M003.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "da6d06c2-2c01-460f-be32-755ed39db9cc",
   "metadata": {},
   "source": [
    "## Pandas\n",
    "\n",
    "Advanced Python Data Analysis Toolkit\n",
    "\n",
    "Hauptwerkzeug zur Verarbeitung von Daten"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "76fc755d-6053-4f4c-9395-111c036069b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f259f03-c9c7-4ead-ae78-24ef6c1bc167",
   "metadata": {},
   "source": [
    "### Serie\n",
    "\n",
    "Numpy Array mit zusätzlichen Eigenschaften\n",
    "\n",
    "- Name\n",
    "- Benannter Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fa30258c-0e7b-44f4-9762-119b5a3501e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     9.00\n",
       "1    83.70\n",
       "2     8.60\n",
       "3     0.38\n",
       "dtype: float64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series([9, 83.7, 8.6, 0.38])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9457e0ca-6520-4be8-9702-de528774cca6",
   "metadata": {},
   "source": [
    "Werte alleine sind nicht aussagekräftig -> Beschriftungen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "08b8ddea-b966-4306-909f-48934043261f",
   "metadata": {},
   "outputs": [],
   "source": [
    "einwohnerM = pd.Series([9, 83.7, 8.6, 0.38])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "90e2ea52-ea7f-4e3f-bcd7-6f240ee0b2f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "einwohnerM.name = \"Einwohnerzahlen DACHLI\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "682636f4-a719-47a2-b41c-876ea4677cc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     9.00\n",
       "1    83.70\n",
       "2     8.60\n",
       "3     0.38\n",
       "Name: Einwohnerzahlen DACHLI, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6bc5d5f2-0105-4f3e-9f73-7e115c1c21f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "einwohnerM.index = [\"AT\", \"DE\", \"CH\", \"LI\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4dc640a1-b6e5-43e6-8eeb-57c27d72d01f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AT     9.00\n",
       "DE    83.70\n",
       "CH     8.60\n",
       "LI     0.38\n",
       "Name: Einwohnerzahlen DACHLI, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ba16c409-03aa-43d7-aecd-af32106974d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 9.  , 83.7 ,  8.6 ,  0.38])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM.values  # Unterliegendes Numpy Array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1585fc0e-ea2d-474d-85cd-055b49647879",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\lk3\\AppData\\Local\\Temp\\ipykernel_12068\\3060421205.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  einwohnerM[0]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "np.float64(9.0)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ffd6dbc7-3492-4fd7-a2f4-594f48ceb7be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(9.0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f17bb31c-adb9-4a8f-b2f3-1990a18b2757",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AT     9.0\n",
       "DE    83.7\n",
       "Name: Einwohnerzahlen DACHLI, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2a418824-41b7-42b7-b41d-2fc8570f0128",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AT     9.0\n",
       "DE    83.7\n",
       "CH     8.6\n",
       "Name: Einwohnerzahlen DACHLI, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM[\"AT\":\"CH\"]  # Textbasierter Bereichsindex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a219ebba-f437-4135-8e26-5c8993a61bf9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(25.419999999999998)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM.mean()  # Funktionen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c94f2950-b03d-4658-a449-9b37011f8383",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AT    9.00\n",
       "CH    8.60\n",
       "LI    0.38\n",
       "Name: Einwohnerzahlen DACHLI, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "einwohnerM[einwohnerM < einwohnerM.mean()]  # Vektorisierung"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a8f721e-2ab8-410e-ba7b-2ac3c0925b13",
   "metadata": {},
   "source": [
    "### DataFrame\n",
    "\n",
    "Effektiv eine Tabelle (2D-Datenset)\n",
    "\n",
    "Jede Zeile/Spalte ist eine Serie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0833d391-311c-4de8-b7f2-9e242c592076",
   "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>Spalte 1</th>\n",
       "      <th>Spalte 2</th>\n",
       "      <th>Spalte 3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Spalte 1  Spalte 2  Spalte 3\n",
       "0         1         4         7\n",
       "1         2         5         8\n",
       "2         3         6         9"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame({\"Spalte 1\": [1, 2, 3], \"Spalte 2\": [4, 5, 6], \"Spalte 3\": [7, 8, 9]})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "931fcfbc-8f3b-43bd-9125-63cf372a03d8",
   "metadata": {},
   "source": [
    "#### Externe Daten einlesen\n",
    "\n",
    "Über die read_... Funktionen können externe Daten eingelesen werden"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d2d65b7e-d215-4598-9be4-2a2b54d913ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"Data/PopulationData.csv\", delimiter=\";\", thousands=\",\", decimal=\".\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0cb33d1b-1522-4e07-8989-e56b04e9c21a",
   "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>#</th>\n",
       "      <th>Country (or dependency)</th>\n",
       "      <th>Population(2020)</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density(P/Km²)</th>\n",
       "      <th>Land Area(Km²)</th>\n",
       "      <th>Migrants(net)</th>\n",
       "      <th>Fert.Rate</th>\n",
       "      <th>Med.Age</th>\n",
       "      <th>UrbanPop %</th>\n",
       "      <th>WorldShare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "      <td>1439323776</td>\n",
       "      <td>0.39 %</td>\n",
       "      <td>5540090</td>\n",
       "      <td>153</td>\n",
       "      <td>9388211</td>\n",
       "      <td>-348399.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>38</td>\n",
       "      <td>61 %</td>\n",
       "      <td>18.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>India</td>\n",
       "      <td>1380004385</td>\n",
       "      <td>0.99 %</td>\n",
       "      <td>13586631</td>\n",
       "      <td>464</td>\n",
       "      <td>2973190</td>\n",
       "      <td>-532687.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>28</td>\n",
       "      <td>35 %</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>United States</td>\n",
       "      <td>331002651</td>\n",
       "      <td>0.59 %</td>\n",
       "      <td>1937734</td>\n",
       "      <td>36</td>\n",
       "      <td>9147420</td>\n",
       "      <td>954806.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>38</td>\n",
       "      <td>83 %</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>273523615</td>\n",
       "      <td>1.07 %</td>\n",
       "      <td>2898047</td>\n",
       "      <td>151</td>\n",
       "      <td>1811570</td>\n",
       "      <td>-98955.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>30</td>\n",
       "      <td>56 %</td>\n",
       "      <td>3.51 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>220892340</td>\n",
       "      <td>2.00 %</td>\n",
       "      <td>4327022</td>\n",
       "      <td>287</td>\n",
       "      <td>770880</td>\n",
       "      <td>-233379.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>231</td>\n",
       "      <td>Montserrat</td>\n",
       "      <td>4992</td>\n",
       "      <td>0.06 %</td>\n",
       "      <td>3</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>10 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>232</td>\n",
       "      <td>Falkland Islands</td>\n",
       "      <td>3480</td>\n",
       "      <td>3.05 %</td>\n",
       "      <td>103</td>\n",
       "      <td>0</td>\n",
       "      <td>12170</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>66 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>233</td>\n",
       "      <td>Niue</td>\n",
       "      <td>1626</td>\n",
       "      <td>0.68 %</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>46 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>234</td>\n",
       "      <td>Tokelau</td>\n",
       "      <td>1357</td>\n",
       "      <td>1.27 %</td>\n",
       "      <td>17</td>\n",
       "      <td>136</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>235</td>\n",
       "      <td>Vatican State</td>\n",
       "      <td>801</td>\n",
       "      <td>0.25 %</td>\n",
       "      <td>2</td>\n",
       "      <td>2003</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>235 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       # Country (or dependency)  Population(2020) YearlyChange  NetChange  \\\n",
       "0      1                   China        1439323776       0.39 %    5540090   \n",
       "1      2                   India        1380004385       0.99 %   13586631   \n",
       "2      3           United States         331002651       0.59 %    1937734   \n",
       "3      4               Indonesia         273523615       1.07 %    2898047   \n",
       "4      5                Pakistan         220892340       2.00 %    4327022   \n",
       "..   ...                     ...               ...          ...        ...   \n",
       "230  231              Montserrat              4992       0.06 %          3   \n",
       "231  232        Falkland Islands              3480       3.05 %        103   \n",
       "232  233                    Niue              1626       0.68 %         11   \n",
       "233  234                 Tokelau              1357       1.27 %         17   \n",
       "234  235           Vatican State               801       0.25 %          2   \n",
       "\n",
       "     Density(P/Km²)  Land Area(Km²)  Migrants(net) Fert.Rate Med.Age  \\\n",
       "0               153         9388211      -348399.0       1.7      38   \n",
       "1               464         2973190      -532687.0       2.2      28   \n",
       "2                36         9147420       954806.0       1.8      38   \n",
       "3               151         1811570       -98955.0       2.3      30   \n",
       "4               287          770880      -233379.0       3.6      23   \n",
       "..              ...             ...            ...       ...     ...   \n",
       "230              50             100            NaN      N.A.    N.A.   \n",
       "231               0           12170            NaN      N.A.    N.A.   \n",
       "232               6             260            NaN      N.A.    N.A.   \n",
       "233             136              10            NaN      N.A.    N.A.   \n",
       "234            2003               0            NaN      N.A.    N.A.   \n",
       "\n",
       "    UrbanPop % WorldShare  \n",
       "0         61 %    18.47 %  \n",
       "1         35 %    17.70 %  \n",
       "2         83 %     4.25 %  \n",
       "3         56 %     3.51 %  \n",
       "4         35 %     2.83 %  \n",
       "..         ...        ...  \n",
       "230       10 %     0.00 %  \n",
       "231       66 %     0.00 %  \n",
       "232       46 %     0.00 %  \n",
       "233        0 %     0.00 %  \n",
       "234       N.A.     0.00 %  \n",
       "\n",
       "[235 rows x 12 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7486dd41-9920-46a3-b673-2d7bfeeb5b10",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 235 entries, 0 to 234\n",
      "Data columns (total 12 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   #                        235 non-null    int64  \n",
      " 1   Country (or dependency)  235 non-null    object \n",
      " 2   Population(2020)         235 non-null    int64  \n",
      " 3   YearlyChange             235 non-null    object \n",
      " 4   NetChange                235 non-null    int64  \n",
      " 5   Density(P/Km²)           235 non-null    int64  \n",
      " 6   Land Area(Km²)           235 non-null    int64  \n",
      " 7   Migrants(net)            201 non-null    float64\n",
      " 8   Fert.Rate                235 non-null    object \n",
      " 9   Med.Age                  235 non-null    object \n",
      " 10  UrbanPop %               235 non-null    object \n",
      " 11  WorldShare               235 non-null    object \n",
      "dtypes: float64(1), int64(5), object(6)\n",
      "memory usage: 22.2+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()  # Datentypen prüfen"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f7a3b3b-92f5-4511-ad74-6e90b771664a",
   "metadata": {},
   "source": [
    "#### Probleme mit dem Datenset\n",
    "- DataFrame selbst\n",
    "    - Spaltennamen\n",
    "    - Index Spalte auf Country setzen\n",
    "- Daten\n",
    "    - Prozentzeichen\n",
    "    - NaN (Leere Zellen)\n",
    "    - N.A. (Text)\n",
    "    - Datentypen"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f531fc57-b785-4df6-a068-33f437beaadb",
   "metadata": {},
   "source": [
    "#### Spaltennamen\n",
    "\n",
    "Um Spaltennamen zu ändern wird die rename Funktion verwendet\n",
    "\n",
    "Um Spalten zu entfernen wird die drop Funktion verwendet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6e7aad56-2d1c-488e-99b4-6eb737bab2e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# data.drop(columns=\"#\")  # Bei jeder Funktion, die das DataFrame verändert, wird immer eine Kopie erzeugt\n",
    "data.drop(columns=\"#\", inplace=True)  # inplace: Wendet die Änderung auf das originale DataFrame an"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b5ea2bb8-393c-41cd-8821-17fe9ff908c2",
   "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 (or dependency)</th>\n",
       "      <th>Population(2020)</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density(P/Km²)</th>\n",
       "      <th>Land Area(Km²)</th>\n",
       "      <th>Migrants(net)</th>\n",
       "      <th>Fert.Rate</th>\n",
       "      <th>Med.Age</th>\n",
       "      <th>UrbanPop %</th>\n",
       "      <th>WorldShare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>China</td>\n",
       "      <td>1439323776</td>\n",
       "      <td>0.39 %</td>\n",
       "      <td>5540090</td>\n",
       "      <td>153</td>\n",
       "      <td>9388211</td>\n",
       "      <td>-348399.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>38</td>\n",
       "      <td>61 %</td>\n",
       "      <td>18.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>India</td>\n",
       "      <td>1380004385</td>\n",
       "      <td>0.99 %</td>\n",
       "      <td>13586631</td>\n",
       "      <td>464</td>\n",
       "      <td>2973190</td>\n",
       "      <td>-532687.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>28</td>\n",
       "      <td>35 %</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United States</td>\n",
       "      <td>331002651</td>\n",
       "      <td>0.59 %</td>\n",
       "      <td>1937734</td>\n",
       "      <td>36</td>\n",
       "      <td>9147420</td>\n",
       "      <td>954806.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>38</td>\n",
       "      <td>83 %</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>273523615</td>\n",
       "      <td>1.07 %</td>\n",
       "      <td>2898047</td>\n",
       "      <td>151</td>\n",
       "      <td>1811570</td>\n",
       "      <td>-98955.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>30</td>\n",
       "      <td>56 %</td>\n",
       "      <td>3.51 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pakistan</td>\n",
       "      <td>220892340</td>\n",
       "      <td>2.00 %</td>\n",
       "      <td>4327022</td>\n",
       "      <td>287</td>\n",
       "      <td>770880</td>\n",
       "      <td>-233379.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>Montserrat</td>\n",
       "      <td>4992</td>\n",
       "      <td>0.06 %</td>\n",
       "      <td>3</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>10 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Falkland Islands</td>\n",
       "      <td>3480</td>\n",
       "      <td>3.05 %</td>\n",
       "      <td>103</td>\n",
       "      <td>0</td>\n",
       "      <td>12170</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>66 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Niue</td>\n",
       "      <td>1626</td>\n",
       "      <td>0.68 %</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>46 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>Tokelau</td>\n",
       "      <td>1357</td>\n",
       "      <td>1.27 %</td>\n",
       "      <td>17</td>\n",
       "      <td>136</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>Vatican State</td>\n",
       "      <td>801</td>\n",
       "      <td>0.25 %</td>\n",
       "      <td>2</td>\n",
       "      <td>2003</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>235 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country (or dependency)  Population(2020) YearlyChange  NetChange  \\\n",
       "0                     China        1439323776       0.39 %    5540090   \n",
       "1                     India        1380004385       0.99 %   13586631   \n",
       "2             United States         331002651       0.59 %    1937734   \n",
       "3                 Indonesia         273523615       1.07 %    2898047   \n",
       "4                  Pakistan         220892340       2.00 %    4327022   \n",
       "..                      ...               ...          ...        ...   \n",
       "230              Montserrat              4992       0.06 %          3   \n",
       "231        Falkland Islands              3480       3.05 %        103   \n",
       "232                    Niue              1626       0.68 %         11   \n",
       "233                 Tokelau              1357       1.27 %         17   \n",
       "234           Vatican State               801       0.25 %          2   \n",
       "\n",
       "     Density(P/Km²)  Land Area(Km²)  Migrants(net) Fert.Rate Med.Age  \\\n",
       "0               153         9388211      -348399.0       1.7      38   \n",
       "1               464         2973190      -532687.0       2.2      28   \n",
       "2                36         9147420       954806.0       1.8      38   \n",
       "3               151         1811570       -98955.0       2.3      30   \n",
       "4               287          770880      -233379.0       3.6      23   \n",
       "..              ...             ...            ...       ...     ...   \n",
       "230              50             100            NaN      N.A.    N.A.   \n",
       "231               0           12170            NaN      N.A.    N.A.   \n",
       "232               6             260            NaN      N.A.    N.A.   \n",
       "233             136              10            NaN      N.A.    N.A.   \n",
       "234            2003               0            NaN      N.A.    N.A.   \n",
       "\n",
       "    UrbanPop % WorldShare  \n",
       "0         61 %    18.47 %  \n",
       "1         35 %    17.70 %  \n",
       "2         83 %     4.25 %  \n",
       "3         56 %     3.51 %  \n",
       "4         35 %     2.83 %  \n",
       "..         ...        ...  \n",
       "230       10 %     0.00 %  \n",
       "231       66 %     0.00 %  \n",
       "232       46 %     0.00 %  \n",
       "233        0 %     0.00 %  \n",
       "234       N.A.     0.00 %  \n",
       "\n",
       "[235 rows x 11 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1611de53-6cc2-4438-b931-ee3e231fa2df",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.rename(columns={\n",
    "    \"Country (or dependency)\": \"Country\",\n",
    "    \"Population(2020)\": \"Pop\",\n",
    "    \"Density(P/Km²)\": \"Density\",\n",
    "    \"Land Area(Km²)\": \"Area\",\n",
    "    \"Migrants(net)\": \"Migrants\",\n",
    "    \"Fert.Rate\": \"FertRate\",\n",
    "    \"Med.Age\": \"MedAge\",\n",
    "    \"UrbanPop %\": \"UrbanPopPct\"\n",
    "}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4081ac3e-f5a6-42ea-babb-174f7d176ec7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density</th>\n",
       "      <th>Area</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>FertRate</th>\n",
       "      <th>MedAge</th>\n",
       "      <th>UrbanPopPct</th>\n",
       "      <th>WorldShare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>China</td>\n",
       "      <td>1439323776</td>\n",
       "      <td>0.39 %</td>\n",
       "      <td>5540090</td>\n",
       "      <td>153</td>\n",
       "      <td>9388211</td>\n",
       "      <td>-348399.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>38</td>\n",
       "      <td>61 %</td>\n",
       "      <td>18.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>India</td>\n",
       "      <td>1380004385</td>\n",
       "      <td>0.99 %</td>\n",
       "      <td>13586631</td>\n",
       "      <td>464</td>\n",
       "      <td>2973190</td>\n",
       "      <td>-532687.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>28</td>\n",
       "      <td>35 %</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United States</td>\n",
       "      <td>331002651</td>\n",
       "      <td>0.59 %</td>\n",
       "      <td>1937734</td>\n",
       "      <td>36</td>\n",
       "      <td>9147420</td>\n",
       "      <td>954806.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>38</td>\n",
       "      <td>83 %</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>273523615</td>\n",
       "      <td>1.07 %</td>\n",
       "      <td>2898047</td>\n",
       "      <td>151</td>\n",
       "      <td>1811570</td>\n",
       "      <td>-98955.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>30</td>\n",
       "      <td>56 %</td>\n",
       "      <td>3.51 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pakistan</td>\n",
       "      <td>220892340</td>\n",
       "      <td>2.00 %</td>\n",
       "      <td>4327022</td>\n",
       "      <td>287</td>\n",
       "      <td>770880</td>\n",
       "      <td>-233379.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>Montserrat</td>\n",
       "      <td>4992</td>\n",
       "      <td>0.06 %</td>\n",
       "      <td>3</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>10 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>Falkland Islands</td>\n",
       "      <td>3480</td>\n",
       "      <td>3.05 %</td>\n",
       "      <td>103</td>\n",
       "      <td>0</td>\n",
       "      <td>12170</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>66 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Niue</td>\n",
       "      <td>1626</td>\n",
       "      <td>0.68 %</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>46 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>Tokelau</td>\n",
       "      <td>1357</td>\n",
       "      <td>1.27 %</td>\n",
       "      <td>17</td>\n",
       "      <td>136</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>Vatican State</td>\n",
       "      <td>801</td>\n",
       "      <td>0.25 %</td>\n",
       "      <td>2</td>\n",
       "      <td>2003</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>235 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Country         Pop YearlyChange  NetChange  Density     Area  \\\n",
       "0               China  1439323776       0.39 %    5540090      153  9388211   \n",
       "1               India  1380004385       0.99 %   13586631      464  2973190   \n",
       "2       United States   331002651       0.59 %    1937734       36  9147420   \n",
       "3           Indonesia   273523615       1.07 %    2898047      151  1811570   \n",
       "4            Pakistan   220892340       2.00 %    4327022      287   770880   \n",
       "..                ...         ...          ...        ...      ...      ...   \n",
       "230        Montserrat        4992       0.06 %          3       50      100   \n",
       "231  Falkland Islands        3480       3.05 %        103        0    12170   \n",
       "232              Niue        1626       0.68 %         11        6      260   \n",
       "233           Tokelau        1357       1.27 %         17      136       10   \n",
       "234     Vatican State         801       0.25 %          2     2003        0   \n",
       "\n",
       "     Migrants FertRate MedAge UrbanPopPct WorldShare  \n",
       "0   -348399.0      1.7     38        61 %    18.47 %  \n",
       "1   -532687.0      2.2     28        35 %    17.70 %  \n",
       "2    954806.0      1.8     38        83 %     4.25 %  \n",
       "3    -98955.0      2.3     30        56 %     3.51 %  \n",
       "4   -233379.0      3.6     23        35 %     2.83 %  \n",
       "..        ...      ...    ...         ...        ...  \n",
       "230       NaN     N.A.   N.A.        10 %     0.00 %  \n",
       "231       NaN     N.A.   N.A.        66 %     0.00 %  \n",
       "232       NaN     N.A.   N.A.        46 %     0.00 %  \n",
       "233       NaN     N.A.   N.A.         0 %     0.00 %  \n",
       "234       NaN     N.A.   N.A.        N.A.     0.00 %  \n",
       "\n",
       "[235 rows x 11 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8782ad2d-8f76-4413-9f50-d804036e79bf",
   "metadata": {},
   "source": [
    "#### Index setzen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "dcf7a0e5-3051-4137-9454-475b0aea883e",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.set_index(\"Country\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b030c82d-f193-4429-86f9-47a8788b7b7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
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       "    </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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>1439323776</td>\n",
       "      <td>0.39 %</td>\n",
       "      <td>5540090</td>\n",
       "      <td>153</td>\n",
       "      <td>9388211</td>\n",
       "      <td>-348399.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>38</td>\n",
       "      <td>61 %</td>\n",
       "      <td>18.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1380004385</td>\n",
       "      <td>0.99 %</td>\n",
       "      <td>13586631</td>\n",
       "      <td>464</td>\n",
       "      <td>2973190</td>\n",
       "      <td>-532687.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>28</td>\n",
       "      <td>35 %</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>331002651</td>\n",
       "      <td>0.59 %</td>\n",
       "      <td>1937734</td>\n",
       "      <td>36</td>\n",
       "      <td>9147420</td>\n",
       "      <td>954806.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>38</td>\n",
       "      <td>83 %</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>273523615</td>\n",
       "      <td>1.07 %</td>\n",
       "      <td>2898047</td>\n",
       "      <td>151</td>\n",
       "      <td>1811570</td>\n",
       "      <td>-98955.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>30</td>\n",
       "      <td>56 %</td>\n",
       "      <td>3.51 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pakistan</th>\n",
       "      <td>220892340</td>\n",
       "      <td>2.00 %</td>\n",
       "      <td>4327022</td>\n",
       "      <td>287</td>\n",
       "      <td>770880</td>\n",
       "      <td>-233379.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montserrat</th>\n",
       "      <td>4992</td>\n",
       "      <td>0.06 %</td>\n",
       "      <td>3</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>10 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Falkland Islands</th>\n",
       "      <td>3480</td>\n",
       "      <td>3.05 %</td>\n",
       "      <td>103</td>\n",
       "      <td>0</td>\n",
       "      <td>12170</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>66 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Niue</th>\n",
       "      <td>1626</td>\n",
       "      <td>0.68 %</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>46 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tokelau</th>\n",
       "      <td>1357</td>\n",
       "      <td>1.27 %</td>\n",
       "      <td>17</td>\n",
       "      <td>136</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vatican State</th>\n",
       "      <td>801</td>\n",
       "      <td>0.25 %</td>\n",
       "      <td>2</td>\n",
       "      <td>2003</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>235 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Pop YearlyChange  NetChange  Density     Area  \\\n",
       "Country                                                                  \n",
       "China             1439323776       0.39 %    5540090      153  9388211   \n",
       "India             1380004385       0.99 %   13586631      464  2973190   \n",
       "United States      331002651       0.59 %    1937734       36  9147420   \n",
       "Indonesia          273523615       1.07 %    2898047      151  1811570   \n",
       "Pakistan           220892340       2.00 %    4327022      287   770880   \n",
       "...                      ...          ...        ...      ...      ...   \n",
       "Montserrat              4992       0.06 %          3       50      100   \n",
       "Falkland Islands        3480       3.05 %        103        0    12170   \n",
       "Niue                    1626       0.68 %         11        6      260   \n",
       "Tokelau                 1357       1.27 %         17      136       10   \n",
       "Vatican State            801       0.25 %          2     2003        0   \n",
       "\n",
       "                  Migrants FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                                            \n",
       "China            -348399.0      1.7     38        61 %    18.47 %  \n",
       "India            -532687.0      2.2     28        35 %    17.70 %  \n",
       "United States     954806.0      1.8     38        83 %     4.25 %  \n",
       "Indonesia         -98955.0      2.3     30        56 %     3.51 %  \n",
       "Pakistan         -233379.0      3.6     23        35 %     2.83 %  \n",
       "...                    ...      ...    ...         ...        ...  \n",
       "Montserrat             NaN     N.A.   N.A.        10 %     0.00 %  \n",
       "Falkland Islands       NaN     N.A.   N.A.        66 %     0.00 %  \n",
       "Niue                   NaN     N.A.   N.A.        46 %     0.00 %  \n",
       "Tokelau                NaN     N.A.   N.A.         0 %     0.00 %  \n",
       "Vatican State          NaN     N.A.   N.A.        N.A.     0.00 %  \n",
       "\n",
       "[235 rows x 10 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
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  {
   "cell_type": "markdown",
   "id": "ba8c3d89-5038-4cec-b66d-17e2f0156281",
   "metadata": {},
   "source": [
    "### Daten angreifen\n",
    "\n",
    "Top/Bottom X: head(X), tail(X)\n",
    "\n",
    "Index:\n",
    "- data[...]: Nur Spalten\n",
    "- data.loc[...]: Nur Zeilen\n",
    "- data.iloc[...]: Nur Zeilen mit Index (ohne Text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5daeec27-ae32-4604-baf8-9626e0f40b2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>954806.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>38</td>\n",
       "      <td>83 %</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "                      Pop YearlyChange  NetChange  Density     Area  Migrants  \\\n",
       "Country                                                                         \n",
       "China          1439323776       0.39 %    5540090      153  9388211 -348399.0   \n",
       "India          1380004385       0.99 %   13586631      464  2973190 -532687.0   \n",
       "United States   331002651       0.59 %    1937734       36  9147420  954806.0   \n",
       "\n",
       "              FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                               \n",
       "China              1.7     38        61 %    18.47 %  \n",
       "India              2.2     28        35 %    17.70 %  \n",
       "United States      1.8     38        83 %     4.25 %  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "25a169d2-9d29-4a2a-949f-1539f50b142a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Niue</th>\n",
       "      <td>1626</td>\n",
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       "      <td>N.A.</td>\n",
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       "      <td>1357</td>\n",
       "      <td>1.27 %</td>\n",
       "      <td>17</td>\n",
       "      <td>136</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0 %</td>\n",
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       "      <th>Vatican State</th>\n",
       "      <td>801</td>\n",
       "      <td>0.25 %</td>\n",
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       "      <td>2003</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
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      "text/plain": [
       "                Pop YearlyChange  NetChange  Density  Area  Migrants FertRate  \\\n",
       "Country                                                                         \n",
       "Niue           1626       0.68 %         11        6   260       NaN     N.A.   \n",
       "Tokelau        1357       1.27 %         17      136    10       NaN     N.A.   \n",
       "Vatican State   801       0.25 %          2     2003     0       NaN     N.A.   \n",
       "\n",
       "              MedAge UrbanPopPct WorldShare  \n",
       "Country                                      \n",
       "Niue            N.A.        46 %     0.00 %  \n",
       "Tokelau         N.A.         0 %     0.00 %  \n",
       "Vatican State   N.A.        N.A.     0.00 %  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0acc620a-ad23-4cc8-87ef-9885e50b5695",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "China               1439323776\n",
       "India               1380004385\n",
       "United States        331002651\n",
       "Indonesia            273523615\n",
       "Pakistan             220892340\n",
       "                       ...    \n",
       "Montserrat                4992\n",
       "Falkland Islands          3480\n",
       "Niue                      1626\n",
       "Tokelau                   1357\n",
       "Vatican State              801\n",
       "Name: Pop, Length: 235, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"Pop\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5081db1a-fd2e-4237-ae03-ae76ab03a111",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pop             1439323776\n",
       "YearlyChange        0.39 %\n",
       "NetChange          5540090\n",
       "Density                153\n",
       "Area               9388211\n",
       "Migrants         -348399.0\n",
       "FertRate               1.7\n",
       "MedAge                  38\n",
       "UrbanPopPct           61 %\n",
       "WorldShare         18.47 %\n",
       "Name: China, dtype: object"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[\"China\"]"
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   "cell_type": "code",
   "execution_count": 37,
   "id": "9d923de2-bcaa-44be-bbfc-527e45311281",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pop             1439323776\n",
       "YearlyChange        0.39 %\n",
       "NetChange          5540090\n",
       "Density                153\n",
       "Area               9388211\n",
       "Name: China, dtype: object"
      ]
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     "execution_count": 37,
     "metadata": {},
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   "source": [
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   "execution_count": 41,
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       "      <th>Indonesia</th>\n",
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       "      <th>Pakistan</th>\n",
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       "      <td>3.6</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</td>\n",
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      "text/plain": [
       "                      Pop YearlyChange  NetChange  Density     Area  Migrants  \\\n",
       "Country                                                                         \n",
       "China          1439323776       0.39 %    5540090      153  9388211 -348399.0   \n",
       "India          1380004385       0.99 %   13586631      464  2973190 -532687.0   \n",
       "United States   331002651       0.59 %    1937734       36  9147420  954806.0   \n",
       "Indonesia       273523615       1.07 %    2898047      151  1811570  -98955.0   \n",
       "Pakistan        220892340       2.00 %    4327022      287   770880 -233379.0   \n",
       "\n",
       "              FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                               \n",
       "China              1.7     38        61 %    18.47 %  \n",
       "India              2.2     28        35 %    17.70 %  \n",
       "United States      1.8     38        83 %     4.25 %  \n",
       "Indonesia          2.3     30        56 %     3.51 %  \n",
       "Pakistan           3.6     23        35 %     2.83 %  "
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   "execution_count": 40,
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    {
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       "                      Pop YearlyChange  NetChange  Density     Area\n",
       "Country                                                            \n",
       "China          1439323776       0.39 %    5540090      153  9388211\n",
       "India          1380004385       0.99 %   13586631      464  2973190\n",
       "United States   331002651       0.59 %    1937734       36  9147420\n",
       "Indonesia       273523615       1.07 %    2898047      151  1811570\n",
       "Pakistan        220892340       2.00 %    4327022      287   770880"
      ]
     },
     "execution_count": 40,
     "metadata": {},
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   "execution_count": 42,
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       "      <td>1439323776</td>\n",
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       "      <th>Indonesia</th>\n",
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       "      <th>Pakistan</th>\n",
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       "      <td>-233379.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</td>\n",
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      "text/plain": [
       "                      Pop YearlyChange  NetChange  Density     Area  Migrants  \\\n",
       "Country                                                                         \n",
       "China          1439323776       0.39 %    5540090      153  9388211 -348399.0   \n",
       "India          1380004385       0.99 %   13586631      464  2973190 -532687.0   \n",
       "United States   331002651       0.59 %    1937734       36  9147420  954806.0   \n",
       "Indonesia       273523615       1.07 %    2898047      151  1811570  -98955.0   \n",
       "Pakistan        220892340       2.00 %    4327022      287   770880 -233379.0   \n",
       "\n",
       "              FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                               \n",
       "China              1.7     38        61 %    18.47 %  \n",
       "India              2.2     28        35 %    17.70 %  \n",
       "United States      1.8     38        83 %     4.25 %  \n",
       "Indonesia          2.3     30        56 %     3.51 %  \n",
       "Pakistan           3.6     23        35 %     2.83 %  "
      ]
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     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
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    "data.iloc[:5]"
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  {
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   "execution_count": 43,
   "id": "0fe4a384-3ed4-4db9-b858-d1c039a3c7b0",
   "metadata": {},
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    {
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       "      <td>26</td>\n",
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       "      <td>1.41 %</td>\n",
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       "      <td>102334404</td>\n",
       "      <td>1.94 %</td>\n",
       "      <td>1946331</td>\n",
       "      <td>103</td>\n",
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       "      <td>25</td>\n",
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       "      <td>1.31 %</td>\n",
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       "      <th>Vietnam</th>\n",
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       "      <th>DR Congo</th>\n",
       "      <td>89561403</td>\n",
       "      <td>3.19 %</td>\n",
       "      <td>2770836</td>\n",
       "      <td>40</td>\n",
       "      <td>2267050</td>\n",
       "      <td>23861.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17</td>\n",
       "      <td>46 %</td>\n",
       "      <td>1.15 %</td>\n",
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       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>84339067</td>\n",
       "      <td>1.09 %</td>\n",
       "      <td>909452</td>\n",
       "      <td>110</td>\n",
       "      <td>769630</td>\n",
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       "      <td>1.08 %</td>\n",
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       "      <td>240</td>\n",
       "      <td>348560</td>\n",
       "      <td>543822.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>46</td>\n",
       "      <td>76 %</td>\n",
       "      <td>1.07 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Thailand</th>\n",
       "      <td>69799978</td>\n",
       "      <td>0.25 %</td>\n",
       "      <td>174396</td>\n",
       "      <td>137</td>\n",
       "      <td>510890</td>\n",
       "      <td>19444.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>40</td>\n",
       "      <td>51 %</td>\n",
       "      <td>0.90 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Pop YearlyChange  NetChange  Density     Area  Migrants  \\\n",
       "Country                                                                      \n",
       "Japan        126476461      -0.30 %    -383840      347   364555   71560.0   \n",
       "Ethiopia     114963588       2.57 %    2884858      115  1000000   30000.0   \n",
       "Philippines  109581078       1.35 %    1464463      368   298170  -67152.0   \n",
       "Egypt        102334404       1.94 %    1946331      103   995450  -38033.0   \n",
       "Vietnam       97338579       0.91 %     876473      314   310070  -80000.0   \n",
       "DR Congo      89561403       3.19 %    2770836       40  2267050   23861.0   \n",
       "Turkey        84339067       1.09 %     909452      110   769630  283922.0   \n",
       "Iran          83992949       1.30 %    1079043       52  1628550  -55000.0   \n",
       "Germany       83783942       0.32 %     266897      240   348560  543822.0   \n",
       "Thailand      69799978       0.25 %     174396      137   510890   19444.0   \n",
       "\n",
       "            FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                             \n",
       "Japan            1.4     48        92 %     1.62 %  \n",
       "Ethiopia         4.3     19        21 %     1.47 %  \n",
       "Philippines      2.6     26        47 %     1.41 %  \n",
       "Egypt            3.3     25        43 %     1.31 %  \n",
       "Vietnam          2.1     32        38 %     1.25 %  \n",
       "DR Congo         6.0     17        46 %     1.15 %  \n",
       "Turkey           2.1     32        76 %     1.08 %  \n",
       "Iran             2.2     32        76 %     1.08 %  \n",
       "Germany          1.6     46        76 %     1.07 %  \n",
       "Thailand         1.5     40        51 %     0.90 %  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[10:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c77d621d-72c2-449a-91a1-15004319b5e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(96217144.9)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Aufgabe: Was ist die Durchschnittsbevölkerung der 10-20 Nationen?\n",
    "np.mean(data.iloc[10:20][\"Pop\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "977d0389-ffee-484a-adfa-968f26d815df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(96217144.9)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[10:20][\"Pop\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3307554e-dd2c-4935-aa0d-3d2556ab57b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(96217144.9)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[\"Japan\":\"Thailand\", \"Pop\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "56f374a1-0dcb-4cae-840b-d10fb2130def",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(96217144.9)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[10:20, 0].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63478111-317b-423f-9575-150ed75d61d3",
   "metadata": {},
   "source": [
    "### Daten sortieren\n",
    "\n",
    "Zwei Funktionen\n",
    "- sort_values(\"Spaltenname\")\n",
    "- sort_index()\n",
    "\n",
    "Mit ascending=True/False die Richtung bestimmen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "244bc27c-73e4-4075-92e7-6e4b8c301fcc",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        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>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density</th>\n",
       "      <th>Area</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>FertRate</th>\n",
       "      <th>MedAge</th>\n",
       "      <th>UrbanPopPct</th>\n",
       "      <th>WorldShare</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>South Korea</th>\n",
       "      <td>51269185</td>\n",
       "      <td>0.09 %</td>\n",
       "      <td>43877</td>\n",
       "      <td>527</td>\n",
       "      <td>97230</td>\n",
       "      <td>11731.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>44</td>\n",
       "      <td>82 %</td>\n",
       "      <td>0.66 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan</th>\n",
       "      <td>23816775</td>\n",
       "      <td>0.18 %</td>\n",
       "      <td>42899</td>\n",
       "      <td>673</td>\n",
       "      <td>35410</td>\n",
       "      <td>30001.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>42</td>\n",
       "      <td>79 %</td>\n",
       "      <td>0.31 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>2860853</td>\n",
       "      <td>-2.47 %</td>\n",
       "      <td>-72555</td>\n",
       "      <td>323</td>\n",
       "      <td>8870</td>\n",
       "      <td>-97986.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>44</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.04 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macao</th>\n",
       "      <td>649335</td>\n",
       "      <td>1.39 %</td>\n",
       "      <td>8890</td>\n",
       "      <td>21645</td>\n",
       "      <td>30</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>39</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.01 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <td>5850342</td>\n",
       "      <td>0.79 %</td>\n",
       "      <td>46005</td>\n",
       "      <td>8358</td>\n",
       "      <td>700</td>\n",
       "      <td>27028.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>42</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.08 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>10196709</td>\n",
       "      <td>-0.29 %</td>\n",
       "      <td>-29478</td>\n",
       "      <td>111</td>\n",
       "      <td>91590</td>\n",
       "      <td>-6000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>46</td>\n",
       "      <td>66 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cyprus</th>\n",
       "      <td>1207359</td>\n",
       "      <td>0.73 %</td>\n",
       "      <td>8784</td>\n",
       "      <td>131</td>\n",
       "      <td>9240</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>37</td>\n",
       "      <td>67 %</td>\n",
       "      <td>0.02 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>60461826</td>\n",
       "      <td>-0.15 %</td>\n",
       "      <td>-88249</td>\n",
       "      <td>206</td>\n",
       "      <td>294140</td>\n",
       "      <td>148943.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47</td>\n",
       "      <td>69 %</td>\n",
       "      <td>0.78 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moldova</th>\n",
       "      <td>4033963</td>\n",
       "      <td>-0.23 %</td>\n",
       "      <td>-9300</td>\n",
       "      <td>123</td>\n",
       "      <td>32850</td>\n",
       "      <td>-1387.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>38</td>\n",
       "      <td>43 %</td>\n",
       "      <td>0.05 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bosnia and Herzegovina</th>\n",
       "      <td>3280819</td>\n",
       "      <td>-0.61 %</td>\n",
       "      <td>-20181</td>\n",
       "      <td>64</td>\n",
       "      <td>51000</td>\n",
       "      <td>-21585.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>43</td>\n",
       "      <td>52 %</td>\n",
       "      <td>0.04 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hong Kong</th>\n",
       "      <td>7496981</td>\n",
       "      <td>0.82 %</td>\n",
       "      <td>60827</td>\n",
       "      <td>7140</td>\n",
       "      <td>1050</td>\n",
       "      <td>29308.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>45</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.10 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>46754778</td>\n",
       "      <td>0.04 %</td>\n",
       "      <td>18002</td>\n",
       "      <td>94</td>\n",
       "      <td>498800</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>45</td>\n",
       "      <td>80 %</td>\n",
       "      <td>0.60 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>10423054</td>\n",
       "      <td>-0.48 %</td>\n",
       "      <td>-50401</td>\n",
       "      <td>81</td>\n",
       "      <td>128900</td>\n",
       "      <td>-16000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>46</td>\n",
       "      <td>85 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ukraine</th>\n",
       "      <td>43733762</td>\n",
       "      <td>-0.59 %</td>\n",
       "      <td>-259876</td>\n",
       "      <td>75</td>\n",
       "      <td>579320</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>41</td>\n",
       "      <td>69 %</td>\n",
       "      <td>0.56 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mauritius</th>\n",
       "      <td>1271768</td>\n",
       "      <td>0.17 %</td>\n",
       "      <td>2100</td>\n",
       "      <td>626</td>\n",
       "      <td>2030</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>37</td>\n",
       "      <td>41 %</td>\n",
       "      <td>0.02 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poland</th>\n",
       "      <td>37846611</td>\n",
       "      <td>-0.11 %</td>\n",
       "      <td>-41157</td>\n",
       "      <td>124</td>\n",
       "      <td>306230</td>\n",
       "      <td>-29395.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>42</td>\n",
       "      <td>60 %</td>\n",
       "      <td>0.49 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>126476461</td>\n",
       "      <td>-0.30 %</td>\n",
       "      <td>-383840</td>\n",
       "      <td>347</td>\n",
       "      <td>364555</td>\n",
       "      <td>71560.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>48</td>\n",
       "      <td>92 %</td>\n",
       "      <td>1.62 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Croatia</th>\n",
       "      <td>4105267</td>\n",
       "      <td>-0.61 %</td>\n",
       "      <td>-25037</td>\n",
       "      <td>73</td>\n",
       "      <td>55960</td>\n",
       "      <td>-8001.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>44</td>\n",
       "      <td>58 %</td>\n",
       "      <td>0.05 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Arab Emirates</th>\n",
       "      <td>9890402</td>\n",
       "      <td>1.23 %</td>\n",
       "      <td>119873</td>\n",
       "      <td>118</td>\n",
       "      <td>83600</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>33</td>\n",
       "      <td>86 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saint Lucia</th>\n",
       "      <td>183627</td>\n",
       "      <td>0.46 %</td>\n",
       "      <td>837</td>\n",
       "      <td>301</td>\n",
       "      <td>610</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>34</td>\n",
       "      <td>19 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Pop YearlyChange  NetChange  Density    Area  \\\n",
       "Country                                                                      \n",
       "South Korea              51269185       0.09 %      43877      527   97230   \n",
       "Taiwan                   23816775       0.18 %      42899      673   35410   \n",
       "Puerto Rico               2860853      -2.47 %     -72555      323    8870   \n",
       "Macao                      649335       1.39 %       8890    21645      30   \n",
       "Singapore                 5850342       0.79 %      46005     8358     700   \n",
       "Portugal                 10196709      -0.29 %     -29478      111   91590   \n",
       "Cyprus                    1207359       0.73 %       8784      131    9240   \n",
       "Italy                    60461826      -0.15 %     -88249      206  294140   \n",
       "Moldova                   4033963      -0.23 %      -9300      123   32850   \n",
       "Bosnia and Herzegovina    3280819      -0.61 %     -20181       64   51000   \n",
       "Hong Kong                 7496981       0.82 %      60827     7140    1050   \n",
       "Spain                    46754778       0.04 %      18002       94  498800   \n",
       "Greece                   10423054      -0.48 %     -50401       81  128900   \n",
       "Ukraine                  43733762      -0.59 %    -259876       75  579320   \n",
       "Mauritius                 1271768       0.17 %       2100      626    2030   \n",
       "Poland                   37846611      -0.11 %     -41157      124  306230   \n",
       "Japan                   126476461      -0.30 %    -383840      347  364555   \n",
       "Croatia                   4105267      -0.61 %     -25037       73   55960   \n",
       "United Arab Emirates      9890402       1.23 %     119873      118   83600   \n",
       "Saint Lucia                183627       0.46 %        837      301     610   \n",
       "\n",
       "                        Migrants FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                                                  \n",
       "South Korea              11731.0      1.1     44        82 %     0.66 %  \n",
       "Taiwan                   30001.0      1.2     42        79 %     0.31 %  \n",
       "Puerto Rico             -97986.0      1.2     44        N.A.     0.04 %  \n",
       "Macao                     5000.0      1.2     39        N.A.     0.01 %  \n",
       "Singapore                27028.0      1.2     42        N.A.     0.08 %  \n",
       "Portugal                 -6000.0      1.3     46        66 %     0.13 %  \n",
       "Cyprus                    5000.0      1.3     37        67 %     0.02 %  \n",
       "Italy                   148943.0      1.3     47        69 %     0.78 %  \n",
       "Moldova                  -1387.0      1.3     38        43 %     0.05 %  \n",
       "Bosnia and Herzegovina  -21585.0      1.3     43        52 %     0.04 %  \n",
       "Hong Kong                29308.0      1.3     45        N.A.     0.10 %  \n",
       "Spain                    40000.0      1.3     45        80 %     0.60 %  \n",
       "Greece                  -16000.0      1.3     46        85 %     0.13 %  \n",
       "Ukraine                  10000.0      1.4     41        69 %     0.56 %  \n",
       "Mauritius                    0.0      1.4     37        41 %     0.02 %  \n",
       "Poland                  -29395.0      1.4     42        60 %     0.49 %  \n",
       "Japan                    71560.0      1.4     48        92 %     1.62 %  \n",
       "Croatia                  -8001.0      1.4     44        58 %     0.05 %  \n",
       "United Arab Emirates     40000.0      1.4     33        86 %     0.13 %  \n",
       "Saint Lucia                  0.0      1.4     34        19 %     0.00 %  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sort_values(\"FertRate\").head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "4f74eb65-8c43-40a5-8e1b-4805b67d06cd",
   "metadata": {
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    "jupyter": {
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   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density</th>\n",
       "      <th>Area</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>FertRate</th>\n",
       "      <th>MedAge</th>\n",
       "      <th>UrbanPopPct</th>\n",
       "      <th>WorldShare</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Vatican State</th>\n",
       "      <td>801</td>\n",
       "      <td>0.25 %</td>\n",
       "      <td>2</td>\n",
       "      <td>2003</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monaco</th>\n",
       "      <td>39242</td>\n",
       "      <td>0.71 %</td>\n",
       "      <td>278</td>\n",
       "      <td>26337</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wallis &amp; Futuna</th>\n",
       "      <td>11239</td>\n",
       "      <td>-1.69 %</td>\n",
       "      <td>-193</td>\n",
       "      <td>80</td>\n",
       "      <td>140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tuvalu</th>\n",
       "      <td>11792</td>\n",
       "      <td>1.25 %</td>\n",
       "      <td>146</td>\n",
       "      <td>393</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>62 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anguilla</th>\n",
       "      <td>15003</td>\n",
       "      <td>0.90 %</td>\n",
       "      <td>134</td>\n",
       "      <td>167</td>\n",
       "      <td>90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan</th>\n",
       "      <td>23816775</td>\n",
       "      <td>0.18 %</td>\n",
       "      <td>42899</td>\n",
       "      <td>673</td>\n",
       "      <td>35410</td>\n",
       "      <td>30001.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>42</td>\n",
       "      <td>79 %</td>\n",
       "      <td>0.31 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <td>5850342</td>\n",
       "      <td>0.79 %</td>\n",
       "      <td>46005</td>\n",
       "      <td>8358</td>\n",
       "      <td>700</td>\n",
       "      <td>27028.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>42</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.08 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>2860853</td>\n",
       "      <td>-2.47 %</td>\n",
       "      <td>-72555</td>\n",
       "      <td>323</td>\n",
       "      <td>8870</td>\n",
       "      <td>-97986.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>44</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.04 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macao</th>\n",
       "      <td>649335</td>\n",
       "      <td>1.39 %</td>\n",
       "      <td>8890</td>\n",
       "      <td>21645</td>\n",
       "      <td>30</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>39</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.01 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Korea</th>\n",
       "      <td>51269185</td>\n",
       "      <td>0.09 %</td>\n",
       "      <td>43877</td>\n",
       "      <td>527</td>\n",
       "      <td>97230</td>\n",
       "      <td>11731.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>44</td>\n",
       "      <td>82 %</td>\n",
       "      <td>0.66 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>235 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Pop YearlyChange  NetChange  Density   Area  Migrants  \\\n",
       "Country                                                                       \n",
       "Vatican State         801       0.25 %          2     2003      0       NaN   \n",
       "Monaco              39242       0.71 %        278    26337      1       NaN   \n",
       "Wallis & Futuna     11239      -1.69 %       -193       80    140       NaN   \n",
       "Tuvalu              11792       1.25 %        146      393     30       NaN   \n",
       "Anguilla            15003       0.90 %        134      167     90       NaN   \n",
       "...                   ...          ...        ...      ...    ...       ...   \n",
       "Taiwan           23816775       0.18 %      42899      673  35410   30001.0   \n",
       "Singapore         5850342       0.79 %      46005     8358    700   27028.0   \n",
       "Puerto Rico       2860853      -2.47 %     -72555      323   8870  -97986.0   \n",
       "Macao              649335       1.39 %       8890    21645     30    5000.0   \n",
       "South Korea      51269185       0.09 %      43877      527  97230   11731.0   \n",
       "\n",
       "                FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                                 \n",
       "Vatican State       N.A.   N.A.        N.A.     0.00 %  \n",
       "Monaco              N.A.   N.A.        N.A.     0.00 %  \n",
       "Wallis & Futuna     N.A.   N.A.         0 %     0.00 %  \n",
       "Tuvalu              N.A.   N.A.        62 %     0.00 %  \n",
       "Anguilla            N.A.   N.A.        N.A.     0.00 %  \n",
       "...                  ...    ...         ...        ...  \n",
       "Taiwan               1.2     42        79 %     0.31 %  \n",
       "Singapore            1.2     42        N.A.     0.08 %  \n",
       "Puerto Rico          1.2     44        N.A.     0.04 %  \n",
       "Macao                1.2     39        N.A.     0.01 %  \n",
       "South Korea          1.1     44        82 %     0.66 %  \n",
       "\n",
       "[235 rows x 10 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sort_values(\"FertRate\", ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "dcd509ca-dbe4-42dc-ac24-dc72428eb32f",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density</th>\n",
       "      <th>Area</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>FertRate</th>\n",
       "      <th>MedAge</th>\n",
       "      <th>UrbanPopPct</th>\n",
       "      <th>WorldShare</th>\n",
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       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>South Korea</th>\n",
       "      <td>51269185</td>\n",
       "      <td>0.09 %</td>\n",
       "      <td>43877</td>\n",
       "      <td>527</td>\n",
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       "      <td>1.1</td>\n",
       "      <td>44</td>\n",
       "      <td>82 %</td>\n",
       "      <td>0.66 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macao</th>\n",
       "      <td>649335</td>\n",
       "      <td>1.39 %</td>\n",
       "      <td>8890</td>\n",
       "      <td>21645</td>\n",
       "      <td>30</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>39</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.01 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>2860853</td>\n",
       "      <td>-2.47 %</td>\n",
       "      <td>-72555</td>\n",
       "      <td>323</td>\n",
       "      <td>8870</td>\n",
       "      <td>-97986.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>44</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.04 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Singapore</th>\n",
       "      <td>5850342</td>\n",
       "      <td>0.79 %</td>\n",
       "      <td>46005</td>\n",
       "      <td>8358</td>\n",
       "      <td>700</td>\n",
       "      <td>27028.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>42</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.08 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taiwan</th>\n",
       "      <td>23816775</td>\n",
       "      <td>0.18 %</td>\n",
       "      <td>42899</td>\n",
       "      <td>673</td>\n",
       "      <td>35410</td>\n",
       "      <td>30001.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>42</td>\n",
       "      <td>79 %</td>\n",
       "      <td>0.31 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bosnia and Herzegovina</th>\n",
       "      <td>3280819</td>\n",
       "      <td>-0.61 %</td>\n",
       "      <td>-20181</td>\n",
       "      <td>64</td>\n",
       "      <td>51000</td>\n",
       "      <td>-21585.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>43</td>\n",
       "      <td>52 %</td>\n",
       "      <td>0.04 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cyprus</th>\n",
       "      <td>1207359</td>\n",
       "      <td>0.73 %</td>\n",
       "      <td>8784</td>\n",
       "      <td>131</td>\n",
       "      <td>9240</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>37</td>\n",
       "      <td>67 %</td>\n",
       "      <td>0.02 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>10423054</td>\n",
       "      <td>-0.48 %</td>\n",
       "      <td>-50401</td>\n",
       "      <td>81</td>\n",
       "      <td>128900</td>\n",
       "      <td>-16000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>46</td>\n",
       "      <td>85 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hong Kong</th>\n",
       "      <td>7496981</td>\n",
       "      <td>0.82 %</td>\n",
       "      <td>60827</td>\n",
       "      <td>7140</td>\n",
       "      <td>1050</td>\n",
       "      <td>29308.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>45</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0.10 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>60461826</td>\n",
       "      <td>-0.15 %</td>\n",
       "      <td>-88249</td>\n",
       "      <td>206</td>\n",
       "      <td>294140</td>\n",
       "      <td>148943.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>47</td>\n",
       "      <td>69 %</td>\n",
       "      <td>0.78 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moldova</th>\n",
       "      <td>4033963</td>\n",
       "      <td>-0.23 %</td>\n",
       "      <td>-9300</td>\n",
       "      <td>123</td>\n",
       "      <td>32850</td>\n",
       "      <td>-1387.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>38</td>\n",
       "      <td>43 %</td>\n",
       "      <td>0.05 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>10196709</td>\n",
       "      <td>-0.29 %</td>\n",
       "      <td>-29478</td>\n",
       "      <td>111</td>\n",
       "      <td>91590</td>\n",
       "      <td>-6000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>46</td>\n",
       "      <td>66 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>46754778</td>\n",
       "      <td>0.04 %</td>\n",
       "      <td>18002</td>\n",
       "      <td>94</td>\n",
       "      <td>498800</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>45</td>\n",
       "      <td>80 %</td>\n",
       "      <td>0.60 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Croatia</th>\n",
       "      <td>4105267</td>\n",
       "      <td>-0.61 %</td>\n",
       "      <td>-25037</td>\n",
       "      <td>73</td>\n",
       "      <td>55960</td>\n",
       "      <td>-8001.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>44</td>\n",
       "      <td>58 %</td>\n",
       "      <td>0.05 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>126476461</td>\n",
       "      <td>-0.30 %</td>\n",
       "      <td>-383840</td>\n",
       "      <td>347</td>\n",
       "      <td>364555</td>\n",
       "      <td>71560.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>48</td>\n",
       "      <td>92 %</td>\n",
       "      <td>1.62 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mauritius</th>\n",
       "      <td>1271768</td>\n",
       "      <td>0.17 %</td>\n",
       "      <td>2100</td>\n",
       "      <td>626</td>\n",
       "      <td>2030</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>37</td>\n",
       "      <td>41 %</td>\n",
       "      <td>0.02 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poland</th>\n",
       "      <td>37846611</td>\n",
       "      <td>-0.11 %</td>\n",
       "      <td>-41157</td>\n",
       "      <td>124</td>\n",
       "      <td>306230</td>\n",
       "      <td>-29395.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>42</td>\n",
       "      <td>60 %</td>\n",
       "      <td>0.49 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saint Lucia</th>\n",
       "      <td>183627</td>\n",
       "      <td>0.46 %</td>\n",
       "      <td>837</td>\n",
       "      <td>301</td>\n",
       "      <td>610</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>34</td>\n",
       "      <td>19 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ukraine</th>\n",
       "      <td>43733762</td>\n",
       "      <td>-0.59 %</td>\n",
       "      <td>-259876</td>\n",
       "      <td>75</td>\n",
       "      <td>579320</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>41</td>\n",
       "      <td>69 %</td>\n",
       "      <td>0.56 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Arab Emirates</th>\n",
       "      <td>9890402</td>\n",
       "      <td>1.23 %</td>\n",
       "      <td>119873</td>\n",
       "      <td>118</td>\n",
       "      <td>83600</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>33</td>\n",
       "      <td>86 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>9006398</td>\n",
       "      <td>0.57 %</td>\n",
       "      <td>51296</td>\n",
       "      <td>109</td>\n",
       "      <td>82409</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>43</td>\n",
       "      <td>57 %</td>\n",
       "      <td>0.12 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>37742154</td>\n",
       "      <td>0.89 %</td>\n",
       "      <td>331107</td>\n",
       "      <td>4</td>\n",
       "      <td>9093510</td>\n",
       "      <td>242032.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>41</td>\n",
       "      <td>81 %</td>\n",
       "      <td>0.48 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Channel Islands</th>\n",
       "      <td>173863</td>\n",
       "      <td>0.93 %</td>\n",
       "      <td>1604</td>\n",
       "      <td>915</td>\n",
       "      <td>190</td>\n",
       "      <td>1351.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>43</td>\n",
       "      <td>30 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finland</th>\n",
       "      <td>5540720</td>\n",
       "      <td>0.15 %</td>\n",
       "      <td>8564</td>\n",
       "      <td>18</td>\n",
       "      <td>303890</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>43</td>\n",
       "      <td>86 %</td>\n",
       "      <td>0.07 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>9660351</td>\n",
       "      <td>-0.25 %</td>\n",
       "      <td>-24328</td>\n",
       "      <td>107</td>\n",
       "      <td>90530</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>43</td>\n",
       "      <td>72 %</td>\n",
       "      <td>0.12 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Luxembourg</th>\n",
       "      <td>625978</td>\n",
       "      <td>1.66 %</td>\n",
       "      <td>10249</td>\n",
       "      <td>242</td>\n",
       "      <td>2590</td>\n",
       "      <td>9741.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>40</td>\n",
       "      <td>88 %</td>\n",
       "      <td>0.01 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malta</th>\n",
       "      <td>441543</td>\n",
       "      <td>0.27 %</td>\n",
       "      <td>1171</td>\n",
       "      <td>1380</td>\n",
       "      <td>320</td>\n",
       "      <td>900.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>43</td>\n",
       "      <td>93 %</td>\n",
       "      <td>0.01 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Macedonia</th>\n",
       "      <td>2083374</td>\n",
       "      <td>0.00 %</td>\n",
       "      <td>-85</td>\n",
       "      <td>83</td>\n",
       "      <td>25220</td>\n",
       "      <td>-1000.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>39</td>\n",
       "      <td>59 %</td>\n",
       "      <td>0.03 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Serbia</th>\n",
       "      <td>8737371</td>\n",
       "      <td>-0.40 %</td>\n",
       "      <td>-34864</td>\n",
       "      <td>100</td>\n",
       "      <td>87460</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>42</td>\n",
       "      <td>56 %</td>\n",
       "      <td>0.11 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Slovakia</th>\n",
       "      <td>5459642</td>\n",
       "      <td>0.05 %</td>\n",
       "      <td>2629</td>\n",
       "      <td>114</td>\n",
       "      <td>48088</td>\n",
       "      <td>1485.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>41</td>\n",
       "      <td>54 %</td>\n",
       "      <td>0.07 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Pop YearlyChange  NetChange  Density     Area  \\\n",
       "Country                                                                       \n",
       "South Korea              51269185       0.09 %      43877      527    97230   \n",
       "Macao                      649335       1.39 %       8890    21645       30   \n",
       "Puerto Rico               2860853      -2.47 %     -72555      323     8870   \n",
       "Singapore                 5850342       0.79 %      46005     8358      700   \n",
       "Taiwan                   23816775       0.18 %      42899      673    35410   \n",
       "Bosnia and Herzegovina    3280819      -0.61 %     -20181       64    51000   \n",
       "Cyprus                    1207359       0.73 %       8784      131     9240   \n",
       "Greece                   10423054      -0.48 %     -50401       81   128900   \n",
       "Hong Kong                 7496981       0.82 %      60827     7140     1050   \n",
       "Italy                    60461826      -0.15 %     -88249      206   294140   \n",
       "Moldova                   4033963      -0.23 %      -9300      123    32850   \n",
       "Portugal                 10196709      -0.29 %     -29478      111    91590   \n",
       "Spain                    46754778       0.04 %      18002       94   498800   \n",
       "Croatia                   4105267      -0.61 %     -25037       73    55960   \n",
       "Japan                   126476461      -0.30 %    -383840      347   364555   \n",
       "Mauritius                 1271768       0.17 %       2100      626     2030   \n",
       "Poland                   37846611      -0.11 %     -41157      124   306230   \n",
       "Saint Lucia                183627       0.46 %        837      301      610   \n",
       "Ukraine                  43733762      -0.59 %    -259876       75   579320   \n",
       "United Arab Emirates      9890402       1.23 %     119873      118    83600   \n",
       "Austria                   9006398       0.57 %      51296      109    82409   \n",
       "Canada                   37742154       0.89 %     331107        4  9093510   \n",
       "Channel Islands            173863       0.93 %       1604      915      190   \n",
       "Finland                   5540720       0.15 %       8564       18   303890   \n",
       "Hungary                   9660351      -0.25 %     -24328      107    90530   \n",
       "Luxembourg                 625978       1.66 %      10249      242     2590   \n",
       "Malta                      441543       0.27 %       1171     1380      320   \n",
       "North Macedonia           2083374       0.00 %        -85       83    25220   \n",
       "Serbia                    8737371      -0.40 %     -34864      100    87460   \n",
       "Slovakia                  5459642       0.05 %       2629      114    48088   \n",
       "\n",
       "                        Migrants FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                                                  \n",
       "South Korea              11731.0      1.1     44        82 %     0.66 %  \n",
       "Macao                     5000.0      1.2     39        N.A.     0.01 %  \n",
       "Puerto Rico             -97986.0      1.2     44        N.A.     0.04 %  \n",
       "Singapore                27028.0      1.2     42        N.A.     0.08 %  \n",
       "Taiwan                   30001.0      1.2     42        79 %     0.31 %  \n",
       "Bosnia and Herzegovina  -21585.0      1.3     43        52 %     0.04 %  \n",
       "Cyprus                    5000.0      1.3     37        67 %     0.02 %  \n",
       "Greece                  -16000.0      1.3     46        85 %     0.13 %  \n",
       "Hong Kong                29308.0      1.3     45        N.A.     0.10 %  \n",
       "Italy                   148943.0      1.3     47        69 %     0.78 %  \n",
       "Moldova                  -1387.0      1.3     38        43 %     0.05 %  \n",
       "Portugal                 -6000.0      1.3     46        66 %     0.13 %  \n",
       "Spain                    40000.0      1.3     45        80 %     0.60 %  \n",
       "Croatia                  -8001.0      1.4     44        58 %     0.05 %  \n",
       "Japan                    71560.0      1.4     48        92 %     1.62 %  \n",
       "Mauritius                    0.0      1.4     37        41 %     0.02 %  \n",
       "Poland                  -29395.0      1.4     42        60 %     0.49 %  \n",
       "Saint Lucia                  0.0      1.4     34        19 %     0.00 %  \n",
       "Ukraine                  10000.0      1.4     41        69 %     0.56 %  \n",
       "United Arab Emirates     40000.0      1.4     33        86 %     0.13 %  \n",
       "Austria                  65000.0      1.5     43        57 %     0.12 %  \n",
       "Canada                  242032.0      1.5     41        81 %     0.48 %  \n",
       "Channel Islands           1351.0      1.5     43        30 %     0.00 %  \n",
       "Finland                  14000.0      1.5     43        86 %     0.07 %  \n",
       "Hungary                   6000.0      1.5     43        72 %     0.12 %  \n",
       "Luxembourg                9741.0      1.5     40        88 %     0.01 %  \n",
       "Malta                      900.0      1.5     43        93 %     0.01 %  \n",
       "North Macedonia          -1000.0      1.5     39        59 %     0.03 %  \n",
       "Serbia                    4000.0      1.5     42        56 %     0.11 %  \n",
       "Slovakia                  1485.0      1.5     41        54 %     0.07 %  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sort_values([\"FertRate\", \"Country\"]).head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "a1ec9deb-b606-458b-a4f7-d8df0e710fce",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density</th>\n",
       "      <th>Area</th>\n",
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       "      <th>FertRate</th>\n",
       "      <th>MedAge</th>\n",
       "      <th>UrbanPopPct</th>\n",
       "      <th>WorldShare</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>38928346</td>\n",
       "      <td>2.33 %</td>\n",
       "      <td>886592</td>\n",
       "      <td>60</td>\n",
       "      <td>652860</td>\n",
       "      <td>-62920.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>18</td>\n",
       "      <td>25 %</td>\n",
       "      <td>0.50 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>2877797</td>\n",
       "      <td>-0.11 %</td>\n",
       "      <td>-3120</td>\n",
       "      <td>105</td>\n",
       "      <td>27400</td>\n",
       "      <td>-14000.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>36</td>\n",
       "      <td>63 %</td>\n",
       "      <td>0.04 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>43851044</td>\n",
       "      <td>1.85 %</td>\n",
       "      <td>797990</td>\n",
       "      <td>18</td>\n",
       "      <td>2381740</td>\n",
       "      <td>-10000.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>29</td>\n",
       "      <td>73 %</td>\n",
       "      <td>0.56 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</th>\n",
       "      <td>55191</td>\n",
       "      <td>-0.22 %</td>\n",
       "      <td>-121</td>\n",
       "      <td>276</td>\n",
       "      <td>200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>88 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>77265</td>\n",
       "      <td>0.16 %</td>\n",
       "      <td>123</td>\n",
       "      <td>164</td>\n",
       "      <td>470</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>88 %</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wallis &amp; Futuna</th>\n",
       "      <td>11239</td>\n",
       "      <td>-1.69 %</td>\n",
       "      <td>-193</td>\n",
       "      <td>80</td>\n",
       "      <td>140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>N.A.</td>\n",
       "      <td>0 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Sahara</th>\n",
       "      <td>597339</td>\n",
       "      <td>2.55 %</td>\n",
       "      <td>14876</td>\n",
       "      <td>2</td>\n",
       "      <td>266000</td>\n",
       "      <td>5582.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>28</td>\n",
       "      <td>87 %</td>\n",
       "      <td>0.01 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\n",
       "      <td>29825964</td>\n",
       "      <td>2.28 %</td>\n",
       "      <td>664042</td>\n",
       "      <td>56</td>\n",
       "      <td>527970</td>\n",
       "      <td>-30000.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>20</td>\n",
       "      <td>38 %</td>\n",
       "      <td>0.38 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\n",
       "      <td>18383955</td>\n",
       "      <td>2.93 %</td>\n",
       "      <td>522925</td>\n",
       "      <td>25</td>\n",
       "      <td>743390</td>\n",
       "      <td>-8000.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>18</td>\n",
       "      <td>45 %</td>\n",
       "      <td>0.24 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>14862924</td>\n",
       "      <td>1.48 %</td>\n",
       "      <td>217456</td>\n",
       "      <td>38</td>\n",
       "      <td>386850</td>\n",
       "      <td>-116858.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>19</td>\n",
       "      <td>38 %</td>\n",
       "      <td>0.19 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>235 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Pop YearlyChange  NetChange  Density     Area  Migrants  \\\n",
       "Country                                                                         \n",
       "Afghanistan      38928346       2.33 %     886592       60   652860  -62920.0   \n",
       "Albania           2877797      -0.11 %      -3120      105    27400  -14000.0   \n",
       "Algeria          43851044       1.85 %     797990       18  2381740  -10000.0   \n",
       "American Samoa      55191      -0.22 %       -121      276      200       NaN   \n",
       "Andorra             77265       0.16 %        123      164      470       NaN   \n",
       "...                   ...          ...        ...      ...      ...       ...   \n",
       "Wallis & Futuna     11239      -1.69 %       -193       80      140       NaN   \n",
       "Western Sahara     597339       2.55 %      14876        2   266000    5582.0   \n",
       "Yemen            29825964       2.28 %     664042       56   527970  -30000.0   \n",
       "Zambia           18383955       2.93 %     522925       25   743390   -8000.0   \n",
       "Zimbabwe         14862924       1.48 %     217456       38   386850 -116858.0   \n",
       "\n",
       "                FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                                 \n",
       "Afghanistan          4.6     18        25 %     0.50 %  \n",
       "Albania              1.6     36        63 %     0.04 %  \n",
       "Algeria              3.1     29        73 %     0.56 %  \n",
       "American Samoa      N.A.   N.A.        88 %     0.00 %  \n",
       "Andorra             N.A.   N.A.        88 %     0.00 %  \n",
       "...                  ...    ...         ...        ...  \n",
       "Wallis & Futuna     N.A.   N.A.         0 %     0.00 %  \n",
       "Western Sahara       2.4     28        87 %     0.01 %  \n",
       "Yemen                3.8     20        38 %     0.38 %  \n",
       "Zambia               4.7     18        45 %     0.24 %  \n",
       "Zimbabwe             3.6     19        38 %     0.19 %  \n",
       "\n",
       "[235 rows x 10 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ad8372a-3a0c-427a-b295-de4486426a0d",
   "metadata": {},
   "source": [
    "### Daten filtern\n",
    "\n",
    "Wie Vektorisierung bei Numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "87d2fdc9-1257-4f86-960c-d3656d8c28e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "China                True\n",
       "India                True\n",
       "United States        True\n",
       "Indonesia            True\n",
       "Pakistan             True\n",
       "                    ...  \n",
       "Montserrat          False\n",
       "Falkland Islands    False\n",
       "Niue                False\n",
       "Tokelau             False\n",
       "Vatican State       False\n",
       "Name: Pop, Length: 235, dtype: bool"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Aufgabe: Finde alle Länder, mit mind. 100m Einwohnern\n",
    "data[\"Pop\"] > 100_000_000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "ed64699a-5892-4ccb-a571-81c2d3492c99",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>1439323776</td>\n",
       "      <td>0.39 %</td>\n",
       "      <td>5540090</td>\n",
       "      <td>153</td>\n",
       "      <td>9388211</td>\n",
       "      <td>-348399.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>38</td>\n",
       "      <td>61 %</td>\n",
       "      <td>18.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1380004385</td>\n",
       "      <td>0.99 %</td>\n",
       "      <td>13586631</td>\n",
       "      <td>464</td>\n",
       "      <td>2973190</td>\n",
       "      <td>-532687.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>28</td>\n",
       "      <td>35 %</td>\n",
       "      <td>17.70 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United States</th>\n",
       "      <td>331002651</td>\n",
       "      <td>0.59 %</td>\n",
       "      <td>1937734</td>\n",
       "      <td>36</td>\n",
       "      <td>9147420</td>\n",
       "      <td>954806.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>38</td>\n",
       "      <td>83 %</td>\n",
       "      <td>4.25 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>273523615</td>\n",
       "      <td>1.07 %</td>\n",
       "      <td>2898047</td>\n",
       "      <td>151</td>\n",
       "      <td>1811570</td>\n",
       "      <td>-98955.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>30</td>\n",
       "      <td>56 %</td>\n",
       "      <td>3.51 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pakistan</th>\n",
       "      <td>220892340</td>\n",
       "      <td>2.00 %</td>\n",
       "      <td>4327022</td>\n",
       "      <td>287</td>\n",
       "      <td>770880</td>\n",
       "      <td>-233379.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>23</td>\n",
       "      <td>35 %</td>\n",
       "      <td>2.83 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>212559417</td>\n",
       "      <td>0.72 %</td>\n",
       "      <td>1509890</td>\n",
       "      <td>25</td>\n",
       "      <td>8358140</td>\n",
       "      <td>21200.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>33</td>\n",
       "      <td>88 %</td>\n",
       "      <td>2.73 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nigeria</th>\n",
       "      <td>206139589</td>\n",
       "      <td>2.58 %</td>\n",
       "      <td>5175990</td>\n",
       "      <td>226</td>\n",
       "      <td>910770</td>\n",
       "      <td>-60000.0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>18</td>\n",
       "      <td>52 %</td>\n",
       "      <td>2.64 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bangladesh</th>\n",
       "      <td>164689383</td>\n",
       "      <td>1.01 %</td>\n",
       "      <td>1643222</td>\n",
       "      <td>1265</td>\n",
       "      <td>130170</td>\n",
       "      <td>-369501.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>28</td>\n",
       "      <td>39 %</td>\n",
       "      <td>2.11 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>145934462</td>\n",
       "      <td>0.04 %</td>\n",
       "      <td>62206</td>\n",
       "      <td>9</td>\n",
       "      <td>16376870</td>\n",
       "      <td>182456.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>40</td>\n",
       "      <td>74 %</td>\n",
       "      <td>1.87 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>128932753</td>\n",
       "      <td>1.06 %</td>\n",
       "      <td>1357224</td>\n",
       "      <td>66</td>\n",
       "      <td>1943950</td>\n",
       "      <td>-60000.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>29</td>\n",
       "      <td>84 %</td>\n",
       "      <td>1.65 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>126476461</td>\n",
       "      <td>-0.30 %</td>\n",
       "      <td>-383840</td>\n",
       "      <td>347</td>\n",
       "      <td>364555</td>\n",
       "      <td>71560.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>48</td>\n",
       "      <td>92 %</td>\n",
       "      <td>1.62 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ethiopia</th>\n",
       "      <td>114963588</td>\n",
       "      <td>2.57 %</td>\n",
       "      <td>2884858</td>\n",
       "      <td>115</td>\n",
       "      <td>1000000</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>19</td>\n",
       "      <td>21 %</td>\n",
       "      <td>1.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Philippines</th>\n",
       "      <td>109581078</td>\n",
       "      <td>1.35 %</td>\n",
       "      <td>1464463</td>\n",
       "      <td>368</td>\n",
       "      <td>298170</td>\n",
       "      <td>-67152.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>26</td>\n",
       "      <td>47 %</td>\n",
       "      <td>1.41 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Egypt</th>\n",
       "      <td>102334404</td>\n",
       "      <td>1.94 %</td>\n",
       "      <td>1946331</td>\n",
       "      <td>103</td>\n",
       "      <td>995450</td>\n",
       "      <td>-38033.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>25</td>\n",
       "      <td>43 %</td>\n",
       "      <td>1.31 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Pop YearlyChange  NetChange  Density      Area  \\\n",
       "Country                                                                \n",
       "China          1439323776       0.39 %    5540090      153   9388211   \n",
       "India          1380004385       0.99 %   13586631      464   2973190   \n",
       "United States   331002651       0.59 %    1937734       36   9147420   \n",
       "Indonesia       273523615       1.07 %    2898047      151   1811570   \n",
       "Pakistan        220892340       2.00 %    4327022      287    770880   \n",
       "Brazil          212559417       0.72 %    1509890       25   8358140   \n",
       "Nigeria         206139589       2.58 %    5175990      226    910770   \n",
       "Bangladesh      164689383       1.01 %    1643222     1265    130170   \n",
       "Russia          145934462       0.04 %      62206        9  16376870   \n",
       "Mexico          128932753       1.06 %    1357224       66   1943950   \n",
       "Japan           126476461      -0.30 %    -383840      347    364555   \n",
       "Ethiopia        114963588       2.57 %    2884858      115   1000000   \n",
       "Philippines     109581078       1.35 %    1464463      368    298170   \n",
       "Egypt           102334404       1.94 %    1946331      103    995450   \n",
       "\n",
       "               Migrants FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                                         \n",
       "China         -348399.0      1.7     38        61 %    18.47 %  \n",
       "India         -532687.0      2.2     28        35 %    17.70 %  \n",
       "United States  954806.0      1.8     38        83 %     4.25 %  \n",
       "Indonesia      -98955.0      2.3     30        56 %     3.51 %  \n",
       "Pakistan      -233379.0      3.6     23        35 %     2.83 %  \n",
       "Brazil          21200.0      1.7     33        88 %     2.73 %  \n",
       "Nigeria        -60000.0      5.4     18        52 %     2.64 %  \n",
       "Bangladesh    -369501.0      2.1     28        39 %     2.11 %  \n",
       "Russia         182456.0      1.8     40        74 %     1.87 %  \n",
       "Mexico         -60000.0      2.1     29        84 %     1.65 %  \n",
       "Japan           71560.0      1.4     48        92 %     1.62 %  \n",
       "Ethiopia        30000.0      4.3     19        21 %     1.47 %  \n",
       "Philippines    -67152.0      2.6     26        47 %     1.41 %  \n",
       "Egypt          -38033.0      3.3     25        43 %     1.31 %  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data[\"Pop\"] > 100_000_000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "33710c30-361f-44e8-920e-d19de51dd6b6",
   "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>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density</th>\n",
       "      <th>Area</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>FertRate</th>\n",
       "      <th>MedAge</th>\n",
       "      <th>UrbanPopPct</th>\n",
       "      <th>WorldShare</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>46754778</td>\n",
       "      <td>0.04 %</td>\n",
       "      <td>18002</td>\n",
       "      <td>94</td>\n",
       "      <td>498800</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>45</td>\n",
       "      <td>80 %</td>\n",
       "      <td>0.60 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uganda</th>\n",
       "      <td>45741007</td>\n",
       "      <td>3.32 %</td>\n",
       "      <td>1471413</td>\n",
       "      <td>229</td>\n",
       "      <td>199810</td>\n",
       "      <td>168694.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17</td>\n",
       "      <td>26 %</td>\n",
       "      <td>0.59 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>45195774</td>\n",
       "      <td>0.93 %</td>\n",
       "      <td>415097</td>\n",
       "      <td>17</td>\n",
       "      <td>2736690</td>\n",
       "      <td>4800.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>32</td>\n",
       "      <td>93 %</td>\n",
       "      <td>0.58 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>43851044</td>\n",
       "      <td>1.85 %</td>\n",
       "      <td>797990</td>\n",
       "      <td>18</td>\n",
       "      <td>2381740</td>\n",
       "      <td>-10000.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>29</td>\n",
       "      <td>73 %</td>\n",
       "      <td>0.56 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sudan</th>\n",
       "      <td>43849260</td>\n",
       "      <td>2.42 %</td>\n",
       "      <td>1036022</td>\n",
       "      <td>25</td>\n",
       "      <td>1765048</td>\n",
       "      <td>-50000.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>20</td>\n",
       "      <td>35 %</td>\n",
       "      <td>0.56 %</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>10423054</td>\n",
       "      <td>-0.48 %</td>\n",
       "      <td>-50401</td>\n",
       "      <td>81</td>\n",
       "      <td>128900</td>\n",
       "      <td>-16000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>46</td>\n",
       "      <td>85 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jordan</th>\n",
       "      <td>10203134</td>\n",
       "      <td>1.00 %</td>\n",
       "      <td>101440</td>\n",
       "      <td>115</td>\n",
       "      <td>88780</td>\n",
       "      <td>10220.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>24</td>\n",
       "      <td>91 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>10196709</td>\n",
       "      <td>-0.29 %</td>\n",
       "      <td>-29478</td>\n",
       "      <td>111</td>\n",
       "      <td>91590</td>\n",
       "      <td>-6000.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>46</td>\n",
       "      <td>66 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Azerbaijan</th>\n",
       "      <td>10139177</td>\n",
       "      <td>0.91 %</td>\n",
       "      <td>91459</td>\n",
       "      <td>123</td>\n",
       "      <td>82658</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>32</td>\n",
       "      <td>56 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sweden</th>\n",
       "      <td>10099265</td>\n",
       "      <td>0.63 %</td>\n",
       "      <td>62886</td>\n",
       "      <td>25</td>\n",
       "      <td>410340</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>41</td>\n",
       "      <td>88 %</td>\n",
       "      <td>0.13 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Pop YearlyChange  NetChange  Density     Area  Migrants  \\\n",
       "Country                                                                    \n",
       "Spain       46754778       0.04 %      18002       94   498800   40000.0   \n",
       "Uganda      45741007       3.32 %    1471413      229   199810  168694.0   \n",
       "Argentina   45195774       0.93 %     415097       17  2736690    4800.0   \n",
       "Algeria     43851044       1.85 %     797990       18  2381740  -10000.0   \n",
       "Sudan       43849260       2.42 %    1036022       25  1765048  -50000.0   \n",
       "...              ...          ...        ...      ...      ...       ...   \n",
       "Greece      10423054      -0.48 %     -50401       81   128900  -16000.0   \n",
       "Jordan      10203134       1.00 %     101440      115    88780   10220.0   \n",
       "Portugal    10196709      -0.29 %     -29478      111    91590   -6000.0   \n",
       "Azerbaijan  10139177       0.91 %      91459      123    82658    1200.0   \n",
       "Sweden      10099265       0.63 %      62886       25   410340   40000.0   \n",
       "\n",
       "           FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                            \n",
       "Spain           1.3     45        80 %     0.60 %  \n",
       "Uganda          5.0     17        26 %     0.59 %  \n",
       "Argentina       2.3     32        93 %     0.58 %  \n",
       "Algeria         3.1     29        73 %     0.56 %  \n",
       "Sudan           4.4     20        35 %     0.56 %  \n",
       "...             ...    ...         ...        ...  \n",
       "Greece          1.3     46        85 %     0.13 %  \n",
       "Jordan          2.8     24        91 %     0.13 %  \n",
       "Portugal        1.3     46        66 %     0.13 %  \n",
       "Azerbaijan      2.1     32        56 %     0.13 %  \n",
       "Sweden          1.9     41        88 %     0.13 %  \n",
       "\n",
       "[62 rows x 10 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Aufgabe: Finde alle Länder, welche zw. 10m und 50m Einwohnern haben\n",
    "data[(data[\"Pop\"] > 10_000_000) & (data[\"Pop\"] < 50_000_000)]  # Bedingungen kombinieren: &, |, ~"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e1b1bb0-a7c2-401f-89bc-eb9243529e8b",
   "metadata": {},
   "source": [
    "### Weiteres"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c3474762-14ff-4c68-8aae-0e3896dc3eeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['China', 'India', 'United States', 'Indonesia', 'Pakistan', 'Brazil',\n",
       "       'Nigeria', 'Bangladesh', 'Russia', 'Mexico',\n",
       "       ...\n",
       "       'Wallis & Futuna', 'Nauru', 'Saint Barthelemy', 'Saint Helena',\n",
       "       'Saint Pierre & Miquelon', 'Montserrat', 'Falkland Islands', 'Niue',\n",
       "       'Tokelau', 'Vatican State'],\n",
       "      dtype='object', name='Country', length=235)"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "1fe87c05-4d45-4623-8c73-0e1b9e13a988",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "China\n",
      "India\n",
      "United States\n",
      "Indonesia\n",
      "Pakistan\n",
      "Brazil\n",
      "Nigeria\n",
      "Bangladesh\n",
      "Russia\n",
      "Mexico\n",
      "Japan\n",
      "Ethiopia\n",
      "Philippines\n",
      "Egypt\n",
      "Vietnam\n",
      "DR Congo\n",
      "Turkey\n",
      "Iran\n",
      "Germany\n",
      "Thailand\n",
      "United Kingdom\n",
      "France\n",
      "Italy\n",
      "Tanzania\n",
      "South Africa\n",
      "Myanmar\n",
      "Kenya\n",
      "South Korea\n",
      "Colombia\n",
      "Spain\n",
      "Uganda\n",
      "Argentina\n",
      "Algeria\n",
      "Sudan\n",
      "Ukraine\n",
      "Iraq\n",
      "Afghanistan\n",
      "Poland\n",
      "Canada\n",
      "Morocco\n",
      "Saudi Arabia\n",
      "Uzbekistan\n",
      "Peru\n",
      "Angola\n",
      "Malaysia\n",
      "Mozambique\n",
      "Ghana\n",
      "Yemen\n",
      "Nepal\n",
      "Venezuela\n",
      "Madagascar\n",
      "Cameroon\n",
      "Côte d'Ivoire\n",
      "North Korea\n",
      "Australia\n",
      "Niger\n",
      "Taiwan\n",
      "Sri Lanka\n",
      "Burkina Faso\n",
      "Mali\n",
      "Romania\n",
      "Malawi\n",
      "Chile\n",
      "Kazakhstan\n",
      "Zambia\n",
      "Guatemala\n",
      "Ecuador\n",
      "Syria\n",
      "Netherlands\n",
      "Senegal\n",
      "Cambodia\n",
      "Chad\n",
      "Somalia\n",
      "Zimbabwe\n",
      "Guinea\n",
      "Rwanda\n",
      "Benin\n",
      "Burundi\n",
      "Tunisia\n",
      "Bolivia\n",
      "Belgium\n",
      "Haiti\n",
      "Cuba\n",
      "South Sudan\n",
      "Dominican Republic\n",
      "Czech Republic (Czechia)\n",
      "Greece\n",
      "Jordan\n",
      "Portugal\n",
      "Azerbaijan\n",
      "Sweden\n",
      "Honduras\n",
      "United Arab Emirates\n",
      "Hungary\n",
      "Tajikistan\n",
      "Belarus\n",
      "Austria\n",
      "Papua New Guinea\n",
      "Serbia\n",
      "Israel\n",
      "Switzerland\n",
      "Togo\n",
      "Sierra Leone\n",
      "Hong Kong\n",
      "Laos\n",
      "Paraguay\n",
      "Bulgaria\n",
      "Libya\n",
      "Lebanon\n",
      "Nicaragua\n",
      "Kyrgyzstan\n",
      "El Salvador\n",
      "Turkmenistan\n",
      "Singapore\n",
      "Denmark\n",
      "Finland\n",
      "Congo\n",
      "Slovakia\n",
      "Norway\n",
      "Oman\n",
      "State of Palestine\n",
      "Costa Rica\n",
      "Liberia\n",
      "Ireland\n",
      "Central African Republic\n",
      "New Zealand\n",
      "Mauritania\n",
      "Panama\n",
      "Kuwait\n",
      "Croatia\n",
      "Moldova\n",
      "Georgia\n",
      "Eritrea\n",
      "Uruguay\n",
      "Bosnia and Herzegovina\n",
      "Mongolia\n",
      "Armenia\n",
      "Jamaica\n",
      "Qatar\n",
      "Albania\n",
      "Puerto Rico\n",
      "Lithuania\n",
      "Namibia\n",
      "Gambia\n",
      "Botswana\n",
      "Gabon\n",
      "Lesotho\n",
      "North Macedonia\n",
      "Slovenia\n",
      "Guinea-Bissau\n",
      "Latvia\n",
      "Bahrain\n",
      "Equatorial Guinea\n",
      "Trinidad and Tobago\n",
      "Estonia\n",
      "Timor-Leste\n",
      "Mauritius\n",
      "Cyprus\n",
      "Eswatini\n",
      "Djibouti\n",
      "Fiji\n",
      "Réunion\n",
      "Comoros\n",
      "Guyana\n",
      "Bhutan\n",
      "Solomon Islands\n",
      "Macao\n",
      "Montenegro\n",
      "Luxembourg\n",
      "Western Sahara\n",
      "Suriname\n",
      "Cabo Verde\n",
      "Micronesia\n",
      "Maldives\n",
      "Malta\n",
      "Brunei\n",
      "Guadeloupe\n",
      "Belize\n",
      "Bahamas\n",
      "Martinique\n",
      "Iceland\n",
      "Vanuatu\n",
      "French Guiana\n",
      "Barbados\n",
      "New Caledonia\n",
      "French Polynesia\n",
      "Mayotte\n",
      "Sao Tome & Principe\n",
      "Samoa\n",
      "Saint Lucia\n",
      "Channel Islands\n",
      "Guam\n",
      "Curaçao\n",
      "Kiribati\n",
      "Grenada\n",
      "St. Vincent & Grenadines\n",
      "Aruba\n",
      "Tonga\n",
      "U.S. Virgin Islands\n",
      "Seychelles\n",
      "Antigua and Barbuda\n",
      "Isle of Man\n",
      "Andorra\n",
      "Dominica\n",
      "Cayman Islands\n",
      "Bermuda\n",
      "Marshall Islands\n",
      "Northern Mariana Islands\n",
      "Greenland\n",
      "American Samoa\n",
      "Saint Kitts & Nevis\n",
      "Faeroe Islands\n",
      "Sint Maarten\n",
      "Monaco\n",
      "Turks and Caicos\n",
      "Saint Martin\n",
      "Liechtenstein\n",
      "San Marino\n",
      "Gibraltar\n",
      "British Virgin Islands\n",
      "Caribbean Netherlands\n",
      "Palau\n",
      "Cook Islands\n",
      "Anguilla\n",
      "Tuvalu\n",
      "Wallis & Futuna\n",
      "Nauru\n",
      "Saint Barthelemy\n",
      "Saint Helena\n",
      "Saint Pierre & Miquelon\n",
      "Montserrat\n",
      "Falkland Islands\n",
      "Niue\n",
      "Tokelau\n",
      "Vatican State\n"
     ]
    }
   ],
   "source": [
    "for x in data.index:\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "f8d4598d-af40-40d4-b0d1-25dfcae9567a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Pop', 'YearlyChange', 'NetChange', 'Density', 'Area', 'Migrants',\n",
       "       'FertRate', 'MedAge', 'UrbanPopPct', 'WorldShare'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "96c5b034-9fdc-45d9-b45c-3d7283eb4334",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MedAge\n",
       "N.A.    34\n",
       "19      14\n",
       "28      12\n",
       "43      11\n",
       "32      11\n",
       "42      10\n",
       "18      10\n",
       "20       9\n",
       "30       8\n",
       "38       7\n",
       "26       7\n",
       "40       7\n",
       "22       7\n",
       "31       6\n",
       "34       6\n",
       "24       6\n",
       "17       6\n",
       "44       5\n",
       "29       5\n",
       "41       5\n",
       "33       5\n",
       "21       5\n",
       "45       5\n",
       "23       4\n",
       "37       4\n",
       "36       4\n",
       "25       4\n",
       "27       4\n",
       "39       3\n",
       "46       3\n",
       "35       3\n",
       "47       2\n",
       "48       1\n",
       "15       1\n",
       "16       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"MedAge\"].value_counts()  # Gibt die Anzahl der einzigartigen Werte anhand einer Spalte zurück"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "18c227a8-c514-42b3-b85e-96f7b49b4b89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x00000236829439D0>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(\"MedAge\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "3a523889-da02-4e8d-be07-41a41b745d06",
   "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>Pop</th>\n",
       "      <th>YearlyChange</th>\n",
       "      <th>NetChange</th>\n",
       "      <th>Density</th>\n",
       "      <th>Area</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>FertRate</th>\n",
       "      <th>MedAge</th>\n",
       "      <th>UrbanPopPct</th>\n",
       "      <th>WorldShare</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ethiopia</th>\n",
       "      <td>114963588</td>\n",
       "      <td>2.57 %</td>\n",
       "      <td>2884858</td>\n",
       "      <td>115</td>\n",
       "      <td>1000000</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>19</td>\n",
       "      <td>21 %</td>\n",
       "      <td>1.47 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cameroon</th>\n",
       "      <td>26545863</td>\n",
       "      <td>2.59 %</td>\n",
       "      <td>669483</td>\n",
       "      <td>56</td>\n",
       "      <td>472710</td>\n",
       "      <td>-4800.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>19</td>\n",
       "      <td>56 %</td>\n",
       "      <td>0.34 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Côte d'Ivoire</th>\n",
       "      <td>26378274</td>\n",
       "      <td>2.57 %</td>\n",
       "      <td>661730</td>\n",
       "      <td>83</td>\n",
       "      <td>318000</td>\n",
       "      <td>-8000.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>19</td>\n",
       "      <td>51 %</td>\n",
       "      <td>0.34 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Senegal</th>\n",
       "      <td>16743927</td>\n",
       "      <td>2.75 %</td>\n",
       "      <td>447563</td>\n",
       "      <td>87</td>\n",
       "      <td>192530</td>\n",
       "      <td>-20000.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>19</td>\n",
       "      <td>49 %</td>\n",
       "      <td>0.21 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>14862924</td>\n",
       "      <td>1.48 %</td>\n",
       "      <td>217456</td>\n",
       "      <td>38</td>\n",
       "      <td>386850</td>\n",
       "      <td>-116858.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>19</td>\n",
       "      <td>38 %</td>\n",
       "      <td>0.19 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Benin</th>\n",
       "      <td>12123200</td>\n",
       "      <td>2.73 %</td>\n",
       "      <td>322049</td>\n",
       "      <td>108</td>\n",
       "      <td>112760</td>\n",
       "      <td>-2000.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>19</td>\n",
       "      <td>48 %</td>\n",
       "      <td>0.16 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Sudan</th>\n",
       "      <td>11193725</td>\n",
       "      <td>1.19 %</td>\n",
       "      <td>131612</td>\n",
       "      <td>18</td>\n",
       "      <td>610952</td>\n",
       "      <td>-174200.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>19</td>\n",
       "      <td>25 %</td>\n",
       "      <td>0.14 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Togo</th>\n",
       "      <td>8278724</td>\n",
       "      <td>2.43 %</td>\n",
       "      <td>196358</td>\n",
       "      <td>152</td>\n",
       "      <td>54390</td>\n",
       "      <td>-2000.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>19</td>\n",
       "      <td>43 %</td>\n",
       "      <td>0.11 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sierra Leone</th>\n",
       "      <td>7976983</td>\n",
       "      <td>2.10 %</td>\n",
       "      <td>163768</td>\n",
       "      <td>111</td>\n",
       "      <td>72180</td>\n",
       "      <td>-4200.0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>19</td>\n",
       "      <td>43 %</td>\n",
       "      <td>0.10 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congo</th>\n",
       "      <td>5518087</td>\n",
       "      <td>2.56 %</td>\n",
       "      <td>137579</td>\n",
       "      <td>16</td>\n",
       "      <td>341500</td>\n",
       "      <td>-4000.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>19</td>\n",
       "      <td>70 %</td>\n",
       "      <td>0.07 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Liberia</th>\n",
       "      <td>5057681</td>\n",
       "      <td>2.44 %</td>\n",
       "      <td>120307</td>\n",
       "      <td>53</td>\n",
       "      <td>96320</td>\n",
       "      <td>-5000.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>19</td>\n",
       "      <td>53 %</td>\n",
       "      <td>0.06 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eritrea</th>\n",
       "      <td>3546421</td>\n",
       "      <td>1.41 %</td>\n",
       "      <td>49304</td>\n",
       "      <td>35</td>\n",
       "      <td>101000</td>\n",
       "      <td>-39858.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>19</td>\n",
       "      <td>63 %</td>\n",
       "      <td>0.05 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Guinea-Bissau</th>\n",
       "      <td>1968001</td>\n",
       "      <td>2.45 %</td>\n",
       "      <td>47079</td>\n",
       "      <td>70</td>\n",
       "      <td>28120</td>\n",
       "      <td>-1399.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>19</td>\n",
       "      <td>45 %</td>\n",
       "      <td>0.03 %</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sao Tome &amp; Principe</th>\n",
       "      <td>219159</td>\n",
       "      <td>1.91 %</td>\n",
       "      <td>4103</td>\n",
       "      <td>228</td>\n",
       "      <td>960</td>\n",
       "      <td>-1680.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>19</td>\n",
       "      <td>74 %</td>\n",
       "      <td>0.00 %</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Pop YearlyChange  NetChange  Density     Area  \\\n",
       "Country                                                                    \n",
       "Ethiopia             114963588       2.57 %    2884858      115  1000000   \n",
       "Cameroon              26545863       2.59 %     669483       56   472710   \n",
       "Côte d'Ivoire         26378274       2.57 %     661730       83   318000   \n",
       "Senegal               16743927       2.75 %     447563       87   192530   \n",
       "Zimbabwe              14862924       1.48 %     217456       38   386850   \n",
       "Benin                 12123200       2.73 %     322049      108   112760   \n",
       "South Sudan           11193725       1.19 %     131612       18   610952   \n",
       "Togo                   8278724       2.43 %     196358      152    54390   \n",
       "Sierra Leone           7976983       2.10 %     163768      111    72180   \n",
       "Congo                  5518087       2.56 %     137579       16   341500   \n",
       "Liberia                5057681       2.44 %     120307       53    96320   \n",
       "Eritrea                3546421       1.41 %      49304       35   101000   \n",
       "Guinea-Bissau          1968001       2.45 %      47079       70    28120   \n",
       "Sao Tome & Principe     219159       1.91 %       4103      228      960   \n",
       "\n",
       "                     Migrants FertRate MedAge UrbanPopPct WorldShare  \n",
       "Country                                                               \n",
       "Ethiopia              30000.0      4.3     19        21 %     1.47 %  \n",
       "Cameroon              -4800.0      4.6     19        56 %     0.34 %  \n",
       "Côte d'Ivoire         -8000.0      4.7     19        51 %     0.34 %  \n",
       "Senegal              -20000.0      4.7     19        49 %     0.21 %  \n",
       "Zimbabwe            -116858.0      3.6     19        38 %     0.19 %  \n",
       "Benin                 -2000.0      4.9     19        48 %     0.16 %  \n",
       "South Sudan         -174200.0      4.7     19        25 %     0.14 %  \n",
       "Togo                  -2000.0      4.4     19        43 %     0.11 %  \n",
       "Sierra Leone          -4200.0      4.3     19        43 %     0.10 %  \n",
       "Congo                 -4000.0      4.5     19        70 %     0.07 %  \n",
       "Liberia               -5000.0      4.4     19        53 %     0.06 %  \n",
       "Eritrea              -39858.0      4.1     19        63 %     0.05 %  \n",
       "Guinea-Bissau         -1399.0      4.5     19        45 %     0.03 %  \n",
       "Sao Tome & Principe   -1680.0      4.4     19        74 %     0.00 %  "
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(\"MedAge\").get_group(\"19\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "7ba81902-93f2-46fc-8d9d-1eec345124aa",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MedAge\n",
       "15      2.420664e+07\n",
       "16      2.025083e+07\n",
       "17      3.539643e+07\n",
       "18      4.148540e+07\n",
       "19      1.824118e+07\n",
       "20      1.939652e+07\n",
       "21      9.621932e+06\n",
       "22      7.686515e+06\n",
       "23      6.028827e+07\n",
       "24      7.213284e+06\n",
       "25      3.304188e+07\n",
       "26      2.510786e+07\n",
       "27      2.088666e+06\n",
       "28      1.398790e+08\n",
       "29      4.693030e+07\n",
       "30      4.894655e+07\n",
       "31      1.847800e+07\n",
       "32      3.284957e+07\n",
       "33      4.789470e+07\n",
       "34      3.726593e+06\n",
       "35      1.595275e+07\n",
       "36      2.161582e+06\n",
       "37      1.772735e+06\n",
       "38      2.590871e+08\n",
       "39      1.120258e+06\n",
       "40      4.277205e+07\n",
       "41      1.942832e+07\n",
       "42      1.717237e+07\n",
       "43      7.631299e+06\n",
       "44      1.210433e+07\n",
       "45      1.320029e+07\n",
       "46      3.480124e+07\n",
       "47      3.041855e+07\n",
       "48      1.264765e+08\n",
       "N.A.    3.333179e+04\n",
       "Name: Pop, dtype: float64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Aufgabe: Was ist der Bevölkerungsdurchschnitt von jeder Gruppe?\n",
    "data.groupby(\"MedAge\")[\"Pop\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "26201d92-c2b8-4787-8e1d-e6d2a0e69bc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Welche dieser Länder sind > 50m?\n",
    "g = data.groupby(\"MedAge\")[\"Pop\"].mean()\n",
    "i = g.index\n",
    "g = pd.Series(np.array(g, dtype=np.int64))\n",
    "g.index = i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "72f6d7af-7333-4fd0-b128-c9bfd15d4621",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MedAge\n",
       "15       24206644\n",
       "16       20250833\n",
       "17       35396425\n",
       "18       41485399\n",
       "19       18241182\n",
       "20       19396523\n",
       "21        9621932\n",
       "22        7686515\n",
       "23       60288272\n",
       "24        7213284\n",
       "25       33041880\n",
       "26       25107858\n",
       "27        2088666\n",
       "28      139879041\n",
       "29       46930304\n",
       "30       48946550\n",
       "31       18478003\n",
       "32       32849571\n",
       "33       47894699\n",
       "34        3726593\n",
       "35       15952753\n",
       "36        2161581\n",
       "37        1772735\n",
       "38      259087065\n",
       "39        1120258\n",
       "40       42772052\n",
       "41       19428317\n",
       "42       17172367\n",
       "43        7631298\n",
       "44       12104325\n",
       "45       13200286\n",
       "46       34801235\n",
       "47       30418545\n",
       "48      126476461\n",
       "N.A.        33331\n",
       "dtype: int64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "eaa558db-3948-4fb8-b0f9-dfe11166059d",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MedAge\n",
       "15      False\n",
       "16      False\n",
       "17      False\n",
       "18      False\n",
       "19      False\n",
       "20      False\n",
       "21      False\n",
       "22      False\n",
       "23       True\n",
       "24      False\n",
       "25      False\n",
       "26      False\n",
       "27      False\n",
       "28       True\n",
       "29      False\n",
       "30      False\n",
       "31      False\n",
       "32      False\n",
       "33      False\n",
       "34      False\n",
       "35      False\n",
       "36      False\n",
       "37      False\n",
       "38       True\n",
       "39      False\n",
       "40      False\n",
       "41      False\n",
       "42      False\n",
       "43      False\n",
       "44      False\n",
       "45      False\n",
       "46      False\n",
       "47      False\n",
       "48       True\n",
       "N.A.    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g > 50_000_000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "4a98c5f2-7373-4b0c-b2b9-46d19a934532",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MedAge\n",
       "23     60288272\n",
       "28    139879041\n",
       "38    259087065\n",
       "48    126476461\n",
       "dtype: int64"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g[g > 50_000_000]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be3b4cd7-4f07-4452-890f-22fb466291e0",
   "metadata": {},
   "source": [
    "### Daten exportieren\n",
    "\n",
    "In Pandas gibt es die to... Funktionen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "da26f314-e2c8-4e11-979b-fd5ac43b56c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv(\"Data/PopulationDataFastFertig.csv\")"
   ]
  }
 ],
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