Challenge_ Tennis_JEREMY_LE.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Challenge Tennis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Avant de se lancer dans l'informatique, observons les données et décrivons les données du mieux possible. Ainsi, on pourra vérifier la vraisemblance des données, vérifier les valeurs manquantes ou abbérantes et comprendre les données. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "De plus, il faut au préalable expliciter le problème de data science posé afin de choisir les données adéquates aux problème."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Describing the problem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ici, nous devons faire la prédiction de match professionnel de tennis. Il s'agit donc d'un problème d'apprentissage supervisé. Le vecteur X (les échantillons) contiendra les features d'un match entre deux joueur d'identifiant ID1 et ID2. Nous verrons par la suite la création de ce vecteur X. Le vecteur Y contiendra les labels associés aux échantillons (match)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les labels seront tels que Y=1 si le joueur 1 remporte le match et Y=0 si le joueur 2 gagne le match. Nous pouvons ainsi définir notre problème d'apprentissage de deux façons différentes: classification ou regression."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Describing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import libraries for data processing and viewing\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Data\n",
    "court = pd.read_csv('courts.csv')\n",
    "facts_atp = pd.read_csv('facts_atp.csv')\n",
    "games_atp = pd.read_csv('games_atp.csv',parse_dates=['DATE_G'])\n",
    "games_atp_public = pd.read_csv('games_atp_public.csv',parse_dates=['DATE_G'])\n",
    "players_atp = pd.read_csv('players_atp.csv')\n",
    "ratings_atp = pd.read_csv('ratings_atp.csv',parse_dates=['DATE_R'])\n",
    "rounds = pd.read_csv('rounds.csv')\n",
    "stat_atp = pd.read_csv('stat_atp.csv')\n",
    "tours_atp = pd.read_csv('tours_atp.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## court.csv "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_C</th>\n",
       "      <th>NAME_C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Hard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Clay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>I.hard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Carpet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Grass</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID_C  NAME_C\n",
       "0     1    Hard\n",
       "1     2    Clay\n",
       "2     3  I.hard\n",
       "3     4  Carpet\n",
       "4     5   Grass"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "court.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La table court.csv contient le mapping entre l'identifiant d'un type de terrain et son nom. Nous n'utiliserons pas cette table dans la suite du projet. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## facts_atp.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_P_F</th>\n",
       "      <th>YEAR_F</th>\n",
       "      <th>TMW_F</th>\n",
       "      <th>TML_F</th>\n",
       "      <th>TBW_F</th>\n",
       "      <th>TBL_F</th>\n",
       "      <th>MF_F</th>\n",
       "      <th>ACES_F</th>\n",
       "      <th>DF_F</th>\n",
       "      <th>SRV1_F</th>\n",
       "      <th>WON1_F</th>\n",
       "      <th>WON2_F</th>\n",
       "      <th>SGW_F</th>\n",
       "      <th>BPS_F</th>\n",
       "      <th>PWR1S_F</th>\n",
       "      <th>PWR2S_F</th>\n",
       "      <th>BPW_F</th>\n",
       "      <th>RGW_F</th>\n",
       "      <th>PRIZE_F</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5992</td>\n",
       "      <td>2012</td>\n",
       "      <td>75</td>\n",
       "      <td>12</td>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>87</td>\n",
       "      <td>512</td>\n",
       "      <td>147</td>\n",
       "      <td>64</td>\n",
       "      <td>75</td>\n",
       "      <td>56</td>\n",
       "      <td>87</td>\n",
       "      <td>66</td>\n",
       "      <td>35</td>\n",
       "      <td>56</td>\n",
       "      <td>46</td>\n",
       "      <td>35</td>\n",
       "      <td>12803737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19</td>\n",
       "      <td>2012</td>\n",
       "      <td>71</td>\n",
       "      <td>12</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>80</td>\n",
       "      <td>665</td>\n",
       "      <td>120</td>\n",
       "      <td>63</td>\n",
       "      <td>78</td>\n",
       "      <td>60</td>\n",
       "      <td>91</td>\n",
       "      <td>69</td>\n",
       "      <td>31</td>\n",
       "      <td>51</td>\n",
       "      <td>42</td>\n",
       "      <td>26</td>\n",
       "      <td>8584842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1075</td>\n",
       "      <td>2012</td>\n",
       "      <td>56</td>\n",
       "      <td>16</td>\n",
       "      <td>18</td>\n",
       "      <td>9</td>\n",
       "      <td>72</td>\n",
       "      <td>521</td>\n",
       "      <td>163</td>\n",
       "      <td>60</td>\n",
       "      <td>74</td>\n",
       "      <td>54</td>\n",
       "      <td>84</td>\n",
       "      <td>67</td>\n",
       "      <td>32</td>\n",
       "      <td>56</td>\n",
       "      <td>41</td>\n",
       "      <td>31</td>\n",
       "      <td>5708230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>677</td>\n",
       "      <td>2012</td>\n",
       "      <td>42</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>48</td>\n",
       "      <td>160</td>\n",
       "      <td>59</td>\n",
       "      <td>67</td>\n",
       "      <td>75</td>\n",
       "      <td>57</td>\n",
       "      <td>88</td>\n",
       "      <td>71</td>\n",
       "      <td>38</td>\n",
       "      <td>55</td>\n",
       "      <td>49</td>\n",
       "      <td>38</td>\n",
       "      <td>4997448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>673</td>\n",
       "      <td>2012</td>\n",
       "      <td>76</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>13</td>\n",
       "      <td>85</td>\n",
       "      <td>279</td>\n",
       "      <td>178</td>\n",
       "      <td>63</td>\n",
       "      <td>73</td>\n",
       "      <td>57</td>\n",
       "      <td>85</td>\n",
       "      <td>65</td>\n",
       "      <td>34</td>\n",
       "      <td>54</td>\n",
       "      <td>44</td>\n",
       "      <td>31</td>\n",
       "      <td>4409340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID_P_F  YEAR_F  TMW_F  TML_F  TBW_F  TBL_F  MF_F  ACES_F  DF_F  SRV1_F  \\\n",
       "0    5992    2012     75     12     17     12    87     512   147      64   \n",
       "1      19    2012     71     12     21     15    80     665   120      63   \n",
       "2    1075    2012     56     16     18      9    72     521   163      60   \n",
       "3     677    2012     42      6      8      3    48     160    59      67   \n",
       "4     673    2012     76     15     20     13    85     279   178      63   \n",
       "\n",
       "   WON1_F  WON2_F  SGW_F  BPS_F  PWR1S_F  PWR2S_F  BPW_F  RGW_F   PRIZE_F  \n",
       "0      75      56     87     66       35       56     46     35  12803737  \n",
       "1      78      60     91     69       31       51     42     26   8584842  \n",
       "2      74      54     84     67       32       56     41     31   5708230  \n",
       "3      75      57     88     71       38       55     49     38   4997448  \n",
       "4      73      57     85     65       34       54     44     31   4409340  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "facts_atp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 948 entries, 0 to 947\n",
      "Data columns (total 19 columns):\n",
      "ID_P_F     948 non-null int64\n",
      "YEAR_F     948 non-null int64\n",
      "TMW_F      948 non-null int64\n",
      "TML_F      948 non-null int64\n",
      "TBW_F      948 non-null int64\n",
      "TBL_F      948 non-null int64\n",
      "MF_F       948 non-null int64\n",
      "ACES_F     948 non-null int64\n",
      "DF_F       948 non-null int64\n",
      "SRV1_F     948 non-null int64\n",
      "WON1_F     948 non-null int64\n",
      "WON2_F     948 non-null int64\n",
      "SGW_F      948 non-null int64\n",
      "BPS_F      948 non-null int64\n",
      "PWR1S_F    948 non-null int64\n",
      "PWR2S_F    948 non-null int64\n",
      "BPW_F      948 non-null int64\n",
      "RGW_F      948 non-null int64\n",
      "PRIZE_F    948 non-null int64\n",
      "dtypes: int64(19)\n",
      "memory usage: 140.8 KB\n"
     ]
    }
   ],
   "source": [
    "facts_atp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "cette table ne contient que peu d'information sur les joueurs et les matchs... Nous ne l'utiliserons donc pas dans la suite du projet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## games_atp.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID1_G</th>\n",
       "      <th>ID2_G</th>\n",
       "      <th>ID_T_G</th>\n",
       "      <th>ID_R_G</th>\n",
       "      <th>RESULT_G</th>\n",
       "      <th>DATE_G</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>17613</td>\n",
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       "      <td>7-6(8) 3-6 10-7</td>\n",
       "      <td>2012-01-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25192</td>\n",
       "      <td>25191</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-2</td>\n",
       "      <td>2012-01-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID1_G  ID2_G  ID_T_G  ID_R_G         RESULT_G     DATE_G\n",
       "0  17613  18854    8887       4  7-6(8) 3-6 10-7 2012-01-31\n",
       "1  25192  25191    8888       4          6-3 6-2 2012-01-31"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_atp.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "      <td>3</td>\n",
       "      <td>6-1 6-1</td>\n",
       "      <td>2016-07-31</td>\n",
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       "      <td>22428</td>\n",
       "      <td>13070</td>\n",
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       "      <td>3</td>\n",
       "      <td>3-6 6-0 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID1_G  ID2_G  ID_T_G  ID_R_G     RESULT_G     DATE_G\n",
       "84483  11742  28075   13296       3      6-1 6-1 2016-07-31\n",
       "84484  22428  13070   13296       3  3-6 6-0 6-3 2016-07-31"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_atp.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 6 columns):\n",
      "ID1_G       84485 non-null int64\n",
      "ID2_G       84485 non-null int64\n",
      "ID_T_G      84485 non-null int64\n",
      "ID_R_G      84485 non-null int64\n",
      "RESULT_G    84485 non-null object\n",
      "DATE_G      84485 non-null datetime64[ns]\n",
      "dtypes: datetime64[ns](1), int64(4), object(1)\n",
      "memory usage: 3.9+ MB\n"
     ]
    }
   ],
   "source": [
    "games_atp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "games_atp.csv sera notre ensemble d'apprentissage (84 485 matchs de 2012 à 2016). cet ensemble permettra de déterminer les paramètres de notre modèle."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## games_atp_public.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th>ID1_G</th>\n",
       "      <th>ID2_G</th>\n",
       "      <th>ID_T_G</th>\n",
       "      <th>ID_R_G</th>\n",
       "      <th>DATE_G</th>\n",
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       "      <td>30589</td>\n",
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       "      <td>4</td>\n",
       "      <td>2016-08-01</td>\n",
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       "      <td>2016-08-01</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID1_G  ID2_G  ID_T_G  ID_R_G     DATE_G\n",
       "0  30589  54796   13296       4 2016-08-01\n",
       "1  54409  24429   13296       4 2016-08-01"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_atp_public.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>ID1_G</th>\n",
       "      <th>ID2_G</th>\n",
       "      <th>ID_T_G</th>\n",
       "      <th>ID_R_G</th>\n",
       "      <th>DATE_G</th>\n",
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       "      <td>673</td>\n",
       "      <td>12842</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-10-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7607</th>\n",
       "      <td>6101</td>\n",
       "      <td>12043</td>\n",
       "      <td>12843</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-10-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID1_G  ID2_G  ID_T_G  ID_R_G     DATE_G\n",
       "7606   3577    673   12842       4 2016-10-03\n",
       "7607   6101  12043   12843       4 2016-10-03"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_atp_public.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7608 entries, 0 to 7607\n",
      "Data columns (total 5 columns):\n",
      "ID1_G     7608 non-null int64\n",
      "ID2_G     7608 non-null int64\n",
      "ID_T_G    7608 non-null int64\n",
      "ID_R_G    7608 non-null int64\n",
      "DATE_G    7608 non-null datetime64[ns]\n",
      "dtypes: datetime64[ns](1), int64(4)\n",
      "memory usage: 297.3 KB\n"
     ]
    }
   ],
   "source": [
    "games_atp_public.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cette ensemble sera notre ensemble test (7608 match fin 2016)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## tours_atp.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_T</th>\n",
       "      <th>NAME_T</th>\n",
       "      <th>ID_C_T</th>\n",
       "      <th>DATE_T</th>\n",
       "      <th>RANK_T</th>\n",
       "      <th>LINK_T</th>\n",
       "      <th>COUNTRY_T</th>\n",
       "      <th>PRIZE_T</th>\n",
       "      <th>RATING_T</th>\n",
       "      <th>URL_T</th>\n",
       "      <th>...</th>\n",
       "      <th>SITE_T</th>\n",
       "      <th>RACE_T</th>\n",
       "      <th>ENTRY_T</th>\n",
       "      <th>SINGLES_T</th>\n",
       "      <th>DOUBLES_T</th>\n",
       "      <th>TIER_T</th>\n",
       "      <th>RESERVE_INT_T</th>\n",
       "      <th>RESERVE_CHAR_T</th>\n",
       "      <th>LIVE_T</th>\n",
       "      <th>RESULT_T</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Australian Men's Hardcourt Championships - Ade...</td>\n",
       "      <td>1</td>\n",
       "      <td>1997-01-01 00:00:00</td>\n",
       "      <td>2</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>AUS</td>\n",
       "      <td>$303K</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Qatar Mobil Open - Doha</td>\n",
       "      <td>1</td>\n",
       "      <td>1997-01-01 00:00:00</td>\n",
       "      <td>2</td>\n",
       "      <td>1601.0</td>\n",
       "      <td>QAT</td>\n",
       "      <td>$600K</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID_T                                             NAME_T  ID_C_T  \\\n",
       "0     1  Australian Men's Hardcourt Championships - Ade...       1   \n",
       "1     2                            Qatar Mobil Open - Doha       1   \n",
       "\n",
       "                DATE_T  RANK_T  LINK_T COUNTRY_T PRIZE_T  RATING_T URL_T  \\\n",
       "0  1997-01-01 00:00:00       2  1600.0       AUS   $303K       NaN   NaN   \n",
       "1  1997-01-01 00:00:00       2  1601.0       QAT   $600K       NaN   NaN   \n",
       "\n",
       "    ...     SITE_T  RACE_T  ENTRY_T  SINGLES_T  DOUBLES_T  TIER_T  \\\n",
       "0   ...        NaN     NaN      NaN        NaN        NaN     NaN   \n",
       "1   ...        NaN     NaN      NaN        NaN        NaN     NaN   \n",
       "\n",
       "   RESERVE_INT_T RESERVE_CHAR_T  LIVE_T RESULT_T  \n",
       "0            NaN            NaN     NaN      NaN  \n",
       "1            NaN            NaN     NaN      NaN  \n",
       "\n",
       "[2 rows x 22 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tours_atp.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 13243 entries, 0 to 13242\n",
      "Data columns (total 22 columns):\n",
      "ID_T              13243 non-null int64\n",
      "NAME_T            13243 non-null object\n",
      "ID_C_T            13243 non-null int64\n",
      "DATE_T            13243 non-null object\n",
      "RANK_T            13243 non-null int64\n",
      "LINK_T            4678 non-null float64\n",
      "COUNTRY_T         13243 non-null object\n",
      "PRIZE_T           11810 non-null object\n",
      "RATING_T          884 non-null float64\n",
      "URL_T             2632 non-null object\n",
      "LATITUDE_T        5557 non-null float64\n",
      "LONGITUDE_T       5557 non-null float64\n",
      "SITE_T            2188 non-null float64\n",
      "RACE_T            1983 non-null float64\n",
      "ENTRY_T           1985 non-null float64\n",
      "SINGLES_T         769 non-null float64\n",
      "DOUBLES_T         768 non-null float64\n",
      "TIER_T            1422 non-null object\n",
      "RESERVE_INT_T     0 non-null float64\n",
      "RESERVE_CHAR_T    4815 non-null object\n",
      "LIVE_T            0 non-null float64\n",
      "RESULT_T          179 non-null float64\n",
      "dtypes: float64(12), int64(3), object(7)\n",
      "memory usage: 2.2+ MB\n"
     ]
    }
   ],
   "source": [
    "tours_atp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "tours_atp.csv contient les informations sur les tournois. Nous ne nous interesserons seulement aux variables expressives. C'est-à-dire : l'identifiant ,le nom, l'identité, la date et le rating du tournoi ."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Players_atp.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_P</th>\n",
       "      <th>NAME_P</th>\n",
       "      <th>DATE_P</th>\n",
       "      <th>COUNTRY_P</th>\n",
       "      <th>RANK_P</th>\n",
       "      <th>PROGRESS_P</th>\n",
       "      <th>POINT_P</th>\n",
       "      <th>HARDPOINT_P</th>\n",
       "      <th>HARDTOUR_P</th>\n",
       "      <th>CLAYPOINT_P</th>\n",
       "      <th>...</th>\n",
       "      <th>CARPETPOINT_P</th>\n",
       "      <th>CARPETTOUR_P</th>\n",
       "      <th>PRIZE_P</th>\n",
       "      <th>CH_P</th>\n",
       "      <th>DR_P</th>\n",
       "      <th>DP_P</th>\n",
       "      <th>DO_P</th>\n",
       "      <th>IHARDPOINT_P</th>\n",
       "      <th>IHARDTOUR_P</th>\n",
       "      <th>ITF_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Gustavo Kuerten</td>\n",
       "      <td>1976-09-10 00:00:00</td>\n",
       "      <td>BRA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Marat Safin</td>\n",
       "      <td>1980-01-27 00:00:00</td>\n",
       "      <td>RUS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID_P           NAME_P               DATE_P COUNTRY_P  RANK_P  PROGRESS_P  \\\n",
       "0     1  Gustavo Kuerten  1976-09-10 00:00:00       BRA     NaN         NaN   \n",
       "1     2      Marat Safin  1980-01-27 00:00:00       RUS     NaN         NaN   \n",
       "\n",
       "   POINT_P  HARDPOINT_P  HARDTOUR_P  CLAYPOINT_P   ...    CARPETPOINT_P  \\\n",
       "0      NaN          NaN         NaN          NaN   ...              NaN   \n",
       "1      NaN          NaN         NaN          NaN   ...              NaN   \n",
       "\n",
       "   CARPETTOUR_P  PRIZE_P  CH_P  DR_P  DP_P  DO_P  IHARDPOINT_P  IHARDTOUR_P  \\\n",
       "0           NaN      NaN   NaN   NaN   NaN   NaN           NaN          NaN   \n",
       "1           NaN      NaN   NaN   NaN   NaN   NaN           NaN          NaN   \n",
       "\n",
       "   ITF_ID  \n",
       "0     NaN  \n",
       "1     NaN  \n",
       "\n",
       "[2 rows x 23 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "players_atp.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 55562 entries, 0 to 55561\n",
      "Data columns (total 23 columns):\n",
      "ID_P             55562 non-null int64\n",
      "NAME_P           55562 non-null object\n",
      "DATE_P           26722 non-null object\n",
      "COUNTRY_P        27342 non-null object\n",
      "RANK_P           900 non-null float64\n",
      "PROGRESS_P       900 non-null float64\n",
      "POINT_P          900 non-null float64\n",
      "HARDPOINT_P      900 non-null float64\n",
      "HARDTOUR_P       900 non-null float64\n",
      "CLAYPOINT_P      900 non-null float64\n",
      "CLAYTOUR_P       900 non-null float64\n",
      "GRASSPOINT_P     900 non-null float64\n",
      "GRASSTOUR_P      900 non-null float64\n",
      "CARPETPOINT_P    900 non-null float64\n",
      "CARPETTOUR_P     900 non-null float64\n",
      "PRIZE_P          1733 non-null float64\n",
      "CH_P             100 non-null float64\n",
      "DR_P             900 non-null float64\n",
      "DP_P             900 non-null float64\n",
      "DO_P             900 non-null float64\n",
      "IHARDPOINT_P     900 non-null float64\n",
      "IHARDTOUR_P      900 non-null float64\n",
      "ITF_ID           15606 non-null float64\n",
      "dtypes: float64(19), int64(1), object(3)\n",
      "memory usage: 9.7+ MB\n"
     ]
    }
   ],
   "source": [
    "players_atp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Players_atp est la mapping des identifiants et des nom de joueur. Cette table n'étant que partiellement pleine, ne sera pas utilisé dans la suite du challenge."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ratings_atp.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE_R</th>\n",
       "      <th>ID_P_R</th>\n",
       "      <th>POINT_R</th>\n",
       "      <th>POS_R</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>5992</td>\n",
       "      <td>13630</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>677</td>\n",
       "      <td>9595</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>19</td>\n",
       "      <td>8170</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>1075</td>\n",
       "      <td>7380</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>673</td>\n",
       "      <td>4925</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      DATE_R  ID_P_R  POINT_R  POS_R\n",
       "0 2012-01-02    5992    13630      1\n",
       "1 2012-01-02     677     9595      2\n",
       "2 2012-01-02      19     8170      3\n",
       "3 2012-01-02    1075     7380      4\n",
       "4 2012-01-02     673     4925      5"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_atp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE_R</th>\n",
       "      <th>ID_P_R</th>\n",
       "      <th>POINT_R</th>\n",
       "      <th>POS_R</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>173395</th>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>35084</td>\n",
       "      <td>24</td>\n",
       "      <td>798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173396</th>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>30626</td>\n",
       "      <td>24</td>\n",
       "      <td>799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173397</th>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>17268</td>\n",
       "      <td>23</td>\n",
       "      <td>800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173398</th>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>21460</td>\n",
       "      <td>23</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173399</th>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>17961</td>\n",
       "      <td>23</td>\n",
       "      <td>802</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           DATE_R  ID_P_R  POINT_R  POS_R\n",
       "173395 2016-07-25   35084       24    798\n",
       "173396 2016-07-25   30626       24    799\n",
       "173397 2016-07-25   17268       23    800\n",
       "173398 2016-07-25   21460       23    801\n",
       "173399 2016-07-25   17961       23    802"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_atp.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 173400 entries, 0 to 173399\n",
      "Data columns (total 4 columns):\n",
      "DATE_R     173400 non-null datetime64[ns]\n",
      "ID_P_R     173400 non-null int64\n",
      "POINT_R    173400 non-null int64\n",
      "POS_R      173400 non-null int64\n",
      "dtypes: datetime64[ns](1), int64(3)\n",
      "memory usage: 5.3 MB\n"
     ]
    }
   ],
   "source": [
    "ratings_atp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_P_R</th>\n",
       "      <th>POINT_R</th>\n",
       "      <th>POS_R</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>173400.000000</td>\n",
       "      <td>173400.000000</td>\n",
       "      <td>173400.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>11812.909769</td>\n",
       "      <td>291.548449</td>\n",
       "      <td>428.008651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7956.892203</td>\n",
       "      <td>810.569058</td>\n",
       "      <td>257.380509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5961.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>207.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>10995.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>413.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>17829.000000</td>\n",
       "      <td>238.000000</td>\n",
       "      <td>647.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>42971.000000</td>\n",
       "      <td>16950.000000</td>\n",
       "      <td>900.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ID_P_R        POINT_R          POS_R\n",
       "count  173400.000000  173400.000000  173400.000000\n",
       "mean    11812.909769     291.548449     428.008651\n",
       "std      7956.892203     810.569058     257.380509\n",
       "min         7.000000      12.000000       1.000000\n",
       "25%      5961.000000      39.000000     207.000000\n",
       "50%     10995.000000      97.000000     413.000000\n",
       "75%     17829.000000     238.000000     647.000000\n",
       "max     42971.000000   16950.000000     900.000000"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings_atp.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "la table ratings contient le classement complet ATP (Rank, ATP point) des joueurs toutes les deux semaines (vu le nombre d'échantillons et le nombre présent maximum (900) dans le classement). On ne retrouve aucune valeur abbérante, ni de valeur manquante."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stat_atp.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID1</th>\n",
       "      <th>ID2</th>\n",
       "      <th>ID_T</th>\n",
       "      <th>ID_R</th>\n",
       "      <th>FS_1</th>\n",
       "      <th>FSOF_1</th>\n",
       "      <th>ACES_1</th>\n",
       "      <th>DF_1</th>\n",
       "      <th>UE_1</th>\n",
       "      <th>W1S_1</th>\n",
       "      <th>...</th>\n",
       "      <th>NAOF_2</th>\n",
       "      <th>TPW_2</th>\n",
       "      <th>FAST_2</th>\n",
       "      <th>A1S_2</th>\n",
       "      <th>A2S_2</th>\n",
       "      <th>RPW_1</th>\n",
       "      <th>RPWOF_1</th>\n",
       "      <th>RPW_2</th>\n",
       "      <th>RPWOF_2</th>\n",
       "      <th>MT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>401</td>\n",
       "      <td>921</td>\n",
       "      <td>2205</td>\n",
       "      <td>1</td>\n",
       "      <td>52.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>65</td>\n",
       "      <td>706</td>\n",
       "      <td>2205</td>\n",
       "      <td>1</td>\n",
       "      <td>37.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>77</td>\n",
       "      <td>406</td>\n",
       "      <td>2205</td>\n",
       "      <td>1</td>\n",
       "      <td>32.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>840</td>\n",
       "      <td>666</td>\n",
       "      <td>2205</td>\n",
       "      <td>2</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>831</td>\n",
       "      <td>880</td>\n",
       "      <td>2205</td>\n",
       "      <td>2</td>\n",
       "      <td>49.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID1  ID2  ID_T  ID_R  FS_1  FSOF_1  ACES_1  DF_1  UE_1  W1S_1 ...   NAOF_2  \\\n",
       "0  401  921  2205     1  52.0    91.0     1.0   2.0  25.0   37.0 ...     32.0   \n",
       "1   65  706  2205     1  37.0    71.0     3.0   6.0  28.0   27.0 ...     10.0   \n",
       "2   77  406  2205     1  32.0    50.0     4.0   0.0   7.0   26.0 ...     26.0   \n",
       "3  840  666  2205     2  50.0    75.0     4.0   2.0  31.0   29.0 ...     29.0   \n",
       "4  831  880  2205     2  49.0    79.0    11.0   5.0  43.0   37.0 ...     11.0   \n",
       "\n",
       "   TPW_2  FAST_2  A1S_2  A2S_2  RPW_1  RPWOF_1  RPW_2  RPWOF_2   MT  \n",
       "0   83.0     NaN    NaN    NaN   31.0     78.0   36.0     91.0  NaN  \n",
       "1   62.0     NaN    NaN    NaN   31.0     67.0   26.0     71.0  NaN  \n",
       "2   46.0     NaN    NaN    NaN   23.0     58.0   11.0     50.0  NaN  \n",
       "3   80.0     NaN    NaN    NaN   38.0     86.0   32.0     75.0  NaN  \n",
       "4   73.0     NaN    NaN    NaN   34.0     81.0   26.0     79.0  NaN  \n",
       "\n",
       "[5 rows x 45 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat_atp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 124273 entries, 0 to 124272\n",
      "Data columns (total 45 columns):\n",
      "ID1        124273 non-null int64\n",
      "ID2        124273 non-null int64\n",
      "ID_T       124273 non-null int64\n",
      "ID_R       124273 non-null int64\n",
      "FS_1       124269 non-null float64\n",
      "FSOF_1     124268 non-null float64\n",
      "ACES_1     122636 non-null float64\n",
      "DF_1       123790 non-null float64\n",
      "UE_1       11621 non-null float64\n",
      "W1S_1      124272 non-null float64\n",
      "W1SOF_1    124272 non-null float64\n",
      "W2S_1      124269 non-null float64\n",
      "W2SOF_1    124269 non-null float64\n",
      "WIS_1      11376 non-null float64\n",
      "BP_1       124240 non-null float64\n",
      "BPOF_1     124240 non-null float64\n",
      "NA_1       8079 non-null float64\n",
      "NAOF_1     8079 non-null float64\n",
      "TPW_1      123937 non-null float64\n",
      "FAST_1     4449 non-null float64\n",
      "A1S_1      4370 non-null float64\n",
      "A2S_1      4362 non-null float64\n",
      "FS_2       124269 non-null float64\n",
      "FSOF_2     124268 non-null float64\n",
      "ACES_2     122627 non-null float64\n",
      "DF_2       123808 non-null float64\n",
      "UE_2       11621 non-null float64\n",
      "W1S_2      124272 non-null float64\n",
      "W1SOF_2    124272 non-null float64\n",
      "W2S_2      124269 non-null float64\n",
      "W2SOF_2    124269 non-null float64\n",
      "WIS_2      11375 non-null float64\n",
      "BP_2       124176 non-null float64\n",
      "BPOF_2     124210 non-null float64\n",
      "NA_2       8079 non-null float64\n",
      "NAOF_2     8078 non-null float64\n",
      "TPW_2      123937 non-null float64\n",
      "FAST_2     4449 non-null float64\n",
      "A1S_2      4370 non-null float64\n",
      "A2S_2      4362 non-null float64\n",
      "RPW_1      123718 non-null float64\n",
      "RPWOF_1    123718 non-null float64\n",
      "RPW_2      123718 non-null float64\n",
      "RPWOF_2    123718 non-null float64\n",
      "MT         99138 non-null object\n",
      "dtypes: float64(40), int64(4), object(1)\n",
      "memory usage: 42.7+ MB\n"
     ]
    }
   ],
   "source": [
    "stat_atp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cette table contient les informations détaillé d'un grand nombre de match (124273). Ne pouvant prendre les données d'un match pour sa prédiction, nous utiliserons cette table afin d'utiliser les matchs antécédents des deux joueurs. Ainsi cette base sera utilisé pour calculer les features d'un match."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il y a beaucoup de valeur manquante/abbérante qu'il faudra traiter au cas par cas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous devons créer notre training set avec des proportions égales. Il s'agit d'une classification bi-classe donc il faut qu'il y a environ autant de match gagné par le joueur 1 que par le joueur 2. Il faut donc transformer notre training set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/gozuslayer/anaconda2/lib/python2.7/site-packages/pandas/core/indexing.py:132: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    }
   ],
   "source": [
    "def unbiased_games_atp(games_atp):\n",
    "    #preparing biased data\n",
    "    #create predict variable\n",
    "    games_atp['result']= games_atp['RESULT_G'].map(lambda x:1)\n",
    "\n",
    "    #swap id1 & id2 and predic variable is 1\n",
    "    games_atp['result'].iloc[::2] = games_atp['RESULT_G'].iloc[::2].map(lambda x:0)\n",
    "    idx = (games_atp['result']==0)\n",
    "    games_atp.loc[idx,['ID1_G','ID2_G']] = games_atp.loc[idx,['ID2_G','ID1_G']].values\n",
    "    return games_atp\n",
    "\n",
    "#checking if result (compare with other notebook) GOOD\n",
    "games_atp_unbiased = unbiased_games_atp(games_atp)\n",
    "train = games_atp_unbiased\n",
    "test = games_atp_public"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Procedons maintenant au nettoyage de stat_atp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/gozuslayer/anaconda2/lib/python2.7/site-packages/numpy/lib/function_base.py:3834: RuntimeWarning: Invalid value encountered in percentile\n",
      "  RuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID1</th>\n",
       "      <th>ID2</th>\n",
       "      <th>ID_T</th>\n",
       "      <th>ID_R</th>\n",
       "      <th>FS_1</th>\n",
       "      <th>FSOF_1</th>\n",
       "      <th>ACES_1</th>\n",
       "      <th>DF_1</th>\n",
       "      <th>UE_1</th>\n",
       "      <th>W1S_1</th>\n",
       "      <th>...</th>\n",
       "      <th>NA_2</th>\n",
       "      <th>NAOF_2</th>\n",
       "      <th>TPW_2</th>\n",
       "      <th>FAST_2</th>\n",
       "      <th>A1S_2</th>\n",
       "      <th>A2S_2</th>\n",
       "      <th>RPW_1</th>\n",
       "      <th>RPWOF_1</th>\n",
       "      <th>RPW_2</th>\n",
       "      <th>RPWOF_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>124273.000000</td>\n",
       "      <td>124273.000000</td>\n",
       "      <td>124273.000000</td>\n",
       "      <td>124273.000000</td>\n",
       "      <td>124269.000000</td>\n",
       "      <td>124268.000000</td>\n",
       "      <td>122636.000000</td>\n",
       "      <td>123790.000000</td>\n",
       "      <td>11621.000000</td>\n",
       "      <td>124272.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>8079.000000</td>\n",
       "      <td>8078.000000</td>\n",
       "      <td>123937.000000</td>\n",
       "      <td>4449.000000</td>\n",
       "      <td>4370.000000</td>\n",
       "      <td>4362.000000</td>\n",
       "      <td>123718.000000</td>\n",
       "      <td>123718.000000</td>\n",
       "      <td>123718.000000</td>\n",
       "      <td>123718.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>11838.072695</td>\n",
       "      <td>13498.939094</td>\n",
       "      <td>10051.389884</td>\n",
       "      <td>4.788377</td>\n",
       "      <td>43.078419</td>\n",
       "      <td>69.199730</td>\n",
       "      <td>4.995531</td>\n",
       "      <td>2.548671</td>\n",
       "      <td>22.541262</td>\n",
       "      <td>31.992613</td>\n",
       "      <td>...</td>\n",
       "      <td>16.316252</td>\n",
       "      <td>27.534167</td>\n",
       "      <td>63.368833</td>\n",
       "      <td>201.753203</td>\n",
       "      <td>180.338215</td>\n",
       "      <td>147.946813</td>\n",
       "      <td>31.286426</td>\n",
       "      <td>71.914055</td>\n",
       "      <td>22.772078</td>\n",
       "      <td>69.154990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>11631.132455</td>\n",
       "      <td>12580.644475</td>\n",
       "      <td>2883.371240</td>\n",
       "      <td>2.860029</td>\n",
       "      <td>16.264655</td>\n",
       "      <td>24.842891</td>\n",
       "      <td>4.433386</td>\n",
       "      <td>2.161332</td>\n",
       "      <td>17.795331</td>\n",
       "      <td>11.323782</td>\n",
       "      <td>...</td>\n",
       "      <td>11.603016</td>\n",
       "      <td>19.537553</td>\n",
       "      <td>26.095818</td>\n",
       "      <td>22.875558</td>\n",
       "      <td>16.505270</td>\n",
       "      <td>14.700695</td>\n",
       "      <td>9.673268</td>\n",
       "      <td>24.605637</td>\n",
       "      <td>11.170876</td>\n",
       "      <td>24.841434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1111.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1687.000000</td>\n",
       "      <td>2379.000000</td>\n",
       "      <td>8089.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8662.000000</td>\n",
       "      <td>10066.000000</td>\n",
       "      <td>10819.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>18398.000000</td>\n",
       "      <td>21973.000000</td>\n",
       "      <td>12698.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>56645.000000</td>\n",
       "      <td>56647.000000</td>\n",
       "      <td>13590.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>243.000000</td>\n",
       "      <td>112.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>224.000000</td>\n",
       "      <td>502.000000</td>\n",
       "      <td>242.000000</td>\n",
       "      <td>212.000000</td>\n",
       "      <td>191.000000</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>253.000000</td>\n",
       "      <td>255.000000</td>\n",
       "      <td>243.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ID1            ID2           ID_T           ID_R  \\\n",
       "count  124273.000000  124273.000000  124273.000000  124273.000000   \n",
       "mean    11838.072695   13498.939094   10051.389884       4.788377   \n",
       "std     11631.132455   12580.644475    2883.371240       2.860029   \n",
       "min         1.000000       1.000000    1111.000000       1.000000   \n",
       "25%      1687.000000    2379.000000    8089.000000       4.000000   \n",
       "50%      8662.000000   10066.000000   10819.000000       4.000000   \n",
       "75%     18398.000000   21973.000000   12698.000000       5.000000   \n",
       "max     56645.000000   56647.000000   13590.000000      17.000000   \n",
       "\n",
       "                FS_1         FSOF_1         ACES_1           DF_1  \\\n",
       "count  124269.000000  124268.000000  122636.000000  123790.000000   \n",
       "mean       43.078419      69.199730       4.995531       2.548671   \n",
       "std        16.264655      24.842891       4.433386       2.161332   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "25%              NaN            NaN            NaN            NaN   \n",
       "50%              NaN            NaN            NaN            NaN   \n",
       "75%              NaN            NaN            NaN            NaN   \n",
       "max       183.000000     243.000000     112.000000      24.000000   \n",
       "\n",
       "               UE_1          W1S_1      ...               NA_2       NAOF_2  \\\n",
       "count  11621.000000  124272.000000      ...        8079.000000  8078.000000   \n",
       "mean      22.541262      31.992613      ...          16.316252    27.534167   \n",
       "std       17.795331      11.323782      ...          11.603016    19.537553   \n",
       "min        0.000000       0.000000      ...           0.000000     0.000000   \n",
       "25%             NaN            NaN      ...                NaN          NaN   \n",
       "50%             NaN            NaN      ...                NaN          NaN   \n",
       "75%             NaN            NaN      ...                NaN          NaN   \n",
       "max      128.000000     144.000000      ...         125.000000   224.000000   \n",
       "\n",
       "               TPW_2       FAST_2        A1S_2        A2S_2          RPW_1  \\\n",
       "count  123937.000000  4449.000000  4370.000000  4362.000000  123718.000000   \n",
       "mean       63.368833   201.753203   180.338215   147.946813      31.286426   \n",
       "std        26.095818    22.875558    16.505270    14.700695       9.673268   \n",
       "min         0.000000     0.000000     0.000000     0.000000       0.000000   \n",
       "25%              NaN          NaN          NaN          NaN            NaN   \n",
       "50%              NaN          NaN          NaN          NaN            NaN   \n",
       "75%              NaN          NaN          NaN          NaN            NaN   \n",
       "max       502.000000   242.000000   212.000000   191.000000     110.000000   \n",
       "\n",
       "             RPWOF_1          RPW_2        RPWOF_2  \n",
       "count  123718.000000  123718.000000  123718.000000  \n",
       "mean       71.914055      22.772078      69.154990  \n",
       "std        24.605637      11.170876      24.841434  \n",
       "min         0.000000       0.000000       0.000000  \n",
       "25%              NaN            NaN            NaN  \n",
       "50%              NaN            NaN            NaN  \n",
       "75%              NaN            NaN            NaN  \n",
       "max       253.000000     255.000000     243.000000  \n",
       "\n",
       "[8 rows x 44 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat_atp.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/gozuslayer/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:5: FutureWarning: \n",
      "The default value for 'return_type' will change to 'axes' in a future release.\n",
      " To use the future behavior now, set return_type='axes'.\n",
      " To keep the previous behavior and silence this warning, set return_type='dict'.\n",
      "/home/gozuslayer/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:7: FutureWarning: \n",
      "The default value for 'return_type' will change to 'axes' in a future release.\n",
      " To use the future behavior now, set return_type='axes'.\n",
      " To keep the previous behavior and silence this warning, set return_type='dict'.\n"
     ]
    },
    {
     "data": {
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GJxeQTxo++fjkAvJJQz7J5O3SdEHB0qVLXStEkE8yPrmAfNLwyccnF5BPGvJJJm+Xpmto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\nYY59G07TNx+fUN70L4YPH17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BlvW95bXng15Gf3MLPYLXcuZ97VXu+MvkqqdiQPna8xPg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\nnw8Cy47/aaRKDggaqxpjxhAcj28StPfYR1BNswi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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff5af031c10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MudMYc3yF/b5mjHnRGNNrjLnHGPOexPZRxpgbjTEbjTFbjDF3GGMOS36PEELk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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff5af0a4790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "columns = ['W1S_','W1SOF_','W2S_','W2SOF_','BP_','BPOF_','RPW_','RPWOF_','TPW_','ACES_','FS_','FSOF_','DF_']\n",
    "columns_player_ID1 = [s + '1' for s in columns]\n",
    "columns_player_ID2 = [s + '2' for s in columns]\n",
    "plt.figure(1)\n",
    "stat_atp[columns_player_ID1].boxplot()\n",
    "plt.figure(2)\n",
    "stat_atp[columns_player_ID2].boxplot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les données sont cohérentes car le joueur 2 perd le match : il doit donc avoir en moyenne des stats inférieur au joueur 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FS_* et FSOF_* correspond à la réussite de premier service. Il n'y a priori aucune valeur abbérante. Pour le traitement des valeur manquantes, on peut décider de les remplir avec la moyenne."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.FS_1 = stat_atp.FS_1.fillna(stat_atp.FS_1.mean())\n",
    "stat_atp.FS_2 = stat_atp.FS_2.fillna(stat_atp.FS_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.FSOF_1 = stat_atp.FSOF_1.fillna(stat_atp.FSOF_1.mean())\n",
    "stat_atp.FSOF_2 = stat_atp.FSOF_2.fillna(stat_atp.FSOF_2.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ACES_* correspond aux nombres d'aces fait pendant le match. De même, on remplit par la moyenne."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.ACES_1 = stat_atp.ACES_1.fillna(stat_atp.ACES_1.mean())\n",
    "stat_atp.ACES_2 = stat_atp.ACES_2.fillna(stat_atp.ACES_2.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DF_* correspond aux doubles fautes commises dans le match. de même"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.DF_1 = stat_atp.DF_1.fillna(stat_atp.DF_1.mean())\n",
    "stat_atp.DF_2 = stat_atp.DF_2.fillna(stat_atp.DF_2.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "De même pour le reste des variables..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.W1S_1 = stat_atp.W1S_1.fillna(stat_atp.W1S_1.mean())\n",
    "stat_atp.W1SOF_1 = stat_atp.W1SOF_1.fillna(stat_atp.W1SOF_1.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.W2SOF_1 = stat_atp.W2SOF_1.fillna(stat_atp.W2SOF_1.mean())\n",
    "stat_atp.W2S_1= stat_atp.W2S_1.fillna(stat_atp.W2S_1.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.BP_1 = stat_atp.BP_1.fillna(stat_atp.BP_1.mean())\n",
    "stat_atp.BP_2 = stat_atp.BP_2.fillna(stat_atp.BP_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.TPW_1= stat_atp.TPW_1.fillna(stat_atp.TPW_1.mean())\n",
    "stat_atp.TPW_2= stat_atp.TPW_2.fillna(stat_atp.TPW_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.RPW_1= stat_atp.RPW_1.fillna(stat_atp.RPW_1.mean())\n",
    "stat_atp.RPW_2= stat_atp.RPW_2.fillna(stat_atp.RPW_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.RPWOF_1= stat_atp.RPWOF_1.fillna(stat_atp.RPWOF_1.mean())\n",
    "stat_atp.RPWOF_2= stat_atp.RPWOF_2.fillna(stat_atp.RPWOF_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.BPOF_1= stat_atp.BPOF_1.fillna(stat_atp.BPOF_1.mean())\n",
    "stat_atp.BPOF_2= stat_atp.BPOF_2.fillna(stat_atp.BPOF_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.W2SOF_1 = stat_atp.W2SOF_1.fillna(stat_atp.W2SOF_1.mean())\n",
    "stat_atp.W2SOF_2 = stat_atp.W2SOF_2.fillna(stat_atp.W2SOF_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.W1SOF_1 = stat_atp.W1SOF_1.fillna(stat_atp.W1SOF_1.mean())\n",
    "stat_atp.W1SOF_2 = stat_atp.W1SOF_2.fillna(stat_atp.W1SOF_2.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "stat_atp.W2S_2= stat_atp.W2S_2.fillna(stat_atp.W2S_2.mean())\n",
    "\n",
    "stat_atp.W2S_1 = stat_atp.W2S_1.fillna(stat_atp.W2S_1.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stat_atp.W1S_2 = stat_atp.W1S_2.fillna(stat_atp.W1S_2.mean())\n",
    "stat_atp.W1S_1 = stat_atp.W1S_1.fillna(stat_atp.W1S_1.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On retire les variables où il manque trop d'information..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 124273 entries, 0 to 124272\n",
      "Data columns (total 45 columns):\n",
      "ID1        124273 non-null int64\n",
      "ID2        124273 non-null int64\n",
      "ID_T       124273 non-null int64\n",
      "ID_R       124273 non-null int64\n",
      "FS_1       124273 non-null float64\n",
      "FSOF_1     124273 non-null float64\n",
      "ACES_1     124273 non-null float64\n",
      "DF_1       124273 non-null float64\n",
      "UE_1       11621 non-null float64\n",
      "W1S_1      124273 non-null float64\n",
      "W1SOF_1    124273 non-null float64\n",
      "W2S_1      124273 non-null float64\n",
      "W2SOF_1    124273 non-null float64\n",
      "WIS_1      11376 non-null float64\n",
      "BP_1       124273 non-null float64\n",
      "BPOF_1     124273 non-null float64\n",
      "NA_1       8079 non-null float64\n",
      "NAOF_1     8079 non-null float64\n",
      "TPW_1      124273 non-null float64\n",
      "FAST_1     4449 non-null float64\n",
      "A1S_1      4370 non-null float64\n",
      "A2S_1      4362 non-null float64\n",
      "FS_2       124273 non-null float64\n",
      "FSOF_2     124273 non-null float64\n",
      "ACES_2     124273 non-null float64\n",
      "DF_2       124273 non-null float64\n",
      "UE_2       11621 non-null float64\n",
      "W1S_2      124273 non-null float64\n",
      "W1SOF_2    124273 non-null float64\n",
      "W2S_2      124273 non-null float64\n",
      "W2SOF_2    124273 non-null float64\n",
      "WIS_2      11375 non-null float64\n",
      "BP_2       124273 non-null float64\n",
      "BPOF_2     124273 non-null float64\n",
      "NA_2       8079 non-null float64\n",
      "NAOF_2     8078 non-null float64\n",
      "TPW_2      124273 non-null float64\n",
      "FAST_2     4449 non-null float64\n",
      "A1S_2      4370 non-null float64\n",
      "A2S_2      4362 non-null float64\n",
      "RPW_1      124273 non-null float64\n",
      "RPWOF_1    124273 non-null float64\n",
      "RPW_2      124273 non-null float64\n",
      "RPWOF_2    124273 non-null float64\n",
      "MT         99138 non-null object\n",
      "dtypes: float64(40), int64(4), object(1)\n",
      "memory usage: 42.7+ MB\n"
     ]
    }
   ],
   "source": [
    "stat_atp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "columns_to_drop = ['UE_','NA_','NAOF_','WIS_','FAST_','A1S_','A2S_']\n",
    "columns_player_ID1 = [s + '1' for s in columns_to_drop]\n",
    "columns_player_ID2 = [s + '2' for s in columns_to_drop]\n",
    "col = columns_player_ID2 + columns_player_ID1\n",
    "stat_atp.drop(col, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 124273 entries, 0 to 124272\n",
      "Data columns (total 31 columns):\n",
      "ID1        124273 non-null int64\n",
      "ID2        124273 non-null int64\n",
      "ID_T       124273 non-null int64\n",
      "ID_R       124273 non-null int64\n",
      "FS_1       124273 non-null float64\n",
      "FSOF_1     124273 non-null float64\n",
      "ACES_1     124273 non-null float64\n",
      "DF_1       124273 non-null float64\n",
      "W1S_1      124273 non-null float64\n",
      "W1SOF_1    124273 non-null float64\n",
      "W2S_1      124273 non-null float64\n",
      "W2SOF_1    124273 non-null float64\n",
      "BP_1       124273 non-null float64\n",
      "BPOF_1     124273 non-null float64\n",
      "TPW_1      124273 non-null float64\n",
      "FS_2       124273 non-null float64\n",
      "FSOF_2     124273 non-null float64\n",
      "ACES_2     124273 non-null float64\n",
      "DF_2       124273 non-null float64\n",
      "W1S_2      124273 non-null float64\n",
      "W1SOF_2    124273 non-null float64\n",
      "W2S_2      124273 non-null float64\n",
      "W2SOF_2    124273 non-null float64\n",
      "BP_2       124273 non-null float64\n",
      "BPOF_2     124273 non-null float64\n",
      "TPW_2      124273 non-null float64\n",
      "RPW_1      124273 non-null float64\n",
      "RPWOF_1    124273 non-null float64\n",
      "RPW_2      124273 non-null float64\n",
      "RPWOF_2    124273 non-null float64\n",
      "MT         99138 non-null object\n",
      "dtypes: float64(26), int64(4), object(1)\n",
      "memory usage: 29.4+ MB\n"
     ]
    }
   ],
   "source": [
    "stat_atp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On admet que lorsqu'un match n'a pas de date (MT : MatchTime) on lui attribue la date du tournoi (dans tours.csv). Cependant lorsque l'on regarde de plus près le MT ne doit pas être bon vu la date des matchs..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('1899-12-30 23:32:21')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime(stat_atp.MT).max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "inf"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stat_atp.MT.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#mergin tables\n",
    "columns_tours_to_keep = ['ID_T','DATE_T']\n",
    "stat_atp = pd.merge(stat_atp,tours_atp[columns_tours_to_keep],on=\"ID_T\",how=\"left\")\n",
    "\n",
    "#Remplissage de la date des matchs.\n",
    "stat_atp.MT = stat_atp.DATE_T\n",
    "stat_atp.drop('DATE_T', axis=1, inplace = \"True\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 124273 entries, 0 to 124272\n",
      "Data columns (total 45 columns):\n",
      "ID1        124273 non-null int64\n",
      "ID2        124273 non-null int64\n",
      "ID_T       124273 non-null int64\n",
      "ID_R       124273 non-null int64\n",
      "FS_1       124269 non-null float64\n",
      "FSOF_1     124268 non-null float64\n",
      "ACES_1     122636 non-null float64\n",
      "DF_1       123790 non-null float64\n",
      "UE_1       11621 non-null float64\n",
      "W1S_1      124272 non-null float64\n",
      "W1SOF_1    124272 non-null float64\n",
      "W2S_1      124269 non-null float64\n",
      "W2SOF_1    124269 non-null float64\n",
      "WIS_1      11376 non-null float64\n",
      "BP_1       124240 non-null float64\n",
      "BPOF_1     124240 non-null float64\n",
      "NA_1       8079 non-null float64\n",
      "NAOF_1     8079 non-null float64\n",
      "TPW_1      123937 non-null float64\n",
      "FAST_1     4449 non-null float64\n",
      "A1S_1      4370 non-null float64\n",
      "A2S_1      4362 non-null float64\n",
      "FS_2       124269 non-null float64\n",
      "FSOF_2     124268 non-null float64\n",
      "ACES_2     122627 non-null float64\n",
      "DF_2       123808 non-null float64\n",
      "UE_2       11621 non-null float64\n",
      "W1S_2      124272 non-null float64\n",
      "W1SOF_2    124272 non-null float64\n",
      "W2S_2      124269 non-null float64\n",
      "W2SOF_2    124269 non-null float64\n",
      "WIS_2      11375 non-null float64\n",
      "BP_2       124176 non-null float64\n",
      "BPOF_2     124210 non-null float64\n",
      "NA_2       8079 non-null float64\n",
      "NAOF_2     8078 non-null float64\n",
      "TPW_2      123937 non-null float64\n",
      "FAST_2     4449 non-null float64\n",
      "A1S_2      4370 non-null float64\n",
      "A2S_2      4362 non-null float64\n",
      "RPW_1      123718 non-null float64\n",
      "RPWOF_1    123718 non-null float64\n",
      "RPW_2      123718 non-null float64\n",
      "RPWOF_2    123718 non-null float64\n",
      "MT         124273 non-null object\n",
      "dtypes: float64(40), int64(4), object(1)\n",
      "memory usage: 43.6+ MB\n"
     ]
    }
   ],
   "source": [
    "stat_atp.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature extraction "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Enrichissons notre table stats_atp avec la tours_atp en y ajoutant le type de surface et le rating du tournoi (grand chelem, masters, ...)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#mergin tables\n",
    "columns_tours_to_keep = ['ID_T','ID_C_T','RANK_T']\n",
    "stat_atp = pd.merge(stat_atp,tours_atp[columns_tours_to_keep],on=\"ID_T\",how=\"left\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#creating total point won percentage per game for player 1 and 2\n",
    "stat_atp['TPW_per_1'] = stat_atp['TPW_1'] / (stat_atp['TPW_1'] + stat_atp['TPW_2'] ) \n",
    "stat_atp['TPW_per_2'] = stat_atp['TPW_2'] / (stat_atp['TPW_1'] + stat_atp['TPW_2'] )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "columns = ['ID','W1S_','W1SOF_','W2S_','W2SOF_','BP_','BPOF_','RPW_','RPWOF_','TPW_','ACES_','FS_','FSOF_','DF_','TPW_per_']\n",
    "columns_player_ID1 = [s + '1' for s in columns]\n",
    "columns_player_ID2 = [s + '2' for s in columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_average_stats_for_two_player_before_date(ID):\n",
    "    \n",
    "    #getting dataframe of both players\n",
    "    df = stat_atp.loc[(stat_atp['ID1']==ID[0])|(stat_atp['ID2']==ID[0])|(stat_atp['ID1']==ID[1])|(stat_atp['ID2']==ID[1])]\n",
    "    \n",
    "    #selecting date before\n",
    "    df = df.loc[pd.to_datetime(df.MT)<ID[2]]\n",
    "    \n",
    "    #division of dataframe between both players\n",
    "    df1 = df.loc[(df['ID1']==ID[0])|(df['ID2']==ID[0])]\n",
    "    df2 = df.loc[(df['ID1']==ID[1])|(df['ID2']==ID[1])]\n",
    "    \n",
    "    res1 = df1.loc[df['ID1']==ID[0]][columns_player_ID1]\n",
    "    res1bis = df1.loc[df['ID2']==ID[0]][columns_player_ID2]\n",
    "    res1bis.columns = columns_player_ID1\n",
    "    res1 = pd.concat([res1,res1bis])\n",
    "    res1 = res1.mean()\n",
    "    \n",
    "    \n",
    "    res4 = df.loc[df['ID2']==ID[1]][columns_player_ID2]\n",
    "    res5 = df.loc[df['ID1']==ID[1]][columns_player_ID1]\n",
    "    res5.columns = columns_player_ID2\n",
    "    res6 = pd.concat([res5,res4])\n",
    "    res6 = res6.mean()\n",
    "    \n",
    "    res = pd.concat([res1,res6],axis=0)\n",
    "    return res\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "KeyboardInterrupt\n",
      "\n"
     ]
    }
   ],
   "source": [
    "train[columns_player_ID1+columns_player_ID2] = train[['ID1_G','ID2_G','DATE_G']].apply(get_average_stats_for_two_player_before_date,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 38 columns):\n",
      "Unnamed: 0    84485 non-null int64\n",
      "ID1_G         84485 non-null int64\n",
      "ID2_G         84485 non-null int64\n",
      "ID_T_G        84485 non-null int64\n",
      "ID_R_G        84485 non-null int64\n",
      "RESULT_G      84485 non-null object\n",
      "DATE_G        84485 non-null object\n",
      "result        84485 non-null int64\n",
      "ID1           79396 non-null float64\n",
      "W1S_1         79396 non-null float64\n",
      "W1SOF_1       79396 non-null float64\n",
      "W2S_1         79396 non-null float64\n",
      "W2SOF_1       79396 non-null float64\n",
      "BP_1          79396 non-null float64\n",
      "BPOF_1        79396 non-null float64\n",
      "RPW_1         79396 non-null float64\n",
      "RPWOF_1       79396 non-null float64\n",
      "TPW_1         79396 non-null float64\n",
      "ACES_1        79396 non-null float64\n",
      "FS_1          79396 non-null float64\n",
      "FSOF_1        79396 non-null float64\n",
      "DF_1          79396 non-null float64\n",
      "TPW_per_1     79396 non-null float64\n",
      "ID2           79389 non-null float64\n",
      "W1S_2         79389 non-null float64\n",
      "W1SOF_2       79389 non-null float64\n",
      "W2S_2         79389 non-null float64\n",
      "W2SOF_2       79389 non-null float64\n",
      "BP_2          79389 non-null float64\n",
      "BPOF_2        79389 non-null float64\n",
      "RPW_2         79389 non-null float64\n",
      "RPWOF_2       79389 non-null float64\n",
      "TPW_2         79389 non-null float64\n",
      "ACES_2        79389 non-null float64\n",
      "FS_2          79389 non-null float64\n",
      "FSOF_2        79389 non-null float64\n",
      "DF_2          79389 non-null float64\n",
      "TPW_per_2     79389 non-null float64\n",
      "dtypes: float64(30), int64(6), object(2)\n",
      "memory usage: 24.5+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il manque certaines données sur des joueurs... "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>ID1_G</th>\n",
       "      <th>ID2_G</th>\n",
       "      <th>ID_T_G</th>\n",
       "      <th>ID_R_G</th>\n",
       "      <th>RESULT_G</th>\n",
       "      <th>DATE_G</th>\n",
       "      <th>result</th>\n",
       "      <th>ID1</th>\n",
       "      <th>W1S_1</th>\n",
       "      <th>...</th>\n",
       "      <th>BP_2</th>\n",
       "      <th>BPOF_2</th>\n",
       "      <th>RPW_2</th>\n",
       "      <th>RPWOF_2</th>\n",
       "      <th>TPW_2</th>\n",
       "      <th>ACES_2</th>\n",
       "      <th>FS_2</th>\n",
       "      <th>FSOF_2</th>\n",
       "      <th>DF_2</th>\n",
       "      <th>TPW_per_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>18854</td>\n",
       "      <td>17613</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(8) 3-6 10-7</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>25192</td>\n",
       "      <td>25191</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-2</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>25197</td>\n",
       "      <td>15916</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(2) 6-4</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>55.500000</td>\n",
       "      <td>59.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>0.561321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31</td>\n",
       "      <td>25086</td>\n",
       "      <td>25087</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 6-2</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>38</td>\n",
       "      <td>12430</td>\n",
       "      <td>1181</td>\n",
       "      <td>8881</td>\n",
       "      <td>2</td>\n",
       "      <td>6-3 7-6(3)</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.992772</td>\n",
       "      <td>5.208032</td>\n",
       "      <td>25.344371</td>\n",
       "      <td>73.642384</td>\n",
       "      <td>72.063873</td>\n",
       "      <td>7.980132</td>\n",
       "      <td>44.423841</td>\n",
       "      <td>73.033113</td>\n",
       "      <td>2.600789</td>\n",
       "      <td>0.491637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>58</td>\n",
       "      <td>24408</td>\n",
       "      <td>17108</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 7-6(2)</td>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>60</td>\n",
       "      <td>17157</td>\n",
       "      <td>19793</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-6(3)</td>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>78</td>\n",
       "      <td>20612</td>\n",
       "      <td>17731</td>\n",
       "      <td>8880</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 3-6 10-6</td>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>82</td>\n",
       "      <td>25090</td>\n",
       "      <td>5554</td>\n",
       "      <td>8881</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 6-1</td>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.351648</td>\n",
       "      <td>5.802198</td>\n",
       "      <td>23.648352</td>\n",
       "      <td>65.439560</td>\n",
       "      <td>68.010989</td>\n",
       "      <td>3.386464</td>\n",
       "      <td>43.406593</td>\n",
       "      <td>65.813187</td>\n",
       "      <td>1.989011</td>\n",
       "      <td>0.521243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>88</td>\n",
       "      <td>16414</td>\n",
       "      <td>20156</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>97</td>\n",
       "      <td>25084</td>\n",
       "      <td>14074</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>7-5 6-7(3) 10-4</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.431034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>102</td>\n",
       "      <td>25083</td>\n",
       "      <td>22347</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>1-6 6-3 12-10</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>104</td>\n",
       "      <td>25085</td>\n",
       "      <td>22755</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 6-4</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>106</td>\n",
       "      <td>20406</td>\n",
       "      <td>5554</td>\n",
       "      <td>8881</td>\n",
       "      <td>9</td>\n",
       "      <td>6-3 6-3</td>\n",
       "      <td>2012-01-04</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.351648</td>\n",
       "      <td>5.802198</td>\n",
       "      <td>23.648352</td>\n",
       "      <td>65.439560</td>\n",
       "      <td>68.010989</td>\n",
       "      <td>3.386464</td>\n",
       "      <td>43.406593</td>\n",
       "      <td>65.813187</td>\n",
       "      <td>1.989011</td>\n",
       "      <td>0.521243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>109</td>\n",
       "      <td>25099</td>\n",
       "      <td>11748</td>\n",
       "      <td>8880</td>\n",
       "      <td>9</td>\n",
       "      <td>6-3 7-5</td>\n",
       "      <td>2012-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.464286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>110</td>\n",
       "      <td>17731</td>\n",
       "      <td>15237</td>\n",
       "      <td>8880</td>\n",
       "      <td>9</td>\n",
       "      <td>6-3 7-5</td>\n",
       "      <td>2012-01-04</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>113</td>\n",
       "      <td>25084</td>\n",
       "      <td>22755</td>\n",
       "      <td>8882</td>\n",
       "      <td>9</td>\n",
       "      <td>6-2 7-5</td>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>114</td>\n",
       "      <td>17613</td>\n",
       "      <td>20156</td>\n",
       "      <td>8882</td>\n",
       "      <td>9</td>\n",
       "      <td>7-5 6-3</td>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>116</td>\n",
       "      <td>25086</td>\n",
       "      <td>19793</td>\n",
       "      <td>8882</td>\n",
       "      <td>9</td>\n",
       "      <td>3-6 6-3 15-13</td>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>122</td>\n",
       "      <td>17108</td>\n",
       "      <td>22347</td>\n",
       "      <td>8882</td>\n",
       "      <td>9</td>\n",
       "      <td>w/o</td>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>126</td>\n",
       "      <td>25103</td>\n",
       "      <td>15237</td>\n",
       "      <td>8880</td>\n",
       "      <td>10</td>\n",
       "      <td>6-2 3-6 13-11</td>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>129</td>\n",
       "      <td>21065</td>\n",
       "      <td>21097</td>\n",
       "      <td>8881</td>\n",
       "      <td>9</td>\n",
       "      <td>6-3 4-6 10-7</td>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>144</td>\n",
       "      <td>22367</td>\n",
       "      <td>25092</td>\n",
       "      <td>8881</td>\n",
       "      <td>9</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>148</td>\n",
       "      <td>25084</td>\n",
       "      <td>19793</td>\n",
       "      <td>8882</td>\n",
       "      <td>10</td>\n",
       "      <td>7-6(1) 6-3</td>\n",
       "      <td>2012-01-06</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>177</td>\n",
       "      <td>25099</td>\n",
       "      <td>25098</td>\n",
       "      <td>8880</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 5-7 10-6</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>190</td>\n",
       "      <td>25088</td>\n",
       "      <td>25089</td>\n",
       "      <td>8881</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 7-5</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>191</td>\n",
       "      <td>22367</td>\n",
       "      <td>25091</td>\n",
       "      <td>8881</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-5</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>197</td>\n",
       "      <td>15237</td>\n",
       "      <td>25100</td>\n",
       "      <td>8880</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(6) 7-5</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>199</td>\n",
       "      <td>17613</td>\n",
       "      <td>12317</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 6-3</td>\n",
       "      <td>2012-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.452991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>217</td>\n",
       "      <td>25103</td>\n",
       "      <td>15916</td>\n",
       "      <td>8880</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-4</td>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>55.500000</td>\n",
       "      <td>59.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>0.561321</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>82300</th>\n",
       "      <td>82300</td>\n",
       "      <td>45941</td>\n",
       "      <td>3747</td>\n",
       "      <td>13177</td>\n",
       "      <td>1</td>\n",
       "      <td>6-0 6-0</td>\n",
       "      <td>2016-07-16</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.142857</td>\n",
       "      <td>7.428571</td>\n",
       "      <td>27.952381</td>\n",
       "      <td>68.619048</td>\n",
       "      <td>67.714286</td>\n",
       "      <td>1.999787</td>\n",
       "      <td>43.476190</td>\n",
       "      <td>67.380952</td>\n",
       "      <td>1.502318</td>\n",
       "      <td>0.499197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82302</th>\n",
       "      <td>82302</td>\n",
       "      <td>54370</td>\n",
       "      <td>28263</td>\n",
       "      <td>13177</td>\n",
       "      <td>1</td>\n",
       "      <td>6-1 6-0</td>\n",
       "      <td>2016-07-16</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.086957</td>\n",
       "      <td>29.652174</td>\n",
       "      <td>75.130435</td>\n",
       "      <td>75.130435</td>\n",
       "      <td>5.217197</td>\n",
       "      <td>39.260870</td>\n",
       "      <td>73.826087</td>\n",
       "      <td>3.173913</td>\n",
       "      <td>0.509653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82332</th>\n",
       "      <td>82332</td>\n",
       "      <td>54380</td>\n",
       "      <td>18122</td>\n",
       "      <td>13179</td>\n",
       "      <td>1</td>\n",
       "      <td>6-1 6-2</td>\n",
       "      <td>2016-07-16</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.233333</td>\n",
       "      <td>5.733333</td>\n",
       "      <td>25.016667</td>\n",
       "      <td>68.558333</td>\n",
       "      <td>69.625000</td>\n",
       "      <td>5.850000</td>\n",
       "      <td>44.650000</td>\n",
       "      <td>70.858333</td>\n",
       "      <td>2.658333</td>\n",
       "      <td>0.502463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82440</th>\n",
       "      <td>82440</td>\n",
       "      <td>22064</td>\n",
       "      <td>23575</td>\n",
       "      <td>13178</td>\n",
       "      <td>1</td>\n",
       "      <td>6-3 6-2</td>\n",
       "      <td>2016-07-16</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.050000</td>\n",
       "      <td>6.850000</td>\n",
       "      <td>30.150000</td>\n",
       "      <td>73.900000</td>\n",
       "      <td>71.850000</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>44.800000</td>\n",
       "      <td>70.750000</td>\n",
       "      <td>3.650000</td>\n",
       "      <td>0.499903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82442</th>\n",
       "      <td>82442</td>\n",
       "      <td>54384</td>\n",
       "      <td>1128</td>\n",
       "      <td>13178</td>\n",
       "      <td>1</td>\n",
       "      <td>6-3 6-2</td>\n",
       "      <td>2016-07-16</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.941176</td>\n",
       "      <td>6.852941</td>\n",
       "      <td>30.205882</td>\n",
       "      <td>74.882353</td>\n",
       "      <td>76.529412</td>\n",
       "      <td>5.470457</td>\n",
       "      <td>42.676471</td>\n",
       "      <td>75.676471</td>\n",
       "      <td>5.058824</td>\n",
       "      <td>0.513421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82469</th>\n",
       "      <td>82469</td>\n",
       "      <td>54197</td>\n",
       "      <td>44821</td>\n",
       "      <td>13176</td>\n",
       "      <td>4</td>\n",
       "      <td>3-6 6-0 21-19</td>\n",
       "      <td>2016-07-12</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.474453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82470</th>\n",
       "      <td>82470</td>\n",
       "      <td>54197</td>\n",
       "      <td>49899</td>\n",
       "      <td>13176</td>\n",
       "      <td>9</td>\n",
       "      <td>7-6(5) 6-4</td>\n",
       "      <td>2016-07-14</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.260870</td>\n",
       "      <td>6.565217</td>\n",
       "      <td>22.130435</td>\n",
       "      <td>60.652174</td>\n",
       "      <td>61.782609</td>\n",
       "      <td>2.869565</td>\n",
       "      <td>38.782609</td>\n",
       "      <td>58.391304</td>\n",
       "      <td>3.260870</td>\n",
       "      <td>0.525356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82652</th>\n",
       "      <td>82652</td>\n",
       "      <td>54407</td>\n",
       "      <td>25150</td>\n",
       "      <td>13177</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-7(5) 10-7</td>\n",
       "      <td>2016-07-18</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.420000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82688</th>\n",
       "      <td>82688</td>\n",
       "      <td>54419</td>\n",
       "      <td>43507</td>\n",
       "      <td>13179</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-1</td>\n",
       "      <td>2016-07-18</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82702</th>\n",
       "      <td>82702</td>\n",
       "      <td>54388</td>\n",
       "      <td>20937</td>\n",
       "      <td>12829</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 6-1</td>\n",
       "      <td>2016-07-18</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.088235</td>\n",
       "      <td>6.205882</td>\n",
       "      <td>24.823529</td>\n",
       "      <td>70.735294</td>\n",
       "      <td>71.323529</td>\n",
       "      <td>2.705882</td>\n",
       "      <td>47.911765</td>\n",
       "      <td>72.117647</td>\n",
       "      <td>2.280843</td>\n",
       "      <td>0.499423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82707</th>\n",
       "      <td>82707</td>\n",
       "      <td>54423</td>\n",
       "      <td>54422</td>\n",
       "      <td>13179</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 3-6 10-6</td>\n",
       "      <td>2016-07-18</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82716</th>\n",
       "      <td>82716</td>\n",
       "      <td>54421</td>\n",
       "      <td>39803</td>\n",
       "      <td>13179</td>\n",
       "      <td>4</td>\n",
       "      <td>6-0 7-6(4)</td>\n",
       "      <td>2016-07-18</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.407407</td>\n",
       "      <td>5.925926</td>\n",
       "      <td>20.703704</td>\n",
       "      <td>57.185185</td>\n",
       "      <td>57.037037</td>\n",
       "      <td>1.111111</td>\n",
       "      <td>37.814815</td>\n",
       "      <td>59.814815</td>\n",
       "      <td>3.074074</td>\n",
       "      <td>0.486727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83436</th>\n",
       "      <td>83436</td>\n",
       "      <td>54576</td>\n",
       "      <td>30375</td>\n",
       "      <td>13184</td>\n",
       "      <td>1</td>\n",
       "      <td>6-0 6-0</td>\n",
       "      <td>2016-07-23</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>7.777778</td>\n",
       "      <td>29.305556</td>\n",
       "      <td>68.416667</td>\n",
       "      <td>68.277778</td>\n",
       "      <td>1.861111</td>\n",
       "      <td>42.666667</td>\n",
       "      <td>65.916667</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>0.513916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83480</th>\n",
       "      <td>83480</td>\n",
       "      <td>24390</td>\n",
       "      <td>18094</td>\n",
       "      <td>13186</td>\n",
       "      <td>1</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>2016-07-23</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.702128</td>\n",
       "      <td>6.680851</td>\n",
       "      <td>26.829787</td>\n",
       "      <td>67.978723</td>\n",
       "      <td>68.382979</td>\n",
       "      <td>3.702128</td>\n",
       "      <td>40.404255</td>\n",
       "      <td>67.914894</td>\n",
       "      <td>2.978723</td>\n",
       "      <td>0.509591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83520</th>\n",
       "      <td>83520</td>\n",
       "      <td>33530</td>\n",
       "      <td>14377</td>\n",
       "      <td>13182</td>\n",
       "      <td>1</td>\n",
       "      <td>w/o</td>\n",
       "      <td>2016-07-23</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.806452</td>\n",
       "      <td>5.387097</td>\n",
       "      <td>24.580645</td>\n",
       "      <td>62.193548</td>\n",
       "      <td>61.870968</td>\n",
       "      <td>2.284063</td>\n",
       "      <td>40.516129</td>\n",
       "      <td>64.258065</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.487017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83588</th>\n",
       "      <td>83588</td>\n",
       "      <td>34915</td>\n",
       "      <td>25703</td>\n",
       "      <td>13422</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-1</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.952381</td>\n",
       "      <td>6.285714</td>\n",
       "      <td>26.523810</td>\n",
       "      <td>66.523810</td>\n",
       "      <td>64.428571</td>\n",
       "      <td>2.523810</td>\n",
       "      <td>39.190476</td>\n",
       "      <td>63.619048</td>\n",
       "      <td>1.978508</td>\n",
       "      <td>0.510333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83603</th>\n",
       "      <td>83603</td>\n",
       "      <td>54595</td>\n",
       "      <td>48239</td>\n",
       "      <td>13184</td>\n",
       "      <td>4</td>\n",
       "      <td>6-7(6) 6-2 10-7</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.090909</td>\n",
       "      <td>6.545455</td>\n",
       "      <td>20.727273</td>\n",
       "      <td>56.545455</td>\n",
       "      <td>60.909091</td>\n",
       "      <td>3.545455</td>\n",
       "      <td>37.727273</td>\n",
       "      <td>59.545455</td>\n",
       "      <td>1.545455</td>\n",
       "      <td>0.529275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83614</th>\n",
       "      <td>83614</td>\n",
       "      <td>54588</td>\n",
       "      <td>54587</td>\n",
       "      <td>13181</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-6(5)</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83638</th>\n",
       "      <td>83638</td>\n",
       "      <td>54589</td>\n",
       "      <td>54590</td>\n",
       "      <td>13181</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-4</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83640</th>\n",
       "      <td>83640</td>\n",
       "      <td>54591</td>\n",
       "      <td>54592</td>\n",
       "      <td>13184</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 3-6 11-9</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83648</th>\n",
       "      <td>83648</td>\n",
       "      <td>54582</td>\n",
       "      <td>8091</td>\n",
       "      <td>12830</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 3-6 11-9</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.466667</td>\n",
       "      <td>7.400000</td>\n",
       "      <td>29.866667</td>\n",
       "      <td>80.733333</td>\n",
       "      <td>81.600000</td>\n",
       "      <td>3.200000</td>\n",
       "      <td>52.400000</td>\n",
       "      <td>75.800000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.524934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83652</th>\n",
       "      <td>83652</td>\n",
       "      <td>54138</td>\n",
       "      <td>26942</td>\n",
       "      <td>13410</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-3</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.111111</td>\n",
       "      <td>5.111111</td>\n",
       "      <td>22.888889</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>57.111111</td>\n",
       "      <td>3.332837</td>\n",
       "      <td>33.555556</td>\n",
       "      <td>62.666667</td>\n",
       "      <td>2.222222</td>\n",
       "      <td>0.439850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83668</th>\n",
       "      <td>83668</td>\n",
       "      <td>31944</td>\n",
       "      <td>5103</td>\n",
       "      <td>13186</td>\n",
       "      <td>3</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.599455</td>\n",
       "      <td>6.504087</td>\n",
       "      <td>27.778671</td>\n",
       "      <td>73.937752</td>\n",
       "      <td>73.565038</td>\n",
       "      <td>5.732970</td>\n",
       "      <td>45.185286</td>\n",
       "      <td>72.414169</td>\n",
       "      <td>1.970027</td>\n",
       "      <td>0.504157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83678</th>\n",
       "      <td>83678</td>\n",
       "      <td>25755</td>\n",
       "      <td>36259</td>\n",
       "      <td>13408</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-0</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.090909</td>\n",
       "      <td>5.181818</td>\n",
       "      <td>23.363636</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>58.363636</td>\n",
       "      <td>1.363636</td>\n",
       "      <td>35.818182</td>\n",
       "      <td>65.181818</td>\n",
       "      <td>2.454545</td>\n",
       "      <td>0.438066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83680</th>\n",
       "      <td>83680</td>\n",
       "      <td>36592</td>\n",
       "      <td>33729</td>\n",
       "      <td>13408</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 7-5</td>\n",
       "      <td>2016-07-25</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.555556</td>\n",
       "      <td>4.222222</td>\n",
       "      <td>18.444444</td>\n",
       "      <td>54.777778</td>\n",
       "      <td>50.111111</td>\n",
       "      <td>2.111111</td>\n",
       "      <td>31.777778</td>\n",
       "      <td>60.777778</td>\n",
       "      <td>3.222222</td>\n",
       "      <td>0.408769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83688</th>\n",
       "      <td>83688</td>\n",
       "      <td>54619</td>\n",
       "      <td>14861</td>\n",
       "      <td>13422</td>\n",
       "      <td>4</td>\n",
       "      <td>6-0 6-0</td>\n",
       "      <td>2016-07-26</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3.727273</td>\n",
       "      <td>8.363636</td>\n",
       "      <td>31.045455</td>\n",
       "      <td>70.984848</td>\n",
       "      <td>72.590909</td>\n",
       "      <td>3.181750</td>\n",
       "      <td>41.439394</td>\n",
       "      <td>69.530303</td>\n",
       "      <td>3.348485</td>\n",
       "      <td>0.522291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83902</th>\n",
       "      <td>83902</td>\n",
       "      <td>54611</td>\n",
       "      <td>54610</td>\n",
       "      <td>13182</td>\n",
       "      <td>4</td>\n",
       "      <td>w/o</td>\n",
       "      <td>2016-07-26</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83904</th>\n",
       "      <td>83904</td>\n",
       "      <td>34888</td>\n",
       "      <td>12950</td>\n",
       "      <td>13183</td>\n",
       "      <td>4</td>\n",
       "      <td>6-0 6-2</td>\n",
       "      <td>2016-07-26</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.866667</td>\n",
       "      <td>6.266667</td>\n",
       "      <td>22.666667</td>\n",
       "      <td>56.866667</td>\n",
       "      <td>57.066667</td>\n",
       "      <td>4.600000</td>\n",
       "      <td>33.933333</td>\n",
       "      <td>55.933333</td>\n",
       "      <td>2.266667</td>\n",
       "      <td>0.508152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84390</th>\n",
       "      <td>84390</td>\n",
       "      <td>38818</td>\n",
       "      <td>25928</td>\n",
       "      <td>13298</td>\n",
       "      <td>1</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>2016-07-30</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.424000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84432</th>\n",
       "      <td>84432</td>\n",
       "      <td>54154</td>\n",
       "      <td>12767</td>\n",
       "      <td>13296</td>\n",
       "      <td>1</td>\n",
       "      <td>6-0 6-0</td>\n",
       "      <td>2016-07-30</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.659091</td>\n",
       "      <td>6.318182</td>\n",
       "      <td>27.522727</td>\n",
       "      <td>72.079545</td>\n",
       "      <td>70.511364</td>\n",
       "      <td>4.518255</td>\n",
       "      <td>42.613636</td>\n",
       "      <td>70.352273</td>\n",
       "      <td>2.602273</td>\n",
       "      <td>0.497175</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5089 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0  ID1_G  ID2_G  ID_T_G  ID_R_G         RESULT_G      DATE_G  \\\n",
       "0               0  18854  17613    8887       4  7-6(8) 3-6 10-7  2012-01-31   \n",
       "1               1  25192  25191    8888       4          6-3 6-2  2012-01-31   \n",
       "21             21  25197  15916    8888       4       7-6(2) 6-4  2012-01-31   \n",
       "31             31  25086  25087    8882       4          6-2 6-2  2012-01-01   \n",
       "38             38  12430   1181    8881       2       6-3 7-6(3)  2012-01-01   \n",
       "58             58  24408  17108    8882       4       6-1 7-6(2)  2012-01-02   \n",
       "60             60  17157  19793    8882       4       6-4 7-6(3)  2012-01-02   \n",
       "78             78  20612  17731    8880       4     6-2 3-6 10-6  2012-01-02   \n",
       "82             82  25090   5554    8881       4          6-2 6-1  2012-01-02   \n",
       "88             88  16414  20156    8882       4          6-4 6-4  2012-01-03   \n",
       "97             97  25084  14074    8882       4  7-5 6-7(3) 10-4  2012-01-03   \n",
       "102           102  25083  22347    8882       4    1-6 6-3 12-10  2012-01-03   \n",
       "104           104  25085  22755    8882       4          6-2 6-4  2012-01-03   \n",
       "106           106  20406   5554    8881       9          6-3 6-3  2012-01-04   \n",
       "109           109  25099  11748    8880       9          6-3 7-5  2012-01-04   \n",
       "110           110  17731  15237    8880       9          6-3 7-5  2012-01-04   \n",
       "113           113  25084  22755    8882       9          6-2 7-5  2012-01-05   \n",
       "114           114  17613  20156    8882       9          7-5 6-3  2012-01-05   \n",
       "116           116  25086  19793    8882       9    3-6 6-3 15-13  2012-01-05   \n",
       "122           122  17108  22347    8882       9              w/o  2012-01-05   \n",
       "126           126  25103  15237    8880      10    6-2 3-6 13-11  2012-01-05   \n",
       "129           129  21065  21097    8881       9     6-3 4-6 10-7  2012-01-05   \n",
       "144           144  22367  25092    8881       9          6-3 6-4  2012-01-05   \n",
       "148           148  25084  19793    8882      10       7-6(1) 6-3  2012-01-06   \n",
       "177           177  25099  25098    8880       4     6-4 5-7 10-6  2012-01-03   \n",
       "190           190  25088  25089    8881       4          6-1 7-5  2012-01-03   \n",
       "191           191  22367  25091    8881       4          6-4 7-5  2012-01-03   \n",
       "197           197  15237  25100    8880       4       7-6(6) 7-5  2012-01-03   \n",
       "199           199  17613  12317    8882       4          6-2 6-3  2012-01-04   \n",
       "217           217  25103  15916    8880       4          6-1 6-4  2012-01-03   \n",
       "...           ...    ...    ...     ...     ...              ...         ...   \n",
       "82300       82300  45941   3747   13177       1          6-0 6-0  2016-07-16   \n",
       "82302       82302  54370  28263   13177       1          6-1 6-0  2016-07-16   \n",
       "82332       82332  54380  18122   13179       1          6-1 6-2  2016-07-16   \n",
       "82440       82440  22064  23575   13178       1          6-3 6-2  2016-07-16   \n",
       "82442       82442  54384   1128   13178       1          6-3 6-2  2016-07-16   \n",
       "82469       82469  54197  44821   13176       4    3-6 6-0 21-19  2016-07-12   \n",
       "82470       82470  54197  49899   13176       9       7-6(5) 6-4  2016-07-14   \n",
       "82652       82652  54407  25150   13177       4  6-4 6-7(5) 10-7  2016-07-18   \n",
       "82688       82688  54419  43507   13179       4          6-1 6-1  2016-07-18   \n",
       "82702       82702  54388  20937   12829       4          6-2 6-1  2016-07-18   \n",
       "82707       82707  54423  54422   13179       4     6-3 3-6 10-6  2016-07-18   \n",
       "82716       82716  54421  39803   13179       4       6-0 7-6(4)  2016-07-18   \n",
       "83436       83436  54576  30375   13184       1          6-0 6-0  2016-07-23   \n",
       "83480       83480  24390  18094   13186       1          6-3 6-4  2016-07-23   \n",
       "83520       83520  33530  14377   13182       1              w/o  2016-07-23   \n",
       "83588       83588  34915  25703   13422       4          6-4 6-1  2016-07-25   \n",
       "83603       83603  54595  48239   13184       4  6-7(6) 6-2 10-7  2016-07-25   \n",
       "83614       83614  54588  54587   13181       4       6-4 7-6(5)  2016-07-25   \n",
       "83638       83638  54589  54590   13181       4          6-1 6-4  2016-07-25   \n",
       "83640       83640  54591  54592   13184       4     6-4 3-6 11-9  2016-07-25   \n",
       "83648       83648  54582   8091   12830       4     6-1 3-6 11-9  2016-07-25   \n",
       "83652       83652  54138  26942   13410       4          6-3 6-3  2016-07-25   \n",
       "83668       83668  31944   5103   13186       3          6-3 6-4  2016-07-25   \n",
       "83678       83678  25755  36259   13408       4          6-3 6-0  2016-07-25   \n",
       "83680       83680  36592  33729   13408       4          6-3 7-5  2016-07-25   \n",
       "83688       83688  54619  14861   13422       4          6-0 6-0  2016-07-26   \n",
       "83902       83902  54611  54610   13182       4              w/o  2016-07-26   \n",
       "83904       83904  34888  12950   13183       4          6-0 6-2  2016-07-26   \n",
       "84390       84390  38818  25928   13298       1          6-3 6-4  2016-07-30   \n",
       "84432       84432  54154  12767   13296       1          6-0 6-0  2016-07-30   \n",
       "\n",
       "       result  ID1  W1S_1    ...          BP_2    BPOF_2      RPW_2  \\\n",
       "0           0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "1           1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "21          1  NaN    NaN    ...      3.000000  5.000000  21.000000   \n",
       "31          1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "38          0  NaN    NaN    ...      1.992772  5.208032  25.344371   \n",
       "58          0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "60          0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "78          0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "82          0  NaN    NaN    ...      2.351648  5.802198  23.648352   \n",
       "88          0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "97          1  NaN    NaN    ...      3.000000  7.000000  21.000000   \n",
       "102         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "104         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "106         0  NaN    NaN    ...      2.351648  5.802198  23.648352   \n",
       "109         1  NaN    NaN    ...      1.000000  5.000000  22.000000   \n",
       "110         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "113         1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "114         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "116         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "122         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "126         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "129         1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "144         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "148         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "177         1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "190         0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "191         1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "197         1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "199         1  NaN    NaN    ...      2.000000  5.000000  18.000000   \n",
       "217         1  NaN    NaN    ...      3.000000  5.000000  21.000000   \n",
       "...       ...  ...    ...    ...           ...       ...        ...   \n",
       "82300       0  NaN    NaN    ...      3.142857  7.428571  27.952381   \n",
       "82302       0  NaN    NaN    ...      3.000000  7.086957  29.652174   \n",
       "82332       0  NaN    NaN    ...      2.233333  5.733333  25.016667   \n",
       "82440       0  NaN    NaN    ...      3.050000  6.850000  30.150000   \n",
       "82442       0  NaN    NaN    ...      2.941176  6.852941  30.205882   \n",
       "82469       1  NaN    NaN    ...      3.000000  8.000000  23.000000   \n",
       "82470       0  NaN    NaN    ...      2.260870  6.565217  22.130435   \n",
       "82652       0  NaN    NaN    ...      1.000000  7.000000  17.000000   \n",
       "82688       0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "82702       0  NaN    NaN    ...      2.088235  6.205882  24.823529   \n",
       "82707       1  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "82716       0  NaN    NaN    ...      2.407407  5.925926  20.703704   \n",
       "83436       0  NaN    NaN    ...      3.500000  7.777778  29.305556   \n",
       "83480       0  NaN    NaN    ...      2.702128  6.680851  26.829787   \n",
       "83520       0  NaN    NaN    ...      2.806452  5.387097  24.580645   \n",
       "83588       0  NaN    NaN    ...      2.952381  6.285714  26.523810   \n",
       "83603       1  NaN    NaN    ...      2.090909  6.545455  20.727273   \n",
       "83614       0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "83638       0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "83640       0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "83648       0  NaN    NaN    ...      2.466667  7.400000  29.866667   \n",
       "83652       0  NaN    NaN    ...      2.111111  5.111111  22.888889   \n",
       "83668       0  NaN    NaN    ...      2.599455  6.504087  27.778671   \n",
       "83678       0  NaN    NaN    ...      2.090909  5.181818  23.363636   \n",
       "83680       0  NaN    NaN    ...      1.555556  4.222222  18.444444   \n",
       "83688       0  NaN    NaN    ...      3.727273  8.363636  31.045455   \n",
       "83902       0  NaN    NaN    ...           NaN       NaN        NaN   \n",
       "83904       0  NaN    NaN    ...      2.866667  6.266667  22.666667   \n",
       "84390       0  NaN    NaN    ...      0.000000  2.000000  17.000000   \n",
       "84432       0  NaN    NaN    ...      2.659091  6.318182  27.522727   \n",
       "\n",
       "         RPWOF_2      TPW_2    ACES_2       FS_2     FSOF_2      DF_2  \\\n",
       "0            NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "1            NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "21     55.500000  59.500000  3.000000  37.000000  50.500000  2.500000   \n",
       "31           NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "38     73.642384  72.063873  7.980132  44.423841  73.033113  2.600789   \n",
       "58           NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "60           NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "78           NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "82     65.439560  68.010989  3.386464  43.406593  65.813187  1.989011   \n",
       "88           NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "97     57.000000  50.000000  0.000000  39.000000  59.000000  2.000000   \n",
       "102          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "104          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "106    65.439560  68.010989  3.386464  43.406593  65.813187  1.989011   \n",
       "109    58.000000  52.000000  5.000000  38.000000  54.000000  0.000000   \n",
       "110          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "113          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "114          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "116          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "122          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "126          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "129          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "144          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "148          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "177          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "190          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "191          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "197          NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "199    57.000000  53.000000  5.000000  41.000000  60.000000  2.000000   \n",
       "217    55.500000  59.500000  3.000000  37.000000  50.500000  2.500000   \n",
       "...          ...        ...       ...        ...        ...       ...   \n",
       "82300  68.619048  67.714286  1.999787  43.476190  67.380952  1.502318   \n",
       "82302  75.130435  75.130435  5.217197  39.260870  73.826087  3.173913   \n",
       "82332  68.558333  69.625000  5.850000  44.650000  70.858333  2.658333   \n",
       "82440  73.900000  71.850000  2.300000  44.800000  70.750000  3.650000   \n",
       "82442  74.882353  76.529412  5.470457  42.676471  75.676471  5.058824   \n",
       "82469  66.000000  65.000000  5.000000  48.000000  71.000000  3.000000   \n",
       "82470  60.652174  61.782609  2.869565  38.782609  58.391304  3.260870   \n",
       "82652  52.000000  42.000000  1.000000  34.000000  48.000000  0.000000   \n",
       "82688        NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "82702  70.735294  71.323529  2.705882  47.911765  72.117647  2.280843   \n",
       "82707        NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "82716  57.185185  57.037037  1.111111  37.814815  59.814815  3.074074   \n",
       "83436  68.416667  68.277778  1.861111  42.666667  65.916667  1.750000   \n",
       "83480  67.978723  68.382979  3.702128  40.404255  67.914894  2.978723   \n",
       "83520  62.193548  61.870968  2.284063  40.516129  64.258065  2.000000   \n",
       "83588  66.523810  64.428571  2.523810  39.190476  63.619048  1.978508   \n",
       "83603  56.545455  60.909091  3.545455  37.727273  59.545455  1.545455   \n",
       "83614        NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "83638        NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "83640        NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "83648  80.733333  81.600000  3.200000  52.400000  75.800000  2.000000   \n",
       "83652  63.000000  57.111111  3.332837  33.555556  62.666667  2.222222   \n",
       "83668  73.937752  73.565038  5.732970  45.185286  72.414169  1.970027   \n",
       "83678  64.000000  58.363636  1.363636  35.818182  65.181818  2.454545   \n",
       "83680  54.777778  50.111111  2.111111  31.777778  60.777778  3.222222   \n",
       "83688  70.984848  72.590909  3.181750  41.439394  69.530303  3.348485   \n",
       "83902        NaN        NaN       NaN        NaN        NaN       NaN   \n",
       "83904  56.866667  57.066667  4.600000  33.933333  55.933333  2.266667   \n",
       "84390  58.000000  53.000000  2.000000  35.000000  67.000000  3.000000   \n",
       "84432  72.079545  70.511364  4.518255  42.613636  70.352273  2.602273   \n",
       "\n",
       "       TPW_per_2  \n",
       "0            NaN  \n",
       "1            NaN  \n",
       "21      0.561321  \n",
       "31           NaN  \n",
       "38      0.491637  \n",
       "58           NaN  \n",
       "60           NaN  \n",
       "78           NaN  \n",
       "82      0.521243  \n",
       "88           NaN  \n",
       "97      0.431034  \n",
       "102          NaN  \n",
       "104          NaN  \n",
       "106     0.521243  \n",
       "109     0.464286  \n",
       "110          NaN  \n",
       "113          NaN  \n",
       "114          NaN  \n",
       "116          NaN  \n",
       "122          NaN  \n",
       "126          NaN  \n",
       "129          NaN  \n",
       "144          NaN  \n",
       "148          NaN  \n",
       "177          NaN  \n",
       "190          NaN  \n",
       "191          NaN  \n",
       "197          NaN  \n",
       "199     0.452991  \n",
       "217     0.561321  \n",
       "...          ...  \n",
       "82300   0.499197  \n",
       "82302   0.509653  \n",
       "82332   0.502463  \n",
       "82440   0.499903  \n",
       "82442   0.513421  \n",
       "82469   0.474453  \n",
       "82470   0.525356  \n",
       "82652   0.420000  \n",
       "82688        NaN  \n",
       "82702   0.499423  \n",
       "82707        NaN  \n",
       "82716   0.486727  \n",
       "83436   0.513916  \n",
       "83480   0.509591  \n",
       "83520   0.487017  \n",
       "83588   0.510333  \n",
       "83603   0.529275  \n",
       "83614        NaN  \n",
       "83638        NaN  \n",
       "83640        NaN  \n",
       "83648   0.524934  \n",
       "83652   0.439850  \n",
       "83668   0.504157  \n",
       "83678   0.438066  \n",
       "83680   0.408769  \n",
       "83688   0.522291  \n",
       "83902        NaN  \n",
       "83904   0.508152  \n",
       "84390   0.424000  \n",
       "84432   0.497175  \n",
       "\n",
       "[5089 rows x 38 columns]"
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.loc[train.ID1.isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_P</th>\n",
       "      <th>NAME_P</th>\n",
       "      <th>DATE_P</th>\n",
       "      <th>COUNTRY_P</th>\n",
       "      <th>RANK_P</th>\n",
       "      <th>PROGRESS_P</th>\n",
       "      <th>POINT_P</th>\n",
       "      <th>HARDPOINT_P</th>\n",
       "      <th>HARDTOUR_P</th>\n",
       "      <th>CLAYPOINT_P</th>\n",
       "      <th>...</th>\n",
       "      <th>CARPETPOINT_P</th>\n",
       "      <th>CARPETTOUR_P</th>\n",
       "      <th>PRIZE_P</th>\n",
       "      <th>CH_P</th>\n",
       "      <th>DR_P</th>\n",
       "      <th>DP_P</th>\n",
       "      <th>DO_P</th>\n",
       "      <th>IHARDPOINT_P</th>\n",
       "      <th>IHARDTOUR_P</th>\n",
       "      <th>ITF_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12203</th>\n",
       "      <td>12430</td>\n",
       "      <td>Prajnesh Gunneswaran</td>\n",
       "      <td>1989-11-12 00:00:00</td>\n",
       "      <td>IND</td>\n",
       "      <td>344.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21070.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID_P                NAME_P               DATE_P COUNTRY_P  RANK_P  \\\n",
       "12203  12430  Prajnesh Gunneswaran  1989-11-12 00:00:00       IND   344.0   \n",
       "\n",
       "       PROGRESS_P  POINT_P  HARDPOINT_P  HARDTOUR_P  CLAYPOINT_P   ...    \\\n",
       "12203        15.0    135.0         64.0        11.0          3.0   ...     \n",
       "\n",
       "       CARPETPOINT_P  CARPETTOUR_P  PRIZE_P  CH_P  DR_P  DP_P  DO_P  \\\n",
       "12203            0.0           0.0  21070.0   NaN   NaN   NaN   NaN   \n",
       "\n",
       "       IHARDPOINT_P  IHARDTOUR_P  ITF_ID  \n",
       "12203           0.0          0.0     NaN  \n",
       "\n",
       "[1 rows x 23 columns]"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "players_atp.loc[players_atp.ID_P ==12430]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_P</th>\n",
       "      <th>NAME_P</th>\n",
       "      <th>DATE_P</th>\n",
       "      <th>COUNTRY_P</th>\n",
       "      <th>RANK_P</th>\n",
       "      <th>PROGRESS_P</th>\n",
       "      <th>POINT_P</th>\n",
       "      <th>HARDPOINT_P</th>\n",
       "      <th>HARDTOUR_P</th>\n",
       "      <th>CLAYPOINT_P</th>\n",
       "      <th>...</th>\n",
       "      <th>CARPETPOINT_P</th>\n",
       "      <th>CARPETTOUR_P</th>\n",
       "      <th>PRIZE_P</th>\n",
       "      <th>CH_P</th>\n",
       "      <th>DR_P</th>\n",
       "      <th>DP_P</th>\n",
       "      <th>DO_P</th>\n",
       "      <th>IHARDPOINT_P</th>\n",
       "      <th>IHARDTOUR_P</th>\n",
       "      <th>ITF_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18317</th>\n",
       "      <td>18854</td>\n",
       "      <td>Martin Emmrich/Andreas Siljestrom</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID_P                             NAME_P DATE_P COUNTRY_P  RANK_P  \\\n",
       "18317  18854  Martin Emmrich/Andreas Siljestrom    NaN       NaN     NaN   \n",
       "\n",
       "       PROGRESS_P  POINT_P  HARDPOINT_P  HARDTOUR_P  CLAYPOINT_P   ...    \\\n",
       "18317         NaN      NaN          NaN         NaN          NaN   ...     \n",
       "\n",
       "       CARPETPOINT_P  CARPETTOUR_P  PRIZE_P  CH_P  DR_P  DP_P  DO_P  \\\n",
       "18317            NaN           NaN      NaN   NaN   NaN   NaN   NaN   \n",
       "\n",
       "       IHARDPOINT_P  IHARDTOUR_P  ITF_ID  \n",
       "18317           NaN          NaN     NaN  \n",
       "\n",
       "[1 rows x 23 columns]"
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "players_atp.loc[players_atp.ID_P ==18854]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Certains joueur ne sont pas dans l'historique des match car ils sont soit trop jeunes (aucun précédent) soit une équipe (double). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 39 columns):\n",
      "Unnamed: 0      84485 non-null int64\n",
      "Unnamed: 0.1    84485 non-null int64\n",
      "ID1_G           84485 non-null int64\n",
      "ID2_G           84485 non-null int64\n",
      "ID_T_G          84485 non-null int64\n",
      "ID_R_G          84485 non-null int64\n",
      "RESULT_G        84485 non-null object\n",
      "DATE_G          84485 non-null object\n",
      "result          84485 non-null int64\n",
      "ID1             79396 non-null float64\n",
      "W1S_1           79396 non-null float64\n",
      "W1SOF_1         79396 non-null float64\n",
      "W2S_1           79396 non-null float64\n",
      "W2SOF_1         79396 non-null float64\n",
      "BP_1            79396 non-null float64\n",
      "BPOF_1          79396 non-null float64\n",
      "RPW_1           79396 non-null float64\n",
      "RPWOF_1         79396 non-null float64\n",
      "TPW_1           79396 non-null float64\n",
      "ACES_1          79396 non-null float64\n",
      "FS_1            79396 non-null float64\n",
      "FSOF_1          79396 non-null float64\n",
      "DF_1            79396 non-null float64\n",
      "TPW_per_1       79396 non-null float64\n",
      "ID2             79389 non-null float64\n",
      "W1S_2           79389 non-null float64\n",
      "W1SOF_2         79389 non-null float64\n",
      "W2S_2           79389 non-null float64\n",
      "W2SOF_2         79389 non-null float64\n",
      "BP_2            79389 non-null float64\n",
      "BPOF_2          79389 non-null float64\n",
      "RPW_2           79389 non-null float64\n",
      "RPWOF_2         79389 non-null float64\n",
      "TPW_2           79389 non-null float64\n",
      "ACES_2          79389 non-null float64\n",
      "FS_2            79389 non-null float64\n",
      "FSOF_2          79389 non-null float64\n",
      "DF_2            79389 non-null float64\n",
      "TPW_per_2       79389 non-null float64\n",
      "dtypes: float64(30), int64(7), object(2)\n",
      "memory usage: 25.1+ MB\n"
     ]
    }
   ],
   "source": [
    "#train.to_csv('HistoricalAverageStat_games_atp.csv')\n",
    "train = pd.read_csv('HistoricalAverageStat_games_atp.csv')\n",
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>ID1_G</th>\n",
       "      <th>ID2_G</th>\n",
       "      <th>ID_T_G</th>\n",
       "      <th>ID_R_G</th>\n",
       "      <th>RESULT_G</th>\n",
       "      <th>DATE_G</th>\n",
       "      <th>result</th>\n",
       "      <th>ID1</th>\n",
       "      <th>...</th>\n",
       "      <th>BP_2</th>\n",
       "      <th>BPOF_2</th>\n",
       "      <th>RPW_2</th>\n",
       "      <th>RPWOF_2</th>\n",
       "      <th>TPW_2</th>\n",
       "      <th>ACES_2</th>\n",
       "      <th>FS_2</th>\n",
       "      <th>FSOF_2</th>\n",
       "      <th>DF_2</th>\n",
       "      <th>TPW_per_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18854</td>\n",
       "      <td>17613</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(8) 3-6 10-7</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>15036.062396</td>\n",
       "      <td>...</td>\n",
       "      <td>2.641724</td>\n",
       "      <td>6.438650</td>\n",
       "      <td>26.276405</td>\n",
       "      <td>69.044217</td>\n",
       "      <td>68.795733</td>\n",
       "      <td>4.064767</td>\n",
       "      <td>42.514255</td>\n",
       "      <td>69.309763</td>\n",
       "      <td>2.971950</td>\n",
       "      <td>0.497677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>25192</td>\n",
       "      <td>25191</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-2</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>15036.062396</td>\n",
       "      <td>...</td>\n",
       "      <td>2.641724</td>\n",
       "      <td>6.438650</td>\n",
       "      <td>26.276405</td>\n",
       "      <td>69.044217</td>\n",
       "      <td>68.795733</td>\n",
       "      <td>4.064767</td>\n",
       "      <td>42.514255</td>\n",
       "      <td>69.309763</td>\n",
       "      <td>2.971950</td>\n",
       "      <td>0.497677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10828</td>\n",
       "      <td>918</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-2</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>10828.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.647108</td>\n",
       "      <td>6.559441</td>\n",
       "      <td>28.170000</td>\n",
       "      <td>76.126667</td>\n",
       "      <td>75.464563</td>\n",
       "      <td>4.596652</td>\n",
       "      <td>44.230000</td>\n",
       "      <td>77.590000</td>\n",
       "      <td>4.043333</td>\n",
       "      <td>0.492314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3316</td>\n",
       "      <td>2379</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-6(5)</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>3316.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.134651</td>\n",
       "      <td>7.582051</td>\n",
       "      <td>30.105263</td>\n",
       "      <td>74.037594</td>\n",
       "      <td>73.473684</td>\n",
       "      <td>2.857143</td>\n",
       "      <td>39.879699</td>\n",
       "      <td>70.804511</td>\n",
       "      <td>2.969925</td>\n",
       "      <td>0.513169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>6277</td>\n",
       "      <td>7869</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>6277.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.642857</td>\n",
       "      <td>6.250000</td>\n",
       "      <td>27.035714</td>\n",
       "      <td>70.535714</td>\n",
       "      <td>68.142857</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>41.714286</td>\n",
       "      <td>68.500000</td>\n",
       "      <td>2.571429</td>\n",
       "      <td>0.487519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2107</td>\n",
       "      <td>7136</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>7-5 5-7 6-3</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>2107.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.952381</td>\n",
       "      <td>5.523810</td>\n",
       "      <td>24.119048</td>\n",
       "      <td>68.571429</td>\n",
       "      <td>66.119048</td>\n",
       "      <td>3.976190</td>\n",
       "      <td>41.095238</td>\n",
       "      <td>69.119048</td>\n",
       "      <td>2.761905</td>\n",
       "      <td>0.480640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>72</td>\n",
       "      <td>678</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-4</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.863898</td>\n",
       "      <td>7.064777</td>\n",
       "      <td>29.757395</td>\n",
       "      <td>78.786327</td>\n",
       "      <td>79.373918</td>\n",
       "      <td>5.543340</td>\n",
       "      <td>46.991556</td>\n",
       "      <td>77.338728</td>\n",
       "      <td>2.348407</td>\n",
       "      <td>0.515438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>563</td>\n",
       "      <td>13796</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>563.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.265823</td>\n",
       "      <td>7.379747</td>\n",
       "      <td>30.341772</td>\n",
       "      <td>74.303797</td>\n",
       "      <td>76.300477</td>\n",
       "      <td>3.518987</td>\n",
       "      <td>46.493671</td>\n",
       "      <td>76.468354</td>\n",
       "      <td>3.367089</td>\n",
       "      <td>0.509757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>775</td>\n",
       "      <td>745</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(3) 6-1</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>775.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.388889</td>\n",
       "      <td>6.246032</td>\n",
       "      <td>27.670635</td>\n",
       "      <td>76.150794</td>\n",
       "      <td>75.669594</td>\n",
       "      <td>5.559524</td>\n",
       "      <td>48.341270</td>\n",
       "      <td>75.468254</td>\n",
       "      <td>3.373016</td>\n",
       "      <td>0.503715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>75</td>\n",
       "      <td>1266</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-6(4)</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.432628</td>\n",
       "      <td>6.497378</td>\n",
       "      <td>27.941964</td>\n",
       "      <td>76.116071</td>\n",
       "      <td>76.361668</td>\n",
       "      <td>6.383929</td>\n",
       "      <td>48.455357</td>\n",
       "      <td>76.598214</td>\n",
       "      <td>2.239057</td>\n",
       "      <td>0.504676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>7826</td>\n",
       "      <td>749</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 6-1</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>7826.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.166667</td>\n",
       "      <td>7.209677</td>\n",
       "      <td>30.075269</td>\n",
       "      <td>77.569892</td>\n",
       "      <td>76.485391</td>\n",
       "      <td>4.220430</td>\n",
       "      <td>49.779570</td>\n",
       "      <td>78.774194</td>\n",
       "      <td>4.419355</td>\n",
       "      <td>0.495449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>638</td>\n",
       "      <td>13651</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-1</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>638.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>25.875000</td>\n",
       "      <td>70.375000</td>\n",
       "      <td>66.250000</td>\n",
       "      <td>1.875000</td>\n",
       "      <td>40.125000</td>\n",
       "      <td>69.875000</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>0.465705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>5058</td>\n",
       "      <td>6002</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-2</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>5058.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.770833</td>\n",
       "      <td>6.250000</td>\n",
       "      <td>26.479167</td>\n",
       "      <td>68.125000</td>\n",
       "      <td>67.894181</td>\n",
       "      <td>3.729167</td>\n",
       "      <td>39.520833</td>\n",
       "      <td>68.125000</td>\n",
       "      <td>2.937500</td>\n",
       "      <td>0.495645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>9839</td>\n",
       "      <td>4454</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(6) 6-2</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>9839.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.901639</td>\n",
       "      <td>6.770492</td>\n",
       "      <td>27.639344</td>\n",
       "      <td>68.049180</td>\n",
       "      <td>67.792932</td>\n",
       "      <td>2.459016</td>\n",
       "      <td>39.311475</td>\n",
       "      <td>68.295082</td>\n",
       "      <td>3.475410</td>\n",
       "      <td>0.497006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>11923</td>\n",
       "      <td>920</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>11923.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.591463</td>\n",
       "      <td>6.310976</td>\n",
       "      <td>25.884146</td>\n",
       "      <td>66.798780</td>\n",
       "      <td>66.628049</td>\n",
       "      <td>3.164634</td>\n",
       "      <td>42.475610</td>\n",
       "      <td>67.725610</td>\n",
       "      <td>1.865854</td>\n",
       "      <td>0.494469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>1823</td>\n",
       "      <td>4078</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-1</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>1823.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.861111</td>\n",
       "      <td>4.944444</td>\n",
       "      <td>22.027778</td>\n",
       "      <td>63.500000</td>\n",
       "      <td>61.426912</td>\n",
       "      <td>3.361111</td>\n",
       "      <td>40.472222</td>\n",
       "      <td>66.527778</td>\n",
       "      <td>2.805556</td>\n",
       "      <td>0.460733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>6691</td>\n",
       "      <td>578</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-2</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>6691.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.294032</td>\n",
       "      <td>6.023346</td>\n",
       "      <td>26.988327</td>\n",
       "      <td>76.517510</td>\n",
       "      <td>78.075392</td>\n",
       "      <td>8.346304</td>\n",
       "      <td>46.509728</td>\n",
       "      <td>75.680934</td>\n",
       "      <td>3.840467</td>\n",
       "      <td>0.504684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>453</td>\n",
       "      <td>7806</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 7-5</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>453.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.651613</td>\n",
       "      <td>6.432258</td>\n",
       "      <td>27.651613</td>\n",
       "      <td>72.967742</td>\n",
       "      <td>71.576617</td>\n",
       "      <td>4.419355</td>\n",
       "      <td>42.438710</td>\n",
       "      <td>71.980645</td>\n",
       "      <td>2.647481</td>\n",
       "      <td>0.502875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>760</td>\n",
       "      <td>520</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-3</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>760.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.839394</td>\n",
       "      <td>7.272727</td>\n",
       "      <td>30.135673</td>\n",
       "      <td>81.306530</td>\n",
       "      <td>80.362580</td>\n",
       "      <td>6.163636</td>\n",
       "      <td>49.163636</td>\n",
       "      <td>80.451515</td>\n",
       "      <td>2.765299</td>\n",
       "      <td>0.503482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>5554</td>\n",
       "      <td>25199</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>5554.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.641724</td>\n",
       "      <td>6.438650</td>\n",
       "      <td>26.276405</td>\n",
       "      <td>69.044217</td>\n",
       "      <td>68.795733</td>\n",
       "      <td>4.064767</td>\n",
       "      <td>42.514255</td>\n",
       "      <td>69.309763</td>\n",
       "      <td>2.971950</td>\n",
       "      <td>0.497677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>516</td>\n",
       "      <td>468</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-6(7)</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>516.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.032934</td>\n",
       "      <td>5.679641</td>\n",
       "      <td>27.158683</td>\n",
       "      <td>81.940120</td>\n",
       "      <td>80.776038</td>\n",
       "      <td>10.745509</td>\n",
       "      <td>48.434132</td>\n",
       "      <td>82.688623</td>\n",
       "      <td>3.353293</td>\n",
       "      <td>0.496033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>25197</td>\n",
       "      <td>15916</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(2) 6-4</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>15036.062396</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>55.500000</td>\n",
       "      <td>59.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>0.561321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>6642</td>\n",
       "      <td>655</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(2) 6-3</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>6642.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.439982</td>\n",
       "      <td>4.473442</td>\n",
       "      <td>24.855384</td>\n",
       "      <td>84.808750</td>\n",
       "      <td>84.994119</td>\n",
       "      <td>19.037671</td>\n",
       "      <td>55.342466</td>\n",
       "      <td>83.578767</td>\n",
       "      <td>2.568827</td>\n",
       "      <td>0.508673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>3685</td>\n",
       "      <td>2123</td>\n",
       "      <td>8889</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 5-7 6-1</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>1</td>\n",
       "      <td>3685.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.175758</td>\n",
       "      <td>29.206061</td>\n",
       "      <td>72.830303</td>\n",
       "      <td>72.569738</td>\n",
       "      <td>2.643715</td>\n",
       "      <td>46.018182</td>\n",
       "      <td>72.436364</td>\n",
       "      <td>2.721212</td>\n",
       "      <td>0.498382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>838</td>\n",
       "      <td>935</td>\n",
       "      <td>8889</td>\n",
       "      <td>4</td>\n",
       "      <td>7-5 6-0</td>\n",
       "      <td>2012-01-31</td>\n",
       "      <td>0</td>\n",
       "      <td>838.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.518349</td>\n",
       "      <td>8.036697</td>\n",
       "      <td>30.417431</td>\n",
       "      <td>72.339450</td>\n",
       "      <td>73.203558</td>\n",
       "      <td>2.954128</td>\n",
       "      <td>45.270642</td>\n",
       "      <td>69.977064</td>\n",
       "      <td>1.932421</td>\n",
       "      <td>0.525667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>9839</td>\n",
       "      <td>22906</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>4-6 6-1 6-3</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>9839.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.641724</td>\n",
       "      <td>6.438650</td>\n",
       "      <td>26.276405</td>\n",
       "      <td>69.044217</td>\n",
       "      <td>68.795733</td>\n",
       "      <td>4.064767</td>\n",
       "      <td>42.514255</td>\n",
       "      <td>69.309763</td>\n",
       "      <td>2.971950</td>\n",
       "      <td>0.497677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>12896</td>\n",
       "      <td>1162</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>6-7(12) 6-3 6-4</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>12896.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.739521</td>\n",
       "      <td>6.970060</td>\n",
       "      <td>30.476905</td>\n",
       "      <td>82.376988</td>\n",
       "      <td>81.572981</td>\n",
       "      <td>4.998822</td>\n",
       "      <td>50.922156</td>\n",
       "      <td>81.074850</td>\n",
       "      <td>2.637725</td>\n",
       "      <td>0.503037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>11517</td>\n",
       "      <td>578</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>11517.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.275366</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>27.012048</td>\n",
       "      <td>76.674699</td>\n",
       "      <td>78.334842</td>\n",
       "      <td>8.421687</td>\n",
       "      <td>46.518072</td>\n",
       "      <td>75.730924</td>\n",
       "      <td>3.871486</td>\n",
       "      <td>0.505812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>3694</td>\n",
       "      <td>3996</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>6-3 6-3</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>3694.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.313333</td>\n",
       "      <td>8.066667</td>\n",
       "      <td>29.926667</td>\n",
       "      <td>73.953333</td>\n",
       "      <td>73.695838</td>\n",
       "      <td>2.073333</td>\n",
       "      <td>42.433333</td>\n",
       "      <td>72.746667</td>\n",
       "      <td>3.253333</td>\n",
       "      <td>0.512690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>7461</td>\n",
       "      <td>13398</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>6-2 6-3</td>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>7461.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>26.500000</td>\n",
       "      <td>77.333333</td>\n",
       "      <td>71.500000</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>48.166667</td>\n",
       "      <td>77.333333</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.443431</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>84455</th>\n",
       "      <td>84455</td>\n",
       "      <td>84455</td>\n",
       "      <td>30801</td>\n",
       "      <td>17964</td>\n",
       "      <td>13298</td>\n",
       "      <td>2</td>\n",
       "      <td>7-5 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>30801.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.027273</td>\n",
       "      <td>6.318182</td>\n",
       "      <td>26.427273</td>\n",
       "      <td>64.745455</td>\n",
       "      <td>64.790909</td>\n",
       "      <td>3.450886</td>\n",
       "      <td>38.736364</td>\n",
       "      <td>64.390909</td>\n",
       "      <td>3.191794</td>\n",
       "      <td>0.499311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84456</th>\n",
       "      <td>84456</td>\n",
       "      <td>84456</td>\n",
       "      <td>25928</td>\n",
       "      <td>11224</td>\n",
       "      <td>13298</td>\n",
       "      <td>2</td>\n",
       "      <td>6-1 6-2</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>25928.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.067568</td>\n",
       "      <td>6.878378</td>\n",
       "      <td>26.608503</td>\n",
       "      <td>64.946412</td>\n",
       "      <td>65.608108</td>\n",
       "      <td>2.481047</td>\n",
       "      <td>38.817568</td>\n",
       "      <td>64.358108</td>\n",
       "      <td>2.200311</td>\n",
       "      <td>0.508021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84457</th>\n",
       "      <td>84457</td>\n",
       "      <td>84457</td>\n",
       "      <td>9658</td>\n",
       "      <td>11438</td>\n",
       "      <td>13298</td>\n",
       "      <td>2</td>\n",
       "      <td>6-2 6-4</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>9658.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.024138</td>\n",
       "      <td>6.920690</td>\n",
       "      <td>27.979310</td>\n",
       "      <td>69.196552</td>\n",
       "      <td>68.859893</td>\n",
       "      <td>4.136543</td>\n",
       "      <td>43.013793</td>\n",
       "      <td>68.713793</td>\n",
       "      <td>3.567409</td>\n",
       "      <td>0.501091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84458</th>\n",
       "      <td>84458</td>\n",
       "      <td>84458</td>\n",
       "      <td>26965</td>\n",
       "      <td>25365</td>\n",
       "      <td>13409</td>\n",
       "      <td>10</td>\n",
       "      <td>6-4 6-2</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>26965.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.837838</td>\n",
       "      <td>8.256757</td>\n",
       "      <td>30.186109</td>\n",
       "      <td>70.029121</td>\n",
       "      <td>72.270270</td>\n",
       "      <td>2.202582</td>\n",
       "      <td>45.054054</td>\n",
       "      <td>68.081081</td>\n",
       "      <td>3.040541</td>\n",
       "      <td>0.533590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84459</th>\n",
       "      <td>84459</td>\n",
       "      <td>84459</td>\n",
       "      <td>12662</td>\n",
       "      <td>12226</td>\n",
       "      <td>13409</td>\n",
       "      <td>10</td>\n",
       "      <td>6-4 6-7(9) 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>12662.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.915094</td>\n",
       "      <td>7.075472</td>\n",
       "      <td>27.301887</td>\n",
       "      <td>68.490566</td>\n",
       "      <td>69.056604</td>\n",
       "      <td>3.433920</td>\n",
       "      <td>41.801887</td>\n",
       "      <td>66.386792</td>\n",
       "      <td>1.753851</td>\n",
       "      <td>0.513368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84460</th>\n",
       "      <td>84460</td>\n",
       "      <td>84460</td>\n",
       "      <td>14427</td>\n",
       "      <td>28925</td>\n",
       "      <td>13414</td>\n",
       "      <td>12</td>\n",
       "      <td>2-6 7-5 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>14427.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.178571</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>28.035714</td>\n",
       "      <td>67.714286</td>\n",
       "      <td>66.642857</td>\n",
       "      <td>2.142857</td>\n",
       "      <td>43.285714</td>\n",
       "      <td>71.071429</td>\n",
       "      <td>3.785714</td>\n",
       "      <td>0.475412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84461</th>\n",
       "      <td>84461</td>\n",
       "      <td>84461</td>\n",
       "      <td>26381</td>\n",
       "      <td>14609</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>6-4 7-5</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>26381.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.994220</td>\n",
       "      <td>7.017341</td>\n",
       "      <td>28.606936</td>\n",
       "      <td>73.352601</td>\n",
       "      <td>74.433526</td>\n",
       "      <td>3.242775</td>\n",
       "      <td>47.485549</td>\n",
       "      <td>73.138728</td>\n",
       "      <td>2.065662</td>\n",
       "      <td>0.513295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84462</th>\n",
       "      <td>84462</td>\n",
       "      <td>84462</td>\n",
       "      <td>3996</td>\n",
       "      <td>9842</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>7-6(4) 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>3996.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.589552</td>\n",
       "      <td>6.604478</td>\n",
       "      <td>27.868027</td>\n",
       "      <td>74.488422</td>\n",
       "      <td>75.014925</td>\n",
       "      <td>6.373134</td>\n",
       "      <td>45.936567</td>\n",
       "      <td>73.466418</td>\n",
       "      <td>2.100746</td>\n",
       "      <td>0.510917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84463</th>\n",
       "      <td>84463</td>\n",
       "      <td>84463</td>\n",
       "      <td>39067</td>\n",
       "      <td>50227</td>\n",
       "      <td>13185</td>\n",
       "      <td>12</td>\n",
       "      <td>6-1 3-6 13-11</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>39067.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.250000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>26.500000</td>\n",
       "      <td>68.250000</td>\n",
       "      <td>69.750000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>40.750000</td>\n",
       "      <td>65.500000</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>0.516236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84464</th>\n",
       "      <td>84464</td>\n",
       "      <td>84464</td>\n",
       "      <td>17268</td>\n",
       "      <td>13209</td>\n",
       "      <td>13411</td>\n",
       "      <td>12</td>\n",
       "      <td>7-5 2-6 6-2</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>17268.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.546392</td>\n",
       "      <td>7.587629</td>\n",
       "      <td>28.193527</td>\n",
       "      <td>65.846959</td>\n",
       "      <td>68.329897</td>\n",
       "      <td>1.737888</td>\n",
       "      <td>47.278351</td>\n",
       "      <td>68.536082</td>\n",
       "      <td>2.409475</td>\n",
       "      <td>0.508408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84465</th>\n",
       "      <td>84465</td>\n",
       "      <td>84465</td>\n",
       "      <td>10590</td>\n",
       "      <td>23575</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>10590.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.181818</td>\n",
       "      <td>7.045455</td>\n",
       "      <td>29.954545</td>\n",
       "      <td>72.727273</td>\n",
       "      <td>71.590909</td>\n",
       "      <td>2.454545</td>\n",
       "      <td>44.409091</td>\n",
       "      <td>70.909091</td>\n",
       "      <td>3.681818</td>\n",
       "      <td>0.501746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84466</th>\n",
       "      <td>84466</td>\n",
       "      <td>84466</td>\n",
       "      <td>39043</td>\n",
       "      <td>7889</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 7-6(5)</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>39043.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.396396</td>\n",
       "      <td>6.396396</td>\n",
       "      <td>26.882883</td>\n",
       "      <td>72.072072</td>\n",
       "      <td>71.045045</td>\n",
       "      <td>5.162162</td>\n",
       "      <td>42.297297</td>\n",
       "      <td>70.324324</td>\n",
       "      <td>2.419357</td>\n",
       "      <td>0.501532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84467</th>\n",
       "      <td>84467</td>\n",
       "      <td>84467</td>\n",
       "      <td>14545</td>\n",
       "      <td>17357</td>\n",
       "      <td>13415</td>\n",
       "      <td>12</td>\n",
       "      <td>7-5 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>14545.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.670588</td>\n",
       "      <td>7.729412</td>\n",
       "      <td>31.105882</td>\n",
       "      <td>72.905882</td>\n",
       "      <td>72.623529</td>\n",
       "      <td>1.992877</td>\n",
       "      <td>43.047059</td>\n",
       "      <td>73.411765</td>\n",
       "      <td>3.517647</td>\n",
       "      <td>0.497874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84468</th>\n",
       "      <td>84468</td>\n",
       "      <td>84468</td>\n",
       "      <td>29665</td>\n",
       "      <td>27358</td>\n",
       "      <td>13421</td>\n",
       "      <td>12</td>\n",
       "      <td>2-6 6-1 6-4</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>29665.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.614286</td>\n",
       "      <td>9.485714</td>\n",
       "      <td>31.642857</td>\n",
       "      <td>65.600000</td>\n",
       "      <td>68.728571</td>\n",
       "      <td>1.322630</td>\n",
       "      <td>41.057143</td>\n",
       "      <td>63.985714</td>\n",
       "      <td>4.442857</td>\n",
       "      <td>0.541536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84469</th>\n",
       "      <td>84469</td>\n",
       "      <td>84469</td>\n",
       "      <td>25332</td>\n",
       "      <td>49890</td>\n",
       "      <td>12830</td>\n",
       "      <td>12</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>25332.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.394737</td>\n",
       "      <td>6.342105</td>\n",
       "      <td>25.842105</td>\n",
       "      <td>73.421053</td>\n",
       "      <td>75.921053</td>\n",
       "      <td>2.894737</td>\n",
       "      <td>48.236842</td>\n",
       "      <td>73.631579</td>\n",
       "      <td>3.131579</td>\n",
       "      <td>0.520866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84470</th>\n",
       "      <td>84470</td>\n",
       "      <td>84470</td>\n",
       "      <td>11020</td>\n",
       "      <td>875</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>7-6(5) 7-5</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>11020.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.904858</td>\n",
       "      <td>6.939271</td>\n",
       "      <td>28.484965</td>\n",
       "      <td>72.436899</td>\n",
       "      <td>71.801088</td>\n",
       "      <td>4.045762</td>\n",
       "      <td>45.874494</td>\n",
       "      <td>70.384615</td>\n",
       "      <td>2.132307</td>\n",
       "      <td>0.504028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84471</th>\n",
       "      <td>84471</td>\n",
       "      <td>84471</td>\n",
       "      <td>27111</td>\n",
       "      <td>29939</td>\n",
       "      <td>13186</td>\n",
       "      <td>12</td>\n",
       "      <td>6-2 6-7(6) 7-6(3)</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>27111.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.895238</td>\n",
       "      <td>7.504762</td>\n",
       "      <td>30.552381</td>\n",
       "      <td>79.923810</td>\n",
       "      <td>79.838095</td>\n",
       "      <td>6.133333</td>\n",
       "      <td>47.657143</td>\n",
       "      <td>78.704762</td>\n",
       "      <td>2.600000</td>\n",
       "      <td>0.505499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84472</th>\n",
       "      <td>84472</td>\n",
       "      <td>84472</td>\n",
       "      <td>23833</td>\n",
       "      <td>10971</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-1 6-0</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>23833.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.118421</td>\n",
       "      <td>7.210526</td>\n",
       "      <td>28.468990</td>\n",
       "      <td>71.328382</td>\n",
       "      <td>72.625000</td>\n",
       "      <td>3.236842</td>\n",
       "      <td>42.677632</td>\n",
       "      <td>73.157895</td>\n",
       "      <td>3.513158</td>\n",
       "      <td>0.504308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84473</th>\n",
       "      <td>84473</td>\n",
       "      <td>84473</td>\n",
       "      <td>21177</td>\n",
       "      <td>29391</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>21177.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>5.800000</td>\n",
       "      <td>26.800000</td>\n",
       "      <td>65.800000</td>\n",
       "      <td>66.800000</td>\n",
       "      <td>2.921290</td>\n",
       "      <td>45.200000</td>\n",
       "      <td>74.400000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.463307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84474</th>\n",
       "      <td>84474</td>\n",
       "      <td>84474</td>\n",
       "      <td>13268</td>\n",
       "      <td>16996</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-2 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>13268.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.248408</td>\n",
       "      <td>5.821656</td>\n",
       "      <td>25.578166</td>\n",
       "      <td>69.255764</td>\n",
       "      <td>68.834395</td>\n",
       "      <td>6.592357</td>\n",
       "      <td>41.388535</td>\n",
       "      <td>68.726115</td>\n",
       "      <td>2.643312</td>\n",
       "      <td>0.501298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84475</th>\n",
       "      <td>84475</td>\n",
       "      <td>84475</td>\n",
       "      <td>8515</td>\n",
       "      <td>3694</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>2-6 6-4 7-5</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>8515.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.524017</td>\n",
       "      <td>6.165939</td>\n",
       "      <td>26.502183</td>\n",
       "      <td>71.624454</td>\n",
       "      <td>72.356527</td>\n",
       "      <td>6.912664</td>\n",
       "      <td>43.100437</td>\n",
       "      <td>72.349345</td>\n",
       "      <td>3.270742</td>\n",
       "      <td>0.504338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84476</th>\n",
       "      <td>84476</td>\n",
       "      <td>84476</td>\n",
       "      <td>10920</td>\n",
       "      <td>14510</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>10920.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.147059</td>\n",
       "      <td>6.911765</td>\n",
       "      <td>26.455882</td>\n",
       "      <td>63.220588</td>\n",
       "      <td>65.617647</td>\n",
       "      <td>3.294118</td>\n",
       "      <td>39.367647</td>\n",
       "      <td>61.735294</td>\n",
       "      <td>1.838235</td>\n",
       "      <td>0.536397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84477</th>\n",
       "      <td>84477</td>\n",
       "      <td>84477</td>\n",
       "      <td>5992</td>\n",
       "      <td>8806</td>\n",
       "      <td>12830</td>\n",
       "      <td>12</td>\n",
       "      <td>6-3 7-5</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>5992.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.326923</td>\n",
       "      <td>8.115385</td>\n",
       "      <td>31.132479</td>\n",
       "      <td>77.739316</td>\n",
       "      <td>79.300722</td>\n",
       "      <td>3.358974</td>\n",
       "      <td>46.179487</td>\n",
       "      <td>75.196581</td>\n",
       "      <td>2.711538</td>\n",
       "      <td>0.520434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84478</th>\n",
       "      <td>84478</td>\n",
       "      <td>84478</td>\n",
       "      <td>11517</td>\n",
       "      <td>11009</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>3-6 7-6(5) 7-6(5)</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>11517.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.144105</td>\n",
       "      <td>5.921397</td>\n",
       "      <td>25.510177</td>\n",
       "      <td>71.979144</td>\n",
       "      <td>71.895197</td>\n",
       "      <td>7.030568</td>\n",
       "      <td>43.934498</td>\n",
       "      <td>71.781659</td>\n",
       "      <td>3.013100</td>\n",
       "      <td>0.498813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84479</th>\n",
       "      <td>84479</td>\n",
       "      <td>84479</td>\n",
       "      <td>13267</td>\n",
       "      <td>18365</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>5-7 6-2 6-4</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>13267.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.021739</td>\n",
       "      <td>5.673913</td>\n",
       "      <td>22.782609</td>\n",
       "      <td>62.956522</td>\n",
       "      <td>61.391304</td>\n",
       "      <td>3.895933</td>\n",
       "      <td>39.413043</td>\n",
       "      <td>67.673913</td>\n",
       "      <td>3.717391</td>\n",
       "      <td>0.461730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84480</th>\n",
       "      <td>84480</td>\n",
       "      <td>84480</td>\n",
       "      <td>23550</td>\n",
       "      <td>24849</td>\n",
       "      <td>13408</td>\n",
       "      <td>12</td>\n",
       "      <td>5-7 6-3 6-4</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>23550.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.532110</td>\n",
       "      <td>8.183486</td>\n",
       "      <td>30.117175</td>\n",
       "      <td>71.872982</td>\n",
       "      <td>73.844037</td>\n",
       "      <td>2.299060</td>\n",
       "      <td>48.027523</td>\n",
       "      <td>73.623853</td>\n",
       "      <td>2.627152</td>\n",
       "      <td>0.510698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84481</th>\n",
       "      <td>84481</td>\n",
       "      <td>84481</td>\n",
       "      <td>12662</td>\n",
       "      <td>25365</td>\n",
       "      <td>13409</td>\n",
       "      <td>12</td>\n",
       "      <td>7-6(4) 1-6 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>12662.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.837838</td>\n",
       "      <td>8.256757</td>\n",
       "      <td>30.186109</td>\n",
       "      <td>70.029121</td>\n",
       "      <td>72.270270</td>\n",
       "      <td>2.202582</td>\n",
       "      <td>45.054054</td>\n",
       "      <td>68.081081</td>\n",
       "      <td>3.040541</td>\n",
       "      <td>0.533590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84482</th>\n",
       "      <td>84482</td>\n",
       "      <td>84482</td>\n",
       "      <td>31290</td>\n",
       "      <td>22798</td>\n",
       "      <td>13412</td>\n",
       "      <td>12</td>\n",
       "      <td>6-1 7-6(6)</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>31290.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.620690</td>\n",
       "      <td>8.362069</td>\n",
       "      <td>29.534483</td>\n",
       "      <td>67.293103</td>\n",
       "      <td>65.948276</td>\n",
       "      <td>3.193172</td>\n",
       "      <td>38.741379</td>\n",
       "      <td>63.603448</td>\n",
       "      <td>3.681874</td>\n",
       "      <td>0.510600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84483</th>\n",
       "      <td>84483</td>\n",
       "      <td>84483</td>\n",
       "      <td>11742</td>\n",
       "      <td>28075</td>\n",
       "      <td>13296</td>\n",
       "      <td>3</td>\n",
       "      <td>6-1 6-1</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1</td>\n",
       "      <td>11742.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.833333</td>\n",
       "      <td>4.111111</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>58.777778</td>\n",
       "      <td>56.777778</td>\n",
       "      <td>3.755914</td>\n",
       "      <td>39.944444</td>\n",
       "      <td>66.277778</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.446692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84484</th>\n",
       "      <td>84484</td>\n",
       "      <td>84484</td>\n",
       "      <td>13070</td>\n",
       "      <td>22428</td>\n",
       "      <td>13296</td>\n",
       "      <td>3</td>\n",
       "      <td>3-6 6-0 6-3</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>0</td>\n",
       "      <td>13070.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.172043</td>\n",
       "      <td>7.569892</td>\n",
       "      <td>28.989247</td>\n",
       "      <td>69.806452</td>\n",
       "      <td>70.290323</td>\n",
       "      <td>4.591350</td>\n",
       "      <td>43.150538</td>\n",
       "      <td>65.827957</td>\n",
       "      <td>3.622669</td>\n",
       "      <td>0.528820</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>84485 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0  Unnamed: 0.1  ID1_G  ID2_G  ID_T_G  ID_R_G  \\\n",
       "0               0             0  18854  17613    8887       4   \n",
       "1               1             1  25192  25191    8888       4   \n",
       "2               2             2  10828    918    8957       4   \n",
       "3               3             3   3316   2379    8957       4   \n",
       "4               4             4   6277   7869    8957       4   \n",
       "5               5             5   2107   7136    8957       4   \n",
       "6               6             6     72    678    8887       4   \n",
       "7               7             7    563  13796    8887       4   \n",
       "8               8             8    775    745    8888       4   \n",
       "9               9             9     75   1266    8888       4   \n",
       "10             10            10   7826    749    8888       4   \n",
       "11             11            11    638  13651    8888       4   \n",
       "12             12            12   5058   6002    8957       4   \n",
       "13             13            13   9839   4454    8957       4   \n",
       "14             14            14  11923    920    8957       4   \n",
       "15             15            15   1823   4078    8957       4   \n",
       "16             16            16   6691    578    8887       4   \n",
       "17             17            17    453   7806    8887       4   \n",
       "18             18            18    760    520    8888       4   \n",
       "19             19            19   5554  25199    8888       4   \n",
       "20             20            20    516    468    8887       4   \n",
       "21             21            21  25197  15916    8888       4   \n",
       "22             22            22   6642    655    8888       4   \n",
       "23             23            23   3685   2123    8889       4   \n",
       "24             24            24    838    935    8889       4   \n",
       "25             25            25   9839  22906    8882       2   \n",
       "26             26            26  12896   1162    8882       2   \n",
       "27             27            27  11517    578    8882       4   \n",
       "28             28            28   3694   3996    8882       2   \n",
       "29             29            29   7461  13398    8882       2   \n",
       "...           ...           ...    ...    ...     ...     ...   \n",
       "84455       84455         84455  30801  17964   13298       2   \n",
       "84456       84456         84456  25928  11224   13298       2   \n",
       "84457       84457         84457   9658  11438   13298       2   \n",
       "84458       84458         84458  26965  25365   13409      10   \n",
       "84459       84459         84459  12662  12226   13409      10   \n",
       "84460       84460         84460  14427  28925   13414      12   \n",
       "84461       84461         84461  26381  14609   12831       3   \n",
       "84462       84462         84462   3996   9842   12831       3   \n",
       "84463       84463         84463  39067  50227   13185      12   \n",
       "84464       84464         84464  17268  13209   13411      12   \n",
       "84465       84465         84465  10590  23575   13297       2   \n",
       "84466       84466         84466  39043   7889   13297       2   \n",
       "84467       84467         84467  14545  17357   13415      12   \n",
       "84468       84468         84468  29665  27358   13421      12   \n",
       "84469       84469         84469  25332  49890   12830      12   \n",
       "84470       84470         84470  11020    875   12831       3   \n",
       "84471       84471         84471  27111  29939   13186      12   \n",
       "84472       84472         84472  23833  10971   13297       2   \n",
       "84473       84473         84473  21177  29391   13297       2   \n",
       "84474       84474         84474  13268  16996   13297       2   \n",
       "84475       84475         84475   8515   3694   13297       2   \n",
       "84476       84476         84476  10920  14510   13297       2   \n",
       "84477       84477         84477   5992   8806   12830      12   \n",
       "84478       84478         84478  11517  11009   12831       3   \n",
       "84479       84479         84479  13267  18365   13297       2   \n",
       "84480       84480         84480  23550  24849   13408      12   \n",
       "84481       84481         84481  12662  25365   13409      12   \n",
       "84482       84482         84482  31290  22798   13412      12   \n",
       "84483       84483         84483  11742  28075   13296       3   \n",
       "84484       84484         84484  13070  22428   13296       3   \n",
       "\n",
       "                RESULT_G      DATE_G  result           ID1    ...      \\\n",
       "0        7-6(8) 3-6 10-7  2012-01-31       0  15036.062396    ...       \n",
       "1                6-3 6-2  2012-01-31       1  15036.062396    ...       \n",
       "2                6-1 6-2  2012-01-31       0  10828.000000    ...       \n",
       "3             6-4 7-6(5)  2012-01-31       1   3316.000000    ...       \n",
       "4                6-4 6-4  2012-01-31       0   6277.000000    ...       \n",
       "5            7-5 5-7 6-3  2012-01-31       1   2107.000000    ...       \n",
       "6                6-1 6-4  2012-01-31       0     72.000000    ...       \n",
       "7                6-4 6-4  2012-01-31       1    563.000000    ...       \n",
       "8             7-6(3) 6-1  2012-01-31       0    775.000000    ...       \n",
       "9             6-4 7-6(4)  2012-01-31       1     75.000000    ...       \n",
       "10               6-2 6-1  2012-01-31       0   7826.000000    ...       \n",
       "11               6-3 6-1  2012-01-31       1    638.000000    ...       \n",
       "12               6-4 6-2  2012-01-31       0   5058.000000    ...       \n",
       "13            7-6(6) 6-2  2012-01-31       1   9839.000000    ...       \n",
       "14               6-3 6-4  2012-01-31       0  11923.000000    ...       \n",
       "15               6-3 6-1  2012-01-31       1   1823.000000    ...       \n",
       "16               6-3 6-2  2012-01-31       0   6691.000000    ...       \n",
       "17               6-3 7-5  2012-01-31       1    453.000000    ...       \n",
       "18               6-1 6-3  2012-01-31       0    760.000000    ...       \n",
       "19               6-3 6-4  2012-01-31       1   5554.000000    ...       \n",
       "20            6-4 7-6(7)  2012-01-31       0    516.000000    ...       \n",
       "21            7-6(2) 6-4  2012-01-31       1  15036.062396    ...       \n",
       "22            7-6(2) 6-3  2012-01-31       0   6642.000000    ...       \n",
       "23           6-3 5-7 6-1  2012-01-31       1   3685.000000    ...       \n",
       "24               7-5 6-0  2012-01-31       0    838.000000    ...       \n",
       "25           4-6 6-1 6-3  2012-01-01       1   9839.000000    ...       \n",
       "26       6-7(12) 6-3 6-4  2012-01-01       0  12896.000000    ...       \n",
       "27               6-4 6-4  2012-01-01       1  11517.000000    ...       \n",
       "28               6-3 6-3  2012-01-01       0   3694.000000    ...       \n",
       "29               6-2 6-3  2012-01-01       1   7461.000000    ...       \n",
       "...                  ...         ...     ...           ...    ...       \n",
       "84455            7-5 6-3  2016-07-31       1  30801.000000    ...       \n",
       "84456            6-1 6-2  2016-07-31       0  25928.000000    ...       \n",
       "84457            6-2 6-4  2016-07-31       1   9658.000000    ...       \n",
       "84458            6-4 6-2  2016-07-31       0  26965.000000    ...       \n",
       "84459     6-4 6-7(9) 6-3  2016-07-31       1  12662.000000    ...       \n",
       "84460        2-6 7-5 6-3  2016-07-31       0  14427.000000    ...       \n",
       "84461            6-4 7-5  2016-07-31       1  26381.000000    ...       \n",
       "84462         7-6(4) 6-3  2016-07-31       0   3996.000000    ...       \n",
       "84463      6-1 3-6 13-11  2016-07-31       1  39067.000000    ...       \n",
       "84464        7-5 2-6 6-2  2016-07-31       0  17268.000000    ...       \n",
       "84465            6-4 6-3  2016-07-31       1  10590.000000    ...       \n",
       "84466         6-4 7-6(5)  2016-07-31       0  39043.000000    ...       \n",
       "84467            7-5 6-3  2016-07-31       1  14545.000000    ...       \n",
       "84468        2-6 6-1 6-4  2016-07-31       0  29665.000000    ...       \n",
       "84469            6-4 6-4  2016-07-31       1  25332.000000    ...       \n",
       "84470         7-6(5) 7-5  2016-07-31       0  11020.000000    ...       \n",
       "84471  6-2 6-7(6) 7-6(3)  2016-07-31       1  27111.000000    ...       \n",
       "84472            6-1 6-0  2016-07-31       0  23833.000000    ...       \n",
       "84473            6-4 6-4  2016-07-31       1  21177.000000    ...       \n",
       "84474            6-2 6-3  2016-07-31       0  13268.000000    ...       \n",
       "84475        2-6 6-4 7-5  2016-07-31       1   8515.000000    ...       \n",
       "84476            6-4 6-4  2016-07-31       0  10920.000000    ...       \n",
       "84477            6-3 7-5  2016-07-31       1   5992.000000    ...       \n",
       "84478  3-6 7-6(5) 7-6(5)  2016-07-31       0  11517.000000    ...       \n",
       "84479        5-7 6-2 6-4  2016-07-31       1  13267.000000    ...       \n",
       "84480        5-7 6-3 6-4  2016-07-31       0  23550.000000    ...       \n",
       "84481     7-6(4) 1-6 6-3  2016-07-31       1  12662.000000    ...       \n",
       "84482         6-1 7-6(6)  2016-07-31       0  31290.000000    ...       \n",
       "84483            6-1 6-1  2016-07-31       1  11742.000000    ...       \n",
       "84484        3-6 6-0 6-3  2016-07-31       0  13070.000000    ...       \n",
       "\n",
       "           BP_2    BPOF_2      RPW_2    RPWOF_2      TPW_2     ACES_2  \\\n",
       "0      2.641724  6.438650  26.276405  69.044217  68.795733   4.064767   \n",
       "1      2.641724  6.438650  26.276405  69.044217  68.795733   4.064767   \n",
       "2      2.647108  6.559441  28.170000  76.126667  75.464563   4.596652   \n",
       "3      3.134651  7.582051  30.105263  74.037594  73.473684   2.857143   \n",
       "4      2.642857  6.250000  27.035714  70.535714  68.142857   4.000000   \n",
       "5      1.952381  5.523810  24.119048  68.571429  66.119048   3.976190   \n",
       "6      2.863898  7.064777  29.757395  78.786327  79.373918   5.543340   \n",
       "7      3.265823  7.379747  30.341772  74.303797  76.300477   3.518987   \n",
       "8      2.388889  6.246032  27.670635  76.150794  75.669594   5.559524   \n",
       "9      2.432628  6.497378  27.941964  76.116071  76.361668   6.383929   \n",
       "10     3.166667  7.209677  30.075269  77.569892  76.485391   4.220430   \n",
       "11     2.000000  6.000000  25.875000  70.375000  66.250000   1.875000   \n",
       "12     2.770833  6.250000  26.479167  68.125000  67.894181   3.729167   \n",
       "13     2.901639  6.770492  27.639344  68.049180  67.792932   2.459016   \n",
       "14     2.591463  6.310976  25.884146  66.798780  66.628049   3.164634   \n",
       "15     1.861111  4.944444  22.027778  63.500000  61.426912   3.361111   \n",
       "16     2.294032  6.023346  26.988327  76.517510  78.075392   8.346304   \n",
       "17     2.651613  6.432258  27.651613  72.967742  71.576617   4.419355   \n",
       "18     2.839394  7.272727  30.135673  81.306530  80.362580   6.163636   \n",
       "19     2.641724  6.438650  26.276405  69.044217  68.795733   4.064767   \n",
       "20     2.032934  5.679641  27.158683  81.940120  80.776038  10.745509   \n",
       "21     3.000000  5.000000  21.000000  55.500000  59.500000   3.000000   \n",
       "22     1.439982  4.473442  24.855384  84.808750  84.994119  19.037671   \n",
       "23     3.000000  7.175758  29.206061  72.830303  72.569738   2.643715   \n",
       "24     3.518349  8.036697  30.417431  72.339450  73.203558   2.954128   \n",
       "25     2.641724  6.438650  26.276405  69.044217  68.795733   4.064767   \n",
       "26     2.739521  6.970060  30.476905  82.376988  81.572981   4.998822   \n",
       "27     2.275366  6.000000  27.012048  76.674699  78.334842   8.421687   \n",
       "28     3.313333  8.066667  29.926667  73.953333  73.695838   2.073333   \n",
       "29     2.333333  4.000000  26.500000  77.333333  71.500000   2.333333   \n",
       "...         ...       ...        ...        ...        ...        ...   \n",
       "84455  3.027273  6.318182  26.427273  64.745455  64.790909   3.450886   \n",
       "84456  3.067568  6.878378  26.608503  64.946412  65.608108   2.481047   \n",
       "84457  3.024138  6.920690  27.979310  69.196552  68.859893   4.136543   \n",
       "84458  3.837838  8.256757  30.186109  70.029121  72.270270   2.202582   \n",
       "84459  2.915094  7.075472  27.301887  68.490566  69.056604   3.433920   \n",
       "84460  3.178571  7.000000  28.035714  67.714286  66.642857   2.142857   \n",
       "84461  2.994220  7.017341  28.606936  73.352601  74.433526   3.242775   \n",
       "84462  2.589552  6.604478  27.868027  74.488422  75.014925   6.373134   \n",
       "84463  2.250000  7.750000  26.500000  68.250000  69.750000   3.000000   \n",
       "84464  3.546392  7.587629  28.193527  65.846959  68.329897   1.737888   \n",
       "84465  3.181818  7.045455  29.954545  72.727273  71.590909   2.454545   \n",
       "84466  2.396396  6.396396  26.882883  72.072072  71.045045   5.162162   \n",
       "84467  3.670588  7.729412  31.105882  72.905882  72.623529   1.992877   \n",
       "84468  4.614286  9.485714  31.642857  65.600000  68.728571   1.322630   \n",
       "84469  2.394737  6.342105  25.842105  73.421053  75.921053   2.894737   \n",
       "84470  2.904858  6.939271  28.484965  72.436899  71.801088   4.045762   \n",
       "84471  2.895238  7.504762  30.552381  79.923810  79.838095   6.133333   \n",
       "84472  3.118421  7.210526  28.468990  71.328382  72.625000   3.236842   \n",
       "84473  3.400000  5.800000  26.800000  65.800000  66.800000   2.921290   \n",
       "84474  2.248408  5.821656  25.578166  69.255764  68.834395   6.592357   \n",
       "84475  2.524017  6.165939  26.502183  71.624454  72.356527   6.912664   \n",
       "84476  3.147059  6.911765  26.455882  63.220588  65.617647   3.294118   \n",
       "84477  3.326923  8.115385  31.132479  77.739316  79.300722   3.358974   \n",
       "84478  2.144105  5.921397  25.510177  71.979144  71.895197   7.030568   \n",
       "84479  2.021739  5.673913  22.782609  62.956522  61.391304   3.895933   \n",
       "84480  3.532110  8.183486  30.117175  71.872982  73.844037   2.299060   \n",
       "84481  3.837838  8.256757  30.186109  70.029121  72.270270   2.202582   \n",
       "84482  3.620690  8.362069  29.534483  67.293103  65.948276   3.193172   \n",
       "84483  1.833333  4.111111  20.000000  58.777778  56.777778   3.755914   \n",
       "84484  3.172043  7.569892  28.989247  69.806452  70.290323   4.591350   \n",
       "\n",
       "            FS_2     FSOF_2      DF_2  TPW_per_2  \n",
       "0      42.514255  69.309763  2.971950   0.497677  \n",
       "1      42.514255  69.309763  2.971950   0.497677  \n",
       "2      44.230000  77.590000  4.043333   0.492314  \n",
       "3      39.879699  70.804511  2.969925   0.513169  \n",
       "4      41.714286  68.500000  2.571429   0.487519  \n",
       "5      41.095238  69.119048  2.761905   0.480640  \n",
       "6      46.991556  77.338728  2.348407   0.515438  \n",
       "7      46.493671  76.468354  3.367089   0.509757  \n",
       "8      48.341270  75.468254  3.373016   0.503715  \n",
       "9      48.455357  76.598214  2.239057   0.504676  \n",
       "10     49.779570  78.774194  4.419355   0.495449  \n",
       "11     40.125000  69.875000  4.250000   0.465705  \n",
       "12     39.520833  68.125000  2.937500   0.495645  \n",
       "13     39.311475  68.295082  3.475410   0.497006  \n",
       "14     42.475610  67.725610  1.865854   0.494469  \n",
       "15     40.472222  66.527778  2.805556   0.460733  \n",
       "16     46.509728  75.680934  3.840467   0.504684  \n",
       "17     42.438710  71.980645  2.647481   0.502875  \n",
       "18     49.163636  80.451515  2.765299   0.503482  \n",
       "19     42.514255  69.309763  2.971950   0.497677  \n",
       "20     48.434132  82.688623  3.353293   0.496033  \n",
       "21     37.000000  50.500000  2.500000   0.561321  \n",
       "22     55.342466  83.578767  2.568827   0.508673  \n",
       "23     46.018182  72.436364  2.721212   0.498382  \n",
       "24     45.270642  69.977064  1.932421   0.525667  \n",
       "25     42.514255  69.309763  2.971950   0.497677  \n",
       "26     50.922156  81.074850  2.637725   0.503037  \n",
       "27     46.518072  75.730924  3.871486   0.505812  \n",
       "28     42.433333  72.746667  3.253333   0.512690  \n",
       "29     48.166667  77.333333  5.000000   0.443431  \n",
       "...          ...        ...       ...        ...  \n",
       "84455  38.736364  64.390909  3.191794   0.499311  \n",
       "84456  38.817568  64.358108  2.200311   0.508021  \n",
       "84457  43.013793  68.713793  3.567409   0.501091  \n",
       "84458  45.054054  68.081081  3.040541   0.533590  \n",
       "84459  41.801887  66.386792  1.753851   0.513368  \n",
       "84460  43.285714  71.071429  3.785714   0.475412  \n",
       "84461  47.485549  73.138728  2.065662   0.513295  \n",
       "84462  45.936567  73.466418  2.100746   0.510917  \n",
       "84463  40.750000  65.500000  1.750000   0.516236  \n",
       "84464  47.278351  68.536082  2.409475   0.508408  \n",
       "84465  44.409091  70.909091  3.681818   0.501746  \n",
       "84466  42.297297  70.324324  2.419357   0.501532  \n",
       "84467  43.047059  73.411765  3.517647   0.497874  \n",
       "84468  41.057143  63.985714  4.442857   0.541536  \n",
       "84469  48.236842  73.631579  3.131579   0.520866  \n",
       "84470  45.874494  70.384615  2.132307   0.504028  \n",
       "84471  47.657143  78.704762  2.600000   0.505499  \n",
       "84472  42.677632  73.157895  3.513158   0.504308  \n",
       "84473  45.200000  74.400000  5.000000   0.463307  \n",
       "84474  41.388535  68.726115  2.643312   0.501298  \n",
       "84475  43.100437  72.349345  3.270742   0.504338  \n",
       "84476  39.367647  61.735294  1.838235   0.536397  \n",
       "84477  46.179487  75.196581  2.711538   0.520434  \n",
       "84478  43.934498  71.781659  3.013100   0.498813  \n",
       "84479  39.413043  67.673913  3.717391   0.461730  \n",
       "84480  48.027523  73.623853  2.627152   0.510698  \n",
       "84481  45.054054  68.081081  3.040541   0.533590  \n",
       "84482  38.741379  63.603448  3.681874   0.510600  \n",
       "84483  39.944444  66.277778  2.000000   0.446692  \n",
       "84484  43.150538  65.827957  3.622669   0.528820  \n",
       "\n",
       "[84485 rows x 39 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#On enleve les match ou il manque des données\n",
    "#train.dropna(inplace=True)\n",
    "\n",
    "#On remplit par la moyenne de la colonne\n",
    "train.fillna(train.mean(),inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 39 columns):\n",
      "Unnamed: 0      84485 non-null int64\n",
      "Unnamed: 0.1    84485 non-null int64\n",
      "ID1_G           84485 non-null int64\n",
      "ID2_G           84485 non-null int64\n",
      "ID_T_G          84485 non-null int64\n",
      "ID_R_G          84485 non-null int64\n",
      "RESULT_G        84485 non-null object\n",
      "DATE_G          84485 non-null object\n",
      "result          84485 non-null int64\n",
      "ID1             79396 non-null float64\n",
      "W1S_1           79396 non-null float64\n",
      "W1SOF_1         79396 non-null float64\n",
      "W2S_1           79396 non-null float64\n",
      "W2SOF_1         79396 non-null float64\n",
      "BP_1            79396 non-null float64\n",
      "BPOF_1          79396 non-null float64\n",
      "RPW_1           79396 non-null float64\n",
      "RPWOF_1         79396 non-null float64\n",
      "TPW_1           79396 non-null float64\n",
      "ACES_1          79396 non-null float64\n",
      "FS_1            79396 non-null float64\n",
      "FSOF_1          79396 non-null float64\n",
      "DF_1            79396 non-null float64\n",
      "TPW_per_1       79396 non-null float64\n",
      "ID2             79389 non-null float64\n",
      "W1S_2           79389 non-null float64\n",
      "W1SOF_2         79389 non-null float64\n",
      "W2S_2           79389 non-null float64\n",
      "W2SOF_2         79389 non-null float64\n",
      "BP_2            79389 non-null float64\n",
      "BPOF_2          79389 non-null float64\n",
      "RPW_2           79389 non-null float64\n",
      "RPWOF_2         79389 non-null float64\n",
      "TPW_2           79389 non-null float64\n",
      "ACES_2          79389 non-null float64\n",
      "FS_2            79389 non-null float64\n",
      "FSOF_2          79389 non-null float64\n",
      "DF_2            79389 non-null float64\n",
      "TPW_per_2       79389 non-null float64\n",
      "dtypes: float64(30), int64(7), object(2)\n",
      "memory usage: 25.1+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "#first service success\n",
    "train['FS'] = (train['FS_1']/train['FSOF_1']) - (train['FS_2']/train['FSOF_2'])\n",
    "\n",
    "#Win on first serve percentage\n",
    "train['W1SP'] = (train['W1S_1']/train['W1SOF_1']) - (train['W1S_2']/train['W1SOF_2'])\n",
    "\n",
    "#Win on second serve percentage\n",
    "train['W2SP'] = (train['W2S_1']/train['W2SOF_1']) - (train['W2S_2']/train['W2SOF_2'])\n",
    "\n",
    "\n",
    "#Overall winning service percentage\n",
    "#W1SP*F1S + W2SP*F2S pour chaque joueur\n",
    "\n",
    "train['WSP1'] = (train['W1S_1']/train['W1SOF_1'])*(train['FS_1']/train['FSOF_1'])+(train['W1S_1']/train['W1SOF_1'])*(1-(train['FS_1']/train['FSOF_1']))\n",
    "train['WSP2'] = (train['W1S_2']/train['W1SOF_2'])*(train['FS_2']/train['FSOF_2'])+(train['W1S_2']/train['W1SOF_2'])*(1-(train['FS_2']/train['FSOF_2']))\n",
    "\n",
    "train['WSP']=train['WSP1'] - train['WSP2']\n",
    "\n",
    "#Winning on return percentage\n",
    "train['WRP1'] = train['RPW_1']/train['RPWOF_1']\n",
    "train['WRP2'] = train['RPW_2']/train['RPWOF_2']\n",
    "\n",
    "train['WRP'] = train['WRP1'] - train['WRP2']\n",
    "\n",
    "\n",
    "\n",
    "#Average aces per game\n",
    "train['ACES'] = train['ACES_1'] - train['ACES_2']\n",
    "\n",
    "#DOUble faute\n",
    "train['DF'] = train['DF_1'] - train['DF_2']\n",
    "\n",
    "#break point percentage\n",
    "train['BP'] = train['BP_1']/train['BPOF_1'] - train['BP_2']/train['BPOF_2']\n",
    "\n",
    "#total point won percentage\n",
    "train['TPW'] = train['TPW_per_1'] - train['TPW_per_2']\n",
    "\n",
    "#Completeness (service won x return won)\n",
    "train['COMPLETE1'] = train['WSP1']*train['WRP1']\n",
    "train['COMPLETE2'] = train['WSP2']*train['WRP2']\n",
    "\n",
    "train['COMPLETE'] = train['COMPLETE1'] - train['COMPLETE2']\n",
    "\n",
    "#Advantage on serve\n",
    "train['SERVE_ADVANTAGE1'] = train['WSP1'] - train['WRP2']\n",
    "train['SERVE_ADVANTAGE2'] = train['WSP2'] - train['WRP1']\n",
    "train['SERVE_ADVANTAGE'] = train['SERVE_ADVANTAGE1'] - train['SERVE_ADVANTAGE2']\n",
    "\n",
    "columns_to_keep = ['ID1_G','ID2_G','ID_T_G','ID_R_G','DATE_G','result'\n",
    "                   ,'W1SP','W2SP','WSP','WRP','ACES','DF','BP','TPW'\n",
    "                   ,'COMPLETE','SERVE_ADVANTAGE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_rank_of_both_player_at_date(ID):\n",
    "    #get frame rating with both players\n",
    "    date_of_match = pd.to_datetime(ID[2])\n",
    "    if (ID[0] in ratings_atp['ID_P_R'].values):\n",
    "        df1 = ratings_atp.loc[(ratings_atp['ID_P_R']==ID[0])]\n",
    "        \n",
    "        df1['diff'] = abs(pd.to_datetime(df1['DATE_R']) - date_of_match)\n",
    "        index1 = df1['diff'].argmin() \n",
    "        res1 = ratings_atp.iloc[index1][['POS_R','POINT_R']]\n",
    "    \n",
    "    else:\n",
    "        res1 = pd.DataFrame(np.array([900,0]))\n",
    "    \n",
    "    \n",
    "    if (ID[1] in ratings_atp['ID_P_R'].values):\n",
    "        df2 = ratings_atp.loc[(ratings_atp['ID_P_R']==ID[1])]\n",
    "       \n",
    "        df2['diff'] = abs(pd.to_datetime(df2['DATE_R']) - date_of_match)\n",
    "        index2 = df2['diff'].argmin() \n",
    "        res2 = ratings_atp.iloc[index2][['POS_R','POINT_R']]\n",
    "    \n",
    "    else:\n",
    "        res2 = pd.DataFrame(np.array([900,0]))\n",
    "    \n",
    "    \n",
    "    res = pd.concat([res1,res2],axis=1)\n",
    "    return res\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 58 columns):\n",
      "Unnamed: 0          84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "ID1_G               84485 non-null int64\n",
      "ID2_G               84485 non-null int64\n",
      "ID_T_G              84485 non-null int64\n",
      "ID_R_G              84485 non-null int64\n",
      "RESULT_G            84485 non-null object\n",
      "DATE_G              84485 non-null object\n",
      "result              84485 non-null int64\n",
      "ID1                 79396 non-null float64\n",
      "W1S_1               79396 non-null float64\n",
      "W1SOF_1             79396 non-null float64\n",
      "W2S_1               79396 non-null float64\n",
      "W2SOF_1             79396 non-null float64\n",
      "BP_1                79396 non-null float64\n",
      "BPOF_1              79396 non-null float64\n",
      "RPW_1               79396 non-null float64\n",
      "RPWOF_1             79396 non-null float64\n",
      "TPW_1               79396 non-null float64\n",
      "ACES_1              79396 non-null float64\n",
      "FS_1                79396 non-null float64\n",
      "FSOF_1              79396 non-null float64\n",
      "DF_1                79396 non-null float64\n",
      "TPW_per_1           79396 non-null float64\n",
      "ID2                 79389 non-null float64\n",
      "W1S_2               79389 non-null float64\n",
      "W1SOF_2             79389 non-null float64\n",
      "W2S_2               79389 non-null float64\n",
      "W2SOF_2             79389 non-null float64\n",
      "BP_2                79389 non-null float64\n",
      "BPOF_2              79389 non-null float64\n",
      "RPW_2               79389 non-null float64\n",
      "RPWOF_2             79389 non-null float64\n",
      "TPW_2               79389 non-null float64\n",
      "ACES_2              79389 non-null float64\n",
      "FS_2                79389 non-null float64\n",
      "FSOF_2              79389 non-null float64\n",
      "DF_2                79389 non-null float64\n",
      "TPW_per_2           79389 non-null float64\n",
      "FS                  76543 non-null float64\n",
      "W1SP                76543 non-null float64\n",
      "W2SP                76543 non-null float64\n",
      "WSP1                79396 non-null float64\n",
      "WSP2                79389 non-null float64\n",
      "WSP                 76543 non-null float64\n",
      "WRP1                79396 non-null float64\n",
      "WRP2                79389 non-null float64\n",
      "WRP                 76543 non-null float64\n",
      "ACES                76543 non-null float64\n",
      "DF                  76543 non-null float64\n",
      "BP                  75915 non-null float64\n",
      "TPW                 76543 non-null float64\n",
      "COMPLETE1           79396 non-null float64\n",
      "COMPLETE2           79389 non-null float64\n",
      "COMPLETE            76543 non-null float64\n",
      "SERVE_ADVANTAGE1    76543 non-null float64\n",
      "SERVE_ADVANTAGE2    76543 non-null float64\n",
      "SERVE_ADVANTAGE     76543 non-null float64\n",
      "dtypes: float64(49), int64(7), object(2)\n",
      "memory usage: 37.4+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il manque des valeurs de BP. Cela correspond surement aux personne n'ayant jamais fait de balle de break..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#break point percentage\n",
    "train['BP1'] = train['BP_1']/train['BPOF_1']\n",
    "train['BP2'] = train['BP_2']/train['BPOF_2']\n",
    "train.BP1 = train.BP1.fillna(0)\n",
    "train.BP2 = train.BP2.fillna(0)\n",
    "train['BP'] = train['BP1'] - train['BP2']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 60 columns):\n",
      "Unnamed: 0          84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "ID1_G               84485 non-null int64\n",
      "ID2_G               84485 non-null int64\n",
      "ID_T_G              84485 non-null int64\n",
      "ID_R_G              84485 non-null int64\n",
      "RESULT_G            84485 non-null object\n",
      "DATE_G              84485 non-null object\n",
      "result              84485 non-null int64\n",
      "ID1                 79396 non-null float64\n",
      "W1S_1               79396 non-null float64\n",
      "W1SOF_1             79396 non-null float64\n",
      "W2S_1               79396 non-null float64\n",
      "W2SOF_1             79396 non-null float64\n",
      "BP_1                79396 non-null float64\n",
      "BPOF_1              79396 non-null float64\n",
      "RPW_1               79396 non-null float64\n",
      "RPWOF_1             79396 non-null float64\n",
      "TPW_1               79396 non-null float64\n",
      "ACES_1              79396 non-null float64\n",
      "FS_1                79396 non-null float64\n",
      "FSOF_1              79396 non-null float64\n",
      "DF_1                79396 non-null float64\n",
      "TPW_per_1           79396 non-null float64\n",
      "ID2                 79389 non-null float64\n",
      "W1S_2               79389 non-null float64\n",
      "W1SOF_2             79389 non-null float64\n",
      "W2S_2               79389 non-null float64\n",
      "W2SOF_2             79389 non-null float64\n",
      "BP_2                79389 non-null float64\n",
      "BPOF_2              79389 non-null float64\n",
      "RPW_2               79389 non-null float64\n",
      "RPWOF_2             79389 non-null float64\n",
      "TPW_2               79389 non-null float64\n",
      "ACES_2              79389 non-null float64\n",
      "FS_2                79389 non-null float64\n",
      "FSOF_2              79389 non-null float64\n",
      "DF_2                79389 non-null float64\n",
      "TPW_per_2           79389 non-null float64\n",
      "FS                  76543 non-null float64\n",
      "W1SP                76543 non-null float64\n",
      "W2SP                76543 non-null float64\n",
      "WSP1                79396 non-null float64\n",
      "WSP2                79389 non-null float64\n",
      "WSP                 76543 non-null float64\n",
      "WRP1                79396 non-null float64\n",
      "WRP2                79389 non-null float64\n",
      "WRP                 76543 non-null float64\n",
      "ACES                76543 non-null float64\n",
      "DF                  76543 non-null float64\n",
      "BP                  84485 non-null float64\n",
      "TPW                 76543 non-null float64\n",
      "COMPLETE1           79396 non-null float64\n",
      "COMPLETE2           79389 non-null float64\n",
      "COMPLETE            76543 non-null float64\n",
      "SERVE_ADVANTAGE1    76543 non-null float64\n",
      "SERVE_ADVANTAGE2    76543 non-null float64\n",
      "SERVE_ADVANTAGE     76543 non-null float64\n",
      "BP1                 84485 non-null float64\n",
      "BP2                 84485 non-null float64\n",
      "dtypes: float64(51), int64(7), object(2)\n",
      "memory usage: 38.7+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 173400 entries, 0 to 173399\n",
      "Data columns (total 4 columns):\n",
      "DATE_R     173400 non-null datetime64[ns]\n",
      "ID_P_R     173400 non-null int64\n",
      "POINT_R    173400 non-null int64\n",
      "POS_R      173400 non-null int64\n",
      "dtypes: datetime64[ns](1), int64(3)\n",
      "memory usage: 5.3 MB\n"
     ]
    }
   ],
   "source": [
    "ratings_atp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#RANK\n",
    "#pd.merge(train, ratings_atp.groupby(['ID_P_R']).mean(), left_on='ID1_G', right_on='ID_P_R',how='left')\n",
    "MeanRating = ratings_atp.groupby(['ID_P_R']).mean().reset_index()\n",
    "train = pd.merge(train, MeanRating, left_on='ID1_G', right_on='ID_P_R',how='left')\n",
    "train = pd.merge(train, MeanRating, left_on='ID2_G', right_on='ID_P_R',how='left')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 84485 entries, 0 to 84484\n",
      "Data columns (total 66 columns):\n",
      "Unnamed: 0          84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "ID1_G               84485 non-null int64\n",
      "ID2_G               84485 non-null int64\n",
      "ID_T_G              84485 non-null int64\n",
      "ID_R_G              84485 non-null int64\n",
      "RESULT_G            84485 non-null object\n",
      "DATE_G              84485 non-null object\n",
      "result              84485 non-null int64\n",
      "ID1                 79396 non-null float64\n",
      "W1S_1               79396 non-null float64\n",
      "W1SOF_1             79396 non-null float64\n",
      "W2S_1               79396 non-null float64\n",
      "W2SOF_1             79396 non-null float64\n",
      "BP_1                79396 non-null float64\n",
      "BPOF_1              79396 non-null float64\n",
      "RPW_1               79396 non-null float64\n",
      "RPWOF_1             79396 non-null float64\n",
      "TPW_1               79396 non-null float64\n",
      "ACES_1              79396 non-null float64\n",
      "FS_1                79396 non-null float64\n",
      "FSOF_1              79396 non-null float64\n",
      "DF_1                79396 non-null float64\n",
      "TPW_per_1           79396 non-null float64\n",
      "ID2                 79389 non-null float64\n",
      "W1S_2               79389 non-null float64\n",
      "W1SOF_2             79389 non-null float64\n",
      "W2S_2               79389 non-null float64\n",
      "W2SOF_2             79389 non-null float64\n",
      "BP_2                79389 non-null float64\n",
      "BPOF_2              79389 non-null float64\n",
      "RPW_2               79389 non-null float64\n",
      "RPWOF_2             79389 non-null float64\n",
      "TPW_2               79389 non-null float64\n",
      "ACES_2              79389 non-null float64\n",
      "FS_2                79389 non-null float64\n",
      "FSOF_2              79389 non-null float64\n",
      "DF_2                79389 non-null float64\n",
      "TPW_per_2           79389 non-null float64\n",
      "FS                  76543 non-null float64\n",
      "W1SP                76543 non-null float64\n",
      "W2SP                76543 non-null float64\n",
      "WSP1                79396 non-null float64\n",
      "WSP2                79389 non-null float64\n",
      "WSP                 76543 non-null float64\n",
      "WRP1                79396 non-null float64\n",
      "WRP2                79389 non-null float64\n",
      "WRP                 76543 non-null float64\n",
      "ACES                76543 non-null float64\n",
      "DF                  76543 non-null float64\n",
      "BP                  84485 non-null float64\n",
      "TPW                 76543 non-null float64\n",
      "COMPLETE1           79396 non-null float64\n",
      "COMPLETE2           79389 non-null float64\n",
      "COMPLETE            76543 non-null float64\n",
      "SERVE_ADVANTAGE1    76543 non-null float64\n",
      "SERVE_ADVANTAGE2    76543 non-null float64\n",
      "SERVE_ADVANTAGE     76543 non-null float64\n",
      "BP1                 84485 non-null float64\n",
      "BP2                 84485 non-null float64\n",
      "ID_P_R_x            61931 non-null float64\n",
      "POINT_R_x           61931 non-null float64\n",
      "POS_R_x             61931 non-null float64\n",
      "ID_P_R_y            61899 non-null float64\n",
      "POINT_R_y           61899 non-null float64\n",
      "POS_R_y             61899 non-null float64\n",
      "dtypes: float64(57), int64(7), object(2)\n",
      "memory usage: 43.2+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#On remplit les valeur manquantes par RANK = max(RANK)=900 et POINT = min(POINT)=0\n",
    "train['POINT_R_x'] = train['POINT_R_x'].fillna(0)\n",
    "train['POINT_R_y'] = train['POINT_R_y'].fillna(0)\n",
    "train['POS_R_x'] = train['POS_R_x'].fillna(900)\n",
    "train['POS_R_y'] = train['POS_R_y'].fillna(900)\n",
    "\n",
    "train['RANK'] = train['POS_R_x'] - train['POS_R_y']\n",
    "train['POINT'] = train['POINT_R_x'] - train['POINT_R_y']\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 84485 entries, 0 to 84484\n",
      "Data columns (total 68 columns):\n",
      "Unnamed: 0          84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "ID1_G               84485 non-null int64\n",
      "ID2_G               84485 non-null int64\n",
      "ID_T_G              84485 non-null int64\n",
      "ID_R_G              84485 non-null int64\n",
      "RESULT_G            84485 non-null object\n",
      "DATE_G              84485 non-null object\n",
      "result              84485 non-null int64\n",
      "ID1                 79396 non-null float64\n",
      "W1S_1               79396 non-null float64\n",
      "W1SOF_1             79396 non-null float64\n",
      "W2S_1               79396 non-null float64\n",
      "W2SOF_1             79396 non-null float64\n",
      "BP_1                79396 non-null float64\n",
      "BPOF_1              79396 non-null float64\n",
      "RPW_1               79396 non-null float64\n",
      "RPWOF_1             79396 non-null float64\n",
      "TPW_1               79396 non-null float64\n",
      "ACES_1              79396 non-null float64\n",
      "FS_1                79396 non-null float64\n",
      "FSOF_1              79396 non-null float64\n",
      "DF_1                79396 non-null float64\n",
      "TPW_per_1           79396 non-null float64\n",
      "ID2                 79389 non-null float64\n",
      "W1S_2               79389 non-null float64\n",
      "W1SOF_2             79389 non-null float64\n",
      "W2S_2               79389 non-null float64\n",
      "W2SOF_2             79389 non-null float64\n",
      "BP_2                79389 non-null float64\n",
      "BPOF_2              79389 non-null float64\n",
      "RPW_2               79389 non-null float64\n",
      "RPWOF_2             79389 non-null float64\n",
      "TPW_2               79389 non-null float64\n",
      "ACES_2              79389 non-null float64\n",
      "FS_2                79389 non-null float64\n",
      "FSOF_2              79389 non-null float64\n",
      "DF_2                79389 non-null float64\n",
      "TPW_per_2           79389 non-null float64\n",
      "FS                  76543 non-null float64\n",
      "W1SP                76543 non-null float64\n",
      "W2SP                76543 non-null float64\n",
      "WSP1                79396 non-null float64\n",
      "WSP2                79389 non-null float64\n",
      "WSP                 76543 non-null float64\n",
      "WRP1                79396 non-null float64\n",
      "WRP2                79389 non-null float64\n",
      "WRP                 76543 non-null float64\n",
      "ACES                76543 non-null float64\n",
      "DF                  76543 non-null float64\n",
      "BP                  84485 non-null float64\n",
      "TPW                 76543 non-null float64\n",
      "COMPLETE1           79396 non-null float64\n",
      "COMPLETE2           79389 non-null float64\n",
      "COMPLETE            76543 non-null float64\n",
      "SERVE_ADVANTAGE1    76543 non-null float64\n",
      "SERVE_ADVANTAGE2    76543 non-null float64\n",
      "SERVE_ADVANTAGE     76543 non-null float64\n",
      "BP1                 84485 non-null float64\n",
      "BP2                 84485 non-null float64\n",
      "ID_P_R_x            61931 non-null float64\n",
      "POINT_R_x           84485 non-null float64\n",
      "POS_R_x             84485 non-null float64\n",
      "ID_P_R_y            61899 non-null float64\n",
      "POINT_R_y           84485 non-null float64\n",
      "POS_R_y             84485 non-null float64\n",
      "RANK                84485 non-null float64\n",
      "POINT               84485 non-null float64\n",
      "dtypes: float64(59), int64(7), object(2)\n",
      "memory usage: 44.5+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train.to_csv('HistoricalAverageStatWithRanking_games_atp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train = pd.read_csv('HistoricalAverageStatWithRanking_games_atp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 69 columns):\n",
      "Unnamed: 0          84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "ID1_G               84485 non-null int64\n",
      "ID2_G               84485 non-null int64\n",
      "ID_T_G              84485 non-null int64\n",
      "ID_R_G              84485 non-null int64\n",
      "RESULT_G            84485 non-null object\n",
      "DATE_G              84485 non-null object\n",
      "result              84485 non-null int64\n",
      "ID1                 79396 non-null float64\n",
      "W1S_1               79396 non-null float64\n",
      "W1SOF_1             79396 non-null float64\n",
      "W2S_1               79396 non-null float64\n",
      "W2SOF_1             79396 non-null float64\n",
      "BP_1                79396 non-null float64\n",
      "BPOF_1              79396 non-null float64\n",
      "RPW_1               79396 non-null float64\n",
      "RPWOF_1             79396 non-null float64\n",
      "TPW_1               79396 non-null float64\n",
      "ACES_1              79396 non-null float64\n",
      "FS_1                79396 non-null float64\n",
      "FSOF_1              79396 non-null float64\n",
      "DF_1                79396 non-null float64\n",
      "TPW_per_1           79396 non-null float64\n",
      "ID2                 79389 non-null float64\n",
      "W1S_2               79389 non-null float64\n",
      "W1SOF_2             79389 non-null float64\n",
      "W2S_2               79389 non-null float64\n",
      "W2SOF_2             79389 non-null float64\n",
      "BP_2                79389 non-null float64\n",
      "BPOF_2              79389 non-null float64\n",
      "RPW_2               79389 non-null float64\n",
      "RPWOF_2             79389 non-null float64\n",
      "TPW_2               79389 non-null float64\n",
      "ACES_2              79389 non-null float64\n",
      "FS_2                79389 non-null float64\n",
      "FSOF_2              79389 non-null float64\n",
      "DF_2                79389 non-null float64\n",
      "TPW_per_2           79389 non-null float64\n",
      "FS                  76543 non-null float64\n",
      "W1SP                76543 non-null float64\n",
      "W2SP                76543 non-null float64\n",
      "WSP1                79396 non-null float64\n",
      "WSP2                79389 non-null float64\n",
      "WSP                 76543 non-null float64\n",
      "WRP1                79396 non-null float64\n",
      "WRP2                79389 non-null float64\n",
      "WRP                 76543 non-null float64\n",
      "ACES                76543 non-null float64\n",
      "DF                  76543 non-null float64\n",
      "BP                  84485 non-null float64\n",
      "TPW                 76543 non-null float64\n",
      "COMPLETE1           79396 non-null float64\n",
      "COMPLETE2           79389 non-null float64\n",
      "COMPLETE            76543 non-null float64\n",
      "SERVE_ADVANTAGE1    76543 non-null float64\n",
      "SERVE_ADVANTAGE2    76543 non-null float64\n",
      "SERVE_ADVANTAGE     76543 non-null float64\n",
      "BP1                 84485 non-null float64\n",
      "BP2                 84485 non-null float64\n",
      "ID_P_R_x            61931 non-null float64\n",
      "POINT_R_x           84485 non-null float64\n",
      "POS_R_x             84485 non-null float64\n",
      "ID_P_R_y            61899 non-null float64\n",
      "POINT_R_y           84485 non-null float64\n",
      "POS_R_y             84485 non-null float64\n",
      "RANK                84485 non-null float64\n",
      "POINT               84485 non-null float64\n",
      "dtypes: float64(59), int64(8), object(2)\n",
      "memory usage: 44.5+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 124273 entries, 0 to 124272\n",
      "Data columns (total 45 columns):\n",
      "ID1        124273 non-null int64\n",
      "ID2        124273 non-null int64\n",
      "ID_T       124273 non-null int64\n",
      "ID_R       124273 non-null int64\n",
      "FS_1       124269 non-null float64\n",
      "FSOF_1     124268 non-null float64\n",
      "ACES_1     122636 non-null float64\n",
      "DF_1       123790 non-null float64\n",
      "UE_1       11621 non-null float64\n",
      "W1S_1      124272 non-null float64\n",
      "W1SOF_1    124272 non-null float64\n",
      "W2S_1      124269 non-null float64\n",
      "W2SOF_1    124269 non-null float64\n",
      "WIS_1      11376 non-null float64\n",
      "BP_1       124240 non-null float64\n",
      "BPOF_1     124240 non-null float64\n",
      "NA_1       8079 non-null float64\n",
      "NAOF_1     8079 non-null float64\n",
      "TPW_1      123937 non-null float64\n",
      "FAST_1     4449 non-null float64\n",
      "A1S_1      4370 non-null float64\n",
      "A2S_1      4362 non-null float64\n",
      "FS_2       124269 non-null float64\n",
      "FSOF_2     124268 non-null float64\n",
      "ACES_2     122627 non-null float64\n",
      "DF_2       123808 non-null float64\n",
      "UE_2       11621 non-null float64\n",
      "W1S_2      124272 non-null float64\n",
      "W1SOF_2    124272 non-null float64\n",
      "W2S_2      124269 non-null float64\n",
      "W2SOF_2    124269 non-null float64\n",
      "WIS_2      11375 non-null float64\n",
      "BP_2       124176 non-null float64\n",
      "BPOF_2     124210 non-null float64\n",
      "NA_2       8079 non-null float64\n",
      "NAOF_2     8078 non-null float64\n",
      "TPW_2      123937 non-null float64\n",
      "FAST_2     4449 non-null float64\n",
      "A1S_2      4370 non-null float64\n",
      "A2S_2      4362 non-null float64\n",
      "RPW_1      123718 non-null float64\n",
      "RPWOF_1    123718 non-null float64\n",
      "RPW_2      123718 non-null float64\n",
      "RPWOF_2    123718 non-null float64\n",
      "MT         99138 non-null object\n",
      "dtypes: float64(40), int64(4), object(1)\n",
      "memory usage: 42.7+ MB\n"
     ]
    }
   ],
   "source": [
    "stat_atp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "KeyboardInterrupt\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "#percentage of all match won\n",
    "#getting percentage of match won\n",
    "def get_percentage_of_match_won_for_both_player_at_date(ID):\n",
    "    df = stat_atp.loc[(stat_atp['ID1']==ID[0])|(stat_atp['ID2']==ID[0])|(stat_atp['ID1']==ID[1])|(stat_atp['ID2']==ID[1])]\n",
    "    \n",
    "    #selecting date before\n",
    "    df = df.loc[(pd.to_datetime(df.MT)<ID[2]) & (df.ID_T != ID[3])]\n",
    "\n",
    "    \n",
    "    #counting match won/lost by ID1\n",
    "    match_won_byID1 = df.loc[df['ID1']==ID[0]]['ID1'].count()\n",
    "    match_loss_byID1 = df.loc[df['ID2']==ID[0]]['ID2'].count()\n",
    "    \n",
    "    #counting match won/lost by ID2\n",
    "    match_won_byID2 = df.loc[df['ID1']==ID[1]]['ID1'].count()\n",
    "    match_loss_byID2 = df.loc[df['ID2']==ID[1]]['ID2'].count()\n",
    "    \n",
    "    res1 = match_won_byID1/float(match_won_byID1+match_loss_byID1)\n",
    "    res2 = match_won_byID2/float(match_won_byID2+match_loss_byID2)\n",
    "    #if players n'a pas de match historiques\n",
    "    if (math.isnan(res1)):\n",
    "        res1 =0\n",
    "    if (math.isnan(res2)):\n",
    "        res2 = 0\n",
    "    \n",
    "    return res1 - res2\n",
    "\n",
    "\n",
    "train['MATCH_WON'] = train[['ID1_G','ID2_G','DATE_G','ID_T_G']].apply(get_percentage_of_match_won_for_both_player_at_date,axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 69 columns):\n",
      "Unnamed: 0          84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "Unnamed: 0.1        84485 non-null int64\n",
      "ID1_G               84485 non-null int64\n",
      "ID2_G               84485 non-null int64\n",
      "ID_T_G              84485 non-null int64\n",
      "ID_R_G              84485 non-null int64\n",
      "RESULT_G            84485 non-null object\n",
      "DATE_G              84485 non-null object\n",
      "result              84485 non-null int64\n",
      "ID1                 79396 non-null float64\n",
      "W1S_1               79396 non-null float64\n",
      "W1SOF_1             79396 non-null float64\n",
      "W2S_1               79396 non-null float64\n",
      "W2SOF_1             79396 non-null float64\n",
      "BP_1                79396 non-null float64\n",
      "BPOF_1              79396 non-null float64\n",
      "RPW_1               79396 non-null float64\n",
      "RPWOF_1             79396 non-null float64\n",
      "TPW_1               79396 non-null float64\n",
      "ACES_1              79396 non-null float64\n",
      "FS_1                79396 non-null float64\n",
      "FSOF_1              79396 non-null float64\n",
      "DF_1                79396 non-null float64\n",
      "TPW_per_1           79396 non-null float64\n",
      "ID2                 79389 non-null float64\n",
      "W1S_2               79389 non-null float64\n",
      "W1SOF_2             79389 non-null float64\n",
      "W2S_2               79389 non-null float64\n",
      "W2SOF_2             79389 non-null float64\n",
      "BP_2                79389 non-null float64\n",
      "BPOF_2              79389 non-null float64\n",
      "RPW_2               79389 non-null float64\n",
      "RPWOF_2             79389 non-null float64\n",
      "TPW_2               79389 non-null float64\n",
      "ACES_2              79389 non-null float64\n",
      "FS_2                79389 non-null float64\n",
      "FSOF_2              79389 non-null float64\n",
      "DF_2                79389 non-null float64\n",
      "TPW_per_2           79389 non-null float64\n",
      "FS                  76543 non-null float64\n",
      "W1SP                76543 non-null float64\n",
      "W2SP                76543 non-null float64\n",
      "WSP1                79396 non-null float64\n",
      "WSP2                79389 non-null float64\n",
      "WSP                 76543 non-null float64\n",
      "WRP1                79396 non-null float64\n",
      "WRP2                79389 non-null float64\n",
      "WRP                 76543 non-null float64\n",
      "ACES                76543 non-null float64\n",
      "DF                  76543 non-null float64\n",
      "BP                  84485 non-null float64\n",
      "TPW                 76543 non-null float64\n",
      "COMPLETE1           79396 non-null float64\n",
      "COMPLETE2           79389 non-null float64\n",
      "COMPLETE            76543 non-null float64\n",
      "SERVE_ADVANTAGE1    76543 non-null float64\n",
      "SERVE_ADVANTAGE2    76543 non-null float64\n",
      "SERVE_ADVANTAGE     76543 non-null float64\n",
      "BP1                 84485 non-null float64\n",
      "BP2                 84485 non-null float64\n",
      "ID_P_R_x            61931 non-null float64\n",
      "POINT_R_x           84485 non-null float64\n",
      "POS_R_x             84485 non-null float64\n",
      "ID_P_R_y            61899 non-null float64\n",
      "POINT_R_y           84485 non-null float64\n",
      "POS_R_y             84485 non-null float64\n",
      "RANK                84485 non-null float64\n",
      "POINT               84485 non-null float64\n",
      "dtypes: float64(59), int64(8), object(2)\n",
      "memory usage: 44.5+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.to_csv('HistoricalAverageStatWithRankingWithMatchWon_games_atp.csv')\n",
    "train = pd.read_csv('HistoricalAverageStatWithRankingWithMatchWon_games_atp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Direct matchup\n",
    "#getting direct matchup\n",
    "def get_direct_match_up_between_players_at_date(ID):\n",
    "    df = stat_atp.loc[((stat_atp['ID1']==ID[0])&(stat_atp['ID2']==ID[1]))|((stat_atp['ID1']==ID[1])&(stat_atp['ID2']==ID[0]))]\n",
    "    \n",
    "    #selecting date before et ne pas prendre le match du tournoi en question\n",
    "    df = df.loc[(pd.to_datetime(df.MT)<ID[2]) & (df.ID_T != ID[3])]\n",
    "\n",
    "    nbr_match_won_by_ID1 = df.loc[(df['ID1']==ID[0])]['ID1'].count()\n",
    "    nbr_match_won_by_ID2 = df.loc[(df['ID1']==ID[1])]['ID1'].count()\n",
    "    if (nbr_match_won_by_ID1 == 0) & (nbr_match_won_by_ID2 == 0):\n",
    "        res = 0\n",
    "    else:\n",
    "        res =  ((nbr_match_won_by_ID1-nbr_match_won_by_ID2)/float(nbr_match_won_by_ID1+nbr_match_won_by_ID2))\n",
    "    \n",
    "    return res\n",
    "\n",
    "\n",
    "train['DIRECT'] = train[['ID1_G','ID2_G','DATE_G','ID_T_G']].apply(get_direct_match_up_between_players_at_date,axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train.to_csv('HistoricalAverageStatWithRankingWithMatchWonWithDirect_games_atp.csv')\n",
    "train = pd.read_csv('HistoricalAverageStatWithRankingWithMatchWonWithDirect_games_atp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 13243 entries, 0 to 13242\n",
      "Data columns (total 22 columns):\n",
      "ID_T              13243 non-null int64\n",
      "NAME_T            13243 non-null object\n",
      "ID_C_T            13243 non-null int64\n",
      "DATE_T            13243 non-null object\n",
      "RANK_T            13243 non-null int64\n",
      "LINK_T            4678 non-null float64\n",
      "COUNTRY_T         13243 non-null object\n",
      "PRIZE_T           11810 non-null object\n",
      "RATING_T          884 non-null float64\n",
      "URL_T             2632 non-null object\n",
      "LATITUDE_T        5557 non-null float64\n",
      "LONGITUDE_T       5557 non-null float64\n",
      "SITE_T            2188 non-null float64\n",
      "RACE_T            1983 non-null float64\n",
      "ENTRY_T           1985 non-null float64\n",
      "SINGLES_T         769 non-null float64\n",
      "DOUBLES_T         768 non-null float64\n",
      "TIER_T            1422 non-null object\n",
      "RESERVE_INT_T     0 non-null float64\n",
      "RESERVE_CHAR_T    4815 non-null object\n",
      "LIVE_T            0 non-null float64\n",
      "RESULT_T          179 non-null float64\n",
      "dtypes: float64(12), int64(3), object(7)\n",
      "memory usage: 2.2+ MB\n"
     ]
    }
   ],
   "source": [
    "tours_atp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#creating dummy variables for round  / Rank of tournament / type of court\n",
    "train = pd.merge(train,tours_atp[['ID_T','ID_C_T','RANK_T']],left_on='ID_T_G',right_on='ID_T',how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>6277</td>\n",
       "      <td>7869</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2107</td>\n",
       "      <td>7136</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>7-5 5-7 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>72</td>\n",
       "      <td>678</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>563</td>\n",
       "      <td>13796</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>775</td>\n",
       "      <td>745</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(3) 6-1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>75</td>\n",
       "      <td>1266</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-6(4)</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>7826</td>\n",
       "      <td>749</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-2 6-1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>638</td>\n",
       "      <td>13651</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>5058</td>\n",
       "      <td>6002</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>9839</td>\n",
       "      <td>4454</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(6) 6-2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>11923</td>\n",
       "      <td>920</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>1823</td>\n",
       "      <td>4078</td>\n",
       "      <td>8957</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>6691</td>\n",
       "      <td>578</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>453</td>\n",
       "      <td>7806</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 7-5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>760</td>\n",
       "      <td>520</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-1 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>5554</td>\n",
       "      <td>25199</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>516</td>\n",
       "      <td>468</td>\n",
       "      <td>8887</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 7-6(7)</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>25197</td>\n",
       "      <td>15916</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(2) 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>6642</td>\n",
       "      <td>655</td>\n",
       "      <td>8888</td>\n",
       "      <td>4</td>\n",
       "      <td>7-6(2) 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>3685</td>\n",
       "      <td>2123</td>\n",
       "      <td>8889</td>\n",
       "      <td>4</td>\n",
       "      <td>6-3 5-7 6-1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>838</td>\n",
       "      <td>935</td>\n",
       "      <td>8889</td>\n",
       "      <td>4</td>\n",
       "      <td>7-5 6-0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>9839</td>\n",
       "      <td>22906</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>4-6 6-1 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>12896</td>\n",
       "      <td>1162</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>6-7(12) 6-3 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>11517</td>\n",
       "      <td>578</td>\n",
       "      <td>8882</td>\n",
       "      <td>4</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>3694</td>\n",
       "      <td>3996</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>6-3 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>7461</td>\n",
       "      <td>13398</td>\n",
       "      <td>8882</td>\n",
       "      <td>2</td>\n",
       "      <td>6-2 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</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>84455</th>\n",
       "      <td>84455</td>\n",
       "      <td>84455</td>\n",
       "      <td>84455</td>\n",
       "      <td>84455</td>\n",
       "      <td>84455</td>\n",
       "      <td>30801</td>\n",
       "      <td>17964</td>\n",
       "      <td>13298</td>\n",
       "      <td>2</td>\n",
       "      <td>7-5 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84456</th>\n",
       "      <td>84456</td>\n",
       "      <td>84456</td>\n",
       "      <td>84456</td>\n",
       "      <td>84456</td>\n",
       "      <td>84456</td>\n",
       "      <td>25928</td>\n",
       "      <td>11224</td>\n",
       "      <td>13298</td>\n",
       "      <td>2</td>\n",
       "      <td>6-1 6-2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84457</th>\n",
       "      <td>84457</td>\n",
       "      <td>84457</td>\n",
       "      <td>84457</td>\n",
       "      <td>84457</td>\n",
       "      <td>84457</td>\n",
       "      <td>9658</td>\n",
       "      <td>11438</td>\n",
       "      <td>13298</td>\n",
       "      <td>2</td>\n",
       "      <td>6-2 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84458</th>\n",
       "      <td>84458</td>\n",
       "      <td>84458</td>\n",
       "      <td>84458</td>\n",
       "      <td>84458</td>\n",
       "      <td>84458</td>\n",
       "      <td>26965</td>\n",
       "      <td>25365</td>\n",
       "      <td>13409</td>\n",
       "      <td>10</td>\n",
       "      <td>6-4 6-2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84459</th>\n",
       "      <td>84459</td>\n",
       "      <td>84459</td>\n",
       "      <td>84459</td>\n",
       "      <td>84459</td>\n",
       "      <td>84459</td>\n",
       "      <td>12662</td>\n",
       "      <td>12226</td>\n",
       "      <td>13409</td>\n",
       "      <td>10</td>\n",
       "      <td>6-4 6-7(9) 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84460</th>\n",
       "      <td>84460</td>\n",
       "      <td>84460</td>\n",
       "      <td>84460</td>\n",
       "      <td>84460</td>\n",
       "      <td>84460</td>\n",
       "      <td>14427</td>\n",
       "      <td>28925</td>\n",
       "      <td>13414</td>\n",
       "      <td>12</td>\n",
       "      <td>2-6 7-5 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84461</th>\n",
       "      <td>84461</td>\n",
       "      <td>84461</td>\n",
       "      <td>84461</td>\n",
       "      <td>84461</td>\n",
       "      <td>84461</td>\n",
       "      <td>26381</td>\n",
       "      <td>14609</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>6-4 7-5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84462</th>\n",
       "      <td>84462</td>\n",
       "      <td>84462</td>\n",
       "      <td>84462</td>\n",
       "      <td>84462</td>\n",
       "      <td>84462</td>\n",
       "      <td>3996</td>\n",
       "      <td>9842</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>7-6(4) 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84463</th>\n",
       "      <td>84463</td>\n",
       "      <td>84463</td>\n",
       "      <td>84463</td>\n",
       "      <td>84463</td>\n",
       "      <td>84463</td>\n",
       "      <td>39067</td>\n",
       "      <td>50227</td>\n",
       "      <td>13185</td>\n",
       "      <td>12</td>\n",
       "      <td>6-1 3-6 13-11</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84464</th>\n",
       "      <td>84464</td>\n",
       "      <td>84464</td>\n",
       "      <td>84464</td>\n",
       "      <td>84464</td>\n",
       "      <td>84464</td>\n",
       "      <td>17268</td>\n",
       "      <td>13209</td>\n",
       "      <td>13411</td>\n",
       "      <td>12</td>\n",
       "      <td>7-5 2-6 6-2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84465</th>\n",
       "      <td>84465</td>\n",
       "      <td>84465</td>\n",
       "      <td>84465</td>\n",
       "      <td>84465</td>\n",
       "      <td>84465</td>\n",
       "      <td>10590</td>\n",
       "      <td>23575</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84466</th>\n",
       "      <td>84466</td>\n",
       "      <td>84466</td>\n",
       "      <td>84466</td>\n",
       "      <td>84466</td>\n",
       "      <td>84466</td>\n",
       "      <td>39043</td>\n",
       "      <td>7889</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 7-6(5)</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84467</th>\n",
       "      <td>84467</td>\n",
       "      <td>84467</td>\n",
       "      <td>84467</td>\n",
       "      <td>84467</td>\n",
       "      <td>84467</td>\n",
       "      <td>14545</td>\n",
       "      <td>17357</td>\n",
       "      <td>13415</td>\n",
       "      <td>12</td>\n",
       "      <td>7-5 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84468</th>\n",
       "      <td>84468</td>\n",
       "      <td>84468</td>\n",
       "      <td>84468</td>\n",
       "      <td>84468</td>\n",
       "      <td>84468</td>\n",
       "      <td>29665</td>\n",
       "      <td>27358</td>\n",
       "      <td>13421</td>\n",
       "      <td>12</td>\n",
       "      <td>2-6 6-1 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84469</th>\n",
       "      <td>84469</td>\n",
       "      <td>84469</td>\n",
       "      <td>84469</td>\n",
       "      <td>84469</td>\n",
       "      <td>84469</td>\n",
       "      <td>25332</td>\n",
       "      <td>49890</td>\n",
       "      <td>12830</td>\n",
       "      <td>12</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84470</th>\n",
       "      <td>84470</td>\n",
       "      <td>84470</td>\n",
       "      <td>84470</td>\n",
       "      <td>84470</td>\n",
       "      <td>84470</td>\n",
       "      <td>11020</td>\n",
       "      <td>875</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>7-6(5) 7-5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84471</th>\n",
       "      <td>84471</td>\n",
       "      <td>84471</td>\n",
       "      <td>84471</td>\n",
       "      <td>84471</td>\n",
       "      <td>84471</td>\n",
       "      <td>27111</td>\n",
       "      <td>29939</td>\n",
       "      <td>13186</td>\n",
       "      <td>12</td>\n",
       "      <td>6-2 6-7(6) 7-6(3)</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84472</th>\n",
       "      <td>84472</td>\n",
       "      <td>84472</td>\n",
       "      <td>84472</td>\n",
       "      <td>84472</td>\n",
       "      <td>84472</td>\n",
       "      <td>23833</td>\n",
       "      <td>10971</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-1 6-0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84473</th>\n",
       "      <td>84473</td>\n",
       "      <td>84473</td>\n",
       "      <td>84473</td>\n",
       "      <td>84473</td>\n",
       "      <td>84473</td>\n",
       "      <td>21177</td>\n",
       "      <td>29391</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84474</th>\n",
       "      <td>84474</td>\n",
       "      <td>84474</td>\n",
       "      <td>84474</td>\n",
       "      <td>84474</td>\n",
       "      <td>84474</td>\n",
       "      <td>13268</td>\n",
       "      <td>16996</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-2 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84475</th>\n",
       "      <td>84475</td>\n",
       "      <td>84475</td>\n",
       "      <td>84475</td>\n",
       "      <td>84475</td>\n",
       "      <td>84475</td>\n",
       "      <td>8515</td>\n",
       "      <td>3694</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>2-6 6-4 7-5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84476</th>\n",
       "      <td>84476</td>\n",
       "      <td>84476</td>\n",
       "      <td>84476</td>\n",
       "      <td>84476</td>\n",
       "      <td>84476</td>\n",
       "      <td>10920</td>\n",
       "      <td>14510</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>6-4 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84477</th>\n",
       "      <td>84477</td>\n",
       "      <td>84477</td>\n",
       "      <td>84477</td>\n",
       "      <td>84477</td>\n",
       "      <td>84477</td>\n",
       "      <td>5992</td>\n",
       "      <td>8806</td>\n",
       "      <td>12830</td>\n",
       "      <td>12</td>\n",
       "      <td>6-3 7-5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84478</th>\n",
       "      <td>84478</td>\n",
       "      <td>84478</td>\n",
       "      <td>84478</td>\n",
       "      <td>84478</td>\n",
       "      <td>84478</td>\n",
       "      <td>11517</td>\n",
       "      <td>11009</td>\n",
       "      <td>12831</td>\n",
       "      <td>3</td>\n",
       "      <td>3-6 7-6(5) 7-6(5)</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84479</th>\n",
       "      <td>84479</td>\n",
       "      <td>84479</td>\n",
       "      <td>84479</td>\n",
       "      <td>84479</td>\n",
       "      <td>84479</td>\n",
       "      <td>13267</td>\n",
       "      <td>18365</td>\n",
       "      <td>13297</td>\n",
       "      <td>2</td>\n",
       "      <td>5-7 6-2 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84480</th>\n",
       "      <td>84480</td>\n",
       "      <td>84480</td>\n",
       "      <td>84480</td>\n",
       "      <td>84480</td>\n",
       "      <td>84480</td>\n",
       "      <td>23550</td>\n",
       "      <td>24849</td>\n",
       "      <td>13408</td>\n",
       "      <td>12</td>\n",
       "      <td>5-7 6-3 6-4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84481</th>\n",
       "      <td>84481</td>\n",
       "      <td>84481</td>\n",
       "      <td>84481</td>\n",
       "      <td>84481</td>\n",
       "      <td>84481</td>\n",
       "      <td>12662</td>\n",
       "      <td>25365</td>\n",
       "      <td>13409</td>\n",
       "      <td>12</td>\n",
       "      <td>7-6(4) 1-6 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84482</th>\n",
       "      <td>84482</td>\n",
       "      <td>84482</td>\n",
       "      <td>84482</td>\n",
       "      <td>84482</td>\n",
       "      <td>84482</td>\n",
       "      <td>31290</td>\n",
       "      <td>22798</td>\n",
       "      <td>13412</td>\n",
       "      <td>12</td>\n",
       "      <td>6-1 7-6(6)</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84483</th>\n",
       "      <td>84483</td>\n",
       "      <td>84483</td>\n",
       "      <td>84483</td>\n",
       "      <td>84483</td>\n",
       "      <td>84483</td>\n",
       "      <td>11742</td>\n",
       "      <td>28075</td>\n",
       "      <td>13296</td>\n",
       "      <td>3</td>\n",
       "      <td>6-1 6-1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84484</th>\n",
       "      <td>84484</td>\n",
       "      <td>84484</td>\n",
       "      <td>84484</td>\n",
       "      <td>84484</td>\n",
       "      <td>84484</td>\n",
       "      <td>13070</td>\n",
       "      <td>22428</td>\n",
       "      <td>13296</td>\n",
       "      <td>3</td>\n",
       "      <td>3-6 6-0 6-3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>84485 rows × 109 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0  Unnamed: 0.1  Unnamed: 0.1  Unnamed: 0.1.1  Unnamed: 0.1.1  \\\n",
       "0               0             0             0               0               0   \n",
       "1               1             1             1               1               1   \n",
       "2               2             2             2               2               2   \n",
       "3               3             3             3               3               3   \n",
       "4               4             4             4               4               4   \n",
       "5               5             5             5               5               5   \n",
       "6               6             6             6               6               6   \n",
       "7               7             7             7               7               7   \n",
       "8               8             8             8               8               8   \n",
       "9               9             9             9               9               9   \n",
       "10             10            10            10              10              10   \n",
       "11             11            11            11              11              11   \n",
       "12             12            12            12              12              12   \n",
       "13             13            13            13              13              13   \n",
       "14             14            14            14              14              14   \n",
       "15             15            15            15              15              15   \n",
       "16             16            16            16              16              16   \n",
       "17             17            17            17              17              17   \n",
       "18             18            18            18              18              18   \n",
       "19             19            19            19              19              19   \n",
       "20             20            20            20              20              20   \n",
       "21             21            21            21              21              21   \n",
       "22             22            22            22              22              22   \n",
       "23             23            23            23              23              23   \n",
       "24             24            24            24              24              24   \n",
       "25             25            25            25              25              25   \n",
       "26             26            26            26              26              26   \n",
       "27             27            27            27              27              27   \n",
       "28             28            28            28              28              28   \n",
       "29             29            29            29              29              29   \n",
       "...           ...           ...           ...             ...             ...   \n",
       "84455       84455         84455         84455           84455           84455   \n",
       "84456       84456         84456         84456           84456           84456   \n",
       "84457       84457         84457         84457           84457           84457   \n",
       "84458       84458         84458         84458           84458           84458   \n",
       "84459       84459         84459         84459           84459           84459   \n",
       "84460       84460         84460         84460           84460           84460   \n",
       "84461       84461         84461         84461           84461           84461   \n",
       "84462       84462         84462         84462           84462           84462   \n",
       "84463       84463         84463         84463           84463           84463   \n",
       "84464       84464         84464         84464           84464           84464   \n",
       "84465       84465         84465         84465           84465           84465   \n",
       "84466       84466         84466         84466           84466           84466   \n",
       "84467       84467         84467         84467           84467           84467   \n",
       "84468       84468         84468         84468           84468           84468   \n",
       "84469       84469         84469         84469           84469           84469   \n",
       "84470       84470         84470         84470           84470           84470   \n",
       "84471       84471         84471         84471           84471           84471   \n",
       "84472       84472         84472         84472           84472           84472   \n",
       "84473       84473         84473         84473           84473           84473   \n",
       "84474       84474         84474         84474           84474           84474   \n",
       "84475       84475         84475         84475           84475           84475   \n",
       "84476       84476         84476         84476           84476           84476   \n",
       "84477       84477         84477         84477           84477           84477   \n",
       "84478       84478         84478         84478           84478           84478   \n",
       "84479       84479         84479         84479           84479           84479   \n",
       "84480       84480         84480         84480           84480           84480   \n",
       "84481       84481         84481         84481           84481           84481   \n",
       "84482       84482         84482         84482           84482           84482   \n",
       "84483       84483         84483         84483           84483           84483   \n",
       "84484       84484         84484         84484           84484           84484   \n",
       "\n",
       "       ID1_G  ID2_G  ID_T_G  ID_R_G           RESULT_G   ...   round__13  \\\n",
       "0      18854  17613    8887       4    7-6(8) 3-6 10-7   ...         0.0   \n",
       "1      25192  25191    8888       4            6-3 6-2   ...         0.0   \n",
       "2      10828    918    8957       4            6-1 6-2   ...         0.0   \n",
       "3       3316   2379    8957       4         6-4 7-6(5)   ...         0.0   \n",
       "4       6277   7869    8957       4            6-4 6-4   ...         0.0   \n",
       "5       2107   7136    8957       4        7-5 5-7 6-3   ...         0.0   \n",
       "6         72    678    8887       4            6-1 6-4   ...         0.0   \n",
       "7        563  13796    8887       4            6-4 6-4   ...         0.0   \n",
       "8        775    745    8888       4         7-6(3) 6-1   ...         0.0   \n",
       "9         75   1266    8888       4         6-4 7-6(4)   ...         0.0   \n",
       "10      7826    749    8888       4            6-2 6-1   ...         0.0   \n",
       "11       638  13651    8888       4            6-3 6-1   ...         0.0   \n",
       "12      5058   6002    8957       4            6-4 6-2   ...         0.0   \n",
       "13      9839   4454    8957       4         7-6(6) 6-2   ...         0.0   \n",
       "14     11923    920    8957       4            6-3 6-4   ...         0.0   \n",
       "15      1823   4078    8957       4            6-3 6-1   ...         0.0   \n",
       "16      6691    578    8887       4            6-3 6-2   ...         0.0   \n",
       "17       453   7806    8887       4            6-3 7-5   ...         0.0   \n",
       "18       760    520    8888       4            6-1 6-3   ...         0.0   \n",
       "19      5554  25199    8888       4            6-3 6-4   ...         0.0   \n",
       "20       516    468    8887       4         6-4 7-6(7)   ...         0.0   \n",
       "21     25197  15916    8888       4         7-6(2) 6-4   ...         0.0   \n",
       "22      6642    655    8888       4         7-6(2) 6-3   ...         0.0   \n",
       "23      3685   2123    8889       4        6-3 5-7 6-1   ...         0.0   \n",
       "24       838    935    8889       4            7-5 6-0   ...         0.0   \n",
       "25      9839  22906    8882       2        4-6 6-1 6-3   ...         0.0   \n",
       "26     12896   1162    8882       2    6-7(12) 6-3 6-4   ...         0.0   \n",
       "27     11517    578    8882       4            6-4 6-4   ...         0.0   \n",
       "28      3694   3996    8882       2            6-3 6-3   ...         0.0   \n",
       "29      7461  13398    8882       2            6-2 6-3   ...         0.0   \n",
       "...      ...    ...     ...     ...                ...   ...         ...   \n",
       "84455  30801  17964   13298       2            7-5 6-3   ...         0.0   \n",
       "84456  25928  11224   13298       2            6-1 6-2   ...         0.0   \n",
       "84457   9658  11438   13298       2            6-2 6-4   ...         0.0   \n",
       "84458  26965  25365   13409      10            6-4 6-2   ...         0.0   \n",
       "84459  12662  12226   13409      10     6-4 6-7(9) 6-3   ...         0.0   \n",
       "84460  14427  28925   13414      12        2-6 7-5 6-3   ...         0.0   \n",
       "84461  26381  14609   12831       3            6-4 7-5   ...         0.0   \n",
       "84462   3996   9842   12831       3         7-6(4) 6-3   ...         0.0   \n",
       "84463  39067  50227   13185      12      6-1 3-6 13-11   ...         0.0   \n",
       "84464  17268  13209   13411      12        7-5 2-6 6-2   ...         0.0   \n",
       "84465  10590  23575   13297       2            6-4 6-3   ...         0.0   \n",
       "84466  39043   7889   13297       2         6-4 7-6(5)   ...         0.0   \n",
       "84467  14545  17357   13415      12            7-5 6-3   ...         0.0   \n",
       "84468  29665  27358   13421      12        2-6 6-1 6-4   ...         0.0   \n",
       "84469  25332  49890   12830      12            6-4 6-4   ...         0.0   \n",
       "84470  11020    875   12831       3         7-6(5) 7-5   ...         0.0   \n",
       "84471  27111  29939   13186      12  6-2 6-7(6) 7-6(3)   ...         0.0   \n",
       "84472  23833  10971   13297       2            6-1 6-0   ...         0.0   \n",
       "84473  21177  29391   13297       2            6-4 6-4   ...         0.0   \n",
       "84474  13268  16996   13297       2            6-2 6-3   ...         0.0   \n",
       "84475   8515   3694   13297       2        2-6 6-4 7-5   ...         0.0   \n",
       "84476  10920  14510   13297       2            6-4 6-4   ...         0.0   \n",
       "84477   5992   8806   12830      12            6-3 7-5   ...         0.0   \n",
       "84478  11517  11009   12831       3  3-6 7-6(5) 7-6(5)   ...         0.0   \n",
       "84479  13267  18365   13297       2        5-7 6-2 6-4   ...         0.0   \n",
       "84480  23550  24849   13408      12        5-7 6-3 6-4   ...         0.0   \n",
       "84481  12662  25365   13409      12     7-6(4) 1-6 6-3   ...         0.0   \n",
       "84482  31290  22798   13412      12         6-1 7-6(6)   ...         0.0   \n",
       "84483  11742  28075   13296       3            6-1 6-1   ...         0.0   \n",
       "84484  13070  22428   13296       3        3-6 6-0 6-3   ...         0.0   \n",
       "\n",
       "       round__14  round__15  round__16  round__17  Carpet  Clay  Grass  Hard  \\\n",
       "0            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "1            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "2            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "3            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "4            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "5            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "6            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "7            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "8            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "9            0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "10           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "11           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "12           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "13           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "14           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "15           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "16           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "17           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "18           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "19           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "20           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "21           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "22           0.0        0.0        0.0        0.0     0.0   0.0    0.0   0.0   \n",
       "23           0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "24           0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "25           0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "26           0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "27           0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "28           0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "29           0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "...          ...        ...        ...        ...     ...   ...    ...   ...   \n",
       "84455        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84456        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84457        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84458        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84459        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84460        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84461        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84462        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84463        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84464        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84465        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84466        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84467        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84468        0.0        0.0        0.0        0.0     0.0   1.0    0.0   0.0   \n",
       "84469        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84470        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84471        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84472        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84473        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84474        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84475        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84476        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84477        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84478        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84479        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84480        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84481        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84482        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84483        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "84484        0.0        0.0        0.0        0.0     0.0   0.0    0.0   1.0   \n",
       "\n",
       "       I.hard  \n",
       "0         1.0  \n",
       "1         1.0  \n",
       "2         1.0  \n",
       "3         1.0  \n",
       "4         1.0  \n",
       "5         1.0  \n",
       "6         1.0  \n",
       "7         1.0  \n",
       "8         1.0  \n",
       "9         1.0  \n",
       "10        1.0  \n",
       "11        1.0  \n",
       "12        1.0  \n",
       "13        1.0  \n",
       "14        1.0  \n",
       "15        1.0  \n",
       "16        1.0  \n",
       "17        1.0  \n",
       "18        1.0  \n",
       "19        1.0  \n",
       "20        1.0  \n",
       "21        1.0  \n",
       "22        1.0  \n",
       "23        0.0  \n",
       "24        0.0  \n",
       "25        0.0  \n",
       "26        0.0  \n",
       "27        0.0  \n",
       "28        0.0  \n",
       "29        0.0  \n",
       "...       ...  \n",
       "84455     0.0  \n",
       "84456     0.0  \n",
       "84457     0.0  \n",
       "84458     0.0  \n",
       "84459     0.0  \n",
       "84460     0.0  \n",
       "84461     0.0  \n",
       "84462     0.0  \n",
       "84463     0.0  \n",
       "84464     0.0  \n",
       "84465     0.0  \n",
       "84466     0.0  \n",
       "84467     0.0  \n",
       "84468     0.0  \n",
       "84469     0.0  \n",
       "84470     0.0  \n",
       "84471     0.0  \n",
       "84472     0.0  \n",
       "84473     0.0  \n",
       "84474     0.0  \n",
       "84475     0.0  \n",
       "84476     0.0  \n",
       "84477     0.0  \n",
       "84478     0.0  \n",
       "84479     0.0  \n",
       "84480     0.0  \n",
       "84481     0.0  \n",
       "84482     0.0  \n",
       "84483     0.0  \n",
       "84484     0.0  \n",
       "\n",
       "[84485 rows x 109 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranks = pd.get_dummies(train['RANK_T'],prefix='rating_tournament')\n",
    "\n",
    "train = pd.merge(train,rounds,left_on='ID_R_G',right_on='ID_R',how='left')\n",
    "roun = pd.get_dummies(train['ID_R_G'],prefix='round_')\n",
    "\n",
    "\n",
    "train = pd.merge(train,court,left_on='ID_C_T',right_on='ID_C',how='left')\n",
    "typecourt = pd.get_dummies(train['NAME_C'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train = pd.concat([train,ranks,roun,typecourt],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'Unnamed: 0', u'Unnamed: 0.1', u'Unnamed: 0.1', u'Unnamed: 0.1.1',\n",
       "       u'Unnamed: 0.1.1', u'ID1_G', u'ID2_G', u'ID_T_G', u'ID_R_G',\n",
       "       u'RESULT_G', u'DATE_G', u'result', u'ID1', u'W1S_1', u'W1SOF_1',\n",
       "       u'W2S_1', u'W2SOF_1', u'BP_1', u'BPOF_1', u'RPW_1', u'RPWOF_1',\n",
       "       u'TPW_1', u'ACES_1', u'FS_1', u'FSOF_1', u'DF_1', u'TPW_per_1', u'ID2',\n",
       "       u'W1S_2', u'W1SOF_2', u'W2S_2', u'W2SOF_2', u'BP_2', u'BPOF_2',\n",
       "       u'RPW_2', u'RPWOF_2', u'TPW_2', u'ACES_2', u'FS_2', u'FSOF_2'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.columns[:40]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'TPW_per_2', u'FS', u'W1SP', u'W2SP', u'WSP1', u'WSP2', u'WSP',\n",
       "       u'WRP1', u'WRP2', u'WRP', u'ACES', u'DF', u'BP', u'TPW', u'COMPLETE1',\n",
       "       u'COMPLETE2', u'COMPLETE', u'SERVE_ADVANTAGE1', u'SERVE_ADVANTAGE2',\n",
       "       u'SERVE_ADVANTAGE', u'BP1', u'BP2', u'ID_P_R_x', u'POINT_R_x',\n",
       "       u'POS_R_x', u'ID_P_R_y', u'POINT_R_y', u'POS_R_y', u'RANK', u'POINT',\n",
       "       u'MATCH_WON', u'DIRECT', u'ID_T', u'ID_C_T', u'RANK_T', u'ID_R',\n",
       "       u'NAME_R', u'ID_C', u'NAME_C', u'rating_tournament_0',\n",
       "       u'rating_tournament_1', u'rating_tournament_2', u'rating_tournament_3',\n",
       "       u'rating_tournament_4', u'rating_tournament_5', u'rating_tournament_6',\n",
       "       u'round__1', u'round__2', u'round__3', u'round__4', u'round__5',\n",
       "       u'round__6', u'round__7', u'round__8', u'round__9', u'round__10',\n",
       "       u'round__11', u'round__12', u'round__13', u'round__14', u'round__15',\n",
       "       u'round__16', u'round__17', u'Carpet', u'Clay', u'Grass', u'Hard',\n",
       "       u'I.hard'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.columns[41:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CheckPoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#train.to_csv('train.csv')\n",
    "train = pd.read_csv('train.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.cross_validation import cross_val_score\n",
    "from sklearn.svm import SVC,LinearSVC\n",
    "\n",
    "from time import time\n",
    "from scipy.stats import randint as sp_randint\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "\n",
    "\n",
    "columns_to_keep = ['ID1_G','ID2_G','ID_T_G','ID_R_G','DATE_G','result'\n",
    "                   ,'W1SP','W2SP','WSP','WRP','ACES','DF','BP','TPW'\n",
    "                   ,'COMPLETE','SERVE_ADVANTAGE','DIRECT','MATCH_WON'\n",
    "                   ,'POINT','RANK'\n",
    "                   ,'rating_tournament_0','rating_tournament_1','rating_tournament_2','rating_tournament_3','rating_tournament_4','rating_tournament_5','rating_tournament_6'\n",
    "                   ,'Carpet','Clay','Grass','Hard','I.hard']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID1_G</th>\n",
       "      <th>ID2_G</th>\n",
       "      <th>ID_T_G</th>\n",
       "      <th>ID_R_G</th>\n",
       "      <th>result</th>\n",
       "      <th>W1SP</th>\n",
       "      <th>W2SP</th>\n",
       "      <th>WSP</th>\n",
       "      <th>WRP</th>\n",
       "      <th>ACES</th>\n",
       "      <th>...</th>\n",
       "      <th>rating_tournament_2</th>\n",
       "      <th>rating_tournament_3</th>\n",
       "      <th>rating_tournament_4</th>\n",
       "      <th>rating_tournament_5</th>\n",
       "      <th>rating_tournament_6</th>\n",
       "      <th>Carpet</th>\n",
       "      <th>Clay</th>\n",
       "      <th>Grass</th>\n",
       "      <th>Hard</th>\n",
       "      <th>I.hard</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.000000</td>\n",
       "      <td>84485.00000</td>\n",
       "      <td>84485.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>15798.731242</td>\n",
       "      <td>15754.100314</td>\n",
       "      <td>11289.880914</td>\n",
       "      <td>4.893022</td>\n",
       "      <td>0.499994</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>0.000185</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.012898</td>\n",
       "      <td>...</td>\n",
       "      <td>0.191135</td>\n",
       "      <td>0.057442</td>\n",
       "      <td>0.068154</td>\n",
       "      <td>0.021696</td>\n",
       "      <td>0.016145</td>\n",
       "      <td>0.017589</td>\n",
       "      <td>0.433900</td>\n",
       "      <td>0.055880</td>\n",
       "      <td>0.35095</td>\n",
       "      <td>0.141682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12213.889993</td>\n",
       "      <td>12214.728310</td>\n",
       "      <td>1411.895256</td>\n",
       "      <td>3.156799</td>\n",
       "      <td>0.500003</td>\n",
       "      <td>0.068401</td>\n",
       "      <td>0.063147</td>\n",
       "      <td>0.068401</td>\n",
       "      <td>0.049928</td>\n",
       "      <td>2.918896</td>\n",
       "      <td>...</td>\n",
       "      <td>0.393197</td>\n",
       "      <td>0.232687</td>\n",
       "      <td>0.252012</td>\n",
       "      <td>0.145690</td>\n",
       "      <td>0.126033</td>\n",
       "      <td>0.131452</td>\n",
       "      <td>0.495614</td>\n",
       "      <td>0.229691</td>\n",
       "      <td>0.47727</td>\n",
       "      <td>0.348726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>8879.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.599550</td>\n",
       "      <td>-0.543478</td>\n",
       "      <td>-0.599550</td>\n",
       "      <td>-0.392850</td>\n",
       "      <td>-31.623407</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6254.000000</td>\n",
       "      <td>6228.000000</td>\n",
       "      <td>10024.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.036255</td>\n",
       "      <td>-0.024456</td>\n",
       "      <td>-0.036255</td>\n",
       "      <td>-0.024921</td>\n",
       "      <td>-1.576904</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>12612.000000</td>\n",
       "      <td>12594.000000</td>\n",
       "      <td>11344.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000114</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>0.000114</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.012898</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>24225.000000</td>\n",
       "      <td>24225.000000</td>\n",
       "      <td>12786.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.036498</td>\n",
       "      <td>0.024775</td>\n",
       "      <td>0.036498</td>\n",
       "      <td>0.024727</td>\n",
       "      <td>1.622991</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>54622.000000</td>\n",
       "      <td>54798.000000</td>\n",
       "      <td>13422.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.612991</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.612991</td>\n",
       "      <td>2.077381</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ID1_G         ID2_G        ID_T_G        ID_R_G        result  \\\n",
       "count  84485.000000  84485.000000  84485.000000  84485.000000  84485.000000   \n",
       "mean   15798.731242  15754.100314  11289.880914      4.893022      0.499994   \n",
       "std    12213.889993  12214.728310   1411.895256      3.156799      0.500003   \n",
       "min        7.000000      7.000000   8879.000000      1.000000      0.000000   \n",
       "25%     6254.000000   6228.000000  10024.000000      3.000000      0.000000   \n",
       "50%    12612.000000  12594.000000  11344.000000      4.000000      0.000000   \n",
       "75%    24225.000000  24225.000000  12786.000000      5.000000      1.000000   \n",
       "max    54622.000000  54798.000000  13422.000000     17.000000      1.000000   \n",
       "\n",
       "               W1SP          W2SP           WSP           WRP          ACES  \\\n",
       "count  84485.000000  84485.000000  84485.000000  84485.000000  84485.000000   \n",
       "mean       0.000111      0.000185      0.000111      0.000110      0.012898   \n",
       "std        0.068401      0.063147      0.068401      0.049928      2.918896   \n",
       "min       -0.599550     -0.543478     -0.599550     -0.392850    -31.623407   \n",
       "25%       -0.036255     -0.024456     -0.036255     -0.024921     -1.576904   \n",
       "50%        0.000114      0.000128      0.000114      0.000080      0.012898   \n",
       "75%        0.036498      0.024775      0.036498      0.024727      1.622991   \n",
       "max        0.612991      0.666667      0.612991      2.077381     22.000000   \n",
       "\n",
       "           ...       rating_tournament_2  rating_tournament_3  \\\n",
       "count      ...              84485.000000         84485.000000   \n",
       "mean       ...                  0.191135             0.057442   \n",
       "std        ...                  0.393197             0.232687   \n",
       "min        ...                  0.000000             0.000000   \n",
       "25%        ...                  0.000000             0.000000   \n",
       "50%        ...                  0.000000             0.000000   \n",
       "75%        ...                  0.000000             0.000000   \n",
       "max        ...                  1.000000             1.000000   \n",
       "\n",
       "       rating_tournament_4  rating_tournament_5  rating_tournament_6  \\\n",
       "count         84485.000000         84485.000000         84485.000000   \n",
       "mean              0.068154             0.021696             0.016145   \n",
       "std               0.252012             0.145690             0.126033   \n",
       "min               0.000000             0.000000             0.000000   \n",
       "25%               0.000000             0.000000             0.000000   \n",
       "50%               0.000000             0.000000             0.000000   \n",
       "75%               0.000000             0.000000             0.000000   \n",
       "max               1.000000             1.000000             1.000000   \n",
       "\n",
       "             Carpet          Clay         Grass         Hard        I.hard  \n",
       "count  84485.000000  84485.000000  84485.000000  84485.00000  84485.000000  \n",
       "mean       0.017589      0.433900      0.055880      0.35095      0.141682  \n",
       "std        0.131452      0.495614      0.229691      0.47727      0.348726  \n",
       "min        0.000000      0.000000      0.000000      0.00000      0.000000  \n",
       "25%        0.000000      0.000000      0.000000      0.00000      0.000000  \n",
       "50%        0.000000      0.000000      0.000000      0.00000      0.000000  \n",
       "75%        0.000000      1.000000      0.000000      1.00000      0.000000  \n",
       "max        1.000000      1.000000      1.000000      1.00000      1.000000  \n",
       "\n",
       "[8 rows x 31 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[columns_to_keep].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simple Random Forest and linear regression on RANK and POINT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "LinearModel = LinearRegression(fit_intercept=False)\n",
    "RandomForest = RandomForestClassifier()\n",
    "\n",
    "POINT_RANK = ['POINT','RANK']\n",
    "X = train[POINT_RANK].values\n",
    "y = train['result'].values\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.59248401884523361"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores = cross_val_score(RandomForest, X, y, cv=5,scoring='accuracy')\n",
    "scores.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RandomizedSearchCV took 69.62 seconds for 20 candidates parameter settings.\n",
      "Model with rank: 1\n",
      "Mean validation score: 0.650 (std: 0.002)\n",
      "Parameters: {'min_samples_split': 7, 'bootstrap': True, 'criterion': 'gini', 'max_depth': 3, 'min_samples_leaf': 4}\n",
      "\n",
      "Model with rank: 2\n",
      "Mean validation score: 0.649 (std: 0.002)\n",
      "Parameters: {'min_samples_split': 9, 'bootstrap': True, 'criterion': 'gini', 'max_depth': 3, 'min_samples_leaf': 9}\n",
      "\n",
      "Model with rank: 3\n",
      "Mean validation score: 0.649 (std: 0.002)\n",
      "Parameters: {'min_samples_split': 7, 'bootstrap': False, 'criterion': 'gini', 'max_depth': 3, 'min_samples_leaf': 8}\n",
      "\n",
      "Model with rank: 3\n",
      "Mean validation score: 0.649 (std: 0.002)\n",
      "Parameters: {'min_samples_split': 8, 'bootstrap': False, 'criterion': 'gini', 'max_depth': 3, 'min_samples_leaf': 5}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def report(results, n_top=3):\n",
    "    for i in range(1, n_top + 1):\n",
    "        candidates = np.flatnonzero(results['rank_test_score'] == i)\n",
    "        for candidate in candidates:\n",
    "            print(\"Model with rank: {0}\".format(i))\n",
    "            print(\"Mean validation score: {0:.3f} (std: {1:.3f})\".format(\n",
    "                  results['mean_test_score'][candidate],\n",
    "                  results['std_test_score'][candidate]))\n",
    "            print(\"Parameters: {0}\".format(results['params'][candidate]))\n",
    "            print(\"\")\n",
    "\n",
    "param_dist = {\"max_depth\": [3, None],\n",
    "              \"min_samples_split\": sp_randint(2, 11),\n",
    "              \"min_samples_leaf\": sp_randint(2, 11),\n",
    "              \"bootstrap\": [True, False],\n",
    "              \"criterion\": [\"gini\", \"entropy\"]}\n",
    "\n",
    "clf = RandomForestClassifier()\n",
    "# run randomized search\n",
    "n_iter_search = 20\n",
    "random_search = RandomizedSearchCV(clf, param_distributions=param_dist,\n",
    "                                   n_iter=n_iter_search)\n",
    "\n",
    "start = time()\n",
    "random_search.fit(X, y)\n",
    "print(\"RandomizedSearchCV took %.2f seconds for %d candidates\"\n",
    "      \" parameter settings.\" % ((time() - start), n_iter_search))\n",
    "report(random_search.cv_results_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "SVM = LinearSVC()\n",
    "scores = cross_val_score(SVM, X, y, cv=5,scoring='accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.47042326047733274"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## historical with ALL Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "LinearModel = LinearRegression(fit_intercept=False)\n",
    "RandomForest = RandomForestClassifier()\n",
    "\n",
    "columns_to_keep = ['W1SP','W2SP','WSP','WRP','ACES','DF','BP','TPW'\n",
    "                   ,'COMPLETE','SERVE_ADVANTAGE','DIRECT','MATCH_WON'\n",
    "                   ,'POINT','RANK'\n",
    "                   ]\n",
    "round_feature = ['round__' + str(i) for i in range(1,17)]\n",
    "rating_feature = ['rating_tournament_' + str(i) for i in range(6)]\n",
    "type_court = ['Carpet','Clay','Grass','Hard','I.hard']\n",
    "columns = columns_to_keep + round_feature + rating_feature + type_court\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.66063831836386089"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "X = train[columns].values\n",
    "Y = train['result'].values\n",
    "scores = cross_val_score(RandomForest, X, Y, cv=5,scoring='accuracy')\n",
    "scores.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RandomizedSearchCV took 80.65 seconds for 20 candidates parameter settings.\n",
      "Model with rank: 1\n",
      "Mean validation score: 0.688 (std: 0.004)\n",
      "Parameters: {'bootstrap': False, 'min_samples_leaf': 4, 'min_samples_split': 6, 'criterion': 'gini', 'max_features': 13, 'max_depth': 5}\n",
      "\n",
      "Model with rank: 2\n",
      "Mean validation score: 0.686 (std: 0.007)\n",
      "Parameters: {'bootstrap': False, 'min_samples_leaf': 4, 'min_samples_split': 7, 'criterion': 'entropy', 'max_features': 11, 'max_depth': 5}\n",
      "\n",
      "Model with rank: 3\n",
      "Mean validation score: 0.685 (std: 0.007)\n",
      "Parameters: {'bootstrap': True, 'min_samples_leaf': 7, 'min_samples_split': 2, 'criterion': 'gini', 'max_features': 8, 'max_depth': 5}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "param_dist = {\"max_depth\": [3,4,5, None],\n",
    "              \"max_features\": sp_randint(2, 18),\n",
    "              \"min_samples_split\": sp_randint(2, 11),\n",
    "              \"min_samples_leaf\": sp_randint(2, 11),\n",
    "              \"bootstrap\": [True, False],\n",
    "              \"criterion\": [\"gini\", \"entropy\"]}\n",
    "\n",
    "clf = RandomForestClassifier()\n",
    "# run randomized search\n",
    "n_iter_search = 20\n",
    "random_search = RandomizedSearchCV(clf, param_distributions=param_dist,\n",
    "                                   n_iter=n_iter_search)\n",
    "\n",
    "start = time()\n",
    "random_search.fit(X, Y)\n",
    "print(\"RandomizedSearchCV took %.2f seconds for %d candidates\"\n",
    "      \" parameter settings.\" % ((time() - start), n_iter_search))\n",
    "\n",
    "def report(results, n_top=3):\n",
    "    for i in range(1, n_top + 1):\n",
    "        candidates = np.flatnonzero(results['rank_test_score'] == i)\n",
    "        for candidate in candidates:\n",
    "            print(\"Model with rank: {0}\".format(i))\n",
    "            print(\"Mean validation score: {0:.3f} (std: {1:.3f})\".format(\n",
    "                  results['mean_test_score'][candidate],\n",
    "                  results['std_test_score'][candidate]))\n",
    "            print(\"Parameters: {0}\".format(results['params'][candidate]))\n",
    "            print(\"\")\n",
    "report(random_search.cv_results_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "SVM = LinearSVC()\n",
    "\n",
    "X = train[columns_to_keep].values\n",
    "Y = train['result'].values\n",
    "scores = cross_val_score(SVM, X, Y, cv=5,scoring='accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.57210202594765569"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}\n",
    "\n",
    "model = GridSearchCV(estimator = SVC(), param_grid = parameters,cv=5,scoring='accuracy')         \n",
    "start = time()\n",
    "model.fit(X, Y)\n",
    "print(\"RandomizedSearchCV took %.2f seconds for %d candidates\"\n",
    "      \" parameter settings.\" % ((time() - start), n_iter_search))\n",
    "report(random_search.cv_results_)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## historical by court"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "columns = ['ID','W1S_','W1SOF_','W2S_','W2SOF_','BP_','BPOF_','RPW_','RPWOF_','TPW_','ACES_','FS_','FSOF_','DF_','TPW_per_']\n",
    "columns_player_ID1 = [s + '1' for s in columns]\n",
    "columns_player_ID2 = [s + '2' for s in columns]\n",
    "#creating total point won percentage per game for player 1 and 2\n",
    "stat_atp_with_court = pd.merge(stat_atp,tours_atp,left_on='ID_T',right_on='ID_T',how='left')\n",
    "stat_atp_with_court['TPW_per_1'] = stat_atp_with_court['TPW_1'] / (stat_atp_with_court['TPW_1'] + stat_atp_with_court['TPW_2'] ) \n",
    "stat_atp_with_court['TPW_per_2'] = stat_atp_with_court['TPW_2'] / (stat_atp_with_court['TPW_1'] + stat_atp_with_court['TPW_2'] )\n",
    "\n",
    "def get_average_stats_for_two_player_before_date_by_court(ID):\n",
    "    #getting dataframe of both players\n",
    "    df = stat_atp_with_court.loc[(stat_atp_with_court['ID1']==ID[0])|(stat_atp_with_court['ID2']==ID[0])|(stat_atp_with_court['ID1']==ID[1])|(stat_atp_with_court['ID2']==ID[1])]\n",
    "    \n",
    "    #selecting date before\n",
    "    df = df.loc[pd.to_datetime(df.MT)<ID[2]]\n",
    "    \n",
    "    #selecting court\n",
    "    df = df.loc[df.ID_C_T==ID[3]]\n",
    "    \n",
    "    #division of dataframe between both players\n",
    "    df1 = df.loc[(df['ID1']==ID[0])|(df['ID2']==ID[0])]\n",
    "    df2 = df.loc[(df['ID1']==ID[1])|(df['ID2']==ID[1])]\n",
    "    \n",
    "    res1 = df1.loc[df['ID1']==ID[0]][columns_player_ID1]\n",
    "    res1bis = df1.loc[df['ID2']==ID[0]][columns_player_ID2]\n",
    "    res1bis.columns = columns_player_ID1\n",
    "    res1 = pd.concat([res1,res1bis])\n",
    "    res1 = res1.mean()\n",
    "    \n",
    "    \n",
    "    res4 = df.loc[df['ID2']==ID[1]][columns_player_ID2]\n",
    "    res5 = df.loc[df['ID1']==ID[1]][columns_player_ID1]\n",
    "    res5.columns = columns_player_ID2\n",
    "    res6 = pd.concat([res5,res4])\n",
    "    res6 = res6.mean()\n",
    "    \n",
    "    res = pd.concat([res1,res6],axis=0)\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def unbiased_games_atp(games_atp):\n",
    "    #preparing biased data\n",
    "    #create predict variable\n",
    "    games_atp['result']= games_atp['RESULT_G'].map(lambda x:1)\n",
    "\n",
    "    #swap id1 & id2 and predic variable is 1\n",
    "    games_atp['result'].iloc[::2] = games_atp['RESULT_G'].iloc[::2].map(lambda x:0)\n",
    "    idx = (games_atp['result']==0)\n",
    "    games_atp.loc[idx,['ID1_G','ID2_G']] = games_atp.loc[idx,['ID2_G','ID1_G']].values\n",
    "    return games_atp\n",
    "\n",
    "#checking if result (compare with other notebook) GOOD\n",
    "games_atp_unbiased = unbiased_games_atp(games_atp)\n",
    "train = games_atp_unbiased\n",
    "\n",
    "\n",
    "train = pd.merge(train,tours_atp[['ID_T','ID_C_T','RANK_T',]],left_on='ID_T_G',right_on='ID_T')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 84485 entries, 0 to 84484\n",
      "Data columns (total 10 columns):\n",
      "ID1_G       84485 non-null int64\n",
      "ID2_G       84485 non-null int64\n",
      "ID_T_G      84485 non-null int64\n",
      "ID_R_G      84485 non-null int64\n",
      "RESULT_G    84485 non-null object\n",
      "DATE_G      84485 non-null datetime64[ns]\n",
      "result      84485 non-null int64\n",
      "ID_T        84485 non-null int64\n",
      "ID_C_T      84485 non-null int64\n",
      "RANK_T      84485 non-null int64\n",
      "dtypes: datetime64[ns](1), int64(8), object(1)\n",
      "memory usage: 7.1+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train[columns_player_ID1+columns_player_ID2] = train[['ID1_G','ID2_G','DATE_G','ID_C_T']].apply(get_average_stats_for_two_player_before_date_by_court,axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train.to_csv('train_historical_by_court.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "train = pd.read_csv('train_historical_by_court.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 84485 entries, 0 to 84484\n",
      "Data columns (total 41 columns):\n",
      "Unnamed: 0    84485 non-null int64\n",
      "ID1_G         84485 non-null int64\n",
      "ID2_G         84485 non-null int64\n",
      "ID_T_G        84485 non-null int64\n",
      "ID_R_G        84485 non-null int64\n",
      "RESULT_G      84485 non-null object\n",
      "DATE_G        84485 non-null object\n",
      "result        84485 non-null int64\n",
      "ID_T          84485 non-null int64\n",
      "ID_C_T        84485 non-null int64\n",
      "RANK_T        84485 non-null int64\n",
      "ID1           83262 non-null float64\n",
      "W1S_1         83262 non-null float64\n",
      "W1SOF_1       83262 non-null float64\n",
      "W2S_1         83262 non-null float64\n",
      "W2SOF_1       83262 non-null float64\n",
      "BP_1          83262 non-null float64\n",
      "BPOF_1        83262 non-null float64\n",
      "RPW_1         83253 non-null float64\n",
      "RPWOF_1       83253 non-null float64\n",
      "TPW_1         83262 non-null float64\n",
      "ACES_1        83258 non-null float64\n",
      "FS_1          83262 non-null float64\n",
      "FSOF_1        83262 non-null float64\n",
      "DF_1          83262 non-null float64\n",
      "TPW_per_1     83262 non-null float64\n",
      "ID2           82166 non-null float64\n",
      "W1S_2         82166 non-null float64\n",
      "W1SOF_2       82166 non-null float64\n",
      "W2S_2         82166 non-null float64\n",
      "W2SOF_2       82166 non-null float64\n",
      "BP_2          82161 non-null float64\n",
      "BPOF_2        82161 non-null float64\n",
      "RPW_2         82117 non-null float64\n",
      "RPWOF_2       82117 non-null float64\n",
      "TPW_2         82166 non-null float64\n",
      "ACES_2        82101 non-null float64\n",
      "FS_2          82166 non-null float64\n",
      "FSOF_2        82166 non-null float64\n",
      "DF_2          82149 non-null float64\n",
      "TPW_per_2     82166 non-null float64\n",
      "dtypes: float64(30), int64(9), object(2)\n",
      "memory usage: 26.4+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "#first service success\n",
    "train['FS'] = (train['FS_1']/train['FSOF_1']) - (train['FS_2']/train['FSOF_2'])\n",
    "\n",
    "#Win on first serve percentage\n",
    "train['W1SP'] = (train['W1S_1']/train['W1SOF_1']) - (train['W1S_2']/train['W1SOF_2'])\n",
    "\n",
    "#Win on second serve percentage\n",
    "train['W2SP'] = (train['W2S_1']/train['W2SOF_1']) - (train['W2S_2']/train['W2SOF_2'])\n",
    "\n",
    "\n",
    "#Overall winning service percentage\n",
    "#W1SP*F1S + W2SP*F2S pour chaque joueur\n",
    "\n",
    "train['WSP1'] = (train['W1S_1']/train['W1SOF_1'])*(train['FS_1']/train['FSOF_1'])+(train['W1S_1']/train['W1SOF_1'])*(1-(train['FS_1']/train['FSOF_1']))\n",
    "train['WSP2'] = (train['W1S_2']/train['W1SOF_2'])*(train['FS_2']/train['FSOF_2'])+(train['W1S_2']/train['W1SOF_2'])*(1-(train['FS_2']/train['FSOF_2']))\n",
    "\n",
    "train['WSP']=train['WSP1'] - train['WSP2']\n",
    "\n",
    "#Winning on return percentage\n",
    "train['WRP1'] = train['RPW_1']/train['RPWOF_1']\n",
    "train['WRP2'] = train['RPW_2']/train['RPWOF_2']\n",
    "\n",
    "train['WRP'] = train['WRP1'] - train['WRP2']\n",
    "\n",
    "\n",
    "\n",
    "#Average aces per game\n",
    "train['ACES'] = train['ACES_1'] - train['ACES_2']\n",
    "\n",
    "#DOUble faute\n",
    "train['DF'] = train['DF_1'] - train['DF_2']\n",
    "\n",
    "#break point percentage\n",
    "train['BP1'] = train['BP_1']/train['BPOF_1']\n",
    "train['BP2'] = train['BP_2']/train['BPOF_2']\n",
    "train.BP1 = train.BP1.fillna(0)\n",
    "train.BP2 = train.BP2.fillna(0)\n",
    "train['BP'] = train['BP1'] - train['BP2']\n",
    "\n",
    "\n",
    "#total point won percentage\n",
    "train['TPW'] = train['TPW_per_1'] - train['TPW_per_2']\n",
    "\n",
    "#Completeness (service won x return won)\n",
    "train['COMPLETE1'] = train['WSP1']*train['WRP1']\n",
    "train['COMPLETE2'] = train['WSP2']*train['WRP2']\n",
    "\n",
    "train['COMPLETE'] = train['COMPLETE1'] - train['COMPLETE2']\n",
    "\n",
    "#Advantage on serve\n",
    "train['SERVE_ADVANTAGE1'] = train['WSP1'] - train['WRP2']\n",
    "train['SERVE_ADVANTAGE2'] = train['WSP2'] - train['WRP1']\n",
    "train['SERVE_ADVANTAGE'] = train['SERVE_ADVANTAGE1'] - train['SERVE_ADVANTAGE2']\n",
    "\n",
    "columns_to_keep = ['ID1_G','ID2_G','ID_T_G','ID_R_G','DATE_G','result'\n",
    "                   ,'W1SP','W2SP','WSP','WRP','ACES','DF','BP','TPW'\n",
    "                   ,'COMPLETE','SERVE_ADVANTAGE']\n",
    "\n",
    "#percentage of all match won\n",
    "#train['MATCH_WON_PER_ID1'],train['MATCH_WON_PER_ID2'] = train[['ID1_G','ID2_G','DATE_G']].apply(get_percentage_of_match_won_for_both_player_at_date,axis=1)\n",
    "#train['MATCH_WON'] = train['MATCH_WON_PER_ID1'] - train['MATCH_WON_PER_ID2']\n",
    "\n",
    "#Direct matchup\n",
    "#train['DIRECT'] = train[['ID1_G','ID2_G','DATE_G']].apply(get_direct_match_up_between_players_at_date,axis=1)\n",
    "\n",
    "\n",
    "#RANK\n",
    "#pd.merge(train, ratings_atp.groupby(['ID_P_R']).mean(), left_on='ID1_G', right_on='ID_P_R',how='left')\n",
    "MeanRating = ratings_atp.groupby(['ID_P_R']).mean().reset_index()\n",
    "train = pd.merge(train, MeanRating, left_on='ID1_G', right_on='ID_P_R',how='left')\n",
    "train = pd.merge(train, MeanRating, left_on='ID2_G', right_on='ID_P_R',how='left')\n",
    "\n",
    "train['RANK'] = train['POS_R_x'] - train['POS_R_y']\n",
    "train['POINT'] = train['POINT_R_x'] - train['POINT_R_y']\n",
    "\n",
    "ranks = pd.get_dummies(train['RANK_T'],prefix='rating_tournament')\n",
    "\n",
    "train = pd.merge(train,rounds,left_on='ID_R_G',right_on='ID_R',how='left')\n",
    "roun = pd.get_dummies(train['ID_R_G'],prefix='round_')\n",
    "\n",
    "\n",
    "train = pd.merge(train,court,left_on='ID_C_T',right_on='ID_C',how='left')\n",
    "typecourt = pd.get_dummies(train['NAME_C'])\n",
    "\n",
    "train = pd.concat([train,ranks,roun,typecourt],axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 84485 entries, 0 to 84484\n",
      "Columns: 103 entries, Unnamed: 0 to I.hard\n",
      "dtypes: float64(88), int64(11), object(4)\n",
      "memory usage: 67.0+ MB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 84485 entries, 0 to 84484\n",
      "Data columns (total 24 columns):\n",
      "W1SP                   81687 non-null float64\n",
      "W2SP                   81687 non-null float64\n",
      "WSP                    81687 non-null float64\n",
      "WRP                    81635 non-null float64\n",
      "ACES                   81620 non-null float64\n",
      "DF                     81670 non-null float64\n",
      "BP                     84485 non-null float64\n",
      "TPW                    81687 non-null float64\n",
      "COMPLETE               81635 non-null float64\n",
      "SERVE_ADVANTAGE        81635 non-null float64\n",
      "POINT                  56608 non-null float64\n",
      "RANK                   56608 non-null float64\n",
      "rating_tournament_0    84485 non-null float64\n",
      "rating_tournament_1    84485 non-null float64\n",
      "rating_tournament_2    84485 non-null float64\n",
      "rating_tournament_3    84485 non-null float64\n",
      "rating_tournament_4    84485 non-null float64\n",
      "rating_tournament_5    84485 non-null float64\n",
      "rating_tournament_6    84485 non-null float64\n",
      "Carpet                 84485 non-null float64\n",
      "Clay                   84485 non-null float64\n",
      "Grass                  84485 non-null float64\n",
      "Hard                   84485 non-null float64\n",
      "I.hard                 84485 non-null float64\n",
      "dtypes: float64(24)\n",
      "memory usage: 16.1 MB\n"
     ]
    }
   ],
   "source": [
    "columns_to_keep = [\n",
    "                   'W1SP','W2SP','WSP','WRP','ACES','DF','BP','TPW'\n",
    "                   ,'COMPLETE','SERVE_ADVANTAGE'\n",
    "                   ,'POINT','RANK'\n",
    "                   ,'rating_tournament_0','rating_tournament_1','rating_tournament_2','rating_tournament_3','rating_tournament_4','rating_tournament_5','rating_tournament_6'\n",
    "                   ,'Carpet','Clay','Grass','Hard','I.hard']\n",
    "train[columns_to_keep].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 56185 entries, 1 to 84484\n",
      "Data columns (total 24 columns):\n",
      "W1SP                   56185 non-null float64\n",
      "W2SP                   56185 non-null float64\n",
      "WSP                    56185 non-null float64\n",
      "WRP                    56185 non-null float64\n",
      "ACES                   56185 non-null float64\n",
      "DF                     56185 non-null float64\n",
      "BP                     56185 non-null float64\n",
      "TPW                    56185 non-null float64\n",
      "COMPLETE               56185 non-null float64\n",
      "SERVE_ADVANTAGE        56185 non-null float64\n",
      "POINT                  56185 non-null float64\n",
      "RANK                   56185 non-null float64\n",
      "rating_tournament_0    56185 non-null float64\n",
      "rating_tournament_1    56185 non-null float64\n",
      "rating_tournament_2    56185 non-null float64\n",
      "rating_tournament_3    56185 non-null float64\n",
      "rating_tournament_4    56185 non-null float64\n",
      "rating_tournament_5    56185 non-null float64\n",
      "rating_tournament_6    56185 non-null float64\n",
      "Carpet                 56185 non-null float64\n",
      "Clay                   56185 non-null float64\n",
      "Grass                  56185 non-null float64\n",
      "Hard                   56185 non-null float64\n",
      "I.hard                 56185 non-null float64\n",
      "dtypes: float64(24)\n",
      "memory usage: 10.7 MB\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.cross_validation import cross_val_score\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "from time import time\n",
    "from scipy.stats import randint as sp_randint\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from sklearn.datasets import load_digits\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "LinearModel = LinearRegression(fit_intercept=False)\n",
    "RandomForest = RandomForestClassifier()\n",
    "\n",
    "\n",
    "X = train[columns_to_keep].dropna()\n",
    "X.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.49902985081201273"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "Y = train.dropna()['result'].values\n",
    "\n",
    "scores = cross_val_score(RandomForest, X, Y, cv=5,scoring='accuracy')\n",
    "scores.mean()"
   ]
  }
 ],
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