gender-fifa-dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "from scipy import stats\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fifa DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 455,
   "metadata": {
    "scrolled": true
   },
   "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>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country ISO3</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Rnk</th>\n",
       "      <th>Total Points  PTS</th>\n",
       "      <th>Previous Points  Prev.Pts</th>\n",
       "      <th>+/-</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>GER</td>\n",
       "      <td>Germany</td>\n",
       "      <td>1</td>\n",
       "      <td>2229</td>\n",
       "      <td>2223.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>USA</td>\n",
       "      <td>USA</td>\n",
       "      <td>2</td>\n",
       "      <td>2184</td>\n",
       "      <td>2201.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>NOR</td>\n",
       "      <td>Norway</td>\n",
       "      <td>3</td>\n",
       "      <td>2075</td>\n",
       "      <td>2062.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>SWE</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>4</td>\n",
       "      <td>2037</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>PRK</td>\n",
       "      <td>Korea DPR</td>\n",
       "      <td>5</td>\n",
       "      <td>2024</td>\n",
       "      <td>1999.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>6</td>\n",
       "      <td>2016</td>\n",
       "      <td>2053.0</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>FRA</td>\n",
       "      <td>France</td>\n",
       "      <td>7</td>\n",
       "      <td>1991</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>DEN</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>8</td>\n",
       "      <td>1975</td>\n",
       "      <td>1955.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>CHN</td>\n",
       "      <td>China PR</td>\n",
       "      <td>9</td>\n",
       "      <td>1970</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>JPN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>10</td>\n",
       "      <td>1950</td>\n",
       "      <td>1916.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>CAN</td>\n",
       "      <td>Canada</td>\n",
       "      <td>11</td>\n",
       "      <td>1946</td>\n",
       "      <td>1932.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>ENG</td>\n",
       "      <td>England</td>\n",
       "      <td>12</td>\n",
       "      <td>1928</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>ITA</td>\n",
       "      <td>Italy</td>\n",
       "      <td>13</td>\n",
       "      <td>1919</td>\n",
       "      <td>1932.0</td>\n",
       "      <td>-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>RUS</td>\n",
       "      <td>Russia</td>\n",
       "      <td>14</td>\n",
       "      <td>1903</td>\n",
       "      <td>1911.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>AUS</td>\n",
       "      <td>Australia</td>\n",
       "      <td>15</td>\n",
       "      <td>1889</td>\n",
       "      <td>1892.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>FIN</td>\n",
       "      <td>Finland</td>\n",
       "      <td>16</td>\n",
       "      <td>1871</td>\n",
       "      <td>1876.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>UKR</td>\n",
       "      <td>Ukraine</td>\n",
       "      <td>17</td>\n",
       "      <td>1834</td>\n",
       "      <td>1834.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>NED</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>18</td>\n",
       "      <td>1824</td>\n",
       "      <td>1815.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>CZE</td>\n",
       "      <td>Czech Republic</td>\n",
       "      <td>19</td>\n",
       "      <td>1803</td>\n",
       "      <td>1805.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>ESP</td>\n",
       "      <td>Spain</td>\n",
       "      <td>20</td>\n",
       "      <td>1793</td>\n",
       "      <td>1793.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>ISL</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>21</td>\n",
       "      <td>1789</td>\n",
       "      <td>1773.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>22</td>\n",
       "      <td>1752</td>\n",
       "      <td>1724.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>KOR</td>\n",
       "      <td>Korea Republic</td>\n",
       "      <td>23</td>\n",
       "      <td>1751</td>\n",
       "      <td>1757.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>NZL</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>24</td>\n",
       "      <td>1748</td>\n",
       "      <td>1751.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>NGA</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>25</td>\n",
       "      <td>1737</td>\n",
       "      <td>1736.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>SCO</td>\n",
       "      <td>Scotland</td>\n",
       "      <td>26</td>\n",
       "      <td>1693</td>\n",
       "      <td>1688.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>TPE</td>\n",
       "      <td>Chinese Taipei</td>\n",
       "      <td>27</td>\n",
       "      <td>1675</td>\n",
       "      <td>1690.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>POL</td>\n",
       "      <td>Poland</td>\n",
       "      <td>28</td>\n",
       "      <td>1667</td>\n",
       "      <td>1658.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>SUI</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>29</td>\n",
       "      <td>1656</td>\n",
       "      <td>1658.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2006</td>\n",
       "      <td>F</td>\n",
       "      <td>SRB</td>\n",
       "      <td>Serbia</td>\n",
       "      <td>30</td>\n",
       "      <td>1650</td>\n",
       "      <td>1650.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year Gender Country ISO3      Country Name  Rnk  Total Points  PTS  \\\n",
       "0   2006      F          GER         Germany      1               2229   \n",
       "1   2006      F          USA             USA      2               2184   \n",
       "2   2006      F          NOR          Norway      3               2075   \n",
       "3   2006      F          SWE          Sweden      4               2037   \n",
       "4   2006      F          PRK       Korea DPR      5               2024   \n",
       "5   2006      F          BRA          Brazil      6               2016   \n",
       "6   2006      F          FRA          France      7               1991   \n",
       "7   2006      F          DEN         Denmark      8               1975   \n",
       "8   2006      F          CHN        China PR      9               1970   \n",
       "9   2006      F          JPN           Japan     10               1950   \n",
       "10  2006      F          CAN          Canada     11               1946   \n",
       "11  2006      F          ENG         England     12               1928   \n",
       "12  2006      F          ITA           Italy     13               1919   \n",
       "13  2006      F          RUS          Russia     14               1903   \n",
       "14  2006      F          AUS       Australia     15               1889   \n",
       "15  2006      F          FIN         Finland     16               1871   \n",
       "16  2006      F          UKR         Ukraine     17               1834   \n",
       "17  2006      F          NED     Netherlands     18               1824   \n",
       "18  2006      F          CZE  Czech Republic     19               1803   \n",
       "19  2006      F          ESP           Spain     20               1793   \n",
       "20  2006      F          ISL         Iceland     21               1789   \n",
       "21  2006      F          MEX          Mexico     22               1752   \n",
       "22  2006      F          KOR  Korea Republic     23               1751   \n",
       "23  2006      F          NZL     New Zealand     24               1748   \n",
       "24  2006      F          NGA         Nigeria     25               1737   \n",
       "25  2006      F          SCO        Scotland     26               1693   \n",
       "26  2006      F          TPE  Chinese Taipei     27               1675   \n",
       "27  2006      F          POL          Poland     28               1667   \n",
       "28  2006      F          SUI     Switzerland     29               1656   \n",
       "29  2006      F          SRB          Serbia     30               1650   \n",
       "\n",
       "    Previous Points  Prev.Pts +/-  \n",
       "0                      2223.0   0  \n",
       "1                      2201.0   0  \n",
       "2                      2062.0   0  \n",
       "3                      2035.0   1  \n",
       "4                      1999.0   2  \n",
       "5                      2053.0  -2  \n",
       "6                      2007.0  -1  \n",
       "7                      1955.0  -1  \n",
       "8                      1989.0  -1  \n",
       "9                      1916.0   3  \n",
       "10                     1932.0  -1  \n",
       "11                     1918.0   0  \n",
       "12                     1932.0  -3  \n",
       "13                     1911.0   0  \n",
       "14                     1892.0   0  \n",
       "15                     1876.0   0  \n",
       "16                     1834.0   0  \n",
       "17                     1815.0   0  \n",
       "18                     1805.0   0  \n",
       "19                     1793.0   0  \n",
       "20                     1773.0   0  \n",
       "21                     1724.0   3  \n",
       "22                     1757.0  -1  \n",
       "23                     1751.0  -1  \n",
       "24                     1736.0  -1  \n",
       "25                     1688.0   1  \n",
       "26                     1690.0  -1  \n",
       "27                     1658.0   0  \n",
       "28                     1658.0  -1  \n",
       "29                     1650.0   0  "
      ]
     },
     "execution_count": 455,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fifa = pd.read_csv('./resources/fifa-ranking/complete_fifa_ranking.csv')\n",
    "fifa.head(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [],
   "source": [
    "fifa['Country Name'] = fifa['Country Name'].apply(lambda x: x.strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "213"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fifa_unique = len(set(fifa['Country ISO3']))\n",
    "fifa_unique"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drop data from missing years"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "⚠️ Dropped 2006 that had some values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country ISO3</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Rnk</th>\n",
       "      <th>Total Points  PTS</th>\n",
       "      <th>Previous Points  Prev.Pts</th>\n",
       "      <th>+/-</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>GER</td>\n",
       "      <td>Germany</td>\n",
       "      <td>1</td>\n",
       "      <td>2201</td>\n",
       "      <td>2201.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>USA</td>\n",
       "      <td>USA</td>\n",
       "      <td>2</td>\n",
       "      <td>2186</td>\n",
       "      <td>2192.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>SWE</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>3</td>\n",
       "      <td>2086</td>\n",
       "      <td>2070.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>4</td>\n",
       "      <td>2082</td>\n",
       "      <td>2082.0</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>NOR</td>\n",
       "      <td>Norway</td>\n",
       "      <td>5</td>\n",
       "      <td>2040</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4698</th>\n",
       "      <td>2018</td>\n",
       "      <td>M</td>\n",
       "      <td>VGB</td>\n",
       "      <td>British Virgin Islands</td>\n",
       "      <td>207</td>\n",
       "      <td>867</td>\n",
       "      <td>867.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4699</th>\n",
       "      <td>2018</td>\n",
       "      <td>M</td>\n",
       "      <td>TCA</td>\n",
       "      <td>Turks and Caicos Islands</td>\n",
       "      <td>208</td>\n",
       "      <td>864</td>\n",
       "      <td>864.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4700</th>\n",
       "      <td>2018</td>\n",
       "      <td>M</td>\n",
       "      <td>AIA</td>\n",
       "      <td>Anguilla</td>\n",
       "      <td>208</td>\n",
       "      <td>864</td>\n",
       "      <td>864.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4701</th>\n",
       "      <td>2018</td>\n",
       "      <td>M</td>\n",
       "      <td>BAH</td>\n",
       "      <td>Bahamas</td>\n",
       "      <td>210</td>\n",
       "      <td>858</td>\n",
       "      <td>858.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4702</th>\n",
       "      <td>2018</td>\n",
       "      <td>M</td>\n",
       "      <td>SMR</td>\n",
       "      <td>San Marino</td>\n",
       "      <td>211</td>\n",
       "      <td>854</td>\n",
       "      <td>854.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3714 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year Gender Country ISO3              Country Name  Rnk  \\\n",
       "140   2007      F          GER                   Germany    1   \n",
       "141   2007      F          USA                       USA    2   \n",
       "142   2007      F          SWE                    Sweden    3   \n",
       "143   2007      F          BRA                    Brazil    4   \n",
       "144   2007      F          NOR                    Norway    5   \n",
       "...    ...    ...          ...                       ...  ...   \n",
       "4698  2018      M          VGB    British Virgin Islands  207   \n",
       "4699  2018      M          TCA  Turks and Caicos Islands  208   \n",
       "4700  2018      M          AIA                  Anguilla  208   \n",
       "4701  2018      M          BAH                   Bahamas  210   \n",
       "4702  2018      M          SMR                San Marino  211   \n",
       "\n",
       "      Total Points  PTS  Previous Points  Prev.Pts +/-  \n",
       "140                2201                     2201.0   0  \n",
       "141                2186                     2192.0   0  \n",
       "142                2086                     2070.0   1  \n",
       "143                2082                     2082.0  -1  \n",
       "144                2040                     2035.0   0  \n",
       "...                 ...                        ...  ..  \n",
       "4698                867                      867.0   0  \n",
       "4699                864                      864.0   0  \n",
       "4700                864                      864.0   0  \n",
       "4701                858                      858.0   0  \n",
       "4702                854                      854.0   0  \n",
       "\n",
       "[3714 rows x 8 columns]"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fifa_sliced_years = fifa[~fifa['Year'].isin([2006,2017,2019,2020])]\n",
    "fifa_sliced_years"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gender DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2018}"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gender = pd.read_csv('./resources/gender-ranking/overall_global_gender_gap.csv')\n",
    "set(gender['Year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "153"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gender_unique = len(set(gender['Country ISO3']))\n",
    "gender_unique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "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 ISO3</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Index</th>\n",
       "      <th>Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1617</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2006</td>\n",
       "      <td>0.6460</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1618</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2007</td>\n",
       "      <td>0.6464</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1619</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.6485</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1620</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2009</td>\n",
       "      <td>0.6518</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1621</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.6574</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1622</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2011</td>\n",
       "      <td>0.6607</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1623</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2014</td>\n",
       "      <td>0.7013</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1624</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.7090</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2016</td>\n",
       "      <td>0.7100</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2018</td>\n",
       "      <td>0.7210</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Country ISO3 Country Name  Year   Index  Rank\n",
       "1617          ZIM     Zimbabwe  2006  0.6460  76.0\n",
       "1618          ZIM     Zimbabwe  2007  0.6464  88.0\n",
       "1619          ZIM     Zimbabwe  2008  0.6485  92.0\n",
       "1620          ZIM     Zimbabwe  2009  0.6518  95.0\n",
       "1621          ZIM     Zimbabwe  2010  0.6574  92.0\n",
       "1622          ZIM     Zimbabwe  2011  0.6607  88.0\n",
       "1623          ZIM     Zimbabwe  2014  0.7013  63.0\n",
       "1624          ZIM     Zimbabwe  2015  0.7090  57.0\n",
       "1625          ZIM     Zimbabwe  2016  0.7100  56.0\n",
       "1626          ZIM     Zimbabwe  2018  0.7210  47.0"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gender[gender['Country ISO3'] =='ZIM']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "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 ISO3</th>\n",
       "      <th>Country Name</th>\n",
       "      <th>Year</th>\n",
       "      <th>Index</th>\n",
       "      <th>Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ANG</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2007</td>\n",
       "      <td>0.6034</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ANG</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.6032</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ANG</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2009</td>\n",
       "      <td>0.6353</td>\n",
       "      <td>106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ANG</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.6712</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ANG</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2011</td>\n",
       "      <td>0.6624</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1622</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2011</td>\n",
       "      <td>0.6607</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1623</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2014</td>\n",
       "      <td>0.7013</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1624</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.7090</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1625</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2016</td>\n",
       "      <td>0.7100</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1626</th>\n",
       "      <td>ZIM</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2018</td>\n",
       "      <td>0.7210</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1512 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Country ISO3 Country Name  Year   Index   Rank\n",
       "1             ANG       Angola  2007  0.6034  110.0\n",
       "2             ANG       Angola  2008  0.6032  114.0\n",
       "3             ANG       Angola  2009  0.6353  106.0\n",
       "4             ANG       Angola  2010  0.6712   81.0\n",
       "5             ANG       Angola  2011  0.6624   87.0\n",
       "...           ...          ...   ...     ...    ...\n",
       "1622          ZIM     Zimbabwe  2011  0.6607   88.0\n",
       "1623          ZIM     Zimbabwe  2014  0.7013   63.0\n",
       "1624          ZIM     Zimbabwe  2015  0.7090   57.0\n",
       "1625          ZIM     Zimbabwe  2016  0.7100   56.0\n",
       "1626          ZIM     Zimbabwe  2018  0.7210   47.0\n",
       "\n",
       "[1512 rows x 5 columns]"
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# I drop 2016 because there are several missing values\n",
    "gender = gender[~gender['Year'].isin([2006])]\n",
    "gender"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Differences between df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have to drop: 60 missing countries\n"
     ]
    }
   ],
   "source": [
    "print(\"I have to drop:\", fifa_unique - gender_unique ,\"missing countries\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merging Dataframes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Merge on Country code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 420,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "214"
      ]
     },
     "execution_count": 420,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged = pd.merge(fifa_sliced_years, gender, how='left', on=['Year', 'Country ISO3'])\n",
    "len(set(merged['Country Name_x']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Merge on Country Name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {
    "scrolled": true
   },
   "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>Year</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country ISO3</th>\n",
       "      <th>Country Name_x</th>\n",
       "      <th>Rnk</th>\n",
       "      <th>Total Points  PTS</th>\n",
       "      <th>Previous Points  Prev.Pts</th>\n",
       "      <th>+/-</th>\n",
       "      <th>Country Name_y</th>\n",
       "      <th>Index</th>\n",
       "      <th>Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>GER</td>\n",
       "      <td>Germany</td>\n",
       "      <td>1</td>\n",
       "      <td>2201</td>\n",
       "      <td>2201.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Germany</td>\n",
       "      <td>0.7618</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>USA</td>\n",
       "      <td>USA</td>\n",
       "      <td>2</td>\n",
       "      <td>2186</td>\n",
       "      <td>2192.0</td>\n",
       "      <td>0</td>\n",
       "      <td>United States</td>\n",
       "      <td>0.7002</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>SWE</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>3</td>\n",
       "      <td>2086</td>\n",
       "      <td>2070.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>0.8146</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>4</td>\n",
       "      <td>2082</td>\n",
       "      <td>2082.0</td>\n",
       "      <td>-1</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>0.6637</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007</td>\n",
       "      <td>F</td>\n",
       "      <td>NOR</td>\n",
       "      <td>Norway</td>\n",
       "      <td>5</td>\n",
       "      <td>2040</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Norway</td>\n",
       "      <td>0.8059</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year Gender Country ISO3 Country Name_x  Rnk  Total Points  PTS  \\\n",
       "0  2007      F          GER        Germany    1               2201   \n",
       "1  2007      F          USA            USA    2               2186   \n",
       "2  2007      F          SWE         Sweden    3               2086   \n",
       "3  2007      F          BRA         Brazil    4               2082   \n",
       "4  2007      F          NOR         Norway    5               2040   \n",
       "\n",
       "   Previous Points  Prev.Pts +/- Country Name_y   Index  Rank  \n",
       "0                     2201.0   0        Germany  0.7618   7.0  \n",
       "1                     2192.0   0  United States  0.7002  31.0  \n",
       "2                     2070.0   1         Sweden  0.8146   1.0  \n",
       "3                     2082.0  -1         Brazil  0.6637  74.0  \n",
       "4                     2035.0   0         Norway  0.8059   2.0  "
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_country = pd.merge(fifa_sliced_years, gender, how='left', on=['Year', 'Country Name'])\n",
    "merged.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Merge on country code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "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>Year</th>\n",
       "      <th>Index</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Rnk</th>\n",
       "      <th>Total Points  PTS</th>\n",
       "      <th>Previous Points  Prev.Pts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2594.000000</td>\n",
       "      <td>2592.000000</td>\n",
       "      <td>2592.000000</td>\n",
       "      <td>2594.000000</td>\n",
       "      <td>2594.000000</td>\n",
       "      <td>2594.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2012.265613</td>\n",
       "      <td>0.689021</td>\n",
       "      <td>66.520062</td>\n",
       "      <td>74.729761</td>\n",
       "      <td>941.523516</td>\n",
       "      <td>941.584811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.340203</td>\n",
       "      <td>0.058704</td>\n",
       "      <td>39.554500</td>\n",
       "      <td>49.939260</td>\n",
       "      <td>573.693257</td>\n",
       "      <td>574.213449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2007.000000</td>\n",
       "      <td>0.451000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2009.000000</td>\n",
       "      <td>0.655000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>406.250000</td>\n",
       "      <td>407.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2012.000000</td>\n",
       "      <td>0.690800</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>959.000000</td>\n",
       "      <td>956.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2015.000000</td>\n",
       "      <td>0.722000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>110.750000</td>\n",
       "      <td>1385.750000</td>\n",
       "      <td>1384.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2018.000000</td>\n",
       "      <td>0.881000</td>\n",
       "      <td>149.000000</td>\n",
       "      <td>210.000000</td>\n",
       "      <td>2228.000000</td>\n",
       "      <td>2229.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year        Index         Rank          Rnk  Total Points  PTS  \\\n",
       "count  2594.000000  2592.000000  2592.000000  2594.000000        2594.000000   \n",
       "mean   2012.265613     0.689021    66.520062    74.729761         941.523516   \n",
       "std       3.340203     0.058704    39.554500    49.939260         573.693257   \n",
       "min    2007.000000     0.451000     1.000000     1.000000           0.000000   \n",
       "25%    2009.000000     0.655000    32.000000    32.000000         406.250000   \n",
       "50%    2012.000000     0.690800    65.000000    69.000000         959.000000   \n",
       "75%    2015.000000     0.722000   100.000000   110.750000        1385.750000   \n",
       "max    2018.000000     0.881000   149.000000   210.000000        2228.000000   \n",
       "\n",
       "       Previous Points  Prev.Pts  \n",
       "count                2594.000000  \n",
       "mean                  941.584811  \n",
       "std                   574.213449  \n",
       "min                     0.000000  \n",
       "25%                   407.250000  \n",
       "50%                   956.500000  \n",
       "75%                  1384.500000  \n",
       "max                  2229.000000  "
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_by_gender = pd.merge(gender, fifa_sliced_years, how='left', on=['Year', 'Country ISO3'])\n",
    "merged_by_gender.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 95 rows with null values\n",
      "There are 109 rows with null values\n",
      "There are 0 rows with null values\n"
     ]
    }
   ],
   "source": [
    "null_values_iso = set(merged[merged[\"Index\"].isnull()]['Country ISO3'])\n",
    "print(\"There are\",len(null_values_iso),\"rows with null values\")\n",
    "\n",
    "null_values_name = set(merged_country[merged_country[\"Index\"].isnull()]['Country Name'])\n",
    "print(\"There are\",len(null_values_name),\"rows with null values\")\n",
    "\n",
    "null_values_by_gender = set(merged_by_gender[merged_by_gender[\"Rnk\"].isnull()]['Country ISO3'])\n",
    "print(\"There are\",len(null_values_by_gender),\"rows with null values\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Column names:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_by_gender['Rank']\n",
    "merged_by_gender = merged_by_gender.rename(columns={'Rank': 'gender_rank', 'Rnk':'fifa_rank'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Int values: I didn't apply this because it gave me later a problem I don't remember"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merged_by_gender['gender_rank'] = merged_by_gender['gender_rank'].apply(lambda x: int(x) if ( pd.notna(x)) else ' ')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data to check for manual cleanup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "set()"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "null_values_by_gender"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_by_gender.to_csv(r'gender-fifa-dataset.csv', index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge df with probability data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 472,
   "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 ISO3</th>\n",
       "      <th>Country Name_x</th>\n",
       "      <th>Year</th>\n",
       "      <th>Index</th>\n",
       "      <th>gender_rank</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country Name_y</th>\n",
       "      <th>fifa_rank</th>\n",
       "      <th>Total Points  PTS</th>\n",
       "      <th>Previous Points  Prev.Pts</th>\n",
       "      <th>+/-</th>\n",
       "      <th>p</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1825</th>\n",
       "      <td>NOR</td>\n",
       "      <td>Norway</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.8239</td>\n",
       "      <td>1.0</td>\n",
       "      <td>M</td>\n",
       "      <td>Norway</td>\n",
       "      <td>59</td>\n",
       "      <td>526</td>\n",
       "      <td>572.0</td>\n",
       "      <td>-5</td>\n",
       "      <td>0.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>NOR</td>\n",
       "      <td>Norway</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.8239</td>\n",
       "      <td>1.0</td>\n",
       "      <td>F</td>\n",
       "      <td>Norway</td>\n",
       "      <td>6</td>\n",
       "      <td>2019</td>\n",
       "      <td>2021.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>FIN</td>\n",
       "      <td>Finland</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.8195</td>\n",
       "      <td>2.0</td>\n",
       "      <td>F</td>\n",
       "      <td>Finland</td>\n",
       "      <td>17</td>\n",
       "      <td>1847</td>\n",
       "      <td>1852.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>804</th>\n",
       "      <td>FIN</td>\n",
       "      <td>Finland</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.8195</td>\n",
       "      <td>2.0</td>\n",
       "      <td>M</td>\n",
       "      <td>Finland</td>\n",
       "      <td>55</td>\n",
       "      <td>535</td>\n",
       "      <td>611.0</td>\n",
       "      <td>-7</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2237</th>\n",
       "      <td>SWE</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>2008</td>\n",
       "      <td>0.8139</td>\n",
       "      <td>3.0</td>\n",
       "      <td>F</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>4</td>\n",
       "      <td>2059</td>\n",
       "      <td>2063.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.575</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Country ISO3 Country Name_x  Year   Index  gender_rank Gender  \\\n",
       "1825          NOR         Norway  2008  0.8239          1.0      M   \n",
       "1824          NOR         Norway  2008  0.8239          1.0      F   \n",
       "803           FIN        Finland  2008  0.8195          2.0      F   \n",
       "804           FIN        Finland  2008  0.8195          2.0      M   \n",
       "2237          SWE         Sweden  2008  0.8139          3.0      F   \n",
       "\n",
       "     Country Name_y  fifa_rank  Total Points  PTS  Previous Points  Prev.Pts  \\\n",
       "1825         Norway         59                526                      572.0   \n",
       "1824         Norway          6               2019                     2021.0   \n",
       "803         Finland         17               1847                     1852.0   \n",
       "804         Finland         55                535                      611.0   \n",
       "2237         Sweden          4               2059                     2063.0   \n",
       "\n",
       "     +/-      p  \n",
       "1825  -5  0.250  \n",
       "1824   0  0.600  \n",
       "803    0  0.000  \n",
       "804   -7  0.000  \n",
       "2237   0  0.575  "
      ]
     },
     "execution_count": 472,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world_cup_probailites = pd.read_csv(r'resources/world-cup-matches/world_cup_probabilities.csv')\n",
    "gender_fifa_probs_df =  pd.merge(merged_by_gender, world_cup_probailites, how='left', on=['Country Name_x', 'Gender'])\n",
    "gender_fifa_probs_df = gender_fifa_probs_df.fillna(0)\n",
    "\n",
    "gender_fifa_probs_df[gender_fifa_probs_df['Year'] == 2008].sort_values('gender_rank').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 473,
   "metadata": {},
   "outputs": [],
   "source": [
    "gender_fifa_probs_df.to_csv(r'gender-fifa-probabilities.csv', index = False)"
   ]
  }
 ],
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