Data Science 1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.preprocessing import scale\n",
    "from customplot import *\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cnx=sqlite3.connect('database.sqlite')\n",
    "df=pd.read_sql_query(\"SELECT * FROM Player_Attributes\",cnx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'player_fifa_api_id', 'player_api_id', 'date', 'overall_rating',\n",
       "       'potential', 'preferred_foot', 'attacking_work_rate',\n",
       "       'defensive_work_rate', 'crossing', 'finishing', 'heading_accuracy',\n",
       "       'short_passing', 'volleys', 'dribbling', 'curve', 'free_kick_accuracy',\n",
       "       'long_passing', 'ball_control', 'acceleration', 'sprint_speed',\n",
       "       'agility', 'reactions', 'balance', 'shot_power', 'jumping', 'stamina',\n",
       "       'strength', 'long_shots', 'aggression', 'interceptions', 'positioning',\n",
       "       'vision', 'penalties', 'marking', 'standing_tackle', 'sliding_tackle',\n",
       "       'gk_diving', 'gk_handling', 'gk_kicking', 'gk_positioning',\n",
       "       'gk_reflexes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>183978.0</td>\n",
       "      <td>91989.500000</td>\n",
       "      <td>53110.018250</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45995.25</td>\n",
       "      <td>91989.5</td>\n",
       "      <td>137983.75</td>\n",
       "      <td>183978.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>player_fifa_api_id</th>\n",
       "      <td>183978.0</td>\n",
       "      <td>165671.524291</td>\n",
       "      <td>53851.094769</td>\n",
       "      <td>2.0</td>\n",
       "      <td>155798.00</td>\n",
       "      <td>183488.0</td>\n",
       "      <td>199848.00</td>\n",
       "      <td>234141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>player_api_id</th>\n",
       "      <td>183978.0</td>\n",
       "      <td>135900.617324</td>\n",
       "      <td>136927.840510</td>\n",
       "      <td>2625.0</td>\n",
       "      <td>34763.00</td>\n",
       "      <td>77741.0</td>\n",
       "      <td>191080.00</td>\n",
       "      <td>750584.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>overall_rating</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>68.600015</td>\n",
       "      <td>7.041139</td>\n",
       "      <td>33.0</td>\n",
       "      <td>64.00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>73.00</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>potential</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>73.460353</td>\n",
       "      <td>6.592271</td>\n",
       "      <td>39.0</td>\n",
       "      <td>69.00</td>\n",
       "      <td>74.0</td>\n",
       "      <td>78.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>crossing</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>55.086883</td>\n",
       "      <td>17.242135</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45.00</td>\n",
       "      <td>59.0</td>\n",
       "      <td>68.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>finishing</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>49.921078</td>\n",
       "      <td>19.038705</td>\n",
       "      <td>1.0</td>\n",
       "      <td>34.00</td>\n",
       "      <td>53.0</td>\n",
       "      <td>65.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>heading_accuracy</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>57.266023</td>\n",
       "      <td>16.488905</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49.00</td>\n",
       "      <td>60.0</td>\n",
       "      <td>68.00</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>short_passing</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>62.429672</td>\n",
       "      <td>14.194068</td>\n",
       "      <td>3.0</td>\n",
       "      <td>57.00</td>\n",
       "      <td>65.0</td>\n",
       "      <td>72.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>volleys</th>\n",
       "      <td>181265.0</td>\n",
       "      <td>49.468436</td>\n",
       "      <td>18.256618</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>52.0</td>\n",
       "      <td>64.00</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dribbling</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>59.175154</td>\n",
       "      <td>17.744688</td>\n",
       "      <td>1.0</td>\n",
       "      <td>52.00</td>\n",
       "      <td>64.0</td>\n",
       "      <td>72.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>curve</th>\n",
       "      <td>181265.0</td>\n",
       "      <td>52.965675</td>\n",
       "      <td>18.255788</td>\n",
       "      <td>2.0</td>\n",
       "      <td>41.00</td>\n",
       "      <td>56.0</td>\n",
       "      <td>67.00</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>free_kick_accuracy</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>49.380950</td>\n",
       "      <td>17.831746</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.00</td>\n",
       "      <td>50.0</td>\n",
       "      <td>63.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>long_passing</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>57.069880</td>\n",
       "      <td>14.394464</td>\n",
       "      <td>3.0</td>\n",
       "      <td>49.00</td>\n",
       "      <td>59.0</td>\n",
       "      <td>67.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ball_control</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>63.388879</td>\n",
       "      <td>15.196671</td>\n",
       "      <td>5.0</td>\n",
       "      <td>58.00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>73.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acceleration</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>67.659357</td>\n",
       "      <td>12.983326</td>\n",
       "      <td>10.0</td>\n",
       "      <td>61.00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>77.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sprint_speed</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>68.051244</td>\n",
       "      <td>12.569721</td>\n",
       "      <td>12.0</td>\n",
       "      <td>62.00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>77.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>agility</th>\n",
       "      <td>181265.0</td>\n",
       "      <td>65.970910</td>\n",
       "      <td>12.954585</td>\n",
       "      <td>11.0</td>\n",
       "      <td>58.00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>75.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reactions</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>66.103706</td>\n",
       "      <td>9.155408</td>\n",
       "      <td>17.0</td>\n",
       "      <td>61.00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>72.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>balance</th>\n",
       "      <td>181265.0</td>\n",
       "      <td>65.189496</td>\n",
       "      <td>13.063188</td>\n",
       "      <td>12.0</td>\n",
       "      <td>58.00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>74.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shot_power</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>61.808427</td>\n",
       "      <td>16.135143</td>\n",
       "      <td>2.0</td>\n",
       "      <td>54.00</td>\n",
       "      <td>65.0</td>\n",
       "      <td>73.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>jumping</th>\n",
       "      <td>181265.0</td>\n",
       "      <td>66.969045</td>\n",
       "      <td>11.006734</td>\n",
       "      <td>14.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>74.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stamina</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>67.038544</td>\n",
       "      <td>13.165262</td>\n",
       "      <td>10.0</td>\n",
       "      <td>61.00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>76.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>strength</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>67.424529</td>\n",
       "      <td>12.072280</td>\n",
       "      <td>10.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>76.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>long_shots</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>53.339431</td>\n",
       "      <td>18.367025</td>\n",
       "      <td>1.0</td>\n",
       "      <td>41.00</td>\n",
       "      <td>58.0</td>\n",
       "      <td>67.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>aggression</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>60.948046</td>\n",
       "      <td>16.089521</td>\n",
       "      <td>6.0</td>\n",
       "      <td>51.00</td>\n",
       "      <td>64.0</td>\n",
       "      <td>73.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>interceptions</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>52.009271</td>\n",
       "      <td>19.450133</td>\n",
       "      <td>1.0</td>\n",
       "      <td>34.00</td>\n",
       "      <td>57.0</td>\n",
       "      <td>68.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>positioning</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>55.786504</td>\n",
       "      <td>18.448292</td>\n",
       "      <td>2.0</td>\n",
       "      <td>45.00</td>\n",
       "      <td>60.0</td>\n",
       "      <td>69.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vision</th>\n",
       "      <td>181265.0</td>\n",
       "      <td>57.873550</td>\n",
       "      <td>15.144086</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49.00</td>\n",
       "      <td>60.0</td>\n",
       "      <td>69.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>penalties</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>55.003986</td>\n",
       "      <td>15.546519</td>\n",
       "      <td>2.0</td>\n",
       "      <td>45.00</td>\n",
       "      <td>57.0</td>\n",
       "      <td>67.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marking</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>46.772242</td>\n",
       "      <td>21.227667</td>\n",
       "      <td>1.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>50.0</td>\n",
       "      <td>66.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>standing_tackle</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>50.351257</td>\n",
       "      <td>21.483706</td>\n",
       "      <td>1.0</td>\n",
       "      <td>29.00</td>\n",
       "      <td>56.0</td>\n",
       "      <td>69.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sliding_tackle</th>\n",
       "      <td>181265.0</td>\n",
       "      <td>48.001462</td>\n",
       "      <td>21.598778</td>\n",
       "      <td>2.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>53.0</td>\n",
       "      <td>67.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gk_diving</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>14.704393</td>\n",
       "      <td>16.865467</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.00</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.00</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gk_handling</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>16.063612</td>\n",
       "      <td>15.867382</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gk_kicking</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>20.998362</td>\n",
       "      <td>21.452980</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gk_positioning</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>16.132154</td>\n",
       "      <td>16.099175</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gk_reflexes</th>\n",
       "      <td>183142.0</td>\n",
       "      <td>16.441439</td>\n",
       "      <td>17.198155</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       count           mean            std     min        25%  \\\n",
       "id                  183978.0   91989.500000   53110.018250     1.0   45995.25   \n",
       "player_fifa_api_id  183978.0  165671.524291   53851.094769     2.0  155798.00   \n",
       "player_api_id       183978.0  135900.617324  136927.840510  2625.0   34763.00   \n",
       "overall_rating      183142.0      68.600015       7.041139    33.0      64.00   \n",
       "potential           183142.0      73.460353       6.592271    39.0      69.00   \n",
       "crossing            183142.0      55.086883      17.242135     1.0      45.00   \n",
       "finishing           183142.0      49.921078      19.038705     1.0      34.00   \n",
       "heading_accuracy    183142.0      57.266023      16.488905     1.0      49.00   \n",
       "short_passing       183142.0      62.429672      14.194068     3.0      57.00   \n",
       "volleys             181265.0      49.468436      18.256618     1.0      35.00   \n",
       "dribbling           183142.0      59.175154      17.744688     1.0      52.00   \n",
       "curve               181265.0      52.965675      18.255788     2.0      41.00   \n",
       "free_kick_accuracy  183142.0      49.380950      17.831746     1.0      36.00   \n",
       "long_passing        183142.0      57.069880      14.394464     3.0      49.00   \n",
       "ball_control        183142.0      63.388879      15.196671     5.0      58.00   \n",
       "acceleration        183142.0      67.659357      12.983326    10.0      61.00   \n",
       "sprint_speed        183142.0      68.051244      12.569721    12.0      62.00   \n",
       "agility             181265.0      65.970910      12.954585    11.0      58.00   \n",
       "reactions           183142.0      66.103706       9.155408    17.0      61.00   \n",
       "balance             181265.0      65.189496      13.063188    12.0      58.00   \n",
       "shot_power          183142.0      61.808427      16.135143     2.0      54.00   \n",
       "jumping             181265.0      66.969045      11.006734    14.0      60.00   \n",
       "stamina             183142.0      67.038544      13.165262    10.0      61.00   \n",
       "strength            183142.0      67.424529      12.072280    10.0      60.00   \n",
       "long_shots          183142.0      53.339431      18.367025     1.0      41.00   \n",
       "aggression          183142.0      60.948046      16.089521     6.0      51.00   \n",
       "interceptions       183142.0      52.009271      19.450133     1.0      34.00   \n",
       "positioning         183142.0      55.786504      18.448292     2.0      45.00   \n",
       "vision              181265.0      57.873550      15.144086     1.0      49.00   \n",
       "penalties           183142.0      55.003986      15.546519     2.0      45.00   \n",
       "marking             183142.0      46.772242      21.227667     1.0      25.00   \n",
       "standing_tackle     183142.0      50.351257      21.483706     1.0      29.00   \n",
       "sliding_tackle      181265.0      48.001462      21.598778     2.0      25.00   \n",
       "gk_diving           183142.0      14.704393      16.865467     1.0       7.00   \n",
       "gk_handling         183142.0      16.063612      15.867382     1.0       8.00   \n",
       "gk_kicking          183142.0      20.998362      21.452980     1.0       8.00   \n",
       "gk_positioning      183142.0      16.132154      16.099175     1.0       8.00   \n",
       "gk_reflexes         183142.0      16.441439      17.198155     1.0       8.00   \n",
       "\n",
       "                         50%        75%       max  \n",
       "id                   91989.5  137983.75  183978.0  \n",
       "player_fifa_api_id  183488.0  199848.00  234141.0  \n",
       "player_api_id        77741.0  191080.00  750584.0  \n",
       "overall_rating          69.0      73.00      94.0  \n",
       "potential               74.0      78.00      97.0  \n",
       "crossing                59.0      68.00      95.0  \n",
       "finishing               53.0      65.00      97.0  \n",
       "heading_accuracy        60.0      68.00      98.0  \n",
       "short_passing           65.0      72.00      97.0  \n",
       "volleys                 52.0      64.00      93.0  \n",
       "dribbling               64.0      72.00      97.0  \n",
       "curve                   56.0      67.00      94.0  \n",
       "free_kick_accuracy      50.0      63.00      97.0  \n",
       "long_passing            59.0      67.00      97.0  \n",
       "ball_control            67.0      73.00      97.0  \n",
       "acceleration            69.0      77.00      97.0  \n",
       "sprint_speed            69.0      77.00      97.0  \n",
       "agility                 68.0      75.00      96.0  \n",
       "reactions               67.0      72.00      96.0  \n",
       "balance                 67.0      74.00      96.0  \n",
       "shot_power              65.0      73.00      97.0  \n",
       "jumping                 68.0      74.00      96.0  \n",
       "stamina                 69.0      76.00      96.0  \n",
       "strength                69.0      76.00      96.0  \n",
       "long_shots              58.0      67.00      96.0  \n",
       "aggression              64.0      73.00      97.0  \n",
       "interceptions           57.0      68.00      96.0  \n",
       "positioning             60.0      69.00      96.0  \n",
       "vision                  60.0      69.00      97.0  \n",
       "penalties               57.0      67.00      96.0  \n",
       "marking                 50.0      66.00      96.0  \n",
       "standing_tackle         56.0      69.00      95.0  \n",
       "sliding_tackle          53.0      67.00      95.0  \n",
       "gk_diving               10.0      13.00      94.0  \n",
       "gk_handling             11.0      15.00      93.0  \n",
       "gk_kicking              12.0      15.00      97.0  \n",
       "gk_positioning          11.0      15.00      96.0  \n",
       "gk_reflexes             11.0      15.00      96.0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>id</th>\n",
       "      <th>player_fifa_api_id</th>\n",
       "      <th>player_api_id</th>\n",
       "      <th>date</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>potential</th>\n",
       "      <th>preferred_foot</th>\n",
       "      <th>attacking_work_rate</th>\n",
       "      <th>defensive_work_rate</th>\n",
       "      <th>crossing</th>\n",
       "      <th>...</th>\n",
       "      <th>vision</th>\n",
       "      <th>penalties</th>\n",
       "      <th>marking</th>\n",
       "      <th>standing_tackle</th>\n",
       "      <th>sliding_tackle</th>\n",
       "      <th>gk_diving</th>\n",
       "      <th>gk_handling</th>\n",
       "      <th>gk_kicking</th>\n",
       "      <th>gk_positioning</th>\n",
       "      <th>gk_reflexes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</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>183948</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183949</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183950</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183951</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183952</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183953</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183954</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183955</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183956</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183957</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183958</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183959</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183960</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183961</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183962</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183963</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183964</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183965</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183966</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183967</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183968</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183969</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183970</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183971</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183972</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183973</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183974</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183975</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183976</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183977</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>183978 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  player_fifa_api_id  player_api_id   date  overall_rating  \\\n",
       "0       False               False          False  False           False   \n",
       "1       False               False          False  False           False   \n",
       "2       False               False          False  False           False   \n",
       "3       False               False          False  False           False   \n",
       "4       False               False          False  False           False   \n",
       "5       False               False          False  False           False   \n",
       "6       False               False          False  False           False   \n",
       "7       False               False          False  False           False   \n",
       "8       False               False          False  False           False   \n",
       "9       False               False          False  False           False   \n",
       "10      False               False          False  False           False   \n",
       "11      False               False          False  False           False   \n",
       "12      False               False          False  False           False   \n",
       "13      False               False          False  False           False   \n",
       "14      False               False          False  False           False   \n",
       "15      False               False          False  False           False   \n",
       "16      False               False          False  False           False   \n",
       "17      False               False          False  False           False   \n",
       "18      False               False          False  False           False   \n",
       "19      False               False          False  False           False   \n",
       "20      False               False          False  False           False   \n",
       "21      False               False          False  False           False   \n",
       "22      False               False          False  False           False   \n",
       "23      False               False          False  False           False   \n",
       "24      False               False          False  False           False   \n",
       "25      False               False          False  False           False   \n",
       "26      False               False          False  False           False   \n",
       "27      False               False          False  False           False   \n",
       "28      False               False          False  False           False   \n",
       "29      False               False          False  False           False   \n",
       "...       ...                 ...            ...    ...             ...   \n",
       "183948  False               False          False  False           False   \n",
       "183949  False               False          False  False           False   \n",
       "183950  False               False          False  False           False   \n",
       "183951  False               False          False  False           False   \n",
       "183952  False               False          False  False           False   \n",
       "183953  False               False          False  False           False   \n",
       "183954  False               False          False  False           False   \n",
       "183955  False               False          False  False           False   \n",
       "183956  False               False          False  False           False   \n",
       "183957  False               False          False  False           False   \n",
       "183958  False               False          False  False           False   \n",
       "183959  False               False          False  False           False   \n",
       "183960  False               False          False  False           False   \n",
       "183961  False               False          False  False           False   \n",
       "183962  False               False          False  False           False   \n",
       "183963  False               False          False  False           False   \n",
       "183964  False               False          False  False           False   \n",
       "183965  False               False          False  False           False   \n",
       "183966  False               False          False  False           False   \n",
       "183967  False               False          False  False           False   \n",
       "183968  False               False          False  False           False   \n",
       "183969  False               False          False  False           False   \n",
       "183970  False               False          False  False           False   \n",
       "183971  False               False          False  False           False   \n",
       "183972  False               False          False  False           False   \n",
       "183973  False               False          False  False           False   \n",
       "183974  False               False          False  False           False   \n",
       "183975  False               False          False  False           False   \n",
       "183976  False               False          False  False           False   \n",
       "183977  False               False          False  False           False   \n",
       "\n",
       "        potential  preferred_foot  attacking_work_rate  defensive_work_rate  \\\n",
       "0           False           False                False                False   \n",
       "1           False           False                False                False   \n",
       "2           False           False                False                False   \n",
       "3           False           False                False                False   \n",
       "4           False           False                False                False   \n",
       "5           False           False                False                False   \n",
       "6           False           False                False                False   \n",
       "7           False           False                False                False   \n",
       "8           False           False                False                False   \n",
       "9           False           False                False                False   \n",
       "10          False           False                False                False   \n",
       "11          False           False                False                False   \n",
       "12          False           False                False                False   \n",
       "13          False           False                False                False   \n",
       "14          False           False                False                False   \n",
       "15          False           False                False                False   \n",
       "16          False           False                False                False   \n",
       "17          False           False                False                False   \n",
       "18          False           False                False                False   \n",
       "19          False           False                False                False   \n",
       "20          False           False                False                False   \n",
       "21          False           False                False                False   \n",
       "22          False           False                False                False   \n",
       "23          False           False                False                False   \n",
       "24          False           False                False                False   \n",
       "25          False           False                False                False   \n",
       "26          False           False                False                False   \n",
       "27          False           False                False                False   \n",
       "28          False           False                False                False   \n",
       "29          False           False                False                False   \n",
       "...           ...             ...                  ...                  ...   \n",
       "183948      False           False                False                False   \n",
       "183949      False           False                False                False   \n",
       "183950      False           False                False                False   \n",
       "183951      False           False                False                False   \n",
       "183952      False           False                False                False   \n",
       "183953      False           False                 True                False   \n",
       "183954      False           False                 True                False   \n",
       "183955      False           False                 True                False   \n",
       "183956      False           False                 True                False   \n",
       "183957      False           False                 True                False   \n",
       "183958      False           False                 True                False   \n",
       "183959      False           False                 True                False   \n",
       "183960      False           False                 True                False   \n",
       "183961      False           False                 True                False   \n",
       "183962      False           False                 True                False   \n",
       "183963      False           False                 True                False   \n",
       "183964      False           False                 True                False   \n",
       "183965      False           False                 True                False   \n",
       "183966      False           False                 True                False   \n",
       "183967      False           False                 True                False   \n",
       "183968      False           False                False                False   \n",
       "183969      False           False                False                False   \n",
       "183970      False           False                False                False   \n",
       "183971      False           False                False                False   \n",
       "183972      False           False                False                False   \n",
       "183973      False           False                False                False   \n",
       "183974      False           False                False                False   \n",
       "183975      False           False                False                False   \n",
       "183976      False           False                False                False   \n",
       "183977      False           False                False                False   \n",
       "\n",
       "        crossing     ...       vision  penalties  marking  standing_tackle  \\\n",
       "0          False     ...        False      False    False            False   \n",
       "1          False     ...        False      False    False            False   \n",
       "2          False     ...        False      False    False            False   \n",
       "3          False     ...        False      False    False            False   \n",
       "4          False     ...        False      False    False            False   \n",
       "5          False     ...        False      False    False            False   \n",
       "6          False     ...        False      False    False            False   \n",
       "7          False     ...        False      False    False            False   \n",
       "8          False     ...        False      False    False            False   \n",
       "9          False     ...        False      False    False            False   \n",
       "10         False     ...        False      False    False            False   \n",
       "11         False     ...        False      False    False            False   \n",
       "12         False     ...        False      False    False            False   \n",
       "13         False     ...        False      False    False            False   \n",
       "14         False     ...        False      False    False            False   \n",
       "15         False     ...        False      False    False            False   \n",
       "16         False     ...        False      False    False            False   \n",
       "17         False     ...        False      False    False            False   \n",
       "18         False     ...        False      False    False            False   \n",
       "19         False     ...        False      False    False            False   \n",
       "20         False     ...        False      False    False            False   \n",
       "21         False     ...        False      False    False            False   \n",
       "22         False     ...        False      False    False            False   \n",
       "23         False     ...        False      False    False            False   \n",
       "24         False     ...        False      False    False            False   \n",
       "25         False     ...        False      False    False            False   \n",
       "26         False     ...        False      False    False            False   \n",
       "27         False     ...        False      False    False            False   \n",
       "28         False     ...        False      False    False            False   \n",
       "29         False     ...        False      False    False            False   \n",
       "...          ...     ...          ...        ...      ...              ...   \n",
       "183948     False     ...        False      False    False            False   \n",
       "183949     False     ...        False      False    False            False   \n",
       "183950     False     ...        False      False    False            False   \n",
       "183951     False     ...        False      False    False            False   \n",
       "183952     False     ...        False      False    False            False   \n",
       "183953     False     ...        False      False    False            False   \n",
       "183954     False     ...        False      False    False            False   \n",
       "183955     False     ...        False      False    False            False   \n",
       "183956     False     ...        False      False    False            False   \n",
       "183957     False     ...        False      False    False            False   \n",
       "183958     False     ...        False      False    False            False   \n",
       "183959     False     ...        False      False    False            False   \n",
       "183960     False     ...        False      False    False            False   \n",
       "183961     False     ...        False      False    False            False   \n",
       "183962     False     ...        False      False    False            False   \n",
       "183963     False     ...        False      False    False            False   \n",
       "183964     False     ...        False      False    False            False   \n",
       "183965     False     ...        False      False    False            False   \n",
       "183966     False     ...        False      False    False            False   \n",
       "183967     False     ...        False      False    False            False   \n",
       "183968     False     ...        False      False    False            False   \n",
       "183969     False     ...        False      False    False            False   \n",
       "183970     False     ...        False      False    False            False   \n",
       "183971     False     ...        False      False    False            False   \n",
       "183972     False     ...        False      False    False            False   \n",
       "183973     False     ...        False      False    False            False   \n",
       "183974     False     ...        False      False    False            False   \n",
       "183975     False     ...        False      False    False            False   \n",
       "183976     False     ...        False      False    False            False   \n",
       "183977     False     ...        False      False    False            False   \n",
       "\n",
       "        sliding_tackle  gk_diving  gk_handling  gk_kicking  gk_positioning  \\\n",
       "0                False      False        False       False           False   \n",
       "1                False      False        False       False           False   \n",
       "2                False      False        False       False           False   \n",
       "3                False      False        False       False           False   \n",
       "4                False      False        False       False           False   \n",
       "5                False      False        False       False           False   \n",
       "6                False      False        False       False           False   \n",
       "7                False      False        False       False           False   \n",
       "8                False      False        False       False           False   \n",
       "9                False      False        False       False           False   \n",
       "10               False      False        False       False           False   \n",
       "11               False      False        False       False           False   \n",
       "12               False      False        False       False           False   \n",
       "13               False      False        False       False           False   \n",
       "14               False      False        False       False           False   \n",
       "15               False      False        False       False           False   \n",
       "16               False      False        False       False           False   \n",
       "17               False      False        False       False           False   \n",
       "18               False      False        False       False           False   \n",
       "19               False      False        False       False           False   \n",
       "20               False      False        False       False           False   \n",
       "21               False      False        False       False           False   \n",
       "22               False      False        False       False           False   \n",
       "23               False      False        False       False           False   \n",
       "24               False      False        False       False           False   \n",
       "25               False      False        False       False           False   \n",
       "26               False      False        False       False           False   \n",
       "27               False      False        False       False           False   \n",
       "28               False      False        False       False           False   \n",
       "29               False      False        False       False           False   \n",
       "...                ...        ...          ...         ...             ...   \n",
       "183948           False      False        False       False           False   \n",
       "183949           False      False        False       False           False   \n",
       "183950           False      False        False       False           False   \n",
       "183951           False      False        False       False           False   \n",
       "183952           False      False        False       False           False   \n",
       "183953           False      False        False       False           False   \n",
       "183954           False      False        False       False           False   \n",
       "183955           False      False        False       False           False   \n",
       "183956           False      False        False       False           False   \n",
       "183957           False      False        False       False           False   \n",
       "183958           False      False        False       False           False   \n",
       "183959           False      False        False       False           False   \n",
       "183960           False      False        False       False           False   \n",
       "183961           False      False        False       False           False   \n",
       "183962           False      False        False       False           False   \n",
       "183963           False      False        False       False           False   \n",
       "183964           False      False        False       False           False   \n",
       "183965           False      False        False       False           False   \n",
       "183966           False      False        False       False           False   \n",
       "183967           False      False        False       False           False   \n",
       "183968           False      False        False       False           False   \n",
       "183969           False      False        False       False           False   \n",
       "183970           False      False        False       False           False   \n",
       "183971           False      False        False       False           False   \n",
       "183972           False      False        False       False           False   \n",
       "183973           False      False        False       False           False   \n",
       "183974           False      False        False       False           False   \n",
       "183975           False      False        False       False           False   \n",
       "183976           False      False        False       False           False   \n",
       "183977           False      False        False       False           False   \n",
       "\n",
       "        gk_reflexes  \n",
       "0             False  \n",
       "1             False  \n",
       "2             False  \n",
       "3             False  \n",
       "4             False  \n",
       "5             False  \n",
       "6             False  \n",
       "7             False  \n",
       "8             False  \n",
       "9             False  \n",
       "10            False  \n",
       "11            False  \n",
       "12            False  \n",
       "13            False  \n",
       "14            False  \n",
       "15            False  \n",
       "16            False  \n",
       "17            False  \n",
       "18            False  \n",
       "19            False  \n",
       "20            False  \n",
       "21            False  \n",
       "22            False  \n",
       "23            False  \n",
       "24            False  \n",
       "25            False  \n",
       "26            False  \n",
       "27            False  \n",
       "28            False  \n",
       "29            False  \n",
       "...             ...  \n",
       "183948        False  \n",
       "183949        False  \n",
       "183950        False  \n",
       "183951        False  \n",
       "183952        False  \n",
       "183953        False  \n",
       "183954        False  \n",
       "183955        False  \n",
       "183956        False  \n",
       "183957        False  \n",
       "183958        False  \n",
       "183959        False  \n",
       "183960        False  \n",
       "183961        False  \n",
       "183962        False  \n",
       "183963        False  \n",
       "183964        False  \n",
       "183965        False  \n",
       "183966        False  \n",
       "183967        False  \n",
       "183968        False  \n",
       "183969        False  \n",
       "183970        False  \n",
       "183971        False  \n",
       "183972        False  \n",
       "183973        False  \n",
       "183974        False  \n",
       "183975        False  \n",
       "183976        False  \n",
       "183977        False  \n",
       "\n",
       "[183978 rows x 42 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(True, (183978, 42))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().any().any(),df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                        0\n",
       "player_fifa_api_id        0\n",
       "player_api_id             0\n",
       "date                      0\n",
       "overall_rating          836\n",
       "potential               836\n",
       "preferred_foot          836\n",
       "attacking_work_rate    3230\n",
       "defensive_work_rate     836\n",
       "crossing                836\n",
       "finishing               836\n",
       "heading_accuracy        836\n",
       "short_passing           836\n",
       "volleys                2713\n",
       "dribbling               836\n",
       "curve                  2713\n",
       "free_kick_accuracy      836\n",
       "long_passing            836\n",
       "ball_control            836\n",
       "acceleration            836\n",
       "sprint_speed            836\n",
       "agility                2713\n",
       "reactions               836\n",
       "balance                2713\n",
       "shot_power              836\n",
       "jumping                2713\n",
       "stamina                 836\n",
       "strength                836\n",
       "long_shots              836\n",
       "aggression              836\n",
       "interceptions           836\n",
       "positioning             836\n",
       "vision                 2713\n",
       "penalties               836\n",
       "marking                 836\n",
       "standing_tackle         836\n",
       "sliding_tackle         2713\n",
       "gk_diving               836\n",
       "gk_handling             836\n",
       "gk_kicking              836\n",
       "gk_positioning          836\n",
       "gk_reflexes             836\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fixing null values\n",
    "rows=df.shape[0]\n",
    "df=df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(False, (180354, 42))"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().any().any(),df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3624"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# rows with null values\n",
    "rows-df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# shuffling the rows of the df to get\n",
    "# a distributed sampe when the top rows are displayed\n",
    "df=df.reindex(np.random.permutation(df.index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>id</th>\n",
       "      <th>player_fifa_api_id</th>\n",
       "      <th>player_api_id</th>\n",
       "      <th>date</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>potential</th>\n",
       "      <th>preferred_foot</th>\n",
       "      <th>attacking_work_rate</th>\n",
       "      <th>defensive_work_rate</th>\n",
       "      <th>crossing</th>\n",
       "      <th>...</th>\n",
       "      <th>vision</th>\n",
       "      <th>penalties</th>\n",
       "      <th>marking</th>\n",
       "      <th>standing_tackle</th>\n",
       "      <th>sliding_tackle</th>\n",
       "      <th>gk_diving</th>\n",
       "      <th>gk_handling</th>\n",
       "      <th>gk_kicking</th>\n",
       "      <th>gk_positioning</th>\n",
       "      <th>gk_reflexes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>161135</th>\n",
       "      <td>161136</td>\n",
       "      <td>135697</td>\n",
       "      <td>38578</td>\n",
       "      <td>2015-02-13 00:00:00</td>\n",
       "      <td>79.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>66.0</td>\n",
       "      <td>...</td>\n",
       "      <td>76.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108720</th>\n",
       "      <td>108721</td>\n",
       "      <td>113343</td>\n",
       "      <td>23686</td>\n",
       "      <td>2007-02-22 00:00:00</td>\n",
       "      <td>73.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183453</th>\n",
       "      <td>183454</td>\n",
       "      <td>223339</td>\n",
       "      <td>570159</td>\n",
       "      <td>2015-10-16 00:00:00</td>\n",
       "      <td>71.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>low</td>\n",
       "      <td>67.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37646</th>\n",
       "      <td>37647</td>\n",
       "      <td>207998</td>\n",
       "      <td>254472</td>\n",
       "      <td>2013-02-15 00:00:00</td>\n",
       "      <td>57.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>12.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67392</th>\n",
       "      <td>67393</td>\n",
       "      <td>173228</td>\n",
       "      <td>40139</td>\n",
       "      <td>2011-08-30 00:00:00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>79.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152556</th>\n",
       "      <td>152557</td>\n",
       "      <td>184575</td>\n",
       "      <td>210398</td>\n",
       "      <td>2015-11-06 00:00:00</td>\n",
       "      <td>75.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>70.0</td>\n",
       "      <td>...</td>\n",
       "      <td>62.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29311</th>\n",
       "      <td>29312</td>\n",
       "      <td>207918</td>\n",
       "      <td>304017</td>\n",
       "      <td>2013-03-08 00:00:00</td>\n",
       "      <td>62.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>low</td>\n",
       "      <td>36.0</td>\n",
       "      <td>...</td>\n",
       "      <td>47.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183686</th>\n",
       "      <td>183687</td>\n",
       "      <td>41236</td>\n",
       "      <td>35724</td>\n",
       "      <td>2010-02-22 00:00:00</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>low</td>\n",
       "      <td>75.0</td>\n",
       "      <td>...</td>\n",
       "      <td>80.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180696</th>\n",
       "      <td>180697</td>\n",
       "      <td>200422</td>\n",
       "      <td>179179</td>\n",
       "      <td>2014-03-21 00:00:00</td>\n",
       "      <td>66.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>left</td>\n",
       "      <td>high</td>\n",
       "      <td>low</td>\n",
       "      <td>64.0</td>\n",
       "      <td>...</td>\n",
       "      <td>51.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95074</th>\n",
       "      <td>95075</td>\n",
       "      <td>204247</td>\n",
       "      <td>281936</td>\n",
       "      <td>2015-10-09 00:00:00</td>\n",
       "      <td>75.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>71.0</td>\n",
       "      <td>...</td>\n",
       "      <td>68.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139189</th>\n",
       "      <td>139190</td>\n",
       "      <td>206098</td>\n",
       "      <td>358149</td>\n",
       "      <td>2016-03-24 00:00:00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>65.0</td>\n",
       "      <td>...</td>\n",
       "      <td>62.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59614</th>\n",
       "      <td>59615</td>\n",
       "      <td>142241</td>\n",
       "      <td>70320</td>\n",
       "      <td>2013-04-12 00:00:00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>low</td>\n",
       "      <td>65.0</td>\n",
       "      <td>...</td>\n",
       "      <td>66.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86627</th>\n",
       "      <td>86628</td>\n",
       "      <td>169588</td>\n",
       "      <td>43248</td>\n",
       "      <td>2014-03-14 00:00:00</td>\n",
       "      <td>79.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>right</td>\n",
       "      <td>low</td>\n",
       "      <td>medium</td>\n",
       "      <td>51.0</td>\n",
       "      <td>...</td>\n",
       "      <td>44.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31391</th>\n",
       "      <td>31392</td>\n",
       "      <td>101336</td>\n",
       "      <td>35989</td>\n",
       "      <td>2010-08-30 00:00:00</td>\n",
       "      <td>74.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>74.0</td>\n",
       "      <td>...</td>\n",
       "      <td>74.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3699</th>\n",
       "      <td>3700</td>\n",
       "      <td>210259</td>\n",
       "      <td>403003</td>\n",
       "      <td>2014-10-17 00:00:00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>low</td>\n",
       "      <td>29.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44426</th>\n",
       "      <td>44427</td>\n",
       "      <td>191487</td>\n",
       "      <td>167069</td>\n",
       "      <td>2011-02-22 00:00:00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>63.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99595</th>\n",
       "      <td>99596</td>\n",
       "      <td>190500</td>\n",
       "      <td>105327</td>\n",
       "      <td>2013-03-08 00:00:00</td>\n",
       "      <td>62.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>52.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62848</th>\n",
       "      <td>62849</td>\n",
       "      <td>137551</td>\n",
       "      <td>25643</td>\n",
       "      <td>2013-02-22 00:00:00</td>\n",
       "      <td>73.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>71.0</td>\n",
       "      <td>...</td>\n",
       "      <td>76.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118815</th>\n",
       "      <td>118816</td>\n",
       "      <td>205362</td>\n",
       "      <td>213485</td>\n",
       "      <td>2012-08-31 00:00:00</td>\n",
       "      <td>75.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>45.0</td>\n",
       "      <td>...</td>\n",
       "      <td>39.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88257</th>\n",
       "      <td>88258</td>\n",
       "      <td>192463</td>\n",
       "      <td>165607</td>\n",
       "      <td>2010-08-30 00:00:00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20401</th>\n",
       "      <td>20402</td>\n",
       "      <td>107280</td>\n",
       "      <td>40718</td>\n",
       "      <td>2007-02-22 00:00:00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>55.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2701</th>\n",
       "      <td>2702</td>\n",
       "      <td>203377</td>\n",
       "      <td>261599</td>\n",
       "      <td>2015-02-27 00:00:00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>63.0</td>\n",
       "      <td>...</td>\n",
       "      <td>65.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159778</th>\n",
       "      <td>159779</td>\n",
       "      <td>189251</td>\n",
       "      <td>119525</td>\n",
       "      <td>2016-04-28 00:00:00</td>\n",
       "      <td>76.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>69.0</td>\n",
       "      <td>...</td>\n",
       "      <td>79.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105579</th>\n",
       "      <td>105580</td>\n",
       "      <td>136194</td>\n",
       "      <td>34106</td>\n",
       "      <td>2007-08-30 00:00:00</td>\n",
       "      <td>85.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>81.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63097</th>\n",
       "      <td>63098</td>\n",
       "      <td>138798</td>\n",
       "      <td>32678</td>\n",
       "      <td>2010-08-30 00:00:00</td>\n",
       "      <td>71.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>11.0</td>\n",
       "      <td>...</td>\n",
       "      <td>44.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56907</th>\n",
       "      <td>56908</td>\n",
       "      <td>45601</td>\n",
       "      <td>30679</td>\n",
       "      <td>2013-02-15 00:00:00</td>\n",
       "      <td>81.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>79.0</td>\n",
       "      <td>...</td>\n",
       "      <td>75.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48989</th>\n",
       "      <td>48990</td>\n",
       "      <td>225126</td>\n",
       "      <td>574642</td>\n",
       "      <td>2015-10-16 00:00:00</td>\n",
       "      <td>63.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>56.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27543</th>\n",
       "      <td>27544</td>\n",
       "      <td>199042</td>\n",
       "      <td>50638</td>\n",
       "      <td>2013-04-26 00:00:00</td>\n",
       "      <td>73.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>76.0</td>\n",
       "      <td>...</td>\n",
       "      <td>85.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63213</th>\n",
       "      <td>63214</td>\n",
       "      <td>215316</td>\n",
       "      <td>245555</td>\n",
       "      <td>2015-02-20 00:00:00</td>\n",
       "      <td>75.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>25.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169008</th>\n",
       "      <td>169009</td>\n",
       "      <td>186648</td>\n",
       "      <td>73116</td>\n",
       "      <td>2013-08-16 00:00:00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>51.0</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123756</th>\n",
       "      <td>123757</td>\n",
       "      <td>121937</td>\n",
       "      <td>27284</td>\n",
       "      <td>2015-03-06 00:00:00</td>\n",
       "      <td>73.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>25.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92503</th>\n",
       "      <td>92504</td>\n",
       "      <td>231823</td>\n",
       "      <td>728414</td>\n",
       "      <td>2016-04-07 00:00:00</td>\n",
       "      <td>59.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>28.0</td>\n",
       "      <td>...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129960</th>\n",
       "      <td>129961</td>\n",
       "      <td>225309</td>\n",
       "      <td>614449</td>\n",
       "      <td>2015-02-13 00:00:00</td>\n",
       "      <td>57.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>52.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93265</th>\n",
       "      <td>93266</td>\n",
       "      <td>187789</td>\n",
       "      <td>12692</td>\n",
       "      <td>2014-09-18 00:00:00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>65.0</td>\n",
       "      <td>...</td>\n",
       "      <td>64.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16750</th>\n",
       "      <td>16751</td>\n",
       "      <td>5047</td>\n",
       "      <td>46540</td>\n",
       "      <td>2007-02-22 00:00:00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>69.0</td>\n",
       "      <td>...</td>\n",
       "      <td>69.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52722</th>\n",
       "      <td>52723</td>\n",
       "      <td>177159</td>\n",
       "      <td>37357</td>\n",
       "      <td>2007-02-22 00:00:00</td>\n",
       "      <td>58.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>56.0</td>\n",
       "      <td>...</td>\n",
       "      <td>63.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119755</th>\n",
       "      <td>119756</td>\n",
       "      <td>138413</td>\n",
       "      <td>23073</td>\n",
       "      <td>2014-09-18 00:00:00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>left</td>\n",
       "      <td>low</td>\n",
       "      <td>high</td>\n",
       "      <td>48.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19047</th>\n",
       "      <td>19048</td>\n",
       "      <td>43020</td>\n",
       "      <td>24978</td>\n",
       "      <td>2013-05-17 00:00:00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>67.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27753</th>\n",
       "      <td>27754</td>\n",
       "      <td>195671</td>\n",
       "      <td>187266</td>\n",
       "      <td>2013-10-25 00:00:00</td>\n",
       "      <td>72.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>30.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79409</th>\n",
       "      <td>79410</td>\n",
       "      <td>5566</td>\n",
       "      <td>26329</td>\n",
       "      <td>2010-02-22 00:00:00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>right</td>\n",
       "      <td>norm</td>\n",
       "      <td>ormal</td>\n",
       "      <td>55.0</td>\n",
       "      <td>...</td>\n",
       "      <td>72.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135174</th>\n",
       "      <td>135175</td>\n",
       "      <td>204436</td>\n",
       "      <td>278867</td>\n",
       "      <td>2013-05-10 00:00:00</td>\n",
       "      <td>65.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>58.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104519</th>\n",
       "      <td>104520</td>\n",
       "      <td>210556</td>\n",
       "      <td>361747</td>\n",
       "      <td>2015-01-23 00:00:00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>40.0</td>\n",
       "      <td>...</td>\n",
       "      <td>52.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108787</th>\n",
       "      <td>108788</td>\n",
       "      <td>178412</td>\n",
       "      <td>102614</td>\n",
       "      <td>2013-09-20 00:00:00</td>\n",
       "      <td>64.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>51.0</td>\n",
       "      <td>...</td>\n",
       "      <td>43.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114011</th>\n",
       "      <td>114012</td>\n",
       "      <td>171018</td>\n",
       "      <td>37631</td>\n",
       "      <td>2015-09-21 00:00:00</td>\n",
       "      <td>79.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>66.0</td>\n",
       "      <td>...</td>\n",
       "      <td>76.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126234</th>\n",
       "      <td>126235</td>\n",
       "      <td>185132</td>\n",
       "      <td>182224</td>\n",
       "      <td>2007-02-22 00:00:00</td>\n",
       "      <td>56.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>38.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6229</th>\n",
       "      <td>6230</td>\n",
       "      <td>163925</td>\n",
       "      <td>41475</td>\n",
       "      <td>2015-01-16 00:00:00</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>left</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>68.0</td>\n",
       "      <td>...</td>\n",
       "      <td>79.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176814</th>\n",
       "      <td>176815</td>\n",
       "      <td>204550</td>\n",
       "      <td>172644</td>\n",
       "      <td>2015-07-03 00:00:00</td>\n",
       "      <td>78.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>72.0</td>\n",
       "      <td>...</td>\n",
       "      <td>71.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35125</th>\n",
       "      <td>35126</td>\n",
       "      <td>204963</td>\n",
       "      <td>282674</td>\n",
       "      <td>2015-09-21 00:00:00</td>\n",
       "      <td>81.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>79.0</td>\n",
       "      <td>...</td>\n",
       "      <td>57.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75082</th>\n",
       "      <td>75083</td>\n",
       "      <td>179620</td>\n",
       "      <td>109637</td>\n",
       "      <td>2011-08-30 00:00:00</td>\n",
       "      <td>70.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>65.0</td>\n",
       "      <td>...</td>\n",
       "      <td>74.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45726</th>\n",
       "      <td>45727</td>\n",
       "      <td>20613</td>\n",
       "      <td>38607</td>\n",
       "      <td>2009-08-30 00:00:00</td>\n",
       "      <td>68.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>77.0</td>\n",
       "      <td>...</td>\n",
       "      <td>66.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68215</th>\n",
       "      <td>68216</td>\n",
       "      <td>190738</td>\n",
       "      <td>171548</td>\n",
       "      <td>2014-09-18 00:00:00</td>\n",
       "      <td>70.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>64.0</td>\n",
       "      <td>...</td>\n",
       "      <td>63.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82644</th>\n",
       "      <td>82645</td>\n",
       "      <td>159447</td>\n",
       "      <td>164059</td>\n",
       "      <td>2013-09-20 00:00:00</td>\n",
       "      <td>64.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>61.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86117</th>\n",
       "      <td>86118</td>\n",
       "      <td>200298</td>\n",
       "      <td>193807</td>\n",
       "      <td>2013-09-20 00:00:00</td>\n",
       "      <td>63.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>right</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>66.0</td>\n",
       "      <td>...</td>\n",
       "      <td>31.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172153</th>\n",
       "      <td>172154</td>\n",
       "      <td>192617</td>\n",
       "      <td>141115</td>\n",
       "      <td>2015-12-03 00:00:00</td>\n",
       "      <td>70.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>left</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>74.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39074</th>\n",
       "      <td>39075</td>\n",
       "      <td>163890</td>\n",
       "      <td>37456</td>\n",
       "      <td>2013-03-22 00:00:00</td>\n",
       "      <td>70.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>10.0</td>\n",
       "      <td>...</td>\n",
       "      <td>33.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77671</th>\n",
       "      <td>77672</td>\n",
       "      <td>112244</td>\n",
       "      <td>30907</td>\n",
       "      <td>2010-02-22 00:00:00</td>\n",
       "      <td>79.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>81.0</td>\n",
       "      <td>...</td>\n",
       "      <td>83.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166932</th>\n",
       "      <td>166933</td>\n",
       "      <td>53993</td>\n",
       "      <td>24452</td>\n",
       "      <td>2013-02-15 00:00:00</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>32.0</td>\n",
       "      <td>...</td>\n",
       "      <td>47.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>188621</td>\n",
       "      <td>101042</td>\n",
       "      <td>2013-05-31 00:00:00</td>\n",
       "      <td>67.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>65.0</td>\n",
       "      <td>...</td>\n",
       "      <td>62.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126021</th>\n",
       "      <td>126022</td>\n",
       "      <td>209984</td>\n",
       "      <td>310199</td>\n",
       "      <td>2016-01-14 00:00:00</td>\n",
       "      <td>64.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>47.0</td>\n",
       "      <td>...</td>\n",
       "      <td>47.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178817</th>\n",
       "      <td>178818</td>\n",
       "      <td>210872</td>\n",
       "      <td>389202</td>\n",
       "      <td>2013-09-20 00:00:00</td>\n",
       "      <td>59.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>low</td>\n",
       "      <td>52.0</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>180354 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            id  player_fifa_api_id  player_api_id                 date  \\\n",
       "161135  161136              135697          38578  2015-02-13 00:00:00   \n",
       "108720  108721              113343          23686  2007-02-22 00:00:00   \n",
       "183453  183454              223339         570159  2015-10-16 00:00:00   \n",
       "37646    37647              207998         254472  2013-02-15 00:00:00   \n",
       "67392    67393              173228          40139  2011-08-30 00:00:00   \n",
       "152556  152557              184575         210398  2015-11-06 00:00:00   \n",
       "29311    29312              207918         304017  2013-03-08 00:00:00   \n",
       "183686  183687               41236          35724  2010-02-22 00:00:00   \n",
       "180696  180697              200422         179179  2014-03-21 00:00:00   \n",
       "95074    95075              204247         281936  2015-10-09 00:00:00   \n",
       "139189  139190              206098         358149  2016-03-24 00:00:00   \n",
       "59614    59615              142241          70320  2013-04-12 00:00:00   \n",
       "86627    86628              169588          43248  2014-03-14 00:00:00   \n",
       "31391    31392              101336          35989  2010-08-30 00:00:00   \n",
       "3699      3700              210259         403003  2014-10-17 00:00:00   \n",
       "44426    44427              191487         167069  2011-02-22 00:00:00   \n",
       "99595    99596              190500         105327  2013-03-08 00:00:00   \n",
       "62848    62849              137551          25643  2013-02-22 00:00:00   \n",
       "118815  118816              205362         213485  2012-08-31 00:00:00   \n",
       "88257    88258              192463         165607  2010-08-30 00:00:00   \n",
       "20401    20402              107280          40718  2007-02-22 00:00:00   \n",
       "2701      2702              203377         261599  2015-02-27 00:00:00   \n",
       "159778  159779              189251         119525  2016-04-28 00:00:00   \n",
       "105579  105580              136194          34106  2007-08-30 00:00:00   \n",
       "63097    63098              138798          32678  2010-08-30 00:00:00   \n",
       "56907    56908               45601          30679  2013-02-15 00:00:00   \n",
       "48989    48990              225126         574642  2015-10-16 00:00:00   \n",
       "27543    27544              199042          50638  2013-04-26 00:00:00   \n",
       "63213    63214              215316         245555  2015-02-20 00:00:00   \n",
       "169008  169009              186648          73116  2013-08-16 00:00:00   \n",
       "...        ...                 ...            ...                  ...   \n",
       "123756  123757              121937          27284  2015-03-06 00:00:00   \n",
       "92503    92504              231823         728414  2016-04-07 00:00:00   \n",
       "129960  129961              225309         614449  2015-02-13 00:00:00   \n",
       "93265    93266              187789          12692  2014-09-18 00:00:00   \n",
       "16750    16751                5047          46540  2007-02-22 00:00:00   \n",
       "52722    52723              177159          37357  2007-02-22 00:00:00   \n",
       "119755  119756              138413          23073  2014-09-18 00:00:00   \n",
       "19047    19048               43020          24978  2013-05-17 00:00:00   \n",
       "27753    27754              195671         187266  2013-10-25 00:00:00   \n",
       "79409    79410                5566          26329  2010-02-22 00:00:00   \n",
       "135174  135175              204436         278867  2013-05-10 00:00:00   \n",
       "104519  104520              210556         361747  2015-01-23 00:00:00   \n",
       "108787  108788              178412         102614  2013-09-20 00:00:00   \n",
       "114011  114012              171018          37631  2015-09-21 00:00:00   \n",
       "126234  126235              185132         182224  2007-02-22 00:00:00   \n",
       "6229      6230              163925          41475  2015-01-16 00:00:00   \n",
       "176814  176815              204550         172644  2015-07-03 00:00:00   \n",
       "35125    35126              204963         282674  2015-09-21 00:00:00   \n",
       "75082    75083              179620         109637  2011-08-30 00:00:00   \n",
       "45726    45727               20613          38607  2009-08-30 00:00:00   \n",
       "68215    68216              190738         171548  2014-09-18 00:00:00   \n",
       "82644    82645              159447         164059  2013-09-20 00:00:00   \n",
       "86117    86118              200298         193807  2013-09-20 00:00:00   \n",
       "172153  172154              192617         141115  2015-12-03 00:00:00   \n",
       "39074    39075              163890          37456  2013-03-22 00:00:00   \n",
       "77671    77672              112244          30907  2010-02-22 00:00:00   \n",
       "166932  166933               53993          24452  2013-02-15 00:00:00   \n",
       "189        190              188621         101042  2013-05-31 00:00:00   \n",
       "126021  126022              209984         310199  2016-01-14 00:00:00   \n",
       "178817  178818              210872         389202  2013-09-20 00:00:00   \n",
       "\n",
       "        overall_rating  potential preferred_foot attacking_work_rate  \\\n",
       "161135            79.0       79.0          right              medium   \n",
       "108720            73.0       76.0          right              medium   \n",
       "183453            71.0       77.0          right                high   \n",
       "37646             57.0       72.0          right              medium   \n",
       "67392             69.0       72.0           left              medium   \n",
       "152556            75.0       77.0           left              medium   \n",
       "29311             62.0       70.0          right                high   \n",
       "183686            88.0       90.0          right              medium   \n",
       "180696            66.0       72.0           left                high   \n",
       "95074             75.0       83.0          right                high   \n",
       "139189            68.0       74.0          right              medium   \n",
       "59614             68.0       70.0           left              medium   \n",
       "86627             79.0       82.0          right                 low   \n",
       "31391             74.0       83.0          right              medium   \n",
       "3699              69.0       80.0          right              medium   \n",
       "44426             68.0       79.0          right                high   \n",
       "99595             62.0       71.0          right                high   \n",
       "62848             73.0       73.0          right                high   \n",
       "118815            75.0       88.0           left              medium   \n",
       "88257             67.0       74.0           left              medium   \n",
       "20401             67.0       68.0          right              medium   \n",
       "2701              68.0       75.0          right              medium   \n",
       "159778            76.0       78.0          right              medium   \n",
       "105579            85.0       86.0          right                high   \n",
       "63097             71.0       81.0          right              medium   \n",
       "56907             81.0       81.0           left              medium   \n",
       "48989             63.0       68.0          right              medium   \n",
       "27543             73.0       83.0          right              medium   \n",
       "63213             75.0       81.0          right              medium   \n",
       "169008            68.0       74.0           left              medium   \n",
       "...                ...        ...            ...                 ...   \n",
       "123756            73.0       73.0          right              medium   \n",
       "92503             59.0       74.0           left              medium   \n",
       "129960            57.0       73.0          right              medium   \n",
       "93265             69.0       74.0           left              medium   \n",
       "16750             67.0       70.0           left              medium   \n",
       "52722             58.0       79.0          right              medium   \n",
       "119755            68.0       68.0           left                 low   \n",
       "19047             67.0       67.0          right              medium   \n",
       "27753             72.0       77.0          right                high   \n",
       "79409             69.0       80.0          right                norm   \n",
       "135174            65.0       76.0           left              medium   \n",
       "104519            67.0       74.0          right              medium   \n",
       "108787            64.0       66.0          right              medium   \n",
       "114011            79.0       80.0          right              medium   \n",
       "126234            56.0       71.0          right              medium   \n",
       "6229              75.0       75.0           left                high   \n",
       "176814            78.0       81.0          right                high   \n",
       "35125             81.0       85.0          right                high   \n",
       "75082             70.0       75.0           left              medium   \n",
       "45726             68.0       75.0          right                high   \n",
       "68215             70.0       75.0          right                high   \n",
       "82644             64.0       69.0          right              medium   \n",
       "86117             63.0       71.0          right                None   \n",
       "172153            70.0       72.0           left                high   \n",
       "39074             70.0       73.0          right              medium   \n",
       "77671             79.0       83.0          right              medium   \n",
       "166932            70.0       70.0          right              medium   \n",
       "189               67.0       71.0           left              medium   \n",
       "126021            64.0       71.0          right              medium   \n",
       "178817            59.0       71.0          right              medium   \n",
       "\n",
       "       defensive_work_rate  crossing     ...       vision  penalties  marking  \\\n",
       "161135              medium      66.0     ...         76.0       77.0     25.0   \n",
       "108720              medium      16.0     ...         25.0       58.0      5.0   \n",
       "183453                 low      67.0     ...         58.0       69.0     17.0   \n",
       "37646               medium      12.0     ...         13.0       33.0     18.0   \n",
       "67392               medium      79.0     ...         58.0       38.0     61.0   \n",
       "152556              medium      70.0     ...         62.0       74.0     15.0   \n",
       "29311                  low      36.0     ...         47.0       73.0     21.0   \n",
       "183686                 low      75.0     ...         80.0       91.0     24.0   \n",
       "180696                 low      64.0     ...         51.0       56.0     20.0   \n",
       "95074               medium      71.0     ...         68.0       64.0     29.0   \n",
       "139189              medium      65.0     ...         62.0       51.0     65.0   \n",
       "59614                  low      65.0     ...         66.0       67.0     16.0   \n",
       "86627               medium      51.0     ...         44.0       43.0     78.0   \n",
       "31391               medium      74.0     ...         74.0       58.0     65.0   \n",
       "3699                   low      29.0     ...         50.0       77.0     27.0   \n",
       "44426               medium      63.0     ...         58.0       58.0     67.0   \n",
       "99595               medium      52.0     ...         60.0       69.0     24.0   \n",
       "62848               medium      71.0     ...         76.0       69.0     11.0   \n",
       "118815                high      45.0     ...         39.0       42.0     80.0   \n",
       "88257               medium      62.0     ...         73.0       43.0     13.0   \n",
       "20401               medium      55.0     ...         58.0       51.0     72.0   \n",
       "2701                medium      63.0     ...         65.0       69.0     29.0   \n",
       "159778              medium      69.0     ...         79.0       71.0     63.0   \n",
       "105579              medium      50.0     ...         81.0       74.0     46.0   \n",
       "63097               medium      11.0     ...         44.0       11.0      9.0   \n",
       "56907               medium      79.0     ...         75.0       82.0     22.0   \n",
       "48989               medium      56.0     ...         60.0       58.0     65.0   \n",
       "27543               medium      76.0     ...         85.0       76.0     57.0   \n",
       "63213               medium      25.0     ...         25.0       26.0     25.0   \n",
       "169008              medium      51.0     ...         55.0       34.0     71.0   \n",
       "...                    ...       ...     ...          ...        ...      ...   \n",
       "123756              medium      25.0     ...         25.0       30.0     25.0   \n",
       "92503                 high      28.0     ...         28.0       35.0     57.0   \n",
       "129960              medium      52.0     ...         56.0       51.0     25.0   \n",
       "93265               medium      65.0     ...         64.0       60.0     47.0   \n",
       "16750               medium      69.0     ...         69.0       56.0     74.0   \n",
       "52722               medium      56.0     ...         63.0       41.0     51.0   \n",
       "119755                high      48.0     ...         50.0       44.0     65.0   \n",
       "19047                 high      62.0     ...         67.0       64.0     67.0   \n",
       "27753               medium      30.0     ...         60.0       74.0     25.0   \n",
       "79409                ormal      55.0     ...         72.0       72.0     74.0   \n",
       "135174              medium      58.0     ...         60.0       43.0     28.0   \n",
       "104519              medium      40.0     ...         52.0       50.0     21.0   \n",
       "108787              medium      51.0     ...         43.0       57.0     64.0   \n",
       "114011              medium      66.0     ...         76.0       69.0     76.0   \n",
       "126234              medium      38.0     ...         60.0       33.0     51.0   \n",
       "6229                medium      68.0     ...         79.0       67.0     32.0   \n",
       "176814              medium      72.0     ...         71.0       71.0     24.0   \n",
       "35125               medium      79.0     ...         57.0       45.0     85.0   \n",
       "75082                 high      65.0     ...         74.0       62.0     67.0   \n",
       "45726               medium      77.0     ...         66.0       68.0     69.0   \n",
       "68215               medium      64.0     ...         63.0       54.0     40.0   \n",
       "82644               medium      61.0     ...         56.0       60.0     67.0   \n",
       "86117                    1      66.0     ...         31.0       35.0     59.0   \n",
       "172153              medium      74.0     ...         60.0       51.0     67.0   \n",
       "39074               medium      10.0     ...         33.0       11.0     12.0   \n",
       "77671               medium      81.0     ...         83.0       75.0     52.0   \n",
       "166932                high      32.0     ...         47.0       47.0     70.0   \n",
       "189                 medium      65.0     ...         62.0       55.0     62.0   \n",
       "126021              medium      47.0     ...         47.0       46.0     55.0   \n",
       "178817                 low      52.0     ...         55.0       49.0     25.0   \n",
       "\n",
       "        standing_tackle  sliding_tackle  gk_diving  gk_handling  gk_kicking  \\\n",
       "161135             29.0            27.0       11.0          5.0        10.0   \n",
       "108720             26.0            18.0       70.0         80.0        77.0   \n",
       "183453             21.0            18.0        8.0          9.0        15.0   \n",
       "37646              19.0            17.0       60.0         55.0        58.0   \n",
       "67392              66.0            68.0        6.0          8.0         7.0   \n",
       "152556             36.0            22.0       11.0         12.0         9.0   \n",
       "29311              16.0            14.0        9.0         15.0         7.0   \n",
       "183686             43.0            28.0       12.0         24.0        72.0   \n",
       "180696             20.0            21.0       15.0         13.0        11.0   \n",
       "95074              37.0            31.0        9.0         12.0         7.0   \n",
       "139189             69.0            68.0        8.0         14.0        12.0   \n",
       "59614              24.0            22.0       14.0          5.0        14.0   \n",
       "86627              83.0            79.0       11.0         15.0        15.0   \n",
       "31391              74.0            80.0       11.0         15.0        10.0   \n",
       "3699               22.0            24.0       14.0         13.0         7.0   \n",
       "44426              69.0            73.0        7.0         13.0         5.0   \n",
       "99595              25.0            27.0        5.0         10.0        15.0   \n",
       "62848              12.0            17.0       13.0          6.0         8.0   \n",
       "118815             78.0            76.0       10.0         15.0        10.0   \n",
       "88257              24.0            24.0        6.0         12.0         6.0   \n",
       "20401              66.0            65.0        4.0          3.0        63.0   \n",
       "2701               36.0            23.0       10.0          5.0        10.0   \n",
       "159778             69.0            69.0       13.0          8.0        13.0   \n",
       "105579             30.0            22.0       11.0         22.0        48.0   \n",
       "63097               7.0             8.0       77.0         64.0        60.0   \n",
       "56907              27.0            25.0       14.0         14.0         8.0   \n",
       "48989              63.0            66.0       15.0         14.0         8.0   \n",
       "27543              65.0            57.0       15.0          7.0        12.0   \n",
       "63213              25.0            25.0       78.0         73.0        69.0   \n",
       "169008             67.0            70.0        8.0         13.0        15.0   \n",
       "...                 ...             ...        ...          ...         ...   \n",
       "123756             25.0            25.0       76.0         72.0        66.0   \n",
       "92503              69.0            62.0       11.0         13.0        14.0   \n",
       "129960             22.0            20.0       11.0         11.0        13.0   \n",
       "93265              57.0            52.0       13.0          5.0         6.0   \n",
       "16750              74.0            73.0       13.0         10.0        66.0   \n",
       "52722              52.0            70.0        7.0         12.0        49.0   \n",
       "119755             72.0            66.0        9.0         15.0        15.0   \n",
       "19047              71.0            69.0       11.0         11.0        10.0   \n",
       "27753              25.0            25.0        8.0         10.0         6.0   \n",
       "79409              72.0            63.0        9.0         22.0        56.0   \n",
       "135174             27.0            28.0        8.0         14.0        12.0   \n",
       "104519             25.0            25.0       10.0          9.0        12.0   \n",
       "108787             62.0            65.0       12.0          6.0        11.0   \n",
       "114011             79.0            72.0        9.0         13.0        16.0   \n",
       "126234             59.0            83.0        6.0         21.0        47.0   \n",
       "6229               35.0            25.0       14.0          7.0        10.0   \n",
       "176814             40.0            37.0        3.0          3.0         3.0   \n",
       "35125              82.0            84.0       13.0         13.0        15.0   \n",
       "75082              68.0            65.0       10.0          7.0        11.0   \n",
       "45726              75.0            69.0        8.0         20.0        62.0   \n",
       "68215              35.0            32.0       12.0         14.0        14.0   \n",
       "82644              65.0            62.0        8.0          8.0         9.0   \n",
       "86117              62.0            60.0       15.0         14.0        12.0   \n",
       "172153             69.0            67.0       11.0          8.0         6.0   \n",
       "39074              11.0            11.0       62.0         80.0        79.0   \n",
       "77671              51.0            44.0        2.0         22.0        76.0   \n",
       "166932             72.0            66.0       14.0         13.0         7.0   \n",
       "189                65.0            60.0        6.0         14.0         6.0   \n",
       "126021             63.0            64.0       14.0         14.0         9.0   \n",
       "178817             25.0            25.0       14.0         13.0         8.0   \n",
       "\n",
       "        gk_positioning  gk_reflexes  \n",
       "161135            14.0         11.0  \n",
       "108720            58.0         81.0  \n",
       "183453            13.0         14.0  \n",
       "37646             52.0         61.0  \n",
       "67392              8.0         12.0  \n",
       "152556            16.0          9.0  \n",
       "29311             15.0          8.0  \n",
       "183686            24.0         24.0  \n",
       "180696            13.0         12.0  \n",
       "95074             13.0          7.0  \n",
       "139189             9.0         14.0  \n",
       "59614             12.0         11.0  \n",
       "86627             14.0          7.0  \n",
       "31391              7.0         10.0  \n",
       "3699              13.0         10.0  \n",
       "44426              7.0         12.0  \n",
       "99595             13.0          7.0  \n",
       "62848             12.0         11.0  \n",
       "118815            14.0         12.0  \n",
       "88257              7.0         16.0  \n",
       "20401              8.0          5.0  \n",
       "2701              11.0          7.0  \n",
       "159778            12.0         10.0  \n",
       "105579            22.0         22.0  \n",
       "63097             67.0         78.0  \n",
       "56907             13.0          5.0  \n",
       "48989             14.0         14.0  \n",
       "27543              8.0         13.0  \n",
       "63213             71.0         78.0  \n",
       "169008             7.0          9.0  \n",
       "...                ...          ...  \n",
       "123756            69.0         78.0  \n",
       "92503              7.0          9.0  \n",
       "129960            11.0          9.0  \n",
       "93265              9.0         11.0  \n",
       "16750             14.0         14.0  \n",
       "52722              7.0          8.0  \n",
       "119755             6.0         13.0  \n",
       "19047             15.0         11.0  \n",
       "27753              8.0         12.0  \n",
       "79409             22.0         22.0  \n",
       "135174            12.0         11.0  \n",
       "104519            12.0          9.0  \n",
       "108787             6.0          8.0  \n",
       "114011            12.0         11.0  \n",
       "126234            21.0         21.0  \n",
       "6229              14.0         11.0  \n",
       "176814             3.0          3.0  \n",
       "35125              9.0         15.0  \n",
       "75082             11.0         15.0  \n",
       "45726             20.0         20.0  \n",
       "68215             15.0         12.0  \n",
       "82644              5.0         10.0  \n",
       "86117              7.0         14.0  \n",
       "172153            12.0          7.0  \n",
       "39074             78.0         63.0  \n",
       "77671             22.0         22.0  \n",
       "166932            12.0          7.0  \n",
       "189                9.0         14.0  \n",
       "126021            14.0         14.0  \n",
       "178817            14.0          9.0  \n",
       "\n",
       "[180354 rows x 42 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df\n"
   ]
  },
  {
   "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>id</th>\n",
       "      <th>player_fifa_api_id</th>\n",
       "      <th>player_api_id</th>\n",
       "      <th>date</th>\n",
       "      <th>overall_rating</th>\n",
       "      <th>potential</th>\n",
       "      <th>preferred_foot</th>\n",
       "      <th>attacking_work_rate</th>\n",
       "      <th>defensive_work_rate</th>\n",
       "      <th>crossing</th>\n",
       "      <th>...</th>\n",
       "      <th>vision</th>\n",
       "      <th>penalties</th>\n",
       "      <th>marking</th>\n",
       "      <th>standing_tackle</th>\n",
       "      <th>sliding_tackle</th>\n",
       "      <th>gk_diving</th>\n",
       "      <th>gk_handling</th>\n",
       "      <th>gk_kicking</th>\n",
       "      <th>gk_positioning</th>\n",
       "      <th>gk_reflexes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>161135</th>\n",
       "      <td>161136</td>\n",
       "      <td>135697</td>\n",
       "      <td>38578</td>\n",
       "      <td>2015-02-13 00:00:00</td>\n",
       "      <td>79.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>66.0</td>\n",
       "      <td>...</td>\n",
       "      <td>76.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108720</th>\n",
       "      <td>108721</td>\n",
       "      <td>113343</td>\n",
       "      <td>23686</td>\n",
       "      <td>2007-02-22 00:00:00</td>\n",
       "      <td>73.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183453</th>\n",
       "      <td>183454</td>\n",
       "      <td>223339</td>\n",
       "      <td>570159</td>\n",
       "      <td>2015-10-16 00:00:00</td>\n",
       "      <td>71.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>right</td>\n",
       "      <td>high</td>\n",
       "      <td>low</td>\n",
       "      <td>67.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37646</th>\n",
       "      <td>37647</td>\n",
       "      <td>207998</td>\n",
       "      <td>254472</td>\n",
       "      <td>2013-02-15 00:00:00</td>\n",
       "      <td>57.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>right</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>12.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67392</th>\n",
       "      <td>67393</td>\n",
       "      <td>173228</td>\n",
       "      <td>40139</td>\n",
       "      <td>2011-08-30 00:00:00</td>\n",
       "      <td>69.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>left</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>79.0</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            id  player_fifa_api_id  player_api_id                 date  \\\n",
       "161135  161136              135697          38578  2015-02-13 00:00:00   \n",
       "108720  108721              113343          23686  2007-02-22 00:00:00   \n",
       "183453  183454              223339         570159  2015-10-16 00:00:00   \n",
       "37646    37647              207998         254472  2013-02-15 00:00:00   \n",
       "67392    67393              173228          40139  2011-08-30 00:00:00   \n",
       "\n",
       "        overall_rating  potential preferred_foot attacking_work_rate  \\\n",
       "161135            79.0       79.0          right              medium   \n",
       "108720            73.0       76.0          right              medium   \n",
       "183453            71.0       77.0          right                high   \n",
       "37646             57.0       72.0          right              medium   \n",
       "67392             69.0       72.0           left              medium   \n",
       "\n",
       "       defensive_work_rate  crossing     ...       vision  penalties  marking  \\\n",
       "161135              medium      66.0     ...         76.0       77.0     25.0   \n",
       "108720              medium      16.0     ...         25.0       58.0      5.0   \n",
       "183453                 low      67.0     ...         58.0       69.0     17.0   \n",
       "37646               medium      12.0     ...         13.0       33.0     18.0   \n",
       "67392               medium      79.0     ...         58.0       38.0     61.0   \n",
       "\n",
       "        standing_tackle  sliding_tackle  gk_diving  gk_handling  gk_kicking  \\\n",
       "161135             29.0            27.0       11.0          5.0        10.0   \n",
       "108720             26.0            18.0       70.0         80.0        77.0   \n",
       "183453             21.0            18.0        8.0          9.0        15.0   \n",
       "37646              19.0            17.0       60.0         55.0        58.0   \n",
       "67392              66.0            68.0        6.0          8.0         7.0   \n",
       "\n",
       "        gk_positioning  gk_reflexes  \n",
       "161135            14.0         11.0  \n",
       "108720            58.0         81.0  \n",
       "183453            13.0         14.0  \n",
       "37646             52.0         61.0  \n",
       "67392              8.0         12.0  \n",
       "\n",
       "[5 rows x 42 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>penalties</th>\n",
       "      <th>overall_rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>161135</th>\n",
       "      <td>77.0</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108720</th>\n",
       "      <td>58.0</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183453</th>\n",
       "      <td>69.0</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37646</th>\n",
       "      <td>33.0</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67392</th>\n",
       "      <td>38.0</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152556</th>\n",
       "      <td>74.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29311</th>\n",
       "      <td>73.0</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183686</th>\n",
       "      <td>91.0</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180696</th>\n",
       "      <td>56.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95074</th>\n",
       "      <td>64.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        penalties  overall_rating\n",
       "161135       77.0            79.0\n",
       "108720       58.0            73.0\n",
       "183453       69.0            71.0\n",
       "37646        33.0            57.0\n",
       "67392        38.0            69.0\n",
       "152556       74.0            75.0\n",
       "29311        73.0            62.0\n",
       "183686       91.0            88.0\n",
       "180696       56.0            66.0\n",
       "95074        64.0            75.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:10][['penalties','overall_rating']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3927151079111884"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['overall_rating'].corr(df['penalties'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "potentialFeatures=['acceleration','curve','free_kick_accuracy','ball_control','shot_power','stamina']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "acceleration:0.2439984883712964\n",
      "curve:0.3575657691094528\n",
      "free_kick_accuracy:0.3498003114423884\n",
      "ball_control:0.44399076282629807\n",
      "shot_power:0.42805313222193914\n",
      "stamina:0.32560565778692413\n"
     ]
    }
   ],
   "source": [
    "for f in potentialFeatures:\n",
    "    related=df['overall_rating'].corr(df[f])\n",
    "    print(f\"{f}:{related}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols=df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'player_fifa_api_id', 'player_api_id', 'date', 'overall_rating',\n",
       "       'potential', 'preferred_foot', 'attacking_work_rate',\n",
       "       'defensive_work_rate', 'crossing', 'finishing', 'heading_accuracy',\n",
       "       'short_passing', 'volleys', 'dribbling', 'curve', 'free_kick_accuracy',\n",
       "       'long_passing', 'ball_control', 'acceleration', 'sprint_speed',\n",
       "       'agility', 'reactions', 'balance', 'shot_power', 'jumping', 'stamina',\n",
       "       'strength', 'long_shots', 'aggression', 'interceptions', 'positioning',\n",
       "       'vision', 'penalties', 'marking', 'standing_tackle', 'sliding_tackle',\n",
       "       'gk_diving', 'gk_handling', 'gk_kicking', 'gk_positioning',\n",
       "       'gk_reflexes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns=['potential',  'crossing', 'finishing', 'heading_accuracy',\n",
    "       'short_passing', 'volleys', 'dribbling', 'curve', 'free_kick_accuracy',\n",
    "       'long_passing', 'ball_control', 'acceleration', 'sprint_speed',\n",
    "       'agility', 'reactions', 'balance', 'shot_power', 'jumping', 'stamina',\n",
    "       'strength', 'long_shots', 'aggression', 'interceptions', 'positioning',\n",
    "       'vision', 'penalties', 'marking', 'standing_tackle', 'sliding_tackle',\n",
    "       'gk_diving', 'gk_handling', 'gk_kicking', 'gk_positioning',\n",
    "       'gk_reflexes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a list containing perason correlation between 'over_ratings'and each columns in columns\n",
    "\n",
    "correlations=[df['overall_rating'].corr(df[f])for f in columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(34, 34)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# making sure the number of the selected features and correlations are the same\n",
    "\n",
    "len(columns),len(correlations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating a function for plotting a df with string columns and numeric values\n",
    "\n",
    "def plot_df(df,y_label):\n",
    "    color='blue'\n",
    "    fig=plt.gcf()\n",
    "    fig.set_size_inches(20,12)\n",
    "    plt.ylabel(y_label)\n",
    "    ax=df2.correlation.plot(linewidth=3.3,color=color)\n",
    "    ax.set_xticks(df2.index)\n",
    "    ax.set_xticklabels(df2.attributes,rotation=75);\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2=pd.DataFrame({'attributes':columns,'correlation':correlations})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_df(df2,'Player\\'s Overall Rating')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "select5features=['gk_kicking','potential','marking','interceptions','standing_tackle']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['gk_kicking', 'potential', 'marking', 'interceptions', 'standing_tackle']"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "select5features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# generate a new data frame by selecting the new 5 features\n",
    "new_dataframe=df[select5features].copy(deep=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>gk_kicking</th>\n",
       "      <th>potential</th>\n",
       "      <th>marking</th>\n",
       "      <th>interceptions</th>\n",
       "      <th>standing_tackle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>161135</th>\n",
       "      <td>10.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108720</th>\n",
       "      <td>77.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183453</th>\n",
       "      <td>15.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37646</th>\n",
       "      <td>58.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67392</th>\n",
       "      <td>7.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>66.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        gk_kicking  potential  marking  interceptions  standing_tackle\n",
       "161135        10.0       79.0     25.0           28.0             29.0\n",
       "108720        77.0       76.0      5.0           62.0             26.0\n",
       "183453        15.0       77.0     17.0           22.0             21.0\n",
       "37646         58.0       72.0     18.0           21.0             19.0\n",
       "67392          7.0       72.0     61.0           67.0             66.0"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_dataframe.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "#perform scaling on the dataframe containing the features\n",
    "data=scale(new_dataframe)\n",
    "# define numer of clusters\n",
    "no_of_clusters=4\n",
    "# Train models.\n",
    "model=KMeans(init='k-means++',n_clusters=no_of_clusters,n_init=20).fit(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________\n",
      "\n",
      "Count of players in each cluster\n",
      "__________________________________________________________________________________________\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    55903\n",
       "1    50476\n",
       "2    50198\n",
       "3    23777\n",
       "dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(90*'_')\n",
    "print(\"\\nCount of players in each cluster\")\n",
    "print(90*'_')\n",
    "pd.value_counts(model.labels_,sort=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a composite dataframe for plotting \n",
    "# use custom functions declared in the customplot.py\n",
    "P=pd_centers(featuresUsed=select5features, centers=model.cluster_centers_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>gk_kicking</th>\n",
       "      <th>potential</th>\n",
       "      <th>marking</th>\n",
       "      <th>interceptions</th>\n",
       "      <th>standing_tackle</th>\n",
       "      <th>prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.477101</td>\n",
       "      <td>0.105743</td>\n",
       "      <td>-0.947630</td>\n",
       "      <td>-0.975204</td>\n",
       "      <td>-0.914202</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.040340</td>\n",
       "      <td>0.704450</td>\n",
       "      <td>1.027860</td>\n",
       "      <td>0.982555</td>\n",
       "      <td>1.030287</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.337584</td>\n",
       "      <td>-0.843429</td>\n",
       "      <td>0.548313</td>\n",
       "      <td>0.407446</td>\n",
       "      <td>0.550867</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.920631</td>\n",
       "      <td>0.037763</td>\n",
       "      <td>-1.111727</td>\n",
       "      <td>-0.653150</td>\n",
       "      <td>-1.200879</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gk_kicking  potential   marking  interceptions  standing_tackle  prediction\n",
       "0   -0.477101   0.105743 -0.947630      -0.975204        -0.914202           0\n",
       "1   -0.040340   0.704450  1.027860       0.982555         1.030287           1\n",
       "2   -0.337584  -0.843429  0.548313       0.407446         0.550867           2\n",
       "3    1.920631   0.037763 -1.111727      -0.653150        -1.200879           3"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plotting a graph inside the matplotlip\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/anilla/customplot.py:31: FutureWarning: 'pandas.tools.plotting.parallel_coordinates' is deprecated, import 'pandas.plotting.parallel_coordinates' instead.\n",
      "  parallel_coordinates(data, 'prediction', color = my_colors, marker='o')\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "parallel_plot(P)"
   ]
  },
  {
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}