Fifa19.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://www.kaggle.com/karangadiya/fifa19#data.csv\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set(style=\"darkgrid\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_raw = pd.read_csv('data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Photo</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Flag</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>...</th>\n",
       "      <th>Composure</th>\n",
       "      <th>Marking</th>\n",
       "      <th>StandingTackle</th>\n",
       "      <th>SlidingTackle</th>\n",
       "      <th>GKDiving</th>\n",
       "      <th>GKHandling</th>\n",
       "      <th>GKKicking</th>\n",
       "      <th>GKPositioning</th>\n",
       "      <th>GKReflexes</th>\n",
       "      <th>Release Clause</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>158023</td>\n",
       "      <td>L. Messi</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/158023.png</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>https://cdn.sofifa.org/flags/52.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>96.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€226.5M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>20801</td>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>33</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/20801.png</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>https://cdn.sofifa.org/flags/38.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>...</td>\n",
       "      <td>95.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€127.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>190871</td>\n",
       "      <td>Neymar Jr</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/190871.png</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>https://cdn.sofifa.org/flags/54.png</td>\n",
       "      <td>92</td>\n",
       "      <td>93</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>...</td>\n",
       "      <td>94.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€228.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>193080</td>\n",
       "      <td>De Gea</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/193080.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>91</td>\n",
       "      <td>93</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>...</td>\n",
       "      <td>68.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>€138.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>192985</td>\n",
       "      <td>K. De Bruyne</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/192985.png</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>92</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>...</td>\n",
       "      <td>88.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€196.4M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>183277</td>\n",
       "      <td>E. Hazard</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/183277.png</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>91.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€172.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>177003</td>\n",
       "      <td>L. Modrić</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/177003.png</td>\n",
       "      <td>Croatia</td>\n",
       "      <td>https://cdn.sofifa.org/flags/10.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>84.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>€137.4M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>176580</td>\n",
       "      <td>L. Suárez</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/176580.png</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>https://cdn.sofifa.org/flags/60.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>€164M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>155862</td>\n",
       "      <td>Sergio Ramos</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/155862.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>82.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€104.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>200389</td>\n",
       "      <td>J. Oblak</td>\n",
       "      <td>25</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/200389.png</td>\n",
       "      <td>Slovenia</td>\n",
       "      <td>https://cdn.sofifa.org/flags/44.png</td>\n",
       "      <td>90</td>\n",
       "      <td>93</td>\n",
       "      <td>Atlético Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>70.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>€144.5M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 89 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0      ID               Name  Age  \\\n",
       "0           0  158023           L. Messi   31   \n",
       "1           1   20801  Cristiano Ronaldo   33   \n",
       "2           2  190871          Neymar Jr   26   \n",
       "3           3  193080             De Gea   27   \n",
       "4           4  192985       K. De Bruyne   27   \n",
       "5           5  183277          E. Hazard   27   \n",
       "6           6  177003          L. Modrić   32   \n",
       "7           7  176580          L. Suárez   31   \n",
       "8           8  155862       Sergio Ramos   32   \n",
       "9           9  200389           J. Oblak   25   \n",
       "\n",
       "                                            Photo Nationality  \\\n",
       "0  https://cdn.sofifa.org/players/4/19/158023.png   Argentina   \n",
       "1   https://cdn.sofifa.org/players/4/19/20801.png    Portugal   \n",
       "2  https://cdn.sofifa.org/players/4/19/190871.png      Brazil   \n",
       "3  https://cdn.sofifa.org/players/4/19/193080.png       Spain   \n",
       "4  https://cdn.sofifa.org/players/4/19/192985.png     Belgium   \n",
       "5  https://cdn.sofifa.org/players/4/19/183277.png     Belgium   \n",
       "6  https://cdn.sofifa.org/players/4/19/177003.png     Croatia   \n",
       "7  https://cdn.sofifa.org/players/4/19/176580.png     Uruguay   \n",
       "8  https://cdn.sofifa.org/players/4/19/155862.png       Spain   \n",
       "9  https://cdn.sofifa.org/players/4/19/200389.png    Slovenia   \n",
       "\n",
       "                                  Flag  Overall  Potential  \\\n",
       "0  https://cdn.sofifa.org/flags/52.png       94         94   \n",
       "1  https://cdn.sofifa.org/flags/38.png       94         94   \n",
       "2  https://cdn.sofifa.org/flags/54.png       92         93   \n",
       "3  https://cdn.sofifa.org/flags/45.png       91         93   \n",
       "4   https://cdn.sofifa.org/flags/7.png       91         92   \n",
       "5   https://cdn.sofifa.org/flags/7.png       91         91   \n",
       "6  https://cdn.sofifa.org/flags/10.png       91         91   \n",
       "7  https://cdn.sofifa.org/flags/60.png       91         91   \n",
       "8  https://cdn.sofifa.org/flags/45.png       91         91   \n",
       "9  https://cdn.sofifa.org/flags/44.png       90         93   \n",
       "\n",
       "                  Club      ...       Composure Marking StandingTackle  \\\n",
       "0         FC Barcelona      ...            96.0    33.0           28.0   \n",
       "1             Juventus      ...            95.0    28.0           31.0   \n",
       "2  Paris Saint-Germain      ...            94.0    27.0           24.0   \n",
       "3    Manchester United      ...            68.0    15.0           21.0   \n",
       "4      Manchester City      ...            88.0    68.0           58.0   \n",
       "5              Chelsea      ...            91.0    34.0           27.0   \n",
       "6          Real Madrid      ...            84.0    60.0           76.0   \n",
       "7         FC Barcelona      ...            85.0    62.0           45.0   \n",
       "8          Real Madrid      ...            82.0    87.0           92.0   \n",
       "9      Atlético Madrid      ...            70.0    27.0           12.0   \n",
       "\n",
       "   SlidingTackle GKDiving  GKHandling  GKKicking  GKPositioning GKReflexes  \\\n",
       "0           26.0      6.0        11.0       15.0           14.0        8.0   \n",
       "1           23.0      7.0        11.0       15.0           14.0       11.0   \n",
       "2           33.0      9.0         9.0       15.0           15.0       11.0   \n",
       "3           13.0     90.0        85.0       87.0           88.0       94.0   \n",
       "4           51.0     15.0        13.0        5.0           10.0       13.0   \n",
       "5           22.0     11.0        12.0        6.0            8.0        8.0   \n",
       "6           73.0     13.0         9.0        7.0           14.0        9.0   \n",
       "7           38.0     27.0        25.0       31.0           33.0       37.0   \n",
       "8           91.0     11.0         8.0        9.0            7.0       11.0   \n",
       "9           18.0     86.0        92.0       78.0           88.0       89.0   \n",
       "\n",
       "  Release Clause  \n",
       "0        €226.5M  \n",
       "1        €127.1M  \n",
       "2        €228.1M  \n",
       "3        €138.6M  \n",
       "4        €196.4M  \n",
       "5        €172.1M  \n",
       "6        €137.4M  \n",
       "7          €164M  \n",
       "8        €104.6M  \n",
       "9        €144.5M  \n",
       "\n",
       "[10 rows x 89 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'ID', 'Name', 'Age', 'Photo', 'Nationality', 'Flag',\n",
       "       'Overall', 'Potential', 'Club', 'Club Logo', 'Value', 'Wage', 'Special',\n",
       "       'Preferred Foot', 'International Reputation', 'Weak Foot',\n",
       "       'Skill Moves', 'Work Rate', 'Body Type', 'Real Face', 'Position',\n",
       "       'Jersey Number', 'Joined', 'Loaned From', 'Contract Valid Until',\n",
       "       'Height', 'Weight', 'LS', 'ST', 'RS', 'LW', 'LF', 'CF', 'RF', 'RW',\n",
       "       'LAM', 'CAM', 'RAM', 'LM', 'LCM', 'CM', 'RCM', 'RM', 'LWB', 'LDM',\n",
       "       'CDM', 'RDM', 'RWB', 'LB', 'LCB', 'CB', 'RCB', 'RB', 'Crossing',\n",
       "       'Finishing', 'HeadingAccuracy', 'ShortPassing', 'Volleys', 'Dribbling',\n",
       "       'Curve', 'FKAccuracy', 'LongPassing', 'BallControl', 'Acceleration',\n",
       "       'SprintSpeed', 'Agility', 'Reactions', 'Balance', 'ShotPower',\n",
       "       'Jumping', 'Stamina', 'Strength', 'LongShots', 'Aggression',\n",
       "       'Interceptions', 'Positioning', 'Vision', 'Penalties', 'Composure',\n",
       "       'Marking', 'StandingTackle', 'SlidingTackle', 'GKDiving', 'GKHandling',\n",
       "       'GKKicking', 'GKPositioning', 'GKReflexes', 'Release Clause'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 18207 entries, 0 to 18206\n",
      "Data columns (total 89 columns):\n",
      "Unnamed: 0                  18207 non-null int64\n",
      "ID                          18207 non-null int64\n",
      "Name                        18207 non-null object\n",
      "Age                         18207 non-null int64\n",
      "Photo                       18207 non-null object\n",
      "Nationality                 18207 non-null object\n",
      "Flag                        18207 non-null object\n",
      "Overall                     18207 non-null int64\n",
      "Potential                   18207 non-null int64\n",
      "Club                        17966 non-null object\n",
      "Club Logo                   18207 non-null object\n",
      "Value                       18207 non-null object\n",
      "Wage                        18207 non-null object\n",
      "Special                     18207 non-null int64\n",
      "Preferred Foot              18159 non-null object\n",
      "International Reputation    18159 non-null float64\n",
      "Weak Foot                   18159 non-null float64\n",
      "Skill Moves                 18159 non-null float64\n",
      "Work Rate                   18159 non-null object\n",
      "Body Type                   18159 non-null object\n",
      "Real Face                   18159 non-null object\n",
      "Position                    18147 non-null object\n",
      "Jersey Number               18147 non-null float64\n",
      "Joined                      16654 non-null object\n",
      "Loaned From                 1264 non-null object\n",
      "Contract Valid Until        17918 non-null object\n",
      "Height                      18159 non-null object\n",
      "Weight                      18159 non-null object\n",
      "LS                          16122 non-null object\n",
      "ST                          16122 non-null object\n",
      "RS                          16122 non-null object\n",
      "LW                          16122 non-null object\n",
      "LF                          16122 non-null object\n",
      "CF                          16122 non-null object\n",
      "RF                          16122 non-null object\n",
      "RW                          16122 non-null object\n",
      "LAM                         16122 non-null object\n",
      "CAM                         16122 non-null object\n",
      "RAM                         16122 non-null object\n",
      "LM                          16122 non-null object\n",
      "LCM                         16122 non-null object\n",
      "CM                          16122 non-null object\n",
      "RCM                         16122 non-null object\n",
      "RM                          16122 non-null object\n",
      "LWB                         16122 non-null object\n",
      "LDM                         16122 non-null object\n",
      "CDM                         16122 non-null object\n",
      "RDM                         16122 non-null object\n",
      "RWB                         16122 non-null object\n",
      "LB                          16122 non-null object\n",
      "LCB                         16122 non-null object\n",
      "CB                          16122 non-null object\n",
      "RCB                         16122 non-null object\n",
      "RB                          16122 non-null object\n",
      "Crossing                    18159 non-null float64\n",
      "Finishing                   18159 non-null float64\n",
      "HeadingAccuracy             18159 non-null float64\n",
      "ShortPassing                18159 non-null float64\n",
      "Volleys                     18159 non-null float64\n",
      "Dribbling                   18159 non-null float64\n",
      "Curve                       18159 non-null float64\n",
      "FKAccuracy                  18159 non-null float64\n",
      "LongPassing                 18159 non-null float64\n",
      "BallControl                 18159 non-null float64\n",
      "Acceleration                18159 non-null float64\n",
      "SprintSpeed                 18159 non-null float64\n",
      "Agility                     18159 non-null float64\n",
      "Reactions                   18159 non-null float64\n",
      "Balance                     18159 non-null float64\n",
      "ShotPower                   18159 non-null float64\n",
      "Jumping                     18159 non-null float64\n",
      "Stamina                     18159 non-null float64\n",
      "Strength                    18159 non-null float64\n",
      "LongShots                   18159 non-null float64\n",
      "Aggression                  18159 non-null float64\n",
      "Interceptions               18159 non-null float64\n",
      "Positioning                 18159 non-null float64\n",
      "Vision                      18159 non-null float64\n",
      "Penalties                   18159 non-null float64\n",
      "Composure                   18159 non-null float64\n",
      "Marking                     18159 non-null float64\n",
      "StandingTackle              18159 non-null float64\n",
      "SlidingTackle               18159 non-null float64\n",
      "GKDiving                    18159 non-null float64\n",
      "GKHandling                  18159 non-null float64\n",
      "GKKicking                   18159 non-null float64\n",
      "GKPositioning               18159 non-null float64\n",
      "GKReflexes                  18159 non-null float64\n",
      "Release Clause              16643 non-null object\n",
      "dtypes: float64(38), int64(6), object(45)\n",
      "memory usage: 12.4+ MB\n"
     ]
    }
   ],
   "source": [
    "data_raw.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18207, 89)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.isnull().any().any() # If true --> there are null values in the DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0                  False\n",
       "ID                          False\n",
       "Name                        False\n",
       "Age                         False\n",
       "Photo                       False\n",
       "Nationality                 False\n",
       "Flag                        False\n",
       "Overall                     False\n",
       "Potential                   False\n",
       "Club                         True\n",
       "Club Logo                   False\n",
       "Value                       False\n",
       "Wage                        False\n",
       "Special                     False\n",
       "Preferred Foot               True\n",
       "International Reputation     True\n",
       "Weak Foot                    True\n",
       "Skill Moves                  True\n",
       "Work Rate                    True\n",
       "Body Type                    True\n",
       "Real Face                    True\n",
       "Position                     True\n",
       "Jersey Number                True\n",
       "Joined                       True\n",
       "Loaned From                  True\n",
       "Contract Valid Until         True\n",
       "Height                       True\n",
       "Weight                       True\n",
       "LS                           True\n",
       "ST                           True\n",
       "                            ...  \n",
       "Dribbling                    True\n",
       "Curve                        True\n",
       "FKAccuracy                   True\n",
       "LongPassing                  True\n",
       "BallControl                  True\n",
       "Acceleration                 True\n",
       "SprintSpeed                  True\n",
       "Agility                      True\n",
       "Reactions                    True\n",
       "Balance                      True\n",
       "ShotPower                    True\n",
       "Jumping                      True\n",
       "Stamina                      True\n",
       "Strength                     True\n",
       "LongShots                    True\n",
       "Aggression                   True\n",
       "Interceptions                True\n",
       "Positioning                  True\n",
       "Vision                       True\n",
       "Penalties                    True\n",
       "Composure                    True\n",
       "Marking                      True\n",
       "StandingTackle               True\n",
       "SlidingTackle                True\n",
       "GKDiving                     True\n",
       "GKHandling                   True\n",
       "GKKicking                    True\n",
       "GKPositioning                True\n",
       "GKReflexes                   True\n",
       "Release Clause               True\n",
       "Length: 89, dtype: bool"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.isnull().any() # Get the columns having NULL/nan values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "76984"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.isnull().sum().sum() # get total number of null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0                      0\n",
       "ID                              0\n",
       "Name                            0\n",
       "Age                             0\n",
       "Photo                           0\n",
       "Nationality                     0\n",
       "Flag                            0\n",
       "Overall                         0\n",
       "Potential                       0\n",
       "Club                          241\n",
       "Club Logo                       0\n",
       "Value                           0\n",
       "Wage                            0\n",
       "Special                         0\n",
       "Preferred Foot                 48\n",
       "International Reputation       48\n",
       "Weak Foot                      48\n",
       "Skill Moves                    48\n",
       "Work Rate                      48\n",
       "Body Type                      48\n",
       "Real Face                      48\n",
       "Position                       60\n",
       "Jersey Number                  60\n",
       "Joined                       1553\n",
       "Loaned From                 16943\n",
       "Contract Valid Until          289\n",
       "Height                         48\n",
       "Weight                         48\n",
       "LS                           2085\n",
       "ST                           2085\n",
       "                            ...  \n",
       "Dribbling                      48\n",
       "Curve                          48\n",
       "FKAccuracy                     48\n",
       "LongPassing                    48\n",
       "BallControl                    48\n",
       "Acceleration                   48\n",
       "SprintSpeed                    48\n",
       "Agility                        48\n",
       "Reactions                      48\n",
       "Balance                        48\n",
       "ShotPower                      48\n",
       "Jumping                        48\n",
       "Stamina                        48\n",
       "Strength                       48\n",
       "LongShots                      48\n",
       "Aggression                     48\n",
       "Interceptions                  48\n",
       "Positioning                    48\n",
       "Vision                         48\n",
       "Penalties                      48\n",
       "Composure                      48\n",
       "Marking                        48\n",
       "StandingTackle                 48\n",
       "SlidingTackle                  48\n",
       "GKDiving                       48\n",
       "GKHandling                     48\n",
       "GKKicking                      48\n",
       "GKPositioning                  48\n",
       "GKReflexes                     48\n",
       "Release Clause               1564\n",
       "Length: 89, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.isnull().sum() # get the number of null values in various columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Photo</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Flag</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>...</th>\n",
       "      <th>Composure</th>\n",
       "      <th>Marking</th>\n",
       "      <th>StandingTackle</th>\n",
       "      <th>SlidingTackle</th>\n",
       "      <th>GKDiving</th>\n",
       "      <th>GKHandling</th>\n",
       "      <th>GKKicking</th>\n",
       "      <th>GKPositioning</th>\n",
       "      <th>GKReflexes</th>\n",
       "      <th>Release Clause</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 89 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Unnamed: 0, ID, Name, Age, Photo, Nationality, Flag, Overall, Potential, Club, Club Logo, Value, Wage, Special, Preferred Foot, International Reputation, Weak Foot, Skill Moves, Work Rate, Body Type, Real Face, Position, Jersey Number, Joined, Loaned From, Contract Valid Until, Height, Weight, LS, ST, RS, LW, LF, CF, RF, RW, LAM, CAM, RAM, LM, LCM, CM, RCM, RM, LWB, LDM, CDM, RDM, RWB, LB, LCB, CB, RCB, RB, Crossing, Finishing, HeadingAccuracy, ShortPassing, Volleys, Dribbling, Curve, FKAccuracy, LongPassing, BallControl, Acceleration, SprintSpeed, Agility, Reactions, Balance, ShotPower, Jumping, Stamina, Strength, LongShots, Aggression, Interceptions, Positioning, Vision, Penalties, Composure, Marking, StandingTackle, SlidingTackle, GKDiving, GKHandling, GKKicking, GKPositioning, GKReflexes, Release Clause]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 89 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nan_rows = data_raw[data_raw['Age'].isnull()] #get the rows having null values in the column 'Age'\n",
    "nan_rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Photo</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Flag</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>...</th>\n",
       "      <th>Composure</th>\n",
       "      <th>Marking</th>\n",
       "      <th>StandingTackle</th>\n",
       "      <th>SlidingTackle</th>\n",
       "      <th>GKDiving</th>\n",
       "      <th>GKHandling</th>\n",
       "      <th>GKKicking</th>\n",
       "      <th>GKPositioning</th>\n",
       "      <th>GKReflexes</th>\n",
       "      <th>Release Clause</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>158023</td>\n",
       "      <td>L. Messi</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/158023.png</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>https://cdn.sofifa.org/flags/52.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>96.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€226.5M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>20801</td>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>33</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/20801.png</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>https://cdn.sofifa.org/flags/38.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>...</td>\n",
       "      <td>95.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€127.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>190871</td>\n",
       "      <td>Neymar Jr</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/190871.png</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>https://cdn.sofifa.org/flags/54.png</td>\n",
       "      <td>92</td>\n",
       "      <td>93</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>...</td>\n",
       "      <td>94.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€228.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>193080</td>\n",
       "      <td>De Gea</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/193080.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>91</td>\n",
       "      <td>93</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>...</td>\n",
       "      <td>68.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>€138.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>192985</td>\n",
       "      <td>K. De Bruyne</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/192985.png</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>92</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>...</td>\n",
       "      <td>88.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€196.4M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>183277</td>\n",
       "      <td>E. Hazard</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/183277.png</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>91.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€172.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>177003</td>\n",
       "      <td>L. Modrić</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/177003.png</td>\n",
       "      <td>Croatia</td>\n",
       "      <td>https://cdn.sofifa.org/flags/10.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>84.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>€137.4M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>176580</td>\n",
       "      <td>L. Suárez</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/176580.png</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>https://cdn.sofifa.org/flags/60.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>€164M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>155862</td>\n",
       "      <td>Sergio Ramos</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/155862.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>82.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€104.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>200389</td>\n",
       "      <td>J. Oblak</td>\n",
       "      <td>25</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/200389.png</td>\n",
       "      <td>Slovenia</td>\n",
       "      <td>https://cdn.sofifa.org/flags/44.png</td>\n",
       "      <td>90</td>\n",
       "      <td>93</td>\n",
       "      <td>Atlético Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>70.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>€144.5M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>188545</td>\n",
       "      <td>R. Lewandowski</td>\n",
       "      <td>29</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/188545.png</td>\n",
       "      <td>Poland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/37.png</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>FC Bayern München</td>\n",
       "      <td>...</td>\n",
       "      <td>86.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>€127.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>182521</td>\n",
       "      <td>T. Kroos</td>\n",
       "      <td>28</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/182521.png</td>\n",
       "      <td>Germany</td>\n",
       "      <td>https://cdn.sofifa.org/flags/21.png</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>€156.8M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>182493</td>\n",
       "      <td>D. Godín</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/182493.png</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>https://cdn.sofifa.org/flags/60.png</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>Atlético Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>82.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>€90.2M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>168542</td>\n",
       "      <td>David Silva</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/168542.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>...</td>\n",
       "      <td>93.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>€111M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>215914</td>\n",
       "      <td>N. Kanté</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/215914.png</td>\n",
       "      <td>France</td>\n",
       "      <td>https://cdn.sofifa.org/flags/18.png</td>\n",
       "      <td>89</td>\n",
       "      <td>90</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>€121.3M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>211110</td>\n",
       "      <td>P. Dybala</td>\n",
       "      <td>24</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/211110.png</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>https://cdn.sofifa.org/flags/52.png</td>\n",
       "      <td>89</td>\n",
       "      <td>94</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>...</td>\n",
       "      <td>84.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€153.5M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>202126</td>\n",
       "      <td>H. Kane</td>\n",
       "      <td>24</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/202126.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>89</td>\n",
       "      <td>91</td>\n",
       "      <td>Tottenham Hotspur</td>\n",
       "      <td>...</td>\n",
       "      <td>89.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€160.7M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>194765</td>\n",
       "      <td>A. Griezmann</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/194765.png</td>\n",
       "      <td>France</td>\n",
       "      <td>https://cdn.sofifa.org/flags/18.png</td>\n",
       "      <td>89</td>\n",
       "      <td>90</td>\n",
       "      <td>Atlético Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>87.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>€165.8M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>192448</td>\n",
       "      <td>M. ter Stegen</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/192448.png</td>\n",
       "      <td>Germany</td>\n",
       "      <td>https://cdn.sofifa.org/flags/21.png</td>\n",
       "      <td>89</td>\n",
       "      <td>92</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>69.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>€123.3M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>192119</td>\n",
       "      <td>T. Courtois</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/192119.png</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>89</td>\n",
       "      <td>90</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>66.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>€113.7M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>189511</td>\n",
       "      <td>Sergio Busquets</td>\n",
       "      <td>29</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/189511.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>89</td>\n",
       "      <td>89</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€105.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>179813</td>\n",
       "      <td>E. Cavani</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/179813.png</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>https://cdn.sofifa.org/flags/60.png</td>\n",
       "      <td>89</td>\n",
       "      <td>89</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>...</td>\n",
       "      <td>82.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>€111M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>167495</td>\n",
       "      <td>M. Neuer</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/167495.png</td>\n",
       "      <td>Germany</td>\n",
       "      <td>https://cdn.sofifa.org/flags/21.png</td>\n",
       "      <td>89</td>\n",
       "      <td>89</td>\n",
       "      <td>FC Bayern München</td>\n",
       "      <td>...</td>\n",
       "      <td>70.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>€62.7M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>153079</td>\n",
       "      <td>S. Agüero</td>\n",
       "      <td>30</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/153079.png</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>https://cdn.sofifa.org/flags/52.png</td>\n",
       "      <td>89</td>\n",
       "      <td>89</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>€119.3M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>138956</td>\n",
       "      <td>G. Chiellini</td>\n",
       "      <td>33</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/138956.png</td>\n",
       "      <td>Italy</td>\n",
       "      <td>https://cdn.sofifa.org/flags/27.png</td>\n",
       "      <td>89</td>\n",
       "      <td>89</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>...</td>\n",
       "      <td>84.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>€44.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>231747</td>\n",
       "      <td>K. Mbappé</td>\n",
       "      <td>19</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/231747.png</td>\n",
       "      <td>France</td>\n",
       "      <td>https://cdn.sofifa.org/flags/18.png</td>\n",
       "      <td>88</td>\n",
       "      <td>95</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>...</td>\n",
       "      <td>86.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>€166.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>209331</td>\n",
       "      <td>M. Salah</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/209331.png</td>\n",
       "      <td>Egypt</td>\n",
       "      <td>https://cdn.sofifa.org/flags/111.png</td>\n",
       "      <td>88</td>\n",
       "      <td>89</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>...</td>\n",
       "      <td>91.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>€137.3M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>200145</td>\n",
       "      <td>Casemiro</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/200145.png</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>https://cdn.sofifa.org/flags/54.png</td>\n",
       "      <td>88</td>\n",
       "      <td>90</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>...</td>\n",
       "      <td>84.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>€126.4M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>198710</td>\n",
       "      <td>J. Rodríguez</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/198710.png</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>https://cdn.sofifa.org/flags/56.png</td>\n",
       "      <td>88</td>\n",
       "      <td>89</td>\n",
       "      <td>FC Bayern München</td>\n",
       "      <td>...</td>\n",
       "      <td>87.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>198219</td>\n",
       "      <td>L. Insigne</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/198219.png</td>\n",
       "      <td>Italy</td>\n",
       "      <td>https://cdn.sofifa.org/flags/27.png</td>\n",
       "      <td>88</td>\n",
       "      <td>88</td>\n",
       "      <td>Napoli</td>\n",
       "      <td>...</td>\n",
       "      <td>83.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>€105.4M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18177</th>\n",
       "      <td>18177</td>\n",
       "      <td>238550</td>\n",
       "      <td>R. Roache</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/238550.png</td>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/25.png</td>\n",
       "      <td>48</td>\n",
       "      <td>69</td>\n",
       "      <td>Blackpool</td>\n",
       "      <td>...</td>\n",
       "      <td>49.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>€193K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18178</th>\n",
       "      <td>18178</td>\n",
       "      <td>243158</td>\n",
       "      <td>L. Wahlstedt</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/243158.png</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>https://cdn.sofifa.org/flags/46.png</td>\n",
       "      <td>48</td>\n",
       "      <td>65</td>\n",
       "      <td>Dalkurd FF</td>\n",
       "      <td>...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>€94K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18179</th>\n",
       "      <td>18179</td>\n",
       "      <td>246243</td>\n",
       "      <td>J. Williams</td>\n",
       "      <td>17</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/246243.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>48</td>\n",
       "      <td>64</td>\n",
       "      <td>Northampton Town</td>\n",
       "      <td>...</td>\n",
       "      <td>37.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€119K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18180</th>\n",
       "      <td>18180</td>\n",
       "      <td>221669</td>\n",
       "      <td>M. Hurst</td>\n",
       "      <td>22</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/221669.png</td>\n",
       "      <td>Scotland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/42.png</td>\n",
       "      <td>48</td>\n",
       "      <td>58</td>\n",
       "      <td>St. Johnstone FC</td>\n",
       "      <td>...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>€78K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18181</th>\n",
       "      <td>18181</td>\n",
       "      <td>245734</td>\n",
       "      <td>C. Maher</td>\n",
       "      <td>17</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/245734.png</td>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/25.png</td>\n",
       "      <td>48</td>\n",
       "      <td>66</td>\n",
       "      <td>Bray Wanderers</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>€109K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18182</th>\n",
       "      <td>18182</td>\n",
       "      <td>246001</td>\n",
       "      <td>Y. Góez</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/246001.png</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>https://cdn.sofifa.org/flags/56.png</td>\n",
       "      <td>48</td>\n",
       "      <td>65</td>\n",
       "      <td>Atlético Nacional</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>€101K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18183</th>\n",
       "      <td>18183</td>\n",
       "      <td>53748</td>\n",
       "      <td>K. Pilkington</td>\n",
       "      <td>44</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/53748.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>Cambridge United</td>\n",
       "      <td>...</td>\n",
       "      <td>56.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18184</th>\n",
       "      <td>18184</td>\n",
       "      <td>241657</td>\n",
       "      <td>D. Horton</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/241657.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>48</td>\n",
       "      <td>55</td>\n",
       "      <td>Lincoln City</td>\n",
       "      <td>...</td>\n",
       "      <td>42.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>€78K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18185</th>\n",
       "      <td>18185</td>\n",
       "      <td>243961</td>\n",
       "      <td>E. Tweed</td>\n",
       "      <td>19</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/243961.png</td>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/25.png</td>\n",
       "      <td>48</td>\n",
       "      <td>59</td>\n",
       "      <td>Derry City</td>\n",
       "      <td>...</td>\n",
       "      <td>43.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€88K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18186</th>\n",
       "      <td>18186</td>\n",
       "      <td>240917</td>\n",
       "      <td>Zhang Yufeng</td>\n",
       "      <td>20</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/240917.png</td>\n",
       "      <td>China PR</td>\n",
       "      <td>https://cdn.sofifa.org/flags/155.png</td>\n",
       "      <td>47</td>\n",
       "      <td>64</td>\n",
       "      <td>Beijing Renhe FC</td>\n",
       "      <td>...</td>\n",
       "      <td>39.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€167K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18187</th>\n",
       "      <td>18187</td>\n",
       "      <td>240158</td>\n",
       "      <td>C. Ehlich</td>\n",
       "      <td>19</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/240158.png</td>\n",
       "      <td>Germany</td>\n",
       "      <td>https://cdn.sofifa.org/flags/21.png</td>\n",
       "      <td>47</td>\n",
       "      <td>59</td>\n",
       "      <td>SpVgg Unterhaching</td>\n",
       "      <td>...</td>\n",
       "      <td>47.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>€66K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18188</th>\n",
       "      <td>18188</td>\n",
       "      <td>240927</td>\n",
       "      <td>L. Collins</td>\n",
       "      <td>17</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/240927.png</td>\n",
       "      <td>Wales</td>\n",
       "      <td>https://cdn.sofifa.org/flags/50.png</td>\n",
       "      <td>47</td>\n",
       "      <td>62</td>\n",
       "      <td>Newport County</td>\n",
       "      <td>...</td>\n",
       "      <td>46.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>€143K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18189</th>\n",
       "      <td>18189</td>\n",
       "      <td>240160</td>\n",
       "      <td>A. Kaltner</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/240160.png</td>\n",
       "      <td>Germany</td>\n",
       "      <td>https://cdn.sofifa.org/flags/21.png</td>\n",
       "      <td>47</td>\n",
       "      <td>61</td>\n",
       "      <td>SpVgg Unterhaching</td>\n",
       "      <td>...</td>\n",
       "      <td>37.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€125K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18190</th>\n",
       "      <td>18190</td>\n",
       "      <td>245569</td>\n",
       "      <td>L. Watkins</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/245569.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>47</td>\n",
       "      <td>67</td>\n",
       "      <td>Cambridge United</td>\n",
       "      <td>...</td>\n",
       "      <td>46.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€165K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18191</th>\n",
       "      <td>18191</td>\n",
       "      <td>245570</td>\n",
       "      <td>J. Norville-Williams</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/245570.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>47</td>\n",
       "      <td>65</td>\n",
       "      <td>Cambridge United</td>\n",
       "      <td>...</td>\n",
       "      <td>36.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>€119K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18192</th>\n",
       "      <td>18192</td>\n",
       "      <td>245571</td>\n",
       "      <td>S. Squire</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/245571.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>47</td>\n",
       "      <td>64</td>\n",
       "      <td>Cambridge United</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€119K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18193</th>\n",
       "      <td>18193</td>\n",
       "      <td>244823</td>\n",
       "      <td>N. Fuentes</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/244823.png</td>\n",
       "      <td>Chile</td>\n",
       "      <td>https://cdn.sofifa.org/flags/55.png</td>\n",
       "      <td>47</td>\n",
       "      <td>64</td>\n",
       "      <td>Unión Española</td>\n",
       "      <td>...</td>\n",
       "      <td>32.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€99K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18194</th>\n",
       "      <td>18194</td>\n",
       "      <td>245862</td>\n",
       "      <td>J. Milli</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/245862.png</td>\n",
       "      <td>Italy</td>\n",
       "      <td>https://cdn.sofifa.org/flags/27.png</td>\n",
       "      <td>47</td>\n",
       "      <td>65</td>\n",
       "      <td>Lecce</td>\n",
       "      <td>...</td>\n",
       "      <td>23.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>€109K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18195</th>\n",
       "      <td>18195</td>\n",
       "      <td>243582</td>\n",
       "      <td>S. Griffin</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/243582.png</td>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/25.png</td>\n",
       "      <td>47</td>\n",
       "      <td>67</td>\n",
       "      <td>Waterford FC</td>\n",
       "      <td>...</td>\n",
       "      <td>41.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€153K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18196</th>\n",
       "      <td>18196</td>\n",
       "      <td>238477</td>\n",
       "      <td>K. Fujikawa</td>\n",
       "      <td>19</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/238477.png</td>\n",
       "      <td>Japan</td>\n",
       "      <td>https://cdn.sofifa.org/flags/163.png</td>\n",
       "      <td>47</td>\n",
       "      <td>61</td>\n",
       "      <td>Júbilo Iwata</td>\n",
       "      <td>...</td>\n",
       "      <td>35.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€113K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18197</th>\n",
       "      <td>18197</td>\n",
       "      <td>246167</td>\n",
       "      <td>D. Holland</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/246167.png</td>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/25.png</td>\n",
       "      <td>47</td>\n",
       "      <td>61</td>\n",
       "      <td>Cork City</td>\n",
       "      <td>...</td>\n",
       "      <td>52.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>€88K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18198</th>\n",
       "      <td>18198</td>\n",
       "      <td>242844</td>\n",
       "      <td>J. Livesey</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/242844.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>47</td>\n",
       "      <td>70</td>\n",
       "      <td>Burton Albion</td>\n",
       "      <td>...</td>\n",
       "      <td>34.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>€165K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18199</th>\n",
       "      <td>18199</td>\n",
       "      <td>244677</td>\n",
       "      <td>M. Baldisimo</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/244677.png</td>\n",
       "      <td>Canada</td>\n",
       "      <td>https://cdn.sofifa.org/flags/70.png</td>\n",
       "      <td>47</td>\n",
       "      <td>69</td>\n",
       "      <td>Vancouver Whitecaps FC</td>\n",
       "      <td>...</td>\n",
       "      <td>40.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>€175K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18200</th>\n",
       "      <td>18200</td>\n",
       "      <td>231381</td>\n",
       "      <td>J. Young</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/231381.png</td>\n",
       "      <td>Scotland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/42.png</td>\n",
       "      <td>47</td>\n",
       "      <td>62</td>\n",
       "      <td>Swindon Town</td>\n",
       "      <td>...</td>\n",
       "      <td>50.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€143K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18201</th>\n",
       "      <td>18201</td>\n",
       "      <td>243413</td>\n",
       "      <td>D. Walsh</td>\n",
       "      <td>18</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/243413.png</td>\n",
       "      <td>Republic of Ireland</td>\n",
       "      <td>https://cdn.sofifa.org/flags/25.png</td>\n",
       "      <td>47</td>\n",
       "      <td>68</td>\n",
       "      <td>Waterford FC</td>\n",
       "      <td>...</td>\n",
       "      <td>43.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€153K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18202</th>\n",
       "      <td>18202</td>\n",
       "      <td>238813</td>\n",
       "      <td>J. Lundstram</td>\n",
       "      <td>19</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/238813.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>47</td>\n",
       "      <td>65</td>\n",
       "      <td>Crewe Alexandra</td>\n",
       "      <td>...</td>\n",
       "      <td>45.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>€143K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18203</th>\n",
       "      <td>18203</td>\n",
       "      <td>243165</td>\n",
       "      <td>N. Christoffersson</td>\n",
       "      <td>19</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/243165.png</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>https://cdn.sofifa.org/flags/46.png</td>\n",
       "      <td>47</td>\n",
       "      <td>63</td>\n",
       "      <td>Trelleborgs FF</td>\n",
       "      <td>...</td>\n",
       "      <td>42.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>€113K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18204</th>\n",
       "      <td>18204</td>\n",
       "      <td>241638</td>\n",
       "      <td>B. Worman</td>\n",
       "      <td>16</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/241638.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>47</td>\n",
       "      <td>67</td>\n",
       "      <td>Cambridge United</td>\n",
       "      <td>...</td>\n",
       "      <td>41.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€165K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18205</th>\n",
       "      <td>18205</td>\n",
       "      <td>246268</td>\n",
       "      <td>D. Walker-Rice</td>\n",
       "      <td>17</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/246268.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>47</td>\n",
       "      <td>66</td>\n",
       "      <td>Tranmere Rovers</td>\n",
       "      <td>...</td>\n",
       "      <td>46.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>€143K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18206</th>\n",
       "      <td>18206</td>\n",
       "      <td>246269</td>\n",
       "      <td>G. Nugent</td>\n",
       "      <td>16</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/246269.png</td>\n",
       "      <td>England</td>\n",
       "      <td>https://cdn.sofifa.org/flags/14.png</td>\n",
       "      <td>46</td>\n",
       "      <td>66</td>\n",
       "      <td>Tranmere Rovers</td>\n",
       "      <td>...</td>\n",
       "      <td>43.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>€165K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18207 rows × 89 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0      ID                  Name  Age  \\\n",
       "0               0  158023              L. Messi   31   \n",
       "1               1   20801     Cristiano Ronaldo   33   \n",
       "2               2  190871             Neymar Jr   26   \n",
       "3               3  193080                De Gea   27   \n",
       "4               4  192985          K. De Bruyne   27   \n",
       "5               5  183277             E. Hazard   27   \n",
       "6               6  177003             L. Modrić   32   \n",
       "7               7  176580             L. Suárez   31   \n",
       "8               8  155862          Sergio Ramos   32   \n",
       "9               9  200389              J. Oblak   25   \n",
       "10             10  188545        R. Lewandowski   29   \n",
       "11             11  182521              T. Kroos   28   \n",
       "12             12  182493              D. Godín   32   \n",
       "13             13  168542           David Silva   32   \n",
       "14             14  215914              N. Kanté   27   \n",
       "15             15  211110             P. Dybala   24   \n",
       "16             16  202126               H. Kane   24   \n",
       "17             17  194765          A. Griezmann   27   \n",
       "18             18  192448         M. ter Stegen   26   \n",
       "19             19  192119           T. Courtois   26   \n",
       "20             20  189511       Sergio Busquets   29   \n",
       "21             21  179813             E. Cavani   31   \n",
       "22             22  167495              M. Neuer   32   \n",
       "23             23  153079             S. Agüero   30   \n",
       "24             24  138956          G. Chiellini   33   \n",
       "25             25  231747             K. Mbappé   19   \n",
       "26             26  209331              M. Salah   26   \n",
       "27             27  200145              Casemiro   26   \n",
       "28             28  198710          J. Rodríguez   26   \n",
       "29             29  198219            L. Insigne   27   \n",
       "...           ...     ...                   ...  ...   \n",
       "18177       18177  238550             R. Roache   18   \n",
       "18178       18178  243158          L. Wahlstedt   18   \n",
       "18179       18179  246243           J. Williams   17   \n",
       "18180       18180  221669              M. Hurst   22   \n",
       "18181       18181  245734              C. Maher   17   \n",
       "18182       18182  246001               Y. Góez   18   \n",
       "18183       18183   53748         K. Pilkington   44   \n",
       "18184       18184  241657             D. Horton   18   \n",
       "18185       18185  243961              E. Tweed   19   \n",
       "18186       18186  240917          Zhang Yufeng   20   \n",
       "18187       18187  240158             C. Ehlich   19   \n",
       "18188       18188  240927            L. Collins   17   \n",
       "18189       18189  240160            A. Kaltner   18   \n",
       "18190       18190  245569            L. Watkins   18   \n",
       "18191       18191  245570  J. Norville-Williams   18   \n",
       "18192       18192  245571             S. Squire   18   \n",
       "18193       18193  244823            N. Fuentes   18   \n",
       "18194       18194  245862              J. Milli   18   \n",
       "18195       18195  243582            S. Griffin   18   \n",
       "18196       18196  238477           K. Fujikawa   19   \n",
       "18197       18197  246167            D. Holland   18   \n",
       "18198       18198  242844            J. Livesey   18   \n",
       "18199       18199  244677          M. Baldisimo   18   \n",
       "18200       18200  231381              J. Young   18   \n",
       "18201       18201  243413              D. Walsh   18   \n",
       "18202       18202  238813          J. Lundstram   19   \n",
       "18203       18203  243165    N. Christoffersson   19   \n",
       "18204       18204  241638             B. Worman   16   \n",
       "18205       18205  246268        D. Walker-Rice   17   \n",
       "18206       18206  246269             G. Nugent   16   \n",
       "\n",
       "                                                Photo          Nationality  \\\n",
       "0      https://cdn.sofifa.org/players/4/19/158023.png            Argentina   \n",
       "1       https://cdn.sofifa.org/players/4/19/20801.png             Portugal   \n",
       "2      https://cdn.sofifa.org/players/4/19/190871.png               Brazil   \n",
       "3      https://cdn.sofifa.org/players/4/19/193080.png                Spain   \n",
       "4      https://cdn.sofifa.org/players/4/19/192985.png              Belgium   \n",
       "5      https://cdn.sofifa.org/players/4/19/183277.png              Belgium   \n",
       "6      https://cdn.sofifa.org/players/4/19/177003.png              Croatia   \n",
       "7      https://cdn.sofifa.org/players/4/19/176580.png              Uruguay   \n",
       "8      https://cdn.sofifa.org/players/4/19/155862.png                Spain   \n",
       "9      https://cdn.sofifa.org/players/4/19/200389.png             Slovenia   \n",
       "10     https://cdn.sofifa.org/players/4/19/188545.png               Poland   \n",
       "11     https://cdn.sofifa.org/players/4/19/182521.png              Germany   \n",
       "12     https://cdn.sofifa.org/players/4/19/182493.png              Uruguay   \n",
       "13     https://cdn.sofifa.org/players/4/19/168542.png                Spain   \n",
       "14     https://cdn.sofifa.org/players/4/19/215914.png               France   \n",
       "15     https://cdn.sofifa.org/players/4/19/211110.png            Argentina   \n",
       "16     https://cdn.sofifa.org/players/4/19/202126.png              England   \n",
       "17     https://cdn.sofifa.org/players/4/19/194765.png               France   \n",
       "18     https://cdn.sofifa.org/players/4/19/192448.png              Germany   \n",
       "19     https://cdn.sofifa.org/players/4/19/192119.png              Belgium   \n",
       "20     https://cdn.sofifa.org/players/4/19/189511.png                Spain   \n",
       "21     https://cdn.sofifa.org/players/4/19/179813.png              Uruguay   \n",
       "22     https://cdn.sofifa.org/players/4/19/167495.png              Germany   \n",
       "23     https://cdn.sofifa.org/players/4/19/153079.png            Argentina   \n",
       "24     https://cdn.sofifa.org/players/4/19/138956.png                Italy   \n",
       "25     https://cdn.sofifa.org/players/4/19/231747.png               France   \n",
       "26     https://cdn.sofifa.org/players/4/19/209331.png                Egypt   \n",
       "27     https://cdn.sofifa.org/players/4/19/200145.png               Brazil   \n",
       "28     https://cdn.sofifa.org/players/4/19/198710.png             Colombia   \n",
       "29     https://cdn.sofifa.org/players/4/19/198219.png                Italy   \n",
       "...                                               ...                  ...   \n",
       "18177  https://cdn.sofifa.org/players/4/19/238550.png  Republic of Ireland   \n",
       "18178  https://cdn.sofifa.org/players/4/19/243158.png               Sweden   \n",
       "18179  https://cdn.sofifa.org/players/4/19/246243.png              England   \n",
       "18180  https://cdn.sofifa.org/players/4/19/221669.png             Scotland   \n",
       "18181  https://cdn.sofifa.org/players/4/19/245734.png  Republic of Ireland   \n",
       "18182  https://cdn.sofifa.org/players/4/19/246001.png             Colombia   \n",
       "18183   https://cdn.sofifa.org/players/4/19/53748.png              England   \n",
       "18184  https://cdn.sofifa.org/players/4/19/241657.png              England   \n",
       "18185  https://cdn.sofifa.org/players/4/19/243961.png  Republic of Ireland   \n",
       "18186  https://cdn.sofifa.org/players/4/19/240917.png             China PR   \n",
       "18187  https://cdn.sofifa.org/players/4/19/240158.png              Germany   \n",
       "18188  https://cdn.sofifa.org/players/4/19/240927.png                Wales   \n",
       "18189  https://cdn.sofifa.org/players/4/19/240160.png              Germany   \n",
       "18190  https://cdn.sofifa.org/players/4/19/245569.png              England   \n",
       "18191  https://cdn.sofifa.org/players/4/19/245570.png              England   \n",
       "18192  https://cdn.sofifa.org/players/4/19/245571.png              England   \n",
       "18193  https://cdn.sofifa.org/players/4/19/244823.png                Chile   \n",
       "18194  https://cdn.sofifa.org/players/4/19/245862.png                Italy   \n",
       "18195  https://cdn.sofifa.org/players/4/19/243582.png  Republic of Ireland   \n",
       "18196  https://cdn.sofifa.org/players/4/19/238477.png                Japan   \n",
       "18197  https://cdn.sofifa.org/players/4/19/246167.png  Republic of Ireland   \n",
       "18198  https://cdn.sofifa.org/players/4/19/242844.png              England   \n",
       "18199  https://cdn.sofifa.org/players/4/19/244677.png               Canada   \n",
       "18200  https://cdn.sofifa.org/players/4/19/231381.png             Scotland   \n",
       "18201  https://cdn.sofifa.org/players/4/19/243413.png  Republic of Ireland   \n",
       "18202  https://cdn.sofifa.org/players/4/19/238813.png              England   \n",
       "18203  https://cdn.sofifa.org/players/4/19/243165.png               Sweden   \n",
       "18204  https://cdn.sofifa.org/players/4/19/241638.png              England   \n",
       "18205  https://cdn.sofifa.org/players/4/19/246268.png              England   \n",
       "18206  https://cdn.sofifa.org/players/4/19/246269.png              England   \n",
       "\n",
       "                                       Flag  Overall  Potential  \\\n",
       "0       https://cdn.sofifa.org/flags/52.png       94         94   \n",
       "1       https://cdn.sofifa.org/flags/38.png       94         94   \n",
       "2       https://cdn.sofifa.org/flags/54.png       92         93   \n",
       "3       https://cdn.sofifa.org/flags/45.png       91         93   \n",
       "4        https://cdn.sofifa.org/flags/7.png       91         92   \n",
       "5        https://cdn.sofifa.org/flags/7.png       91         91   \n",
       "6       https://cdn.sofifa.org/flags/10.png       91         91   \n",
       "7       https://cdn.sofifa.org/flags/60.png       91         91   \n",
       "8       https://cdn.sofifa.org/flags/45.png       91         91   \n",
       "9       https://cdn.sofifa.org/flags/44.png       90         93   \n",
       "10      https://cdn.sofifa.org/flags/37.png       90         90   \n",
       "11      https://cdn.sofifa.org/flags/21.png       90         90   \n",
       "12      https://cdn.sofifa.org/flags/60.png       90         90   \n",
       "13      https://cdn.sofifa.org/flags/45.png       90         90   \n",
       "14      https://cdn.sofifa.org/flags/18.png       89         90   \n",
       "15      https://cdn.sofifa.org/flags/52.png       89         94   \n",
       "16      https://cdn.sofifa.org/flags/14.png       89         91   \n",
       "17      https://cdn.sofifa.org/flags/18.png       89         90   \n",
       "18      https://cdn.sofifa.org/flags/21.png       89         92   \n",
       "19       https://cdn.sofifa.org/flags/7.png       89         90   \n",
       "20      https://cdn.sofifa.org/flags/45.png       89         89   \n",
       "21      https://cdn.sofifa.org/flags/60.png       89         89   \n",
       "22      https://cdn.sofifa.org/flags/21.png       89         89   \n",
       "23      https://cdn.sofifa.org/flags/52.png       89         89   \n",
       "24      https://cdn.sofifa.org/flags/27.png       89         89   \n",
       "25      https://cdn.sofifa.org/flags/18.png       88         95   \n",
       "26     https://cdn.sofifa.org/flags/111.png       88         89   \n",
       "27      https://cdn.sofifa.org/flags/54.png       88         90   \n",
       "28      https://cdn.sofifa.org/flags/56.png       88         89   \n",
       "29      https://cdn.sofifa.org/flags/27.png       88         88   \n",
       "...                                     ...      ...        ...   \n",
       "18177   https://cdn.sofifa.org/flags/25.png       48         69   \n",
       "18178   https://cdn.sofifa.org/flags/46.png       48         65   \n",
       "18179   https://cdn.sofifa.org/flags/14.png       48         64   \n",
       "18180   https://cdn.sofifa.org/flags/42.png       48         58   \n",
       "18181   https://cdn.sofifa.org/flags/25.png       48         66   \n",
       "18182   https://cdn.sofifa.org/flags/56.png       48         65   \n",
       "18183   https://cdn.sofifa.org/flags/14.png       48         48   \n",
       "18184   https://cdn.sofifa.org/flags/14.png       48         55   \n",
       "18185   https://cdn.sofifa.org/flags/25.png       48         59   \n",
       "18186  https://cdn.sofifa.org/flags/155.png       47         64   \n",
       "18187   https://cdn.sofifa.org/flags/21.png       47         59   \n",
       "18188   https://cdn.sofifa.org/flags/50.png       47         62   \n",
       "18189   https://cdn.sofifa.org/flags/21.png       47         61   \n",
       "18190   https://cdn.sofifa.org/flags/14.png       47         67   \n",
       "18191   https://cdn.sofifa.org/flags/14.png       47         65   \n",
       "18192   https://cdn.sofifa.org/flags/14.png       47         64   \n",
       "18193   https://cdn.sofifa.org/flags/55.png       47         64   \n",
       "18194   https://cdn.sofifa.org/flags/27.png       47         65   \n",
       "18195   https://cdn.sofifa.org/flags/25.png       47         67   \n",
       "18196  https://cdn.sofifa.org/flags/163.png       47         61   \n",
       "18197   https://cdn.sofifa.org/flags/25.png       47         61   \n",
       "18198   https://cdn.sofifa.org/flags/14.png       47         70   \n",
       "18199   https://cdn.sofifa.org/flags/70.png       47         69   \n",
       "18200   https://cdn.sofifa.org/flags/42.png       47         62   \n",
       "18201   https://cdn.sofifa.org/flags/25.png       47         68   \n",
       "18202   https://cdn.sofifa.org/flags/14.png       47         65   \n",
       "18203   https://cdn.sofifa.org/flags/46.png       47         63   \n",
       "18204   https://cdn.sofifa.org/flags/14.png       47         67   \n",
       "18205   https://cdn.sofifa.org/flags/14.png       47         66   \n",
       "18206   https://cdn.sofifa.org/flags/14.png       46         66   \n",
       "\n",
       "                         Club      ...       Composure Marking StandingTackle  \\\n",
       "0                FC Barcelona      ...            96.0    33.0           28.0   \n",
       "1                    Juventus      ...            95.0    28.0           31.0   \n",
       "2         Paris Saint-Germain      ...            94.0    27.0           24.0   \n",
       "3           Manchester United      ...            68.0    15.0           21.0   \n",
       "4             Manchester City      ...            88.0    68.0           58.0   \n",
       "5                     Chelsea      ...            91.0    34.0           27.0   \n",
       "6                 Real Madrid      ...            84.0    60.0           76.0   \n",
       "7                FC Barcelona      ...            85.0    62.0           45.0   \n",
       "8                 Real Madrid      ...            82.0    87.0           92.0   \n",
       "9             Atlético Madrid      ...            70.0    27.0           12.0   \n",
       "10          FC Bayern München      ...            86.0    34.0           42.0   \n",
       "11                Real Madrid      ...            85.0    72.0           79.0   \n",
       "12            Atlético Madrid      ...            82.0    90.0           89.0   \n",
       "13            Manchester City      ...            93.0    59.0           53.0   \n",
       "14                    Chelsea      ...            85.0    90.0           91.0   \n",
       "15                   Juventus      ...            84.0    23.0           20.0   \n",
       "16          Tottenham Hotspur      ...            89.0    56.0           36.0   \n",
       "17            Atlético Madrid      ...            87.0    59.0           47.0   \n",
       "18               FC Barcelona      ...            69.0    25.0           13.0   \n",
       "19                Real Madrid      ...            66.0    20.0           18.0   \n",
       "20               FC Barcelona      ...            90.0    90.0           86.0   \n",
       "21        Paris Saint-Germain      ...            82.0    52.0           45.0   \n",
       "22          FC Bayern München      ...            70.0    17.0           10.0   \n",
       "23            Manchester City      ...            90.0    30.0           20.0   \n",
       "24                   Juventus      ...            84.0    93.0           93.0   \n",
       "25        Paris Saint-Germain      ...            86.0    34.0           34.0   \n",
       "26                  Liverpool      ...            91.0    38.0           43.0   \n",
       "27                Real Madrid      ...            84.0    88.0           90.0   \n",
       "28          FC Bayern München      ...            87.0    52.0           41.0   \n",
       "29                     Napoli      ...            83.0    51.0           24.0   \n",
       "...                       ...      ...             ...     ...            ...   \n",
       "18177               Blackpool      ...            49.0    18.0           16.0   \n",
       "18178              Dalkurd FF      ...            28.0    16.0           11.0   \n",
       "18179        Northampton Town      ...            37.0    42.0           51.0   \n",
       "18180        St. Johnstone FC      ...            28.0    12.0           15.0   \n",
       "18181          Bray Wanderers      ...            38.0    43.0           49.0   \n",
       "18182       Atlético Nacional      ...            38.0    44.0           42.0   \n",
       "18183        Cambridge United      ...            56.0    15.0           15.0   \n",
       "18184            Lincoln City      ...            42.0    47.0           49.0   \n",
       "18185              Derry City      ...            43.0    39.0           39.0   \n",
       "18186        Beijing Renhe FC      ...            39.0    53.0           41.0   \n",
       "18187      SpVgg Unterhaching      ...            47.0    40.0           42.0   \n",
       "18188          Newport County      ...            46.0    33.0           38.0   \n",
       "18189      SpVgg Unterhaching      ...            37.0    28.0           15.0   \n",
       "18190        Cambridge United      ...            46.0    35.0           44.0   \n",
       "18191        Cambridge United      ...            36.0    45.0           42.0   \n",
       "18192        Cambridge United      ...            38.0    41.0           41.0   \n",
       "18193          Unión Española      ...            32.0    41.0           48.0   \n",
       "18194                   Lecce      ...            23.0     6.0           10.0   \n",
       "18195            Waterford FC      ...            41.0    44.0           37.0   \n",
       "18196            Júbilo Iwata      ...            35.0    41.0           44.0   \n",
       "18197               Cork City      ...            52.0    41.0           47.0   \n",
       "18198           Burton Albion      ...            34.0    15.0           11.0   \n",
       "18199  Vancouver Whitecaps FC      ...            40.0    48.0           49.0   \n",
       "18200            Swindon Town      ...            50.0    15.0           17.0   \n",
       "18201            Waterford FC      ...            43.0    44.0           47.0   \n",
       "18202         Crewe Alexandra      ...            45.0    40.0           48.0   \n",
       "18203          Trelleborgs FF      ...            42.0    22.0           15.0   \n",
       "18204        Cambridge United      ...            41.0    32.0           13.0   \n",
       "18205         Tranmere Rovers      ...            46.0    20.0           25.0   \n",
       "18206         Tranmere Rovers      ...            43.0    40.0           43.0   \n",
       "\n",
       "       SlidingTackle GKDiving  GKHandling  GKKicking  GKPositioning  \\\n",
       "0               26.0      6.0        11.0       15.0           14.0   \n",
       "1               23.0      7.0        11.0       15.0           14.0   \n",
       "2               33.0      9.0         9.0       15.0           15.0   \n",
       "3               13.0     90.0        85.0       87.0           88.0   \n",
       "4               51.0     15.0        13.0        5.0           10.0   \n",
       "5               22.0     11.0        12.0        6.0            8.0   \n",
       "6               73.0     13.0         9.0        7.0           14.0   \n",
       "7               38.0     27.0        25.0       31.0           33.0   \n",
       "8               91.0     11.0         8.0        9.0            7.0   \n",
       "9               18.0     86.0        92.0       78.0           88.0   \n",
       "10              19.0     15.0         6.0       12.0            8.0   \n",
       "11              69.0     10.0        11.0       13.0            7.0   \n",
       "12              89.0      6.0         8.0       15.0            5.0   \n",
       "13              29.0      6.0        15.0        7.0            6.0   \n",
       "14              85.0     15.0        12.0       10.0            7.0   \n",
       "15              20.0      5.0         4.0        4.0            5.0   \n",
       "16              38.0      8.0        10.0       11.0           14.0   \n",
       "17              48.0     14.0         8.0       14.0           13.0   \n",
       "18              10.0     87.0        85.0       88.0           85.0   \n",
       "19              16.0     85.0        91.0       72.0           86.0   \n",
       "20              80.0      5.0         8.0       13.0            9.0   \n",
       "21              39.0     12.0         5.0       13.0           13.0   \n",
       "22              11.0     90.0        86.0       91.0           87.0   \n",
       "23              12.0     13.0        15.0        6.0           11.0   \n",
       "24              90.0      3.0         3.0        2.0            4.0   \n",
       "25              32.0     13.0         5.0        7.0           11.0   \n",
       "26              41.0     14.0        14.0        9.0           11.0   \n",
       "27              87.0     13.0        14.0       16.0           12.0   \n",
       "28              44.0     15.0        15.0       15.0            5.0   \n",
       "29              22.0      8.0         4.0       14.0            9.0   \n",
       "...              ...      ...         ...        ...            ...   \n",
       "18177           11.0      6.0         9.0       11.0            7.0   \n",
       "18178           10.0     47.0        46.0       50.0           45.0   \n",
       "18179           49.0     14.0        11.0        7.0           11.0   \n",
       "18180           16.0     45.0        49.0       50.0           50.0   \n",
       "18181           45.0      8.0        10.0       12.0            9.0   \n",
       "18182           46.0      9.0        15.0       15.0            8.0   \n",
       "18183           13.0     45.0        48.0       44.0           49.0   \n",
       "18184           53.0     12.0         5.0       12.0           14.0   \n",
       "18185           48.0      6.0        11.0        9.0            5.0   \n",
       "18186           51.0     15.0         7.0       14.0            6.0   \n",
       "18187           42.0     13.0        12.0       11.0           15.0   \n",
       "18188           41.0      5.0        12.0        8.0           13.0   \n",
       "18189           22.0     15.0         5.0       14.0           12.0   \n",
       "18190           47.0     13.0         7.0       14.0           10.0   \n",
       "18191           46.0     15.0        13.0        6.0           14.0   \n",
       "18192           44.0     11.0        11.0        8.0           12.0   \n",
       "18193           48.0      6.0        10.0        6.0           12.0   \n",
       "18194           11.0     52.0        52.0       52.0           40.0   \n",
       "18195           48.0     13.0        14.0       12.0            7.0   \n",
       "18196           54.0     10.0        12.0        6.0           11.0   \n",
       "18197           38.0     13.0         6.0        9.0           10.0   \n",
       "18198           13.0     46.0        52.0       58.0           42.0   \n",
       "18199           49.0      7.0         7.0        9.0           14.0   \n",
       "18200           14.0     11.0        15.0       12.0           12.0   \n",
       "18201           53.0      9.0        10.0        9.0           11.0   \n",
       "18202           47.0     10.0        13.0        7.0            8.0   \n",
       "18203           19.0     10.0         9.0        9.0            5.0   \n",
       "18204           11.0      6.0         5.0       10.0            6.0   \n",
       "18205           27.0     14.0         6.0       14.0            8.0   \n",
       "18206           50.0     10.0        15.0        9.0           12.0   \n",
       "\n",
       "      GKReflexes Release Clause  \n",
       "0            8.0        €226.5M  \n",
       "1           11.0        €127.1M  \n",
       "2           11.0        €228.1M  \n",
       "3           94.0        €138.6M  \n",
       "4           13.0        €196.4M  \n",
       "5            8.0        €172.1M  \n",
       "6            9.0        €137.4M  \n",
       "7           37.0          €164M  \n",
       "8           11.0        €104.6M  \n",
       "9           89.0        €144.5M  \n",
       "10          10.0        €127.1M  \n",
       "11          10.0        €156.8M  \n",
       "12          15.0         €90.2M  \n",
       "13          12.0          €111M  \n",
       "14          10.0        €121.3M  \n",
       "15           8.0        €153.5M  \n",
       "16          11.0        €160.7M  \n",
       "17          14.0        €165.8M  \n",
       "18          90.0        €123.3M  \n",
       "19          88.0        €113.7M  \n",
       "20          13.0        €105.6M  \n",
       "21          10.0          €111M  \n",
       "22          87.0         €62.7M  \n",
       "23          14.0        €119.3M  \n",
       "24           3.0         €44.6M  \n",
       "25           6.0        €166.1M  \n",
       "26          14.0        €137.3M  \n",
       "27          12.0        €126.4M  \n",
       "28          14.0            NaN  \n",
       "29          10.0        €105.4M  \n",
       "...          ...            ...  \n",
       "18177       12.0          €193K  \n",
       "18178       51.0           €94K  \n",
       "18179        8.0          €119K  \n",
       "18180       45.0           €78K  \n",
       "18181       10.0          €109K  \n",
       "18182        6.0          €101K  \n",
       "18183       46.0            NaN  \n",
       "18184       15.0           €78K  \n",
       "18185        8.0           €88K  \n",
       "18186        8.0          €167K  \n",
       "18187       12.0           €66K  \n",
       "18188       10.0          €143K  \n",
       "18189        8.0          €125K  \n",
       "18190        8.0          €165K  \n",
       "18191       12.0          €119K  \n",
       "18192       13.0          €119K  \n",
       "18193       11.0           €99K  \n",
       "18194       44.0          €109K  \n",
       "18195       13.0          €153K  \n",
       "18196        8.0          €113K  \n",
       "18197       15.0           €88K  \n",
       "18198       48.0          €165K  \n",
       "18199       15.0          €175K  \n",
       "18200       11.0          €143K  \n",
       "18201       13.0          €153K  \n",
       "18202        9.0          €143K  \n",
       "18203       12.0          €113K  \n",
       "18204       13.0          €165K  \n",
       "18205        9.0          €143K  \n",
       "18206        9.0          €165K  \n",
       "\n",
       "[18207 rows x 89 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "non_nan_rows = data_raw[data_raw['Age'].notnull()] #get the rows having non null values in the column 'Age'\n",
    "non_nan_rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age\n",
       "16    46.523810\n",
       "17    47.104530\n",
       "18    46.610656\n",
       "19    47.872674\n",
       "20    50.047696\n",
       "21    50.757213\n",
       "22    51.719101\n",
       "23    52.917983\n",
       "24    53.812546\n",
       "25    54.339177\n",
       "26    55.615051\n",
       "27    55.419689\n",
       "28    55.974522\n",
       "29    55.700837\n",
       "30    57.486900\n",
       "31    57.539660\n",
       "32    57.047038\n",
       "33    56.862408\n",
       "34    56.545906\n",
       "35    52.928205\n",
       "36    53.834646\n",
       "37    55.925926\n",
       "38    51.621622\n",
       "39    50.280000\n",
       "40    44.923077\n",
       "41    57.200000\n",
       "42    64.000000\n",
       "44    16.000000\n",
       "45    40.000000\n",
       "Name: Vision, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.groupby('Age').Vision.mean() # for the various Ages, share the mean of Vision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1f5548f0898>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_raw.groupby('Age').Vision.mean().plot(kind='bar') # for the various Ages, share the mean of Vision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age\n",
       "16      42\n",
       "17     289\n",
       "18     732\n",
       "19    1024\n",
       "20    1240\n",
       "21    1423\n",
       "22    1340\n",
       "23    1332\n",
       "24    1358\n",
       "25    1319\n",
       "26    1387\n",
       "27    1162\n",
       "28    1101\n",
       "29     959\n",
       "30     917\n",
       "31     707\n",
       "32     574\n",
       "33     408\n",
       "34     404\n",
       "35     196\n",
       "36     127\n",
       "37      82\n",
       "38      37\n",
       "39      25\n",
       "40      13\n",
       "41       5\n",
       "42       1\n",
       "44       2\n",
       "45       1\n",
       "Name: ID, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.groupby('Age').ID.count() # for the various Ages, share the number of records "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1f555800048>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_raw.groupby('Age').ID.count().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>count</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>42</td>\n",
       "      <td>64</td>\n",
       "      <td>46</td>\n",
       "      <td>54.452381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>289</td>\n",
       "      <td>77</td>\n",
       "      <td>47</td>\n",
       "      <td>56.404844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>732</td>\n",
       "      <td>82</td>\n",
       "      <td>47</td>\n",
       "      <td>57.741803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1024</td>\n",
       "      <td>88</td>\n",
       "      <td>47</td>\n",
       "      <td>59.583008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1240</td>\n",
       "      <td>81</td>\n",
       "      <td>47</td>\n",
       "      <td>61.858871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1423</td>\n",
       "      <td>83</td>\n",
       "      <td>48</td>\n",
       "      <td>63.480675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1340</td>\n",
       "      <td>86</td>\n",
       "      <td>48</td>\n",
       "      <td>64.994030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1332</td>\n",
       "      <td>86</td>\n",
       "      <td>50</td>\n",
       "      <td>66.244745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1358</td>\n",
       "      <td>89</td>\n",
       "      <td>50</td>\n",
       "      <td>67.306333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1319</td>\n",
       "      <td>90</td>\n",
       "      <td>51</td>\n",
       "      <td>67.973465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1387</td>\n",
       "      <td>92</td>\n",
       "      <td>50</td>\n",
       "      <td>68.514780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1162</td>\n",
       "      <td>91</td>\n",
       "      <td>50</td>\n",
       "      <td>68.949225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1101</td>\n",
       "      <td>90</td>\n",
       "      <td>51</td>\n",
       "      <td>69.213442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>959</td>\n",
       "      <td>90</td>\n",
       "      <td>53</td>\n",
       "      <td>69.246090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>917</td>\n",
       "      <td>89</td>\n",
       "      <td>52</td>\n",
       "      <td>69.695747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>707</td>\n",
       "      <td>94</td>\n",
       "      <td>50</td>\n",
       "      <td>69.850071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>574</td>\n",
       "      <td>91</td>\n",
       "      <td>52</td>\n",
       "      <td>69.529617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>408</td>\n",
       "      <td>94</td>\n",
       "      <td>48</td>\n",
       "      <td>69.558824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>404</td>\n",
       "      <td>86</td>\n",
       "      <td>54</td>\n",
       "      <td>69.539604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>196</td>\n",
       "      <td>85</td>\n",
       "      <td>53</td>\n",
       "      <td>68.132653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>127</td>\n",
       "      <td>85</td>\n",
       "      <td>53</td>\n",
       "      <td>67.937008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>82</td>\n",
       "      <td>84</td>\n",
       "      <td>55</td>\n",
       "      <td>68.939024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>37</td>\n",
       "      <td>74</td>\n",
       "      <td>54</td>\n",
       "      <td>67.378378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>25</td>\n",
       "      <td>80</td>\n",
       "      <td>52</td>\n",
       "      <td>67.640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>13</td>\n",
       "      <td>88</td>\n",
       "      <td>52</td>\n",
       "      <td>67.692308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>5</td>\n",
       "      <td>77</td>\n",
       "      <td>59</td>\n",
       "      <td>67.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>65.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2</td>\n",
       "      <td>53</td>\n",
       "      <td>48</td>\n",
       "      <td>50.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1</td>\n",
       "      <td>71</td>\n",
       "      <td>71</td>\n",
       "      <td>71.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     count  max  min       mean\n",
       "Age                            \n",
       "16      42   64   46  54.452381\n",
       "17     289   77   47  56.404844\n",
       "18     732   82   47  57.741803\n",
       "19    1024   88   47  59.583008\n",
       "20    1240   81   47  61.858871\n",
       "21    1423   83   48  63.480675\n",
       "22    1340   86   48  64.994030\n",
       "23    1332   86   50  66.244745\n",
       "24    1358   89   50  67.306333\n",
       "25    1319   90   51  67.973465\n",
       "26    1387   92   50  68.514780\n",
       "27    1162   91   50  68.949225\n",
       "28    1101   90   51  69.213442\n",
       "29     959   90   53  69.246090\n",
       "30     917   89   52  69.695747\n",
       "31     707   94   50  69.850071\n",
       "32     574   91   52  69.529617\n",
       "33     408   94   48  69.558824\n",
       "34     404   86   54  69.539604\n",
       "35     196   85   53  68.132653\n",
       "36     127   85   53  67.937008\n",
       "37      82   84   55  68.939024\n",
       "38      37   74   54  67.378378\n",
       "39      25   80   52  67.640000\n",
       "40      13   88   52  67.692308\n",
       "41       5   77   59  67.600000\n",
       "42       1   65   65  65.000000\n",
       "44       2   53   48  50.500000\n",
       "45       1   71   71  71.000000"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.groupby('Age').Overall.agg(['count','max','min','mean']) # 4 functions for Overall corresponding to various age groups "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1f5558d8a58>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_raw.groupby('Age').Overall.agg(['max','min','mean']).plot(kind='bar') # 4 functions for Overall corresponding to various age groups "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Special</th>\n",
       "      <th>International Reputation</th>\n",
       "      <th>Weak Foot</th>\n",
       "      <th>Skill Moves</th>\n",
       "      <th>Jersey Number</th>\n",
       "      <th>Crossing</th>\n",
       "      <th>...</th>\n",
       "      <th>Penalties</th>\n",
       "      <th>Composure</th>\n",
       "      <th>Marking</th>\n",
       "      <th>StandingTackle</th>\n",
       "      <th>SlidingTackle</th>\n",
       "      <th>GKDiving</th>\n",
       "      <th>GKHandling</th>\n",
       "      <th>GKKicking</th>\n",
       "      <th>GKPositioning</th>\n",
       "      <th>GKReflexes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>16</th>\n",
       "      <td>16707.452381</td>\n",
       "      <td>244184.309524</td>\n",
       "      <td>54.452381</td>\n",
       "      <td>73.190476</td>\n",
       "      <td>1347.880952</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.761905</td>\n",
       "      <td>2.095238</td>\n",
       "      <td>28.380952</td>\n",
       "      <td>38.404762</td>\n",
       "      <td>...</td>\n",
       "      <td>45.976190</td>\n",
       "      <td>46.404762</td>\n",
       "      <td>31.142857</td>\n",
       "      <td>33.666667</td>\n",
       "      <td>33.523810</td>\n",
       "      <td>14.071429</td>\n",
       "      <td>13.952381</td>\n",
       "      <td>13.904762</td>\n",
       "      <td>13.714286</td>\n",
       "      <td>13.571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>15858.183391</td>\n",
       "      <td>243575.795848</td>\n",
       "      <td>56.404844</td>\n",
       "      <td>74.339100</td>\n",
       "      <td>1378.802768</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.832753</td>\n",
       "      <td>2.177700</td>\n",
       "      <td>32.421603</td>\n",
       "      <td>40.202091</td>\n",
       "      <td>...</td>\n",
       "      <td>44.062718</td>\n",
       "      <td>48.020906</td>\n",
       "      <td>36.080139</td>\n",
       "      <td>37.839721</td>\n",
       "      <td>37.167247</td>\n",
       "      <td>15.121951</td>\n",
       "      <td>15.135889</td>\n",
       "      <td>14.658537</td>\n",
       "      <td>14.331010</td>\n",
       "      <td>14.731707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>15169.502732</td>\n",
       "      <td>242059.147541</td>\n",
       "      <td>57.741803</td>\n",
       "      <td>73.530055</td>\n",
       "      <td>1396.504098</td>\n",
       "      <td>1.001366</td>\n",
       "      <td>2.840164</td>\n",
       "      <td>2.120219</td>\n",
       "      <td>31.267760</td>\n",
       "      <td>40.724044</td>\n",
       "      <td>...</td>\n",
       "      <td>44.584699</td>\n",
       "      <td>49.023224</td>\n",
       "      <td>38.163934</td>\n",
       "      <td>39.185792</td>\n",
       "      <td>38.005464</td>\n",
       "      <td>15.285519</td>\n",
       "      <td>15.096995</td>\n",
       "      <td>15.024590</td>\n",
       "      <td>14.774590</td>\n",
       "      <td>15.265027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>14127.623047</td>\n",
       "      <td>239909.397461</td>\n",
       "      <td>59.583008</td>\n",
       "      <td>73.146484</td>\n",
       "      <td>1439.607422</td>\n",
       "      <td>1.006856</td>\n",
       "      <td>2.885406</td>\n",
       "      <td>2.214496</td>\n",
       "      <td>28.852106</td>\n",
       "      <td>43.475024</td>\n",
       "      <td>...</td>\n",
       "      <td>44.922625</td>\n",
       "      <td>50.398629</td>\n",
       "      <td>40.714985</td>\n",
       "      <td>41.039177</td>\n",
       "      <td>40.023506</td>\n",
       "      <td>14.594515</td>\n",
       "      <td>14.416259</td>\n",
       "      <td>14.284035</td>\n",
       "      <td>14.383937</td>\n",
       "      <td>14.635651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>12592.683065</td>\n",
       "      <td>236829.318548</td>\n",
       "      <td>61.858871</td>\n",
       "      <td>73.213710</td>\n",
       "      <td>1498.423387</td>\n",
       "      <td>1.004850</td>\n",
       "      <td>2.881164</td>\n",
       "      <td>2.268391</td>\n",
       "      <td>24.334142</td>\n",
       "      <td>45.899757</td>\n",
       "      <td>...</td>\n",
       "      <td>45.402587</td>\n",
       "      <td>52.679871</td>\n",
       "      <td>44.118836</td>\n",
       "      <td>44.549717</td>\n",
       "      <td>43.215036</td>\n",
       "      <td>14.875505</td>\n",
       "      <td>14.630558</td>\n",
       "      <td>14.488278</td>\n",
       "      <td>14.428456</td>\n",
       "      <td>14.895715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11325.862263</td>\n",
       "      <td>233497.117358</td>\n",
       "      <td>63.480675</td>\n",
       "      <td>72.957836</td>\n",
       "      <td>1525.961349</td>\n",
       "      <td>1.014075</td>\n",
       "      <td>2.906404</td>\n",
       "      <td>2.324419</td>\n",
       "      <td>22.292958</td>\n",
       "      <td>46.996481</td>\n",
       "      <td>...</td>\n",
       "      <td>45.805067</td>\n",
       "      <td>54.382125</td>\n",
       "      <td>44.009852</td>\n",
       "      <td>44.536946</td>\n",
       "      <td>42.966221</td>\n",
       "      <td>15.807178</td>\n",
       "      <td>15.637579</td>\n",
       "      <td>15.729064</td>\n",
       "      <td>15.550317</td>\n",
       "      <td>15.997889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10283.697015</td>\n",
       "      <td>229615.907463</td>\n",
       "      <td>64.994030</td>\n",
       "      <td>72.819403</td>\n",
       "      <td>1564.734328</td>\n",
       "      <td>1.037453</td>\n",
       "      <td>2.897378</td>\n",
       "      <td>2.342322</td>\n",
       "      <td>20.070412</td>\n",
       "      <td>48.723596</td>\n",
       "      <td>...</td>\n",
       "      <td>45.986517</td>\n",
       "      <td>55.930337</td>\n",
       "      <td>46.642697</td>\n",
       "      <td>47.186517</td>\n",
       "      <td>45.223221</td>\n",
       "      <td>16.464419</td>\n",
       "      <td>16.263670</td>\n",
       "      <td>15.991760</td>\n",
       "      <td>16.046442</td>\n",
       "      <td>16.483146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>9190.186186</td>\n",
       "      <td>224956.507508</td>\n",
       "      <td>66.244745</td>\n",
       "      <td>72.555556</td>\n",
       "      <td>1599.694444</td>\n",
       "      <td>1.046652</td>\n",
       "      <td>2.949586</td>\n",
       "      <td>2.416855</td>\n",
       "      <td>18.702866</td>\n",
       "      <td>50.093303</td>\n",
       "      <td>...</td>\n",
       "      <td>47.495109</td>\n",
       "      <td>57.536494</td>\n",
       "      <td>47.595937</td>\n",
       "      <td>47.960873</td>\n",
       "      <td>45.825433</td>\n",
       "      <td>15.774266</td>\n",
       "      <td>15.562829</td>\n",
       "      <td>15.549285</td>\n",
       "      <td>15.597442</td>\n",
       "      <td>16.066968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>8365.949190</td>\n",
       "      <td>220173.610457</td>\n",
       "      <td>67.306333</td>\n",
       "      <td>72.079529</td>\n",
       "      <td>1626.293814</td>\n",
       "      <td>1.074539</td>\n",
       "      <td>2.970480</td>\n",
       "      <td>2.430258</td>\n",
       "      <td>17.983026</td>\n",
       "      <td>50.985240</td>\n",
       "      <td>...</td>\n",
       "      <td>48.366052</td>\n",
       "      <td>59.177860</td>\n",
       "      <td>47.801476</td>\n",
       "      <td>48.423616</td>\n",
       "      <td>46.363838</td>\n",
       "      <td>16.334317</td>\n",
       "      <td>15.902583</td>\n",
       "      <td>15.708487</td>\n",
       "      <td>16.032472</td>\n",
       "      <td>16.291513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>7826.916603</td>\n",
       "      <td>216729.450341</td>\n",
       "      <td>67.973465</td>\n",
       "      <td>71.290371</td>\n",
       "      <td>1645.456406</td>\n",
       "      <td>1.101372</td>\n",
       "      <td>2.971799</td>\n",
       "      <td>2.464177</td>\n",
       "      <td>17.544207</td>\n",
       "      <td>51.734756</td>\n",
       "      <td>...</td>\n",
       "      <td>49.367378</td>\n",
       "      <td>60.150152</td>\n",
       "      <td>48.932165</td>\n",
       "      <td>48.876524</td>\n",
       "      <td>46.656250</td>\n",
       "      <td>16.320122</td>\n",
       "      <td>16.011433</td>\n",
       "      <td>15.869665</td>\n",
       "      <td>15.963415</td>\n",
       "      <td>16.319360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>7357.815429</td>\n",
       "      <td>214231.351118</td>\n",
       "      <td>68.514780</td>\n",
       "      <td>70.176640</td>\n",
       "      <td>1671.739005</td>\n",
       "      <td>1.102026</td>\n",
       "      <td>2.963821</td>\n",
       "      <td>2.481187</td>\n",
       "      <td>16.360145</td>\n",
       "      <td>53.309696</td>\n",
       "      <td>...</td>\n",
       "      <td>50.466715</td>\n",
       "      <td>61.625904</td>\n",
       "      <td>50.002894</td>\n",
       "      <td>50.917511</td>\n",
       "      <td>48.488423</td>\n",
       "      <td>15.385673</td>\n",
       "      <td>15.176556</td>\n",
       "      <td>14.952243</td>\n",
       "      <td>15.010854</td>\n",
       "      <td>15.370478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>7044.093804</td>\n",
       "      <td>207906.765921</td>\n",
       "      <td>68.949225</td>\n",
       "      <td>69.709122</td>\n",
       "      <td>1670.036145</td>\n",
       "      <td>1.152850</td>\n",
       "      <td>2.988774</td>\n",
       "      <td>2.494819</td>\n",
       "      <td>16.920553</td>\n",
       "      <td>52.647668</td>\n",
       "      <td>...</td>\n",
       "      <td>50.126079</td>\n",
       "      <td>61.696028</td>\n",
       "      <td>49.262522</td>\n",
       "      <td>49.537133</td>\n",
       "      <td>47.085492</td>\n",
       "      <td>16.469775</td>\n",
       "      <td>16.233161</td>\n",
       "      <td>16.134715</td>\n",
       "      <td>16.167530</td>\n",
       "      <td>16.638169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>6802.815622</td>\n",
       "      <td>205519.499546</td>\n",
       "      <td>69.213442</td>\n",
       "      <td>69.444142</td>\n",
       "      <td>1685.115350</td>\n",
       "      <td>1.169245</td>\n",
       "      <td>3.014559</td>\n",
       "      <td>2.463148</td>\n",
       "      <td>16.827116</td>\n",
       "      <td>53.705187</td>\n",
       "      <td>...</td>\n",
       "      <td>51.303913</td>\n",
       "      <td>62.747953</td>\n",
       "      <td>51.138308</td>\n",
       "      <td>51.262056</td>\n",
       "      <td>48.970883</td>\n",
       "      <td>16.080073</td>\n",
       "      <td>15.862602</td>\n",
       "      <td>15.610555</td>\n",
       "      <td>15.919017</td>\n",
       "      <td>16.274795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>6802.105318</td>\n",
       "      <td>199563.615224</td>\n",
       "      <td>69.246090</td>\n",
       "      <td>69.357664</td>\n",
       "      <td>1674.816475</td>\n",
       "      <td>1.196653</td>\n",
       "      <td>2.968619</td>\n",
       "      <td>2.390167</td>\n",
       "      <td>16.313808</td>\n",
       "      <td>52.512552</td>\n",
       "      <td>...</td>\n",
       "      <td>50.697699</td>\n",
       "      <td>62.279289</td>\n",
       "      <td>51.461297</td>\n",
       "      <td>52.167364</td>\n",
       "      <td>49.404812</td>\n",
       "      <td>17.108787</td>\n",
       "      <td>16.856695</td>\n",
       "      <td>16.806485</td>\n",
       "      <td>17.013598</td>\n",
       "      <td>17.199791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>6340.322792</td>\n",
       "      <td>197805.304253</td>\n",
       "      <td>69.695747</td>\n",
       "      <td>69.700109</td>\n",
       "      <td>1697.188659</td>\n",
       "      <td>1.194323</td>\n",
       "      <td>3.040393</td>\n",
       "      <td>2.437773</td>\n",
       "      <td>16.408297</td>\n",
       "      <td>54.234716</td>\n",
       "      <td>...</td>\n",
       "      <td>52.609170</td>\n",
       "      <td>63.931223</td>\n",
       "      <td>50.812227</td>\n",
       "      <td>51.436681</td>\n",
       "      <td>48.644105</td>\n",
       "      <td>16.445415</td>\n",
       "      <td>16.241266</td>\n",
       "      <td>16.044760</td>\n",
       "      <td>16.455240</td>\n",
       "      <td>16.575328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>6364.196605</td>\n",
       "      <td>185851.957567</td>\n",
       "      <td>69.850071</td>\n",
       "      <td>69.850071</td>\n",
       "      <td>1689.958982</td>\n",
       "      <td>1.304533</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.402266</td>\n",
       "      <td>16.620739</td>\n",
       "      <td>53.300283</td>\n",
       "      <td>...</td>\n",
       "      <td>52.526912</td>\n",
       "      <td>64.511331</td>\n",
       "      <td>51.257790</td>\n",
       "      <td>51.427762</td>\n",
       "      <td>48.844193</td>\n",
       "      <td>17.651558</td>\n",
       "      <td>17.386686</td>\n",
       "      <td>17.263456</td>\n",
       "      <td>17.626062</td>\n",
       "      <td>17.903683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>6587.426829</td>\n",
       "      <td>181439.325784</td>\n",
       "      <td>69.529617</td>\n",
       "      <td>69.529617</td>\n",
       "      <td>1667.606272</td>\n",
       "      <td>1.297909</td>\n",
       "      <td>2.993031</td>\n",
       "      <td>2.313589</td>\n",
       "      <td>15.668990</td>\n",
       "      <td>52.419861</td>\n",
       "      <td>...</td>\n",
       "      <td>51.184669</td>\n",
       "      <td>63.909408</td>\n",
       "      <td>51.848432</td>\n",
       "      <td>51.930314</td>\n",
       "      <td>49.503484</td>\n",
       "      <td>19.113240</td>\n",
       "      <td>18.686411</td>\n",
       "      <td>18.663763</td>\n",
       "      <td>19.073171</td>\n",
       "      <td>19.202091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>6524.340686</td>\n",
       "      <td>170341.774510</td>\n",
       "      <td>69.558824</td>\n",
       "      <td>69.558824</td>\n",
       "      <td>1659.397059</td>\n",
       "      <td>1.339066</td>\n",
       "      <td>2.941032</td>\n",
       "      <td>2.321867</td>\n",
       "      <td>14.780247</td>\n",
       "      <td>51.270270</td>\n",
       "      <td>...</td>\n",
       "      <td>52.117936</td>\n",
       "      <td>64.675676</td>\n",
       "      <td>52.199017</td>\n",
       "      <td>52.393120</td>\n",
       "      <td>49.697789</td>\n",
       "      <td>19.083538</td>\n",
       "      <td>18.958231</td>\n",
       "      <td>18.828010</td>\n",
       "      <td>19.265356</td>\n",
       "      <td>19.135135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>6356.237624</td>\n",
       "      <td>177387.477723</td>\n",
       "      <td>69.539604</td>\n",
       "      <td>69.539604</td>\n",
       "      <td>1641.742574</td>\n",
       "      <td>1.277916</td>\n",
       "      <td>3.009926</td>\n",
       "      <td>2.228288</td>\n",
       "      <td>14.647643</td>\n",
       "      <td>51.037221</td>\n",
       "      <td>...</td>\n",
       "      <td>52.660050</td>\n",
       "      <td>65.200993</td>\n",
       "      <td>49.238213</td>\n",
       "      <td>49.610422</td>\n",
       "      <td>47.853598</td>\n",
       "      <td>20.238213</td>\n",
       "      <td>20.493797</td>\n",
       "      <td>19.813896</td>\n",
       "      <td>20.138958</td>\n",
       "      <td>20.692308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>7580.760204</td>\n",
       "      <td>145731.255102</td>\n",
       "      <td>68.132653</td>\n",
       "      <td>68.132653</td>\n",
       "      <td>1534.591837</td>\n",
       "      <td>1.287179</td>\n",
       "      <td>2.897436</td>\n",
       "      <td>2.061538</td>\n",
       "      <td>16.866667</td>\n",
       "      <td>44.471795</td>\n",
       "      <td>...</td>\n",
       "      <td>47.425641</td>\n",
       "      <td>63.102564</td>\n",
       "      <td>43.379487</td>\n",
       "      <td>42.789744</td>\n",
       "      <td>40.784615</td>\n",
       "      <td>26.758974</td>\n",
       "      <td>26.410256</td>\n",
       "      <td>26.184615</td>\n",
       "      <td>27.317949</td>\n",
       "      <td>27.323077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>7737.795276</td>\n",
       "      <td>138680.803150</td>\n",
       "      <td>67.937008</td>\n",
       "      <td>67.937008</td>\n",
       "      <td>1534.803150</td>\n",
       "      <td>1.330709</td>\n",
       "      <td>2.976378</td>\n",
       "      <td>2.047244</td>\n",
       "      <td>13.181102</td>\n",
       "      <td>45.125984</td>\n",
       "      <td>...</td>\n",
       "      <td>48.551181</td>\n",
       "      <td>63.732283</td>\n",
       "      <td>43.559055</td>\n",
       "      <td>42.259843</td>\n",
       "      <td>40.314961</td>\n",
       "      <td>28.070866</td>\n",
       "      <td>27.826772</td>\n",
       "      <td>27.590551</td>\n",
       "      <td>28.968504</td>\n",
       "      <td>28.433071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>6922.914634</td>\n",
       "      <td>118433.792683</td>\n",
       "      <td>68.939024</td>\n",
       "      <td>68.939024</td>\n",
       "      <td>1501.914634</td>\n",
       "      <td>1.370370</td>\n",
       "      <td>2.888889</td>\n",
       "      <td>2.012346</td>\n",
       "      <td>14.450000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>47.172840</td>\n",
       "      <td>65.024691</td>\n",
       "      <td>44.432099</td>\n",
       "      <td>40.777778</td>\n",
       "      <td>39.283951</td>\n",
       "      <td>31.246914</td>\n",
       "      <td>31.666667</td>\n",
       "      <td>29.456790</td>\n",
       "      <td>32.160494</td>\n",
       "      <td>31.395062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>7851.000000</td>\n",
       "      <td>121981.216216</td>\n",
       "      <td>67.378378</td>\n",
       "      <td>67.378378</td>\n",
       "      <td>1421.351351</td>\n",
       "      <td>1.513514</td>\n",
       "      <td>2.918919</td>\n",
       "      <td>1.810811</td>\n",
       "      <td>14.486486</td>\n",
       "      <td>40.729730</td>\n",
       "      <td>...</td>\n",
       "      <td>43.864865</td>\n",
       "      <td>61.297297</td>\n",
       "      <td>39.567568</td>\n",
       "      <td>38.810811</td>\n",
       "      <td>36.729730</td>\n",
       "      <td>34.513514</td>\n",
       "      <td>34.297297</td>\n",
       "      <td>34.108108</td>\n",
       "      <td>35.432432</td>\n",
       "      <td>34.945946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>7557.720000</td>\n",
       "      <td>110876.880000</td>\n",
       "      <td>67.640000</td>\n",
       "      <td>67.640000</td>\n",
       "      <td>1407.720000</td>\n",
       "      <td>1.440000</td>\n",
       "      <td>3.040000</td>\n",
       "      <td>1.760000</td>\n",
       "      <td>12.920000</td>\n",
       "      <td>35.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>43.080000</td>\n",
       "      <td>62.080000</td>\n",
       "      <td>36.240000</td>\n",
       "      <td>33.600000</td>\n",
       "      <td>32.200000</td>\n",
       "      <td>37.920000</td>\n",
       "      <td>38.840000</td>\n",
       "      <td>36.280000</td>\n",
       "      <td>39.560000</td>\n",
       "      <td>37.360000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>8445.461538</td>\n",
       "      <td>117940.538462</td>\n",
       "      <td>67.692308</td>\n",
       "      <td>67.692308</td>\n",
       "      <td>1279.076923</td>\n",
       "      <td>1.615385</td>\n",
       "      <td>2.692308</td>\n",
       "      <td>1.538462</td>\n",
       "      <td>9.230769</td>\n",
       "      <td>29.615385</td>\n",
       "      <td>...</td>\n",
       "      <td>39.923077</td>\n",
       "      <td>55.846154</td>\n",
       "      <td>35.692308</td>\n",
       "      <td>31.230769</td>\n",
       "      <td>30.307692</td>\n",
       "      <td>44.846154</td>\n",
       "      <td>44.923077</td>\n",
       "      <td>43.384615</td>\n",
       "      <td>46.384615</td>\n",
       "      <td>43.769231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>8038.200000</td>\n",
       "      <td>106085.400000</td>\n",
       "      <td>67.600000</td>\n",
       "      <td>67.600000</td>\n",
       "      <td>1412.000000</td>\n",
       "      <td>1.400000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>15.200000</td>\n",
       "      <td>39.200000</td>\n",
       "      <td>...</td>\n",
       "      <td>37.600000</td>\n",
       "      <td>64.600000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>31.200000</td>\n",
       "      <td>45.800000</td>\n",
       "      <td>41.800000</td>\n",
       "      <td>43.800000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>44.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>10545.000000</td>\n",
       "      <td>140183.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>1296.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>63.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>17954.500000</td>\n",
       "      <td>52855.500000</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>850.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>19.500000</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>13.500000</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>54.500000</td>\n",
       "      <td>45.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>4741.000000</td>\n",
       "      <td>140029.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>1256.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>74.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29 rows × 43 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0             ID    Overall  Potential      Special  \\\n",
       "Age                                                                   \n",
       "16   16707.452381  244184.309524  54.452381  73.190476  1347.880952   \n",
       "17   15858.183391  243575.795848  56.404844  74.339100  1378.802768   \n",
       "18   15169.502732  242059.147541  57.741803  73.530055  1396.504098   \n",
       "19   14127.623047  239909.397461  59.583008  73.146484  1439.607422   \n",
       "20   12592.683065  236829.318548  61.858871  73.213710  1498.423387   \n",
       "21   11325.862263  233497.117358  63.480675  72.957836  1525.961349   \n",
       "22   10283.697015  229615.907463  64.994030  72.819403  1564.734328   \n",
       "23    9190.186186  224956.507508  66.244745  72.555556  1599.694444   \n",
       "24    8365.949190  220173.610457  67.306333  72.079529  1626.293814   \n",
       "25    7826.916603  216729.450341  67.973465  71.290371  1645.456406   \n",
       "26    7357.815429  214231.351118  68.514780  70.176640  1671.739005   \n",
       "27    7044.093804  207906.765921  68.949225  69.709122  1670.036145   \n",
       "28    6802.815622  205519.499546  69.213442  69.444142  1685.115350   \n",
       "29    6802.105318  199563.615224  69.246090  69.357664  1674.816475   \n",
       "30    6340.322792  197805.304253  69.695747  69.700109  1697.188659   \n",
       "31    6364.196605  185851.957567  69.850071  69.850071  1689.958982   \n",
       "32    6587.426829  181439.325784  69.529617  69.529617  1667.606272   \n",
       "33    6524.340686  170341.774510  69.558824  69.558824  1659.397059   \n",
       "34    6356.237624  177387.477723  69.539604  69.539604  1641.742574   \n",
       "35    7580.760204  145731.255102  68.132653  68.132653  1534.591837   \n",
       "36    7737.795276  138680.803150  67.937008  67.937008  1534.803150   \n",
       "37    6922.914634  118433.792683  68.939024  68.939024  1501.914634   \n",
       "38    7851.000000  121981.216216  67.378378  67.378378  1421.351351   \n",
       "39    7557.720000  110876.880000  67.640000  67.640000  1407.720000   \n",
       "40    8445.461538  117940.538462  67.692308  67.692308  1279.076923   \n",
       "41    8038.200000  106085.400000  67.600000  67.600000  1412.000000   \n",
       "42   10545.000000  140183.000000  65.000000  65.000000  1296.000000   \n",
       "44   17954.500000   52855.500000  50.500000  50.500000   850.000000   \n",
       "45    4741.000000  140029.000000  71.000000  71.000000  1256.000000   \n",
       "\n",
       "     International Reputation  Weak Foot  Skill Moves  Jersey Number  \\\n",
       "Age                                                                    \n",
       "16                   1.000000   2.761905     2.095238      28.380952   \n",
       "17                   1.000000   2.832753     2.177700      32.421603   \n",
       "18                   1.001366   2.840164     2.120219      31.267760   \n",
       "19                   1.006856   2.885406     2.214496      28.852106   \n",
       "20                   1.004850   2.881164     2.268391      24.334142   \n",
       "21                   1.014075   2.906404     2.324419      22.292958   \n",
       "22                   1.037453   2.897378     2.342322      20.070412   \n",
       "23                   1.046652   2.949586     2.416855      18.702866   \n",
       "24                   1.074539   2.970480     2.430258      17.983026   \n",
       "25                   1.101372   2.971799     2.464177      17.544207   \n",
       "26                   1.102026   2.963821     2.481187      16.360145   \n",
       "27                   1.152850   2.988774     2.494819      16.920553   \n",
       "28                   1.169245   3.014559     2.463148      16.827116   \n",
       "29                   1.196653   2.968619     2.390167      16.313808   \n",
       "30                   1.194323   3.040393     2.437773      16.408297   \n",
       "31                   1.304533   3.000000     2.402266      16.620739   \n",
       "32                   1.297909   2.993031     2.313589      15.668990   \n",
       "33                   1.339066   2.941032     2.321867      14.780247   \n",
       "34                   1.277916   3.009926     2.228288      14.647643   \n",
       "35                   1.287179   2.897436     2.061538      16.866667   \n",
       "36                   1.330709   2.976378     2.047244      13.181102   \n",
       "37                   1.370370   2.888889     2.012346      14.450000   \n",
       "38                   1.513514   2.918919     1.810811      14.486486   \n",
       "39                   1.440000   3.040000     1.760000      12.920000   \n",
       "40                   1.615385   2.692308     1.538462       9.230769   \n",
       "41                   1.400000   3.000000     1.800000      15.200000   \n",
       "42                   2.000000   3.000000     1.000000       1.000000   \n",
       "44                   1.000000   2.000000     1.000000      39.000000   \n",
       "45                   2.000000   3.000000     1.000000      21.000000   \n",
       "\n",
       "      Crossing     ...      Penalties  Composure    Marking  StandingTackle  \\\n",
       "Age                ...                                                        \n",
       "16   38.404762     ...      45.976190  46.404762  31.142857       33.666667   \n",
       "17   40.202091     ...      44.062718  48.020906  36.080139       37.839721   \n",
       "18   40.724044     ...      44.584699  49.023224  38.163934       39.185792   \n",
       "19   43.475024     ...      44.922625  50.398629  40.714985       41.039177   \n",
       "20   45.899757     ...      45.402587  52.679871  44.118836       44.549717   \n",
       "21   46.996481     ...      45.805067  54.382125  44.009852       44.536946   \n",
       "22   48.723596     ...      45.986517  55.930337  46.642697       47.186517   \n",
       "23   50.093303     ...      47.495109  57.536494  47.595937       47.960873   \n",
       "24   50.985240     ...      48.366052  59.177860  47.801476       48.423616   \n",
       "25   51.734756     ...      49.367378  60.150152  48.932165       48.876524   \n",
       "26   53.309696     ...      50.466715  61.625904  50.002894       50.917511   \n",
       "27   52.647668     ...      50.126079  61.696028  49.262522       49.537133   \n",
       "28   53.705187     ...      51.303913  62.747953  51.138308       51.262056   \n",
       "29   52.512552     ...      50.697699  62.279289  51.461297       52.167364   \n",
       "30   54.234716     ...      52.609170  63.931223  50.812227       51.436681   \n",
       "31   53.300283     ...      52.526912  64.511331  51.257790       51.427762   \n",
       "32   52.419861     ...      51.184669  63.909408  51.848432       51.930314   \n",
       "33   51.270270     ...      52.117936  64.675676  52.199017       52.393120   \n",
       "34   51.037221     ...      52.660050  65.200993  49.238213       49.610422   \n",
       "35   44.471795     ...      47.425641  63.102564  43.379487       42.789744   \n",
       "36   45.125984     ...      48.551181  63.732283  43.559055       42.259843   \n",
       "37   43.000000     ...      47.172840  65.024691  44.432099       40.777778   \n",
       "38   40.729730     ...      43.864865  61.297297  39.567568       38.810811   \n",
       "39   35.600000     ...      43.080000  62.080000  36.240000       33.600000   \n",
       "40   29.615385     ...      39.923077  55.846154  35.692308       31.230769   \n",
       "41   39.200000     ...      37.600000  64.600000  35.000000       33.000000   \n",
       "42   23.000000     ...      11.000000  45.000000  27.000000       24.000000   \n",
       "44   15.000000     ...      19.500000  51.000000  17.000000       15.000000   \n",
       "45   19.000000     ...      23.000000  62.000000  23.000000       12.000000   \n",
       "\n",
       "     SlidingTackle   GKDiving  GKHandling  GKKicking  GKPositioning  \\\n",
       "Age                                                                   \n",
       "16       33.523810  14.071429   13.952381  13.904762      13.714286   \n",
       "17       37.167247  15.121951   15.135889  14.658537      14.331010   \n",
       "18       38.005464  15.285519   15.096995  15.024590      14.774590   \n",
       "19       40.023506  14.594515   14.416259  14.284035      14.383937   \n",
       "20       43.215036  14.875505   14.630558  14.488278      14.428456   \n",
       "21       42.966221  15.807178   15.637579  15.729064      15.550317   \n",
       "22       45.223221  16.464419   16.263670  15.991760      16.046442   \n",
       "23       45.825433  15.774266   15.562829  15.549285      15.597442   \n",
       "24       46.363838  16.334317   15.902583  15.708487      16.032472   \n",
       "25       46.656250  16.320122   16.011433  15.869665      15.963415   \n",
       "26       48.488423  15.385673   15.176556  14.952243      15.010854   \n",
       "27       47.085492  16.469775   16.233161  16.134715      16.167530   \n",
       "28       48.970883  16.080073   15.862602  15.610555      15.919017   \n",
       "29       49.404812  17.108787   16.856695  16.806485      17.013598   \n",
       "30       48.644105  16.445415   16.241266  16.044760      16.455240   \n",
       "31       48.844193  17.651558   17.386686  17.263456      17.626062   \n",
       "32       49.503484  19.113240   18.686411  18.663763      19.073171   \n",
       "33       49.697789  19.083538   18.958231  18.828010      19.265356   \n",
       "34       47.853598  20.238213   20.493797  19.813896      20.138958   \n",
       "35       40.784615  26.758974   26.410256  26.184615      27.317949   \n",
       "36       40.314961  28.070866   27.826772  27.590551      28.968504   \n",
       "37       39.283951  31.246914   31.666667  29.456790      32.160494   \n",
       "38       36.729730  34.513514   34.297297  34.108108      35.432432   \n",
       "39       32.200000  37.920000   38.840000  36.280000      39.560000   \n",
       "40       30.307692  44.846154   44.923077  43.384615      46.384615   \n",
       "41       31.200000  45.800000   41.800000  43.800000      48.000000   \n",
       "42       22.000000  64.000000   63.000000  62.000000      67.000000   \n",
       "44       13.500000  46.500000   52.000000  50.000000      54.500000   \n",
       "45       11.000000  70.000000   64.000000  65.000000      73.000000   \n",
       "\n",
       "     GKReflexes  \n",
       "Age              \n",
       "16    13.571429  \n",
       "17    14.731707  \n",
       "18    15.265027  \n",
       "19    14.635651  \n",
       "20    14.895715  \n",
       "21    15.997889  \n",
       "22    16.483146  \n",
       "23    16.066968  \n",
       "24    16.291513  \n",
       "25    16.319360  \n",
       "26    15.370478  \n",
       "27    16.638169  \n",
       "28    16.274795  \n",
       "29    17.199791  \n",
       "30    16.575328  \n",
       "31    17.903683  \n",
       "32    19.202091  \n",
       "33    19.135135  \n",
       "34    20.692308  \n",
       "35    27.323077  \n",
       "36    28.433071  \n",
       "37    31.395062  \n",
       "38    34.945946  \n",
       "39    37.360000  \n",
       "40    43.769231  \n",
       "41    44.000000  \n",
       "42    63.000000  \n",
       "44    45.000000  \n",
       "45    74.000000  \n",
       "\n",
       "[29 rows x 43 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.groupby('Age').mean() # gives the mean for all of the numeric columns corresponding to various Ages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'ID', 'Name', 'Age', 'Photo', 'Nationality', 'Flag',\n",
       "       'Overall', 'Potential', 'Club', 'Club Logo', 'Value', 'Wage', 'Special',\n",
       "       'Preferred Foot', 'International Reputation', 'Weak Foot',\n",
       "       'Skill Moves', 'Work Rate', 'Body Type', 'Real Face', 'Position',\n",
       "       'Jersey Number', 'Joined', 'Loaned From', 'Contract Valid Until',\n",
       "       'Height', 'Weight', 'LS', 'ST', 'RS', 'LW', 'LF', 'CF', 'RF', 'RW',\n",
       "       'LAM', 'CAM', 'RAM', 'LM', 'LCM', 'CM', 'RCM', 'RM', 'LWB', 'LDM',\n",
       "       'CDM', 'RDM', 'RWB', 'LB', 'LCB', 'CB', 'RCB', 'RB', 'Crossing',\n",
       "       'Finishing', 'HeadingAccuracy', 'ShortPassing', 'Volleys', 'Dribbling',\n",
       "       'Curve', 'FKAccuracy', 'LongPassing', 'BallControl', 'Acceleration',\n",
       "       'SprintSpeed', 'Agility', 'Reactions', 'Balance', 'ShotPower',\n",
       "       'Jumping', 'Stamina', 'Strength', 'LongShots', 'Aggression',\n",
       "       'Interceptions', 'Positioning', 'Vision', 'Penalties', 'Composure',\n",
       "       'Marking', 'StandingTackle', 'SlidingTackle', 'GKDiving', 'GKHandling',\n",
       "       'GKKicking', 'GKPositioning', 'GKReflexes', 'Release_Clause'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rename a column (pass a dictionary to columns()'s first argument)\n",
    "data_raw.rename(columns={'Release Clause':'Release_Clause'},inplace=True)\n",
    "data_raw.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'ID', 'Name', 'Age', 'Photo', 'Nationality', 'Flag',\n",
       "       'Overall', 'Potential', 'Club', 'Club Logo', 'Value', 'Wage', 'Special',\n",
       "       'Preferred Foot', 'International Reputation', 'Weak Foot',\n",
       "       'Skill Moves', 'Work_Rate', 'Body_Type', 'Real Face', 'Position',\n",
       "       'Jersey Number', 'Joined', 'Loaned From', 'Contract Valid Until',\n",
       "       'Height', 'Weight', 'LS', 'ST', 'RS', 'LW', 'LF', 'CF', 'RF', 'RW',\n",
       "       'LAM', 'CAM', 'RAM', 'LM', 'LCM', 'CM', 'RCM', 'RM', 'LWB', 'LDM',\n",
       "       'CDM', 'RDM', 'RWB', 'LB', 'LCB', 'CB', 'RCB', 'RB', 'Crossing',\n",
       "       'Finishing', 'HeadingAccuracy', 'ShortPassing', 'Volleys', 'Dribbling',\n",
       "       'Curve', 'FKAccuracy', 'LongPassing', 'BallControl', 'Acceleration',\n",
       "       'SprintSpeed', 'Agility', 'Reactions', 'Balance', 'ShotPower',\n",
       "       'Jumping', 'Stamina', 'Strength', 'LongShots', 'Aggression',\n",
       "       'Interceptions', 'Positioning', 'Vision', 'Penalties', 'Composure',\n",
       "       'Marking', 'StandingTackle', 'SlidingTackle', 'GKDiving', 'GKHandling',\n",
       "       'GKKicking', 'GKPositioning', 'GKReflexes', 'Release_Clause'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rename multiple column\n",
    "data_raw.rename(columns={'Body Type':'Body_Type','Work Rate':'Work_Rate'},inplace=True)\n",
    "data_raw.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Unnamed</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Photo</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Flag</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>...</th>\n",
       "      <th>Composure</th>\n",
       "      <th>Marking</th>\n",
       "      <th>StandingTackle</th>\n",
       "      <th>SlidingTackle</th>\n",
       "      <th>GKDiving</th>\n",
       "      <th>GKHandling</th>\n",
       "      <th>GKKicking</th>\n",
       "      <th>GKPositioning</th>\n",
       "      <th>GKReflexes</th>\n",
       "      <th>Release_Clause</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>158023</td>\n",
       "      <td>L. Messi</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/158023.png</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>https://cdn.sofifa.org/flags/52.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>96.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€226.5M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>20801</td>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>33</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/20801.png</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>https://cdn.sofifa.org/flags/38.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>...</td>\n",
       "      <td>95.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€127.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>190871</td>\n",
       "      <td>Neymar Jr</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/190871.png</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>https://cdn.sofifa.org/flags/54.png</td>\n",
       "      <td>92</td>\n",
       "      <td>93</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>...</td>\n",
       "      <td>94.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€228.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>193080</td>\n",
       "      <td>De Gea</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/193080.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>91</td>\n",
       "      <td>93</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>...</td>\n",
       "      <td>68.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>€138.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>192985</td>\n",
       "      <td>K. De Bruyne</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/192985.png</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>92</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>...</td>\n",
       "      <td>88.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€196.4M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 89 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed      ID               Name  Age  \\\n",
       "0        0  158023           L. Messi   31   \n",
       "1        1   20801  Cristiano Ronaldo   33   \n",
       "2        2  190871          Neymar Jr   26   \n",
       "3        3  193080             De Gea   27   \n",
       "4        4  192985       K. De Bruyne   27   \n",
       "\n",
       "                                            Photo Nationality  \\\n",
       "0  https://cdn.sofifa.org/players/4/19/158023.png   Argentina   \n",
       "1   https://cdn.sofifa.org/players/4/19/20801.png    Portugal   \n",
       "2  https://cdn.sofifa.org/players/4/19/190871.png      Brazil   \n",
       "3  https://cdn.sofifa.org/players/4/19/193080.png       Spain   \n",
       "4  https://cdn.sofifa.org/players/4/19/192985.png     Belgium   \n",
       "\n",
       "                                  Flag  Overall  Potential  \\\n",
       "0  https://cdn.sofifa.org/flags/52.png       94         94   \n",
       "1  https://cdn.sofifa.org/flags/38.png       94         94   \n",
       "2  https://cdn.sofifa.org/flags/54.png       92         93   \n",
       "3  https://cdn.sofifa.org/flags/45.png       91         93   \n",
       "4   https://cdn.sofifa.org/flags/7.png       91         92   \n",
       "\n",
       "                  Club      ...       Composure Marking StandingTackle  \\\n",
       "0         FC Barcelona      ...            96.0    33.0           28.0   \n",
       "1             Juventus      ...            95.0    28.0           31.0   \n",
       "2  Paris Saint-Germain      ...            94.0    27.0           24.0   \n",
       "3    Manchester United      ...            68.0    15.0           21.0   \n",
       "4      Manchester City      ...            88.0    68.0           58.0   \n",
       "\n",
       "   SlidingTackle GKDiving  GKHandling  GKKicking  GKPositioning GKReflexes  \\\n",
       "0           26.0      6.0        11.0       15.0           14.0        8.0   \n",
       "1           23.0      7.0        11.0       15.0           14.0       11.0   \n",
       "2           33.0      9.0         9.0       15.0           15.0       11.0   \n",
       "3           13.0     90.0        85.0       87.0           88.0       94.0   \n",
       "4           51.0     15.0        13.0        5.0           10.0       13.0   \n",
       "\n",
       "  Release_Clause  \n",
       "0        €226.5M  \n",
       "1        €127.1M  \n",
       "2        €228.1M  \n",
       "3        €138.6M  \n",
       "4        €196.4M  \n",
       "\n",
       "[5 rows x 89 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Overwrite all previous columns\n",
    "data1=data_raw.copy() # copying the dataframe object\n",
    "new_cols = ['Unnamed', 'ID', 'Name', 'Age', 'Photo', 'Nationality', 'Flag',\n",
    "       'Overall', 'Potential', 'Club', 'Club Logo', 'Value', 'Wage', 'Special',\n",
    "       'Preferred Foot', 'International Reputation', 'Weak Foot',\n",
    "       'Skill Moves', 'Work_Rate', 'Body_Type', 'Real Face', 'Position',\n",
    "       'Jersey Number', 'Joined', 'Loaned From', 'Contract Valid Until',\n",
    "       'Height', 'Weight', 'LS', 'ST', 'RS', 'LW', 'LF', 'CF', 'RF', 'RW',\n",
    "       'LAM', 'CAM', 'RAM', 'LM', 'LCM', 'CM', 'RCM', 'RM', 'LWB', 'LDM',\n",
    "       'CDM', 'RDM', 'RWB', 'LB', 'LCB', 'CB', 'RCB', 'RB', 'Crossing',\n",
    "       'Finishing', 'HeadingAccuracy', 'ShortPassing', 'Volleys', 'Dribbling',\n",
    "       'Curve', 'FKAccuracy', 'LongPassing', 'BallControl', 'Acceleration',\n",
    "       'SprintSpeed', 'Agility', 'Reactions', 'Balance', 'ShotPower',\n",
    "       'Jumping', 'Stamina', 'Strength', 'LongShots', 'Aggression',\n",
    "       'Interceptions', 'Positioning', 'Vision', 'Penalties', 'Composure',\n",
    "       'Marking', 'StandingTackle', 'SlidingTackle', 'GKDiving', 'GKHandling',\n",
    "       'GKKicking', 'GKPositioning', 'GKReflexes', 'Release_Clause']\n",
    "data1.columns = new_cols\n",
    "data1.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Photo</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Flag</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>...</th>\n",
       "      <th>Composure</th>\n",
       "      <th>Marking</th>\n",
       "      <th>StandingTackle</th>\n",
       "      <th>SlidingTackle</th>\n",
       "      <th>GKDiving</th>\n",
       "      <th>GKHandling</th>\n",
       "      <th>GKKicking</th>\n",
       "      <th>GKPositioning</th>\n",
       "      <th>GKReflexes</th>\n",
       "      <th>Release_Clause</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>158023</td>\n",
       "      <td>L. Messi</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/158023.png</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>https://cdn.sofifa.org/flags/52.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>...</td>\n",
       "      <td>96.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>€226.5M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>20801</td>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>33</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/20801.png</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>https://cdn.sofifa.org/flags/38.png</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>...</td>\n",
       "      <td>95.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€127.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>190871</td>\n",
       "      <td>Neymar Jr</td>\n",
       "      <td>26</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/190871.png</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>https://cdn.sofifa.org/flags/54.png</td>\n",
       "      <td>92</td>\n",
       "      <td>93</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>...</td>\n",
       "      <td>94.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>€228.1M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>193080</td>\n",
       "      <td>De Gea</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/193080.png</td>\n",
       "      <td>Spain</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>91</td>\n",
       "      <td>93</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>...</td>\n",
       "      <td>68.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>€138.6M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>192985</td>\n",
       "      <td>K. De Bruyne</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/players/4/19/192985.png</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>92</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>...</td>\n",
       "      <td>88.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>€196.4M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 89 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0      ID               Name  Age  \\\n",
       "0           0  158023           L. Messi   31   \n",
       "1           1   20801  Cristiano Ronaldo   33   \n",
       "2           2  190871          Neymar Jr   26   \n",
       "3           3  193080             De Gea   27   \n",
       "4           4  192985       K. De Bruyne   27   \n",
       "\n",
       "                                            Photo Nationality  \\\n",
       "0  https://cdn.sofifa.org/players/4/19/158023.png   Argentina   \n",
       "1   https://cdn.sofifa.org/players/4/19/20801.png    Portugal   \n",
       "2  https://cdn.sofifa.org/players/4/19/190871.png      Brazil   \n",
       "3  https://cdn.sofifa.org/players/4/19/193080.png       Spain   \n",
       "4  https://cdn.sofifa.org/players/4/19/192985.png     Belgium   \n",
       "\n",
       "                                  Flag  Overall  Potential  \\\n",
       "0  https://cdn.sofifa.org/flags/52.png       94         94   \n",
       "1  https://cdn.sofifa.org/flags/38.png       94         94   \n",
       "2  https://cdn.sofifa.org/flags/54.png       92         93   \n",
       "3  https://cdn.sofifa.org/flags/45.png       91         93   \n",
       "4   https://cdn.sofifa.org/flags/7.png       91         92   \n",
       "\n",
       "                  Club      ...       Composure Marking StandingTackle  \\\n",
       "0         FC Barcelona      ...            96.0    33.0           28.0   \n",
       "1             Juventus      ...            95.0    28.0           31.0   \n",
       "2  Paris Saint-Germain      ...            94.0    27.0           24.0   \n",
       "3    Manchester United      ...            68.0    15.0           21.0   \n",
       "4      Manchester City      ...            88.0    68.0           58.0   \n",
       "\n",
       "   SlidingTackle GKDiving  GKHandling  GKKicking  GKPositioning GKReflexes  \\\n",
       "0           26.0      6.0        11.0       15.0           14.0        8.0   \n",
       "1           23.0      7.0        11.0       15.0           14.0       11.0   \n",
       "2           33.0      9.0         9.0       15.0           15.0       11.0   \n",
       "3           13.0     90.0        85.0       87.0           88.0       94.0   \n",
       "4           51.0     15.0        13.0        5.0           10.0       13.0   \n",
       "\n",
       "  Release_Clause  \n",
       "0        €226.5M  \n",
       "1        €127.1M  \n",
       "2        €228.1M  \n",
       "3        €138.6M  \n",
       "4        €196.4M  \n",
       "\n",
       "[5 rows x 89 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed', 'ID', 'Name', 'Age', 'Photo', 'Nationality', 'Flag',\n",
       "       'Overall', 'Potential', 'Club', 'Club Logo', 'Value', 'Wage', 'Special',\n",
       "       'Preferred Foot', 'International Reputation', 'Weak Foot',\n",
       "       'Skill Moves', 'Work_Rate', 'Body_Type', 'Real Face', 'Position',\n",
       "       'Jersey Number', 'Joined', 'Loaned From', 'Contract Valid Until',\n",
       "       'Height', 'Weight', 'LS', 'ST', 'RS', 'LW', 'LF', 'CF', 'RF', 'RW',\n",
       "       'LAM', 'CAM', 'RAM', 'LM', 'LCM', 'CM', 'RCM', 'RM', 'LWB', 'LDM',\n",
       "       'CDM', 'RDM', 'RWB', 'LB', 'LCB', 'CB', 'RCB', 'RB', 'Crossing',\n",
       "       'Finishing', 'HeadingAccuracy', 'ShortPassing', 'Volleys', 'Dribbling',\n",
       "       'Curve', 'FKAccuracy', 'LongPassing', 'BallControl', 'Acceleration',\n",
       "       'SprintSpeed', 'Agility', 'Reactions', 'Balance', 'ShotPower',\n",
       "       'Jumping', 'Stamina', 'Strength', 'LongShots', 'Aggression',\n",
       "       'Interceptions', 'Positioning', 'Vision', 'Penalties', 'Composure',\n",
       "       'Marking', 'StandingTackle', 'SlidingTackle', 'GKDiving', 'GKHandling',\n",
       "       'GKKicking', 'GKPositioning', 'GKReflexes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove a column\n",
    "data1.drop('Release_Clause',axis=1,inplace=True) # axis=1 means column axis, axis = 0 means row axis\n",
    "data1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed', 'ID', 'Name', 'Age', 'Flag', 'Overall', 'Potential', 'Club',\n",
       "       'Club Logo', 'Value', 'Wage', 'Special', 'Preferred Foot',\n",
       "       'International Reputation', 'Weak Foot', 'Skill Moves', 'Work_Rate',\n",
       "       'Body_Type', 'Real Face', 'Position', 'Jersey Number', 'Joined',\n",
       "       'Loaned From', 'Contract Valid Until', 'Height', 'Weight', 'LS', 'ST',\n",
       "       'RS', 'LW', 'LF', 'CF', 'RF', 'RW', 'LAM', 'CAM', 'RAM', 'LM', 'LCM',\n",
       "       'CM', 'RCM', 'RM', 'LWB', 'LDM', 'CDM', 'RDM', 'RWB', 'LB', 'LCB', 'CB',\n",
       "       'RCB', 'RB', 'Crossing', 'Finishing', 'HeadingAccuracy', 'ShortPassing',\n",
       "       'Volleys', 'Dribbling', 'Curve', 'FKAccuracy', 'LongPassing',\n",
       "       'BallControl', 'Acceleration', 'SprintSpeed', 'Agility', 'Reactions',\n",
       "       'Balance', 'ShotPower', 'Jumping', 'Stamina', 'Strength', 'LongShots',\n",
       "       'Aggression', 'Interceptions', 'Positioning', 'Vision', 'Penalties',\n",
       "       'Composure', 'Marking', 'StandingTackle', 'SlidingTackle', 'GKDiving',\n",
       "       'GKHandling', 'GKKicking', 'GKPositioning', 'GKReflexes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove Multiple Columns\n",
    "data1.drop(['Nationality','Photo'],axis=1,inplace=True)\n",
    "data1.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Unnamed</th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Flag</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>Club Logo</th>\n",
       "      <th>Value</th>\n",
       "      <th>...</th>\n",
       "      <th>Penalties</th>\n",
       "      <th>Composure</th>\n",
       "      <th>Marking</th>\n",
       "      <th>StandingTackle</th>\n",
       "      <th>SlidingTackle</th>\n",
       "      <th>GKDiving</th>\n",
       "      <th>GKHandling</th>\n",
       "      <th>GKKicking</th>\n",
       "      <th>GKPositioning</th>\n",
       "      <th>GKReflexes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>193080</td>\n",
       "      <td>De Gea</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/flags/45.png</td>\n",
       "      <td>91</td>\n",
       "      <td>93</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>https://cdn.sofifa.org/teams/2/light/11.png</td>\n",
       "      <td>€72M</td>\n",
       "      <td>...</td>\n",
       "      <td>40.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>192985</td>\n",
       "      <td>K. De Bruyne</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>92</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>https://cdn.sofifa.org/teams/2/light/10.png</td>\n",
       "      <td>€102M</td>\n",
       "      <td>...</td>\n",
       "      <td>79.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>183277</td>\n",
       "      <td>E. Hazard</td>\n",
       "      <td>27</td>\n",
       "      <td>https://cdn.sofifa.org/flags/7.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>https://cdn.sofifa.org/teams/2/light/5.png</td>\n",
       "      <td>€93M</td>\n",
       "      <td>...</td>\n",
       "      <td>86.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>177003</td>\n",
       "      <td>L. Modrić</td>\n",
       "      <td>32</td>\n",
       "      <td>https://cdn.sofifa.org/flags/10.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>Real Madrid</td>\n",
       "      <td>https://cdn.sofifa.org/teams/2/light/243.png</td>\n",
       "      <td>€67M</td>\n",
       "      <td>...</td>\n",
       "      <td>82.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>176580</td>\n",
       "      <td>L. Suárez</td>\n",
       "      <td>31</td>\n",
       "      <td>https://cdn.sofifa.org/flags/60.png</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>https://cdn.sofifa.org/teams/2/light/241.png</td>\n",
       "      <td>€80M</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 86 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed      ID          Name  Age                                 Flag  \\\n",
       "3        3  193080        De Gea   27  https://cdn.sofifa.org/flags/45.png   \n",
       "4        4  192985  K. De Bruyne   27   https://cdn.sofifa.org/flags/7.png   \n",
       "5        5  183277     E. Hazard   27   https://cdn.sofifa.org/flags/7.png   \n",
       "6        6  177003     L. Modrić   32  https://cdn.sofifa.org/flags/10.png   \n",
       "7        7  176580     L. Suárez   31  https://cdn.sofifa.org/flags/60.png   \n",
       "\n",
       "   Overall  Potential               Club  \\\n",
       "3       91         93  Manchester United   \n",
       "4       91         92    Manchester City   \n",
       "5       91         91            Chelsea   \n",
       "6       91         91        Real Madrid   \n",
       "7       91         91       FC Barcelona   \n",
       "\n",
       "                                      Club Logo  Value    ...     Penalties  \\\n",
       "3   https://cdn.sofifa.org/teams/2/light/11.png   €72M    ...          40.0   \n",
       "4   https://cdn.sofifa.org/teams/2/light/10.png  €102M    ...          79.0   \n",
       "5    https://cdn.sofifa.org/teams/2/light/5.png   €93M    ...          86.0   \n",
       "6  https://cdn.sofifa.org/teams/2/light/243.png   €67M    ...          82.0   \n",
       "7  https://cdn.sofifa.org/teams/2/light/241.png   €80M    ...          85.0   \n",
       "\n",
       "   Composure Marking  StandingTackle  SlidingTackle  GKDiving GKHandling  \\\n",
       "3       68.0    15.0            21.0           13.0      90.0       85.0   \n",
       "4       88.0    68.0            58.0           51.0      15.0       13.0   \n",
       "5       91.0    34.0            27.0           22.0      11.0       12.0   \n",
       "6       84.0    60.0            76.0           73.0      13.0        9.0   \n",
       "7       85.0    62.0            45.0           38.0      27.0       25.0   \n",
       "\n",
       "  GKKicking GKPositioning GKReflexes  \n",
       "3      87.0          88.0       94.0  \n",
       "4       5.0          10.0       13.0  \n",
       "5       6.0           8.0        8.0  \n",
       "6       7.0          14.0        9.0  \n",
       "7      31.0          33.0       37.0  \n",
       "\n",
       "[5 rows x 86 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1.drop([0,1,2],axis=0,inplace=True) # Remove first 3 rows\n",
    "data1.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://www.youtube.com/watch?v=zY4doF6xSxY&index=7&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# New Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data_raw[data_raw.notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "76984"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Potential</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>L. Messi</td>\n",
       "      <td>31</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>33</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Neymar Jr</td>\n",
       "      <td>26</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>De Gea</td>\n",
       "      <td>27</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>K. De Bruyne</td>\n",
       "      <td>27</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>E. Hazard</td>\n",
       "      <td>27</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>L. Modrić</td>\n",
       "      <td>32</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>L. Suárez</td>\n",
       "      <td>31</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sergio Ramos</td>\n",
       "      <td>32</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>J. Oblak</td>\n",
       "      <td>25</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>R. Lewandowski</td>\n",
       "      <td>29</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>T. Kroos</td>\n",
       "      <td>28</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>D. Godín</td>\n",
       "      <td>32</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>David Silva</td>\n",
       "      <td>32</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>N. Kanté</td>\n",
       "      <td>27</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>P. Dybala</td>\n",
       "      <td>24</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>H. Kane</td>\n",
       "      <td>24</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>A. Griezmann</td>\n",
       "      <td>27</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M. ter Stegen</td>\n",
       "      <td>26</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>T. Courtois</td>\n",
       "      <td>26</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Sergio Busquets</td>\n",
       "      <td>29</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>E. Cavani</td>\n",
       "      <td>31</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>M. Neuer</td>\n",
       "      <td>32</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>S. Agüero</td>\n",
       "      <td>30</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>G. Chiellini</td>\n",
       "      <td>33</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>K. Mbappé</td>\n",
       "      <td>19</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>M. Salah</td>\n",
       "      <td>26</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Casemiro</td>\n",
       "      <td>26</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>J. Rodríguez</td>\n",
       "      <td>26</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>L. Insigne</td>\n",
       "      <td>27</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18177</th>\n",
       "      <td>R. Roache</td>\n",
       "      <td>18</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18178</th>\n",
       "      <td>L. Wahlstedt</td>\n",
       "      <td>18</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18179</th>\n",
       "      <td>J. Williams</td>\n",
       "      <td>17</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18180</th>\n",
       "      <td>M. Hurst</td>\n",
       "      <td>22</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18181</th>\n",
       "      <td>C. Maher</td>\n",
       "      <td>17</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18182</th>\n",
       "      <td>Y. Góez</td>\n",
       "      <td>18</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18183</th>\n",
       "      <td>K. Pilkington</td>\n",
       "      <td>44</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18184</th>\n",
       "      <td>D. Horton</td>\n",
       "      <td>18</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18185</th>\n",
       "      <td>E. Tweed</td>\n",
       "      <td>19</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18186</th>\n",
       "      <td>Zhang Yufeng</td>\n",
       "      <td>20</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18187</th>\n",
       "      <td>C. Ehlich</td>\n",
       "      <td>19</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18188</th>\n",
       "      <td>L. Collins</td>\n",
       "      <td>17</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18189</th>\n",
       "      <td>A. Kaltner</td>\n",
       "      <td>18</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18190</th>\n",
       "      <td>L. Watkins</td>\n",
       "      <td>18</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18191</th>\n",
       "      <td>J. Norville-Williams</td>\n",
       "      <td>18</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18192</th>\n",
       "      <td>S. Squire</td>\n",
       "      <td>18</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18193</th>\n",
       "      <td>N. Fuentes</td>\n",
       "      <td>18</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18194</th>\n",
       "      <td>J. Milli</td>\n",
       "      <td>18</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18195</th>\n",
       "      <td>S. Griffin</td>\n",
       "      <td>18</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18196</th>\n",
       "      <td>K. Fujikawa</td>\n",
       "      <td>19</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18197</th>\n",
       "      <td>D. Holland</td>\n",
       "      <td>18</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18198</th>\n",
       "      <td>J. Livesey</td>\n",
       "      <td>18</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18199</th>\n",
       "      <td>M. Baldisimo</td>\n",
       "      <td>18</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18200</th>\n",
       "      <td>J. Young</td>\n",
       "      <td>18</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18201</th>\n",
       "      <td>D. Walsh</td>\n",
       "      <td>18</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18202</th>\n",
       "      <td>J. Lundstram</td>\n",
       "      <td>19</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18203</th>\n",
       "      <td>N. Christoffersson</td>\n",
       "      <td>19</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18204</th>\n",
       "      <td>B. Worman</td>\n",
       "      <td>16</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18205</th>\n",
       "      <td>D. Walker-Rice</td>\n",
       "      <td>17</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18206</th>\n",
       "      <td>G. Nugent</td>\n",
       "      <td>16</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18207 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Name  Age  Potential\n",
       "0                  L. Messi   31         94\n",
       "1         Cristiano Ronaldo   33         94\n",
       "2                 Neymar Jr   26         93\n",
       "3                    De Gea   27         93\n",
       "4              K. De Bruyne   27         92\n",
       "5                 E. Hazard   27         91\n",
       "6                 L. Modrić   32         91\n",
       "7                 L. Suárez   31         91\n",
       "8              Sergio Ramos   32         91\n",
       "9                  J. Oblak   25         93\n",
       "10           R. Lewandowski   29         90\n",
       "11                 T. Kroos   28         90\n",
       "12                 D. Godín   32         90\n",
       "13              David Silva   32         90\n",
       "14                 N. Kanté   27         90\n",
       "15                P. Dybala   24         94\n",
       "16                  H. Kane   24         91\n",
       "17             A. Griezmann   27         90\n",
       "18            M. ter Stegen   26         92\n",
       "19              T. Courtois   26         90\n",
       "20          Sergio Busquets   29         89\n",
       "21                E. Cavani   31         89\n",
       "22                 M. Neuer   32         89\n",
       "23                S. Agüero   30         89\n",
       "24             G. Chiellini   33         89\n",
       "25                K. Mbappé   19         95\n",
       "26                 M. Salah   26         89\n",
       "27                 Casemiro   26         90\n",
       "28             J. Rodríguez   26         89\n",
       "29               L. Insigne   27         88\n",
       "...                     ...  ...        ...\n",
       "18177             R. Roache   18         69\n",
       "18178          L. Wahlstedt   18         65\n",
       "18179           J. Williams   17         64\n",
       "18180              M. Hurst   22         58\n",
       "18181              C. Maher   17         66\n",
       "18182               Y. Góez   18         65\n",
       "18183         K. Pilkington   44         48\n",
       "18184             D. Horton   18         55\n",
       "18185              E. Tweed   19         59\n",
       "18186          Zhang Yufeng   20         64\n",
       "18187             C. Ehlich   19         59\n",
       "18188            L. Collins   17         62\n",
       "18189            A. Kaltner   18         61\n",
       "18190            L. Watkins   18         67\n",
       "18191  J. Norville-Williams   18         65\n",
       "18192             S. Squire   18         64\n",
       "18193            N. Fuentes   18         64\n",
       "18194              J. Milli   18         65\n",
       "18195            S. Griffin   18         67\n",
       "18196           K. Fujikawa   19         61\n",
       "18197            D. Holland   18         61\n",
       "18198            J. Livesey   18         70\n",
       "18199          M. Baldisimo   18         69\n",
       "18200              J. Young   18         62\n",
       "18201              D. Walsh   18         68\n",
       "18202          J. Lundstram   19         65\n",
       "18203    N. Christoffersson   19         63\n",
       "18204             B. Worman   16         67\n",
       "18205        D. Walker-Rice   17         66\n",
       "18206             G. Nugent   16         66\n",
       "\n",
       "[18207 rows x 3 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['Name','Age','Potential']][data.notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "d1 = data[['Name','Age','Potential','Overall','Vision']][data.Age==19]\n",
    "d2 = data[['Name','Age','Potential','Overall','Vision']][data.Age==25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\Anaconda3\\lib\\site-packages\\numpy\\lib\\histograms.py:754: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "C:\\Users\\DELL\\Anaconda3\\lib\\site-packages\\numpy\\lib\\histograms.py:755: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure() #Plots in matplotlib reside within a figure object, use plt.figure to create new figure\n",
    "#Create one or more subplots using add_subplot, because you can't create blank figure\n",
    "ax = fig.add_subplot(1,1,1)\n",
    "#Variable\n",
    "ax.hist(d1['Vision'],bins = 5) # Here you can play with number of bins\n",
    "plt.title('Age 19')\n",
    "plt.xlabel('V')\n",
    "plt.ylabel('Number of Players')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\DELL\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(data['Age'], data['Vision']) #Variable Plot\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure() #Plots in matplotlib reside within a figure object, use plt.figure to create new figure\n",
    "#Create one or more subplots using add_subplot, because you can't create blank figure\n",
    "ax = fig.add_subplot(1,1,1)\n",
    "#Variable\n",
    "ax.hist(d2['Vision'],bins = 5) # Here you can play with number of bins\n",
    "plt.title('Age 25')\n",
    "plt.xlabel('V')\n",
    "plt.ylabel('Number of Players')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}