          ...          ...          ...          ...   \n",
       "261    1777557.0    1791003.0    1797085.0    1788878.0    1790133.0   \n",
       "262   29274002.0   30034389.0   30790513.0   31546691.0   32284046.0   \n",
       "263   56422274.0   56641209.0   57339635.0   58087055.0   58801927.0   \n",
       "264   16767761.0   17298054.0   17835893.0   18380477.0   18927715.0   \n",
       "265   14452704.0   14751101.0   15052184.0   15354608.0   15669666.0   \n",
       "\n",
       "            2021         2022  \n",
       "0       106537.0     106445.0  \n",
       "1    702977106.0  720859132.0  \n",
       "2     40099462.0   41128771.0  \n",
       "3    478185907.0  490330870.0  \n",
       "4     34503774.0   35588987.0  \n",
       "..           ...          ...  \n",
       "261    1786038.0    1761985.0  \n",
       "262   32981641.0   33696614.0  \n",
       "263   59392255.0   59893885.0  \n",
       "264   19473125.0   20017675.0  \n",
       "265   15993524.0   16320537.0  \n",
       "\n",
       "[266 rows x 67 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"C:\\\\Users\\\\Admin\\\\Downloads\\\\population.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c6dbc827",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Indicator Name</th>\n",
       "      <th>Indicator Code</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>...</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>ABW</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>54608.0</td>\n",
       "      <td>55811.0</td>\n",
       "      <td>56682.0</td>\n",
       "      <td>57475.0</td>\n",
       "      <td>58178.0</td>\n",
       "      <td>58782.0</td>\n",
       "      <td>...</td>\n",
       "      <td>102880.0</td>\n",
       "      <td>103594.0</td>\n",
       "      <td>104257.0</td>\n",
       "      <td>104874.0</td>\n",
       "      <td>105439.0</td>\n",
       "      <td>105962.0</td>\n",
       "      <td>106442.0</td>\n",
       "      <td>106585.0</td>\n",
       "      <td>106537.0</td>\n",
       "      <td>106445.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Africa Eastern and Southern</td>\n",
       "      <td>AFE</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>130692579.0</td>\n",
       "      <td>134169237.0</td>\n",
       "      <td>137835590.0</td>\n",
       "      <td>141630546.0</td>\n",
       "      <td>145605995.0</td>\n",
       "      <td>149742351.0</td>\n",
       "      <td>...</td>\n",
       "      <td>567892149.0</td>\n",
       "      <td>583651101.0</td>\n",
       "      <td>600008424.0</td>\n",
       "      <td>616377605.0</td>\n",
       "      <td>632746570.0</td>\n",
       "      <td>649757148.0</td>\n",
       "      <td>667242986.0</td>\n",
       "      <td>685112979.0</td>\n",
       "      <td>702977106.0</td>\n",
       "      <td>720859132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>8622466.0</td>\n",
       "      <td>8790140.0</td>\n",
       "      <td>8969047.0</td>\n",
       "      <td>9157465.0</td>\n",
       "      <td>9355514.0</td>\n",
       "      <td>9565147.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31541209.0</td>\n",
       "      <td>32716210.0</td>\n",
       "      <td>33753499.0</td>\n",
       "      <td>34636207.0</td>\n",
       "      <td>35643418.0</td>\n",
       "      <td>36686784.0</td>\n",
       "      <td>37769499.0</td>\n",
       "      <td>38972230.0</td>\n",
       "      <td>40099462.0</td>\n",
       "      <td>41128771.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Africa Western and Central</td>\n",
       "      <td>AFW</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>97256290.0</td>\n",
       "      <td>99314028.0</td>\n",
       "      <td>101445032.0</td>\n",
       "      <td>103667517.0</td>\n",
       "      <td>105959979.0</td>\n",
       "      <td>108336203.0</td>\n",
       "      <td>...</td>\n",
       "      <td>387204553.0</td>\n",
       "      <td>397855507.0</td>\n",
       "      <td>408690375.0</td>\n",
       "      <td>419778384.0</td>\n",
       "      <td>431138704.0</td>\n",
       "      <td>442646825.0</td>\n",
       "      <td>454306063.0</td>\n",
       "      <td>466189102.0</td>\n",
       "      <td>478185907.0</td>\n",
       "      <td>490330870.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>AGO</td>\n",
       "      <td>Population, total</td>\n",
       "      <td>SP.POP.TOTL</td>\n",
       "      <td>5357195.0</td>\n",
       "      <td>5441333.0</td>\n",
       "      <td>5521400.0</td>\n",
       "      <td>5599827.0</td>\n",
       "      <td>5673199.0</td>\n",
       "      <td>5736582.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26147002.0</td>\n",
       "      <td>27128337.0</td>\n",
       "      <td>28127721.0</td>\n",
       "      <td>29154746.0</td>\n",
       "      <td>30208628.0</td>\n",
       "      <td>31273533.0</td>\n",
       "      <td>32353588.0</td>\n",
       "      <td>33428486.0</td>\n",
       "      <td>34503774.0</td>\n",
       "      <td>35588987.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Country Name Country Code     Indicator Name Indicator Code  \\\n",
       "0                        Aruba          ABW  Population, total    SP.POP.TOTL   \n",
       "1  Africa Eastern and Southern          AFE  Population, total    SP.POP.TOTL   \n",
       "2                  Afghanistan          AFG  Population, total    SP.POP.TOTL   \n",
       "3   Africa Western and Central          AFW  Population, total    SP.POP.TOTL   \n",
       "4                       Angola          AGO  Population, total    SP.POP.TOTL   \n",
       "\n",
       "          1960         1961         1962         1963         1964  \\\n",
       "0      54608.0      55811.0      56682.0      57475.0      58178.0   \n",
       "1  130692579.0  134169237.0  137835590.0  141630546.0  145605995.0   \n",
       "2    8622466.0    8790140.0    8969047.0    9157465.0    9355514.0   \n",
       "3   97256290.0   99314028.0  101445032.0  103667517.0  105959979.0   \n",
       "4    5357195.0    5441333.0    5521400.0    5599827.0    5673199.0   \n",
       "\n",
       "          1965  ...         2013         2014         2015         2016  \\\n",
       "0      58782.0  ...     102880.0     103594.0     104257.0     104874.0   \n",
       "1  149742351.0  ...  567892149.0  583651101.0  600008424.0  616377605.0   \n",
       "2    9565147.0  ...   31541209.0   32716210.0   33753499.0   34636207.0   \n",
       "3  108336203.0  ...  387204553.0  397855507.0  408690375.0  419778384.0   \n",
       "4    5736582.0  ...   26147002.0   27128337.0   28127721.0   29154746.0   \n",
       "\n",
       "          2017         2018         2019         2020         2021  \\\n",
       "0     105439.0     105962.0     106442.0     106585.0     106537.0   \n",
       "1  632746570.0  649757148.0  667242986.0  685112979.0  702977106.0   \n",
       "2   35643418.0   36686784.0   37769499.0   38972230.0   40099462.0   \n",
       "3  431138704.0  442646825.0  454306063.0  466189102.0  478185907.0   \n",
       "4   30208628.0   31273533.0   32353588.0   33428486.0   34503774.0   \n",
       "\n",
       "          2022  \n",
       "0     106445.0  \n",
       "1  720859132.0  \n",
       "2   41128771.0  \n",
       "3  490330870.0  \n",
       "4   35588987.0  \n",
       "\n",
       "[5 rows x 67 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d6992021",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of                     Country Name Country Code     Indicator Name  \\\n",
       "0                          Aruba          ABW  Population, total   \n",
       "1    Africa Eastern and Southern          AFE  Population, total   \n",
       "2                    Afghanistan          AFG  Population, total   \n",
       "3     Africa Western and Central          AFW  Population, total   \n",
       "4                         Angola          AGO  Population, total   \n",
       "..                           ...          ...                ...   \n",
       "261                       Kosovo          XKX  Population, total   \n",
       "262                  Yemen, Rep.          YEM  Population, total   \n",
       "263                 South Africa          ZAF  Population, total   \n",
       "264                       Zambia          ZMB  Population, total   \n",
       "265                     Zimbabwe          ZWE  Population, total   \n",
       "\n",
       "    Indicator Code         1960         1961         1962         1963  \\\n",
       "0      SP.POP.TOTL      54608.0      55811.0      56682.0      57475.0   \n",
       "1      SP.POP.TOTL  130692579.0  134169237.0  137835590.0  141630546.0   \n",
       "2      SP.POP.TOTL    8622466.0    8790140.0    8969047.0    9157465.0   \n",
       "3      SP.POP.TOTL   97256290.0   99314028.0  101445032.0  103667517.0   \n",
       "4      SP.POP.TOTL    5357195.0    5441333.0    5521400.0    5599827.0   \n",
       "..             ...          ...          ...          ...          ...   \n",
       "261    SP.POP.TOTL     947000.0     966000.0     994000.0    1022000.0   \n",
       "262    SP.POP.TOTL    5542459.0    5646668.0    5753386.0    5860197.0   \n",
       "263    SP.POP.TOTL   16520441.0   16989464.0   17503133.0   18042215.0   \n",
       "264    SP.POP.TOTL    3119430.0    3219451.0    3323427.0    3431381.0   \n",
       "265    SP.POP.TOTL    3806310.0    3925952.0    4049778.0    4177931.0   \n",
       "\n",
       "            1964         1965  ...         2013         2014         2015  \\\n",
       "0        58178.0      58782.0  ...     102880.0     103594.0     104257.0   \n",
       "1    145605995.0  149742351.0  ...  567892149.0  583651101.0  600008424.0   \n",
       "2      9355514.0    9565147.0  ...   31541209.0   32716210.0   33753499.0   \n",
       "3    105959979.0  108336203.0  ...  387204553.0  397855507.0  408690375.0   \n",
       "4      5673199.0    5736582.0  ...   26147002.0   27128337.0   28127721.0   \n",
       "..           ...          ...  ...          ...          ...          ...   \n",
       "261    1050000.0    1078000.0  ...    1818117.0    1812771.0    1788196.0   \n",
       "262    5973803.0    6097298.0  ...   26984002.0   27753304.0   28516545.0   \n",
       "263   18603097.0   19187194.0  ...   53873616.0   54729551.0   55876504.0   \n",
       "264    3542764.0    3658024.0  ...   15234976.0   15737793.0   16248230.0   \n",
       "265    4310332.0    4447149.0  ...   13555422.0   13855753.0   14154937.0   \n",
       "\n",
       "            2016         2017         2018         2019         2020  \\\n",
       "0       104874.0     105439.0     105962.0     106442.0     106585.0   \n",
       "1    616377605.0  632746570.0  649757148.0  667242986.0  685112979.0   \n",
       "2     34636207.0   35643418.0   36686784.0   37769499.0   38972230.0   \n",
       "3    419778384.0  431138704.0  442646825.0  454306063.0  466189102.0   \n",
       "4     29154746.0   30208628.0   31273533.0   32353588.0   33428486.0   \n",
       "..           ...          ...          ...          ...          ...   \n",
       "261    1777557.0    1791003.0    1797085.0    1788878.0    1790133.0   \n",
       "262   29274002.0   30034389.0   30790513.0   31546691.0   32284046.0   \n",
       "263   56422274.0   56641209.0   57339635.0   58087055.0   58801927.0   \n",
       "264   16767761.0   17298054.0   17835893.0   18380477.0   18927715.0   \n",
       "265   14452704.0   14751101.0   15052184.0   15354608.0   15669666.0   \n",
       "\n",
       "            2021         2022  \n",
       "0       106537.0     106445.0  \n",
       "1    702977106.0  720859132.0  \n",
       "2     40099462.0   41128771.0  \n",
       "3    478185907.0  490330870.0  \n",
       "4     34503774.0   35588987.0  \n",
       "..           ...          ...  \n",
       "261    1786038.0    1761985.0  \n",
       "262   32981641.0   33696614.0  \n",
       "263   59392255.0   59893885.0  \n",
       "264   19473125.0   20017675.0  \n",
       "265   15993524.0   16320537.0  \n",
       "\n",
       "[266 rows x 67 columns]>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "870ce8f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "countries_to_plot = ['United States', 'Canada', 'Brazil', 'Japan', 'Germany', 'France']\n",
    "filtered_data = df[df['Country Name'].isin(countries_to_plot)]\n",
    "\n",
    "#Creating the bar chart\n",
    "plt.bar (filtered_data['Country Name'], filtered_data['2022'])\n",
    "plt.xlabel ('Country Name')\n",
    "plt.ylabel ('Population in 2022')\n",
    "plt.title('Population of selected countries in 2022')\n",
    "plt.xticks(rotation=45, ha='right') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "66dbd5e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming 'filtered_data['2022']' contains numerical data for the population\n",
    "plt.hist(filtered_data['2022'], bins=10)  # You can change the number of bins as needed\n",
    "plt.xlabel('Population in 2022')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of Population in 2022')\n",
    "plt.xticks(rotation=45, ha='right')  # Adjust if necessary for histogram\n",
    "plt.show()\n"
   ]
  }
 ],
 "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": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}