Code.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Importing important libraries:\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import preprocessing\n",
    "\n",
    "\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import accuracy_score as acc\n",
    "\n",
    "\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import cross_val_predict\n",
    "\n",
    "\n",
    "from sklearn.metrics import make_scorer, accuracy_score\n",
    "from sklearn.model_selection import GridSearchCV,RandomizedSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Reading the data:\n",
    "\n",
    "data=pd.read_csv('data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>match_event_id</th>\n",
       "      <th>location_x</th>\n",
       "      <th>location_y</th>\n",
       "      <th>remaining_min</th>\n",
       "      <th>power_of_shot</th>\n",
       "      <th>knockout_match</th>\n",
       "      <th>game_season</th>\n",
       "      <th>remaining_sec</th>\n",
       "      <th>distance_of_shot</th>\n",
       "      <th>...</th>\n",
       "      <th>lat/lng</th>\n",
       "      <th>type_of_shot</th>\n",
       "      <th>type_of_combined_shot</th>\n",
       "      <th>match_id</th>\n",
       "      <th>team_id</th>\n",
       "      <th>remaining_min.1</th>\n",
       "      <th>power_of_shot.1</th>\n",
       "      <th>knockout_match.1</th>\n",
       "      <th>remaining_sec.1</th>\n",
       "      <th>distance_of_shot.1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>27.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>...</td>\n",
       "      <td>45.539131, -122.651648</td>\n",
       "      <td>shot - 30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20000012</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>10.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>50.608</td>\n",
       "      <td>54.2000</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>12.0</td>\n",
       "      <td>-157.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>22.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>...</td>\n",
       "      <td>45.539131, -122.651648</td>\n",
       "      <td>shot - 45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20000012</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>10.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>28.800</td>\n",
       "      <td>22.0000</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>35.0</td>\n",
       "      <td>-101.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>45.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>...</td>\n",
       "      <td>45.539131, -122.651648</td>\n",
       "      <td>shot - 25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20000012</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>92.64</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>63.7216</td>\n",
       "      <td>54.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>43.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>52.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>...</td>\n",
       "      <td>45.539131, -122.651648</td>\n",
       "      <td>NaN</td>\n",
       "      <td>shot - 3</td>\n",
       "      <td>20000012</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>122.608</td>\n",
       "      <td>52.0000</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>45.539131, -122.651648</td>\n",
       "      <td>NaN</td>\n",
       "      <td>shot - 1</td>\n",
       "      <td>20000012</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>42.64</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>19.0000</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  match_event_id  location_x  location_y  remaining_min  \\\n",
       "0           0            10.0       167.0        72.0           10.0   \n",
       "1           1            12.0      -157.0         0.0           10.0   \n",
       "2           2            35.0      -101.0       135.0            7.0   \n",
       "3           3            43.0       138.0       175.0            6.0   \n",
       "4           4           155.0         0.0         0.0            NaN   \n",
       "\n",
       "   power_of_shot  knockout_match game_season  remaining_sec  distance_of_shot  \\\n",
       "0            1.0             0.0     2000-01           27.0              38.0   \n",
       "1            1.0             0.0     2000-01           22.0              35.0   \n",
       "2            1.0             0.0     2000-01           45.0              36.0   \n",
       "3            1.0             0.0     2000-01           52.0              42.0   \n",
       "4            2.0             0.0     2000-01           19.0              20.0   \n",
       "\n",
       "   ...                 lat/lng type_of_shot type_of_combined_shot  match_id  \\\n",
       "0  ...  45.539131, -122.651648    shot - 30                   NaN  20000012   \n",
       "1  ...  45.539131, -122.651648    shot - 45                   NaN  20000012   \n",
       "2  ...  45.539131, -122.651648    shot - 25                   NaN  20000012   \n",
       "3  ...  45.539131, -122.651648          NaN              shot - 3  20000012   \n",
       "4  ...  45.539131, -122.651648          NaN              shot - 1  20000012   \n",
       "\n",
       "      team_id remaining_min.1 power_of_shot.1  knockout_match.1  \\\n",
       "0  1610612747           10.00             1.0            50.608   \n",
       "1  1610612747           10.00             1.0            28.800   \n",
       "2  1610612747           92.64             1.0             0.000   \n",
       "3  1610612747             NaN             1.0           122.608   \n",
       "4  1610612747           42.64             2.0             0.000   \n",
       "\n",
       "  remaining_sec.1 distance_of_shot.1  \n",
       "0         54.2000               38.0  \n",
       "1         22.0000               35.0  \n",
       "2         63.7216               54.4  \n",
       "3         52.0000               42.0  \n",
       "4         19.0000               20.0  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>match_event_id</th>\n",
       "      <th>location_x</th>\n",
       "      <th>location_y</th>\n",
       "      <th>remaining_min</th>\n",
       "      <th>power_of_shot</th>\n",
       "      <th>knockout_match</th>\n",
       "      <th>remaining_sec</th>\n",
       "      <th>distance_of_shot</th>\n",
       "      <th>is_goal</th>\n",
       "      <th>shot_id_number</th>\n",
       "      <th>match_id</th>\n",
       "      <th>team_id</th>\n",
       "      <th>remaining_min.1</th>\n",
       "      <th>power_of_shot.1</th>\n",
       "      <th>knockout_match.1</th>\n",
       "      <th>remaining_sec.1</th>\n",
       "      <th>distance_of_shot.1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>30697.000000</td>\n",
       "      <td>29134.000000</td>\n",
       "      <td>29236.000000</td>\n",
       "      <td>29157.000000</td>\n",
       "      <td>29135.000000</td>\n",
       "      <td>29211.000000</td>\n",
       "      <td>29180.000000</td>\n",
       "      <td>29103.000000</td>\n",
       "      <td>29130.000000</td>\n",
       "      <td>24429.000000</td>\n",
       "      <td>29134.000000</td>\n",
       "      <td>3.069700e+04</td>\n",
       "      <td>3.069700e+04</td>\n",
       "      <td>29162.000000</td>\n",
       "      <td>29158.000000</td>\n",
       "      <td>29204.000000</td>\n",
       "      <td>29158.000000</td>\n",
       "      <td>29129.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>15348.000000</td>\n",
       "      <td>249.576028</td>\n",
       "      <td>7.383876</td>\n",
       "      <td>91.126933</td>\n",
       "      <td>4.883233</td>\n",
       "      <td>2.519359</td>\n",
       "      <td>0.145956</td>\n",
       "      <td>28.329382</td>\n",
       "      <td>33.448884</td>\n",
       "      <td>0.445331</td>\n",
       "      <td>15368.581039</td>\n",
       "      <td>2.476407e+07</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>18.204615</td>\n",
       "      <td>15.994109</td>\n",
       "      <td>16.599402</td>\n",
       "      <td>39.027303</td>\n",
       "      <td>38.801852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8861.604943</td>\n",
       "      <td>150.186019</td>\n",
       "      <td>110.263049</td>\n",
       "      <td>87.676395</td>\n",
       "      <td>3.452533</td>\n",
       "      <td>1.153976</td>\n",
       "      <td>0.353068</td>\n",
       "      <td>17.470663</td>\n",
       "      <td>9.369656</td>\n",
       "      <td>0.497013</td>\n",
       "      <td>8866.520772</td>\n",
       "      <td>7.755175e+06</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>29.416973</td>\n",
       "      <td>29.676815</td>\n",
       "      <td>35.172016</td>\n",
       "      <td>29.835284</td>\n",
       "      <td>18.787711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-250.000000</td>\n",
       "      <td>-44.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000001e+07</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7674.000000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>-68.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7693.250000</td>\n",
       "      <td>2.050008e+07</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>26.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>15348.000000</td>\n",
       "      <td>254.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15378.500000</td>\n",
       "      <td>2.090035e+07</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>36.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>23022.000000</td>\n",
       "      <td>369.000000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>23055.750000</td>\n",
       "      <td>2.960047e+07</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>44.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>30696.000000</td>\n",
       "      <td>659.000000</td>\n",
       "      <td>248.000000</td>\n",
       "      <td>791.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>4.990009e+07</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>128.761600</td>\n",
       "      <td>118.360000</td>\n",
       "      <td>141.352320</td>\n",
       "      <td>144.785600</td>\n",
       "      <td>115.728000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0  match_event_id    location_x    location_y  \\\n",
       "count  30697.000000    29134.000000  29236.000000  29157.000000   \n",
       "mean   15348.000000      249.576028      7.383876     91.126933   \n",
       "std     8861.604943      150.186019    110.263049     87.676395   \n",
       "min        0.000000        2.000000   -250.000000    -44.000000   \n",
       "25%     7674.000000      111.000000    -68.000000      4.000000   \n",
       "50%    15348.000000      254.000000      0.000000     74.000000   \n",
       "75%    23022.000000      369.000000     95.000000    160.000000   \n",
       "max    30696.000000      659.000000    248.000000    791.000000   \n",
       "\n",
       "       remaining_min  power_of_shot  knockout_match  remaining_sec  \\\n",
       "count   29135.000000   29211.000000    29180.000000   29103.000000   \n",
       "mean        4.883233       2.519359        0.145956      28.329382   \n",
       "std         3.452533       1.153976        0.353068      17.470663   \n",
       "min         0.000000       1.000000        0.000000       0.000000   \n",
       "25%         2.000000       1.000000        0.000000      13.000000   \n",
       "50%         5.000000       3.000000        0.000000      28.000000   \n",
       "75%         8.000000       3.000000        0.000000      43.000000   \n",
       "max        11.000000       7.000000        1.000000      59.000000   \n",
       "\n",
       "       distance_of_shot       is_goal  shot_id_number      match_id  \\\n",
       "count      29130.000000  24429.000000    29134.000000  3.069700e+04   \n",
       "mean          33.448884      0.445331    15368.581039  2.476407e+07   \n",
       "std            9.369656      0.497013     8866.520772  7.755175e+06   \n",
       "min           20.000000      0.000000        1.000000  2.000001e+07   \n",
       "25%           25.000000      0.000000     7693.250000  2.050008e+07   \n",
       "50%           35.000000      0.000000    15378.500000  2.090035e+07   \n",
       "75%           41.000000      1.000000    23055.750000  2.960047e+07   \n",
       "max           99.000000      1.000000    30697.000000  4.990009e+07   \n",
       "\n",
       "            team_id  remaining_min.1  power_of_shot.1  knockout_match.1  \\\n",
       "count  3.069700e+04     29162.000000     29158.000000      29204.000000   \n",
       "mean   1.610613e+09        18.204615        15.994109         16.599402   \n",
       "std    0.000000e+00        29.416973        29.676815         35.172016   \n",
       "min    1.610613e+09         0.000000         1.000000          0.000000   \n",
       "25%    1.610613e+09         3.000000         2.000000          0.000000   \n",
       "50%    1.610613e+09         6.000000         3.000000          0.000000   \n",
       "75%    1.610613e+09        11.000000         4.000000          1.000000   \n",
       "max    1.610613e+09       128.761600       118.360000        141.352320   \n",
       "\n",
       "       remaining_sec.1  distance_of_shot.1  \n",
       "count     29158.000000        29129.000000  \n",
       "mean         39.027303           38.801852  \n",
       "std          29.835284           18.787711  \n",
       "min           0.000000            9.400000  \n",
       "25%          17.000000           26.000000  \n",
       "50%          35.000000           36.000000  \n",
       "75%          52.000000           44.000000  \n",
       "max         144.785600          115.728000  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30697, 28)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Dropping unnecessary columns from the dataset:\n",
    "\n",
    "data.drop(columns=['Unnamed: 0','match_event_id','game_season','team_name','date_of_game','shot_id_number','lat/lng','type_of_shot','type_of_combined_shot','match_id','team_id',],inplace=True)\n",
    "data=data.iloc[:,:-5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location_x</th>\n",
       "      <th>location_y</th>\n",
       "      <th>remaining_min</th>\n",
       "      <th>power_of_shot</th>\n",
       "      <th>knockout_match</th>\n",
       "      <th>remaining_sec</th>\n",
       "      <th>distance_of_shot</th>\n",
       "      <th>is_goal</th>\n",
       "      <th>area_of_shot</th>\n",
       "      <th>shot_basics</th>\n",
       "      <th>range_of_shot</th>\n",
       "      <th>home/away</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>167.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Right Side(R)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>MANU @ POR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-157.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Left Side(L)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>8-16 ft.</td>\n",
       "      <td>MANU @ POR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-101.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Left Side Center(LC)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>138.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Right Side Center(RC)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>MANU @ POR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Center(C)</td>\n",
       "      <td>Goal Area</td>\n",
       "      <td>Less Than 8 ft.</td>\n",
       "      <td>MANU @ POR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   location_x  location_y  remaining_min  power_of_shot  knockout_match  \\\n",
       "0       167.0        72.0           10.0            1.0             0.0   \n",
       "1      -157.0         0.0           10.0            1.0             0.0   \n",
       "2      -101.0       135.0            7.0            1.0             0.0   \n",
       "3       138.0       175.0            6.0            1.0             0.0   \n",
       "4         0.0         0.0            NaN            2.0             0.0   \n",
       "\n",
       "   remaining_sec  distance_of_shot  is_goal           area_of_shot  \\\n",
       "0           27.0              38.0      NaN          Right Side(R)   \n",
       "1           22.0              35.0      0.0           Left Side(L)   \n",
       "2           45.0              36.0      1.0   Left Side Center(LC)   \n",
       "3           52.0              42.0      0.0  Right Side Center(RC)   \n",
       "4           19.0              20.0      1.0              Center(C)   \n",
       "\n",
       "  shot_basics    range_of_shot   home/away  \n",
       "0   Mid Range        16-24 ft.  MANU @ POR  \n",
       "1   Mid Range         8-16 ft.  MANU @ POR  \n",
       "2   Mid Range        16-24 ft.         NaN  \n",
       "3   Mid Range        16-24 ft.  MANU @ POR  \n",
       "4   Goal Area  Less Than 8 ft.  MANU @ POR  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30697, 12)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location_x</th>\n",
       "      <th>location_y</th>\n",
       "      <th>remaining_min</th>\n",
       "      <th>power_of_shot</th>\n",
       "      <th>knockout_match</th>\n",
       "      <th>remaining_sec</th>\n",
       "      <th>distance_of_shot</th>\n",
       "      <th>is_goal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29236.000000</td>\n",
       "      <td>29157.000000</td>\n",
       "      <td>29135.000000</td>\n",
       "      <td>29211.000000</td>\n",
       "      <td>29180.000000</td>\n",
       "      <td>29103.000000</td>\n",
       "      <td>29130.000000</td>\n",
       "      <td>24429.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.383876</td>\n",
       "      <td>91.126933</td>\n",
       "      <td>4.883233</td>\n",
       "      <td>2.519359</td>\n",
       "      <td>0.145956</td>\n",
       "      <td>28.329382</td>\n",
       "      <td>33.448884</td>\n",
       "      <td>0.445331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>110.263049</td>\n",
       "      <td>87.676395</td>\n",
       "      <td>3.452533</td>\n",
       "      <td>1.153976</td>\n",
       "      <td>0.353068</td>\n",
       "      <td>17.470663</td>\n",
       "      <td>9.369656</td>\n",
       "      <td>0.497013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-250.000000</td>\n",
       "      <td>-44.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-68.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>95.000000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>248.000000</td>\n",
       "      <td>791.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         location_x    location_y  remaining_min  power_of_shot  \\\n",
       "count  29236.000000  29157.000000   29135.000000   29211.000000   \n",
       "mean       7.383876     91.126933       4.883233       2.519359   \n",
       "std      110.263049     87.676395       3.452533       1.153976   \n",
       "min     -250.000000    -44.000000       0.000000       1.000000   \n",
       "25%      -68.000000      4.000000       2.000000       1.000000   \n",
       "50%        0.000000     74.000000       5.000000       3.000000   \n",
       "75%       95.000000    160.000000       8.000000       3.000000   \n",
       "max      248.000000    791.000000      11.000000       7.000000   \n",
       "\n",
       "       knockout_match  remaining_sec  distance_of_shot       is_goal  \n",
       "count    29180.000000   29103.000000      29130.000000  24429.000000  \n",
       "mean         0.145956      28.329382         33.448884      0.445331  \n",
       "std          0.353068      17.470663          9.369656      0.497013  \n",
       "min          0.000000       0.000000         20.000000      0.000000  \n",
       "25%          0.000000      13.000000         25.000000      0.000000  \n",
       "50%          0.000000      28.000000         35.000000      0.000000  \n",
       "75%          0.000000      43.000000         41.000000      1.000000  \n",
       "max          1.000000      59.000000         99.000000      1.000000  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location_x</th>\n",
       "      <th>location_y</th>\n",
       "      <th>remaining_min</th>\n",
       "      <th>power_of_shot</th>\n",
       "      <th>knockout_match</th>\n",
       "      <th>remaining_sec</th>\n",
       "      <th>distance_of_shot</th>\n",
       "      <th>is_goal</th>\n",
       "      <th>area_of_shot</th>\n",
       "      <th>shot_basics</th>\n",
       "      <th>range_of_shot</th>\n",
       "      <th>home/away</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29236.000000</td>\n",
       "      <td>29157.000000</td>\n",
       "      <td>29135.000000</td>\n",
       "      <td>29211.000000</td>\n",
       "      <td>29180.000000</td>\n",
       "      <td>29103.000000</td>\n",
       "      <td>29130.000000</td>\n",
       "      <td>24429.000000</td>\n",
       "      <td>29195</td>\n",
       "      <td>29122</td>\n",
       "      <td>29133</td>\n",
       "      <td>29200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\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>6</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\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>Center(C)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>Less Than 8 ft.</td>\n",
       "      <td>MANU @ SAS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\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>12761</td>\n",
       "      <td>11955</td>\n",
       "      <td>8933</td>\n",
       "      <td>971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.383876</td>\n",
       "      <td>91.126933</td>\n",
       "      <td>4.883233</td>\n",
       "      <td>2.519359</td>\n",
       "      <td>0.145956</td>\n",
       "      <td>28.329382</td>\n",
       "      <td>33.448884</td>\n",
       "      <td>0.445331</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>110.263049</td>\n",
       "      <td>87.676395</td>\n",
       "      <td>3.452533</td>\n",
       "      <td>1.153976</td>\n",
       "      <td>0.353068</td>\n",
       "      <td>17.470663</td>\n",
       "      <td>9.369656</td>\n",
       "      <td>0.497013</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-250.000000</td>\n",
       "      <td>-44.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-68.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</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>0.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0.000000</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>95.000000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</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>248.000000</td>\n",
       "      <td>791.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          location_x    location_y  remaining_min  power_of_shot  \\\n",
       "count   29236.000000  29157.000000   29135.000000   29211.000000   \n",
       "unique           NaN           NaN            NaN            NaN   \n",
       "top              NaN           NaN            NaN            NaN   \n",
       "freq             NaN           NaN            NaN            NaN   \n",
       "mean        7.383876     91.126933       4.883233       2.519359   \n",
       "std       110.263049     87.676395       3.452533       1.153976   \n",
       "min      -250.000000    -44.000000       0.000000       1.000000   \n",
       "25%       -68.000000      4.000000       2.000000       1.000000   \n",
       "50%         0.000000     74.000000       5.000000       3.000000   \n",
       "75%        95.000000    160.000000       8.000000       3.000000   \n",
       "max       248.000000    791.000000      11.000000       7.000000   \n",
       "\n",
       "        knockout_match  remaining_sec  distance_of_shot       is_goal  \\\n",
       "count     29180.000000   29103.000000      29130.000000  24429.000000   \n",
       "unique             NaN            NaN               NaN           NaN   \n",
       "top                NaN            NaN               NaN           NaN   \n",
       "freq               NaN            NaN               NaN           NaN   \n",
       "mean          0.145956      28.329382         33.448884      0.445331   \n",
       "std           0.353068      17.470663          9.369656      0.497013   \n",
       "min           0.000000       0.000000         20.000000      0.000000   \n",
       "25%           0.000000      13.000000         25.000000      0.000000   \n",
       "50%           0.000000      28.000000         35.000000      0.000000   \n",
       "75%           0.000000      43.000000         41.000000      1.000000   \n",
       "max           1.000000      59.000000         99.000000      1.000000   \n",
       "\n",
       "       area_of_shot shot_basics    range_of_shot   home/away  \n",
       "count         29195       29122            29133       29200  \n",
       "unique            6           7                5          74  \n",
       "top       Center(C)   Mid Range  Less Than 8 ft.  MANU @ SAS  \n",
       "freq          12761       11955             8933         971  \n",
       "mean            NaN         NaN              NaN         NaN  \n",
       "std             NaN         NaN              NaN         NaN  \n",
       "min             NaN         NaN              NaN         NaN  \n",
       "25%             NaN         NaN              NaN         NaN  \n",
       "50%             NaN         NaN              NaN         NaN  \n",
       "75%             NaN         NaN              NaN         NaN  \n",
       "max             NaN         NaN              NaN         NaN  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Mid Range          11955\n",
       "Goal Area           6787\n",
       "Penalty Spot        5321\n",
       "Goal Line           4357\n",
       "Right Corner         367\n",
       "Left Corner          268\n",
       "Mid Ground Line       67\n",
       "Name: shot_basics, dtype: int64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['shot_basics'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Less Than 8 ft.    8933\n",
       "16-24 ft.          7892\n",
       "8-16 ft.           6290\n",
       "24+ ft.            5937\n",
       "Back Court Shot      81\n",
       "Name: range_of_shot, dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['range_of_shot'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Center(C)                12761\n",
       "Right Side Center(RC)     4562\n",
       "Right Side(R)             4370\n",
       "Left Side Center(LC)      3848\n",
       "Left Side(L)              3573\n",
       "Mid Ground(MG)              81\n",
       "Name: area_of_shot, dtype: int64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['area_of_shot'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "location_x          1461\n",
       "location_y          1540\n",
       "remaining_min       1562\n",
       "power_of_shot       1486\n",
       "knockout_match      1517\n",
       "remaining_sec       1594\n",
       "distance_of_shot    1567\n",
       "is_goal             6268\n",
       "area_of_shot        1502\n",
       "shot_basics         1575\n",
       "range_of_shot       1564\n",
       "home/away           1497\n",
       "dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location_x</th>\n",
       "      <th>location_y</th>\n",
       "      <th>remaining_min</th>\n",
       "      <th>power_of_shot</th>\n",
       "      <th>knockout_match</th>\n",
       "      <th>remaining_sec</th>\n",
       "      <th>distance_of_shot</th>\n",
       "      <th>is_goal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29236.000000</td>\n",
       "      <td>29157.000000</td>\n",
       "      <td>29135.000000</td>\n",
       "      <td>29211.000000</td>\n",
       "      <td>29180.000000</td>\n",
       "      <td>29103.000000</td>\n",
       "      <td>29130.000000</td>\n",
       "      <td>24429.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.383876</td>\n",
       "      <td>91.126933</td>\n",
       "      <td>4.883233</td>\n",
       "      <td>2.519359</td>\n",
       "      <td>0.145956</td>\n",
       "      <td>28.329382</td>\n",
       "      <td>33.448884</td>\n",
       "      <td>0.445331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>110.263049</td>\n",
       "      <td>87.676395</td>\n",
       "      <td>3.452533</td>\n",
       "      <td>1.153976</td>\n",
       "      <td>0.353068</td>\n",
       "      <td>17.470663</td>\n",
       "      <td>9.369656</td>\n",
       "      <td>0.497013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-250.000000</td>\n",
       "      <td>-44.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-68.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>95.000000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>248.000000</td>\n",
       "      <td>791.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         location_x    location_y  remaining_min  power_of_shot  \\\n",
       "count  29236.000000  29157.000000   29135.000000   29211.000000   \n",
       "mean       7.383876     91.126933       4.883233       2.519359   \n",
       "std      110.263049     87.676395       3.452533       1.153976   \n",
       "min     -250.000000    -44.000000       0.000000       1.000000   \n",
       "25%      -68.000000      4.000000       2.000000       1.000000   \n",
       "50%        0.000000     74.000000       5.000000       3.000000   \n",
       "75%       95.000000    160.000000       8.000000       3.000000   \n",
       "max      248.000000    791.000000      11.000000       7.000000   \n",
       "\n",
       "       knockout_match  remaining_sec  distance_of_shot       is_goal  \n",
       "count    29180.000000   29103.000000      29130.000000  24429.000000  \n",
       "mean         0.145956      28.329382         33.448884      0.445331  \n",
       "std          0.353068      17.470663          9.369656      0.497013  \n",
       "min          0.000000       0.000000         20.000000      0.000000  \n",
       "25%          0.000000      13.000000         25.000000      0.000000  \n",
       "50%          0.000000      28.000000         35.000000      0.000000  \n",
       "75%          0.000000      43.000000         41.000000      1.000000  \n",
       "max          1.000000      59.000000         99.000000      1.000000  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Filling the reamining missing values:\n",
    "\n",
    "data['location_x'].fillna(data['location_x'].mean(), inplace=True)\n",
    "data['location_y'].fillna(data['location_y'].mean(), inplace=True)\n",
    "data['remaining_min'].fillna(data['remaining_min'].mean(), inplace=True)\n",
    "data['power_of_shot'].fillna(data['power_of_shot'].median(), inplace=True)\n",
    "data['knockout_match'].fillna(data['knockout_match'].median(), inplace=True)\n",
    "data['remaining_sec'].fillna(data['remaining_sec'].mean(), inplace=True)\n",
    "data['distance_of_shot'].fillna(data['distance_of_shot'].mean(), inplace=True)\n",
    "data['shot_basics'].fillna(value='Mid Range', inplace=True)\n",
    "data['range_of_shot'].fillna(value='Less Than 8 ft.', inplace=True)\n",
    "data['area_of_shot'].fillna(value='Center(C)', inplace=True)\n",
    "data['home/away'].fillna(value='MANU @ SAS', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "location_x             0\n",
       "location_y             0\n",
       "remaining_min          0\n",
       "power_of_shot          0\n",
       "knockout_match         0\n",
       "remaining_sec          0\n",
       "distance_of_shot       0\n",
       "is_goal             6268\n",
       "area_of_shot           0\n",
       "shot_basics            0\n",
       "range_of_shot          0\n",
       "home/away              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Transforming the feature 'home/away' into a categorical variable having values only 'home' and 'away' :\n",
    "\n",
    "for i in range(data.shape[0]):\n",
    "    if('@' in data.loc[i,'home/away']):\n",
    "        data.loc[i,'home/away']='away'\n",
    "        \n",
    "    if('vs' in data.loc[i,'home/away']):\n",
    "        data.loc[i,'home/away']='home'\n",
    "    \n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location_x</th>\n",
       "      <th>location_y</th>\n",
       "      <th>remaining_min</th>\n",
       "      <th>power_of_shot</th>\n",
       "      <th>knockout_match</th>\n",
       "      <th>remaining_sec</th>\n",
       "      <th>distance_of_shot</th>\n",
       "      <th>is_goal</th>\n",
       "      <th>area_of_shot</th>\n",
       "      <th>shot_basics</th>\n",
       "      <th>range_of_shot</th>\n",
       "      <th>home/away</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>167.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Right Side(R)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>away</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-157.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Left Side(L)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>8-16 ft.</td>\n",
       "      <td>away</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-101.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Left Side Center(LC)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>away</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>138.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Right Side Center(RC)</td>\n",
       "      <td>Mid Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>away</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.883233</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Center(C)</td>\n",
       "      <td>Goal Area</td>\n",
       "      <td>Less Than 8 ft.</td>\n",
       "      <td>away</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   location_x  location_y  remaining_min  power_of_shot  knockout_match  \\\n",
       "0       167.0        72.0      10.000000            1.0             0.0   \n",
       "1      -157.0         0.0      10.000000            1.0             0.0   \n",
       "2      -101.0       135.0       7.000000            1.0             0.0   \n",
       "3       138.0       175.0       6.000000            1.0             0.0   \n",
       "4         0.0         0.0       4.883233            2.0             0.0   \n",
       "\n",
       "   remaining_sec  distance_of_shot  is_goal           area_of_shot  \\\n",
       "0           27.0              38.0      NaN          Right Side(R)   \n",
       "1           22.0              35.0      0.0           Left Side(L)   \n",
       "2           45.0              36.0      1.0   Left Side Center(LC)   \n",
       "3           52.0              42.0      0.0  Right Side Center(RC)   \n",
       "4           19.0              20.0      1.0              Center(C)   \n",
       "\n",
       "  shot_basics    range_of_shot home/away  \n",
       "0   Mid Range        16-24 ft.      away  \n",
       "1   Mid Range         8-16 ft.      away  \n",
       "2   Mid Range        16-24 ft.      away  \n",
       "3   Mid Range        16-24 ft.      away  \n",
       "4   Goal Area  Less Than 8 ft.      away  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Splitting the data into train and test dataset:\n",
    "\n",
    "test=data[data['is_goal'].isnull()]\n",
    "train=data[data['is_goal'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "location_x          float64\n",
       "location_y          float64\n",
       "remaining_min       float64\n",
       "power_of_shot       float64\n",
       "knockout_match      float64\n",
       "remaining_sec       float64\n",
       "distance_of_shot    float64\n",
       "is_goal             float64\n",
       "area_of_shot         object\n",
       "shot_basics          object\n",
       "range_of_shot        object\n",
       "home/away            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['location_x', 'location_y', 'remaining_min', 'power_of_shot',\n",
       "       'knockout_match', 'remaining_sec', 'distance_of_shot', 'is_goal',\n",
       "       'area_of_shot', 'shot_basics', 'range_of_shot', 'home/away'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "### PREPARING y, X AND X_test:\n",
    "\n",
    "y=train['is_goal'].values\n",
    "\n",
    "X=train[['location_x', 'location_y', 'remaining_min', 'power_of_shot','knockout_match', 'remaining_sec', 'distance_of_shot','area_of_shot', 'shot_basics', 'range_of_shot', 'home/away']].values\n",
    "X_test=test[['location_x', 'location_y', 'remaining_min', 'power_of_shot','knockout_match', 'remaining_sec', 'distance_of_shot','area_of_shot', 'shot_basics', 'range_of_shot', 'home/away']].values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "### LABEL ENCODING:\n",
    "\n",
    "area_of_shot=preprocessing.LabelEncoder()\n",
    "shot_basics=preprocessing.LabelEncoder()\n",
    "range_of_shot=preprocessing.LabelEncoder()\n",
    "last=preprocessing.LabelEncoder()\n",
    "\n",
    "## FOR Area_of_shot:\n",
    "\n",
    "area_of_shot.fit(['Mid Ground(MG)','Right Side(R)', 'Left Side(L)', 'Left Side Center(LC)','Right Side Center(RC)', 'Center(C)'])\n",
    "\n",
    "X[:,-4]=area_of_shot.transform(X[:,-4])\n",
    "X_test[:,-4]=area_of_shot.transform(X_test[:,-4])\n",
    "\n",
    "\n",
    "## FOR Shot_basics:\n",
    "\n",
    "shot_basics.fit(['Mid Range','Mid Ground Line', 'Right Corner', 'Left Corner' ,'Goal Area', 'Goal Line', 'Penalty Spot'])\n",
    "\n",
    "X[:,-3]=shot_basics.transform(X[:,-3])\n",
    "X_test[:,-3]=shot_basics.transform(X_test[:,-3])\n",
    "\n",
    "\n",
    "## FOR Range_of_shot:\n",
    "\n",
    "range_of_shot.fit(['Back Court Shot','24+ ft.','16-24 ft.', '8-16 ft.', 'Less Than 8 ft.'])\n",
    "\n",
    "X[:,-2]=range_of_shot.transform(X[:,-2])\n",
    "X_test[:,-2]=range_of_shot.transform(X_test[:,-2])\n",
    "\n",
    "## FOR last column:\n",
    "\n",
    "last.fit(['away','home'])\n",
    "\n",
    "X[:,-1]=last.transform(X[:,-1])\n",
    "X_test[:,-1]=last.transform(X_test[:,-1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "### STANDARDISING X AND X_TEST:\n",
    "\n",
    "\n",
    "X_=preprocessing.StandardScaler().fit(X).transform(X)\n",
    "X_test_=preprocessing.StandardScaler().fit(X_test).transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "### TEST TRAIN SPLIT:\n",
    "\n",
    "x_train,x_test_,Y_train,Y_test=train_test_split(X_,y,test_size=0.3,random_state=0) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "59.216809933142315"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### LOGISTIC REGRESSION:\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "lr=LogisticRegression(C=5, solver='liblinear').fit(x_train,Y_train)\n",
    "\n",
    "yhat=lr.predict(x_test_)\n",
    "\n",
    "acc(Y_test,yhat)*100\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "59.46240960567608"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# KNN:\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "k=1000\n",
    "\n",
    "\n",
    "neigh=KNeighborsClassifier(n_neighbors=k).fit(x_train,Y_train)\n",
    "\n",
    "yhat1=neigh.predict(x_test_)\n",
    "\n",
    "acc(Y_test,yhat1)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "59.91267567198799"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### SVM (RBF)\n",
    "\n",
    "from sklearn import svm\n",
    "\n",
    "clf3=svm.SVC(kernel='rbf',gamma=0.05, C=8, probability=True)\n",
    "\n",
    "\n",
    "clf3.fit(x_train,Y_train)\n",
    "\n",
    "yhat3=clf3.predict(x_test_)\n",
    "\n",
    "(acc(Y_test,yhat3))*100\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "59.9672533769955"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### DECISION TREE:\n",
    "\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "tree=DecisionTreeClassifier(criterion='entropy', max_depth=4)\n",
    "\n",
    "\n",
    "\n",
    "tree.fit(x_train,Y_train)\n",
    "\n",
    "yhat2=tree.predict(x_test_)\n",
    "\n",
    "acc(Y_test,yhat2)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['bootstrap', 'class_weight', 'criterion', 'max_depth', 'max_features', 'max_leaf_nodes', 'min_impurity_decrease', 'min_impurity_split', 'min_samples_leaf', 'min_samples_split', 'min_weight_fraction_leaf', 'n_estimators', 'n_jobs', 'oob_score', 'random_state', 'verbose', 'warm_start'])"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### RANDOM FOREST CLASSIFIER\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import make_scorer, accuracy_score\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# Choose the type of classifier. \n",
    "rnd = RandomForestClassifier()\n",
    "\n",
    "\n",
    "### TO GET PARAMETERS OF ANY MODEL:\n",
    "\n",
    "rnd.get_params().keys()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Akshat Singhal\\Anaconda3\\lib\\site-packages\\sklearn\\model_selection\\_split.py:1978: FutureWarning: The default value of cv will change from 3 to 5 in version 0.22. Specify it explicitly to silence this warning.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "60.06276436075863"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### GRIDSEARCH + RANDOM FOREST CLASSIFIER:\n",
    "\n",
    "\n",
    "# Choose some parameter combinations to try\n",
    "parameters = {'n_estimators': [4, 6, 9], \n",
    "              'max_features': ['log2', 'sqrt','auto'], \n",
    "              'criterion': ['entropy', 'gini'],\n",
    "              'max_depth': [2, 3,5, 6, 10], \n",
    "              'min_samples_split': [2, 3, 5],\n",
    "              'min_samples_leaf': [1,5,8]\n",
    "             }\n",
    "\n",
    "# Type of scoring used to compare parameter combinations\n",
    "acc_scorer = make_scorer(accuracy_score)\n",
    "\n",
    "# Run the grid search\n",
    "grid_obj = GridSearchCV(rnd, parameters, scoring=acc_scorer)\n",
    "grid_obj = grid_obj.fit(x_train, Y_train)\n",
    "\n",
    "# Set the clf to the best combination of parameters\n",
    "rnd = grid_obj.best_estimator_  \n",
    "\n",
    "# Fit the best algorithm to the data. \n",
    "rnd.fit(x_train, Y_train)\n",
    "\n",
    "yhat7=rnd.predict(x_test_)\n",
    "\n",
    "(acc(Y_test,yhat7))*100\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "59.91267567198799"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### VOTING CLASSIFIER(ENSEMBLE)\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import VotingClassifier\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "\n",
    "\n",
    "voting_clf=VotingClassifier(estimators=[('lr',lr),('rf', rnd),('dt',tree),('knn',neigh),('rbf',clf3)], voting='soft')\n",
    "\n",
    "voting_clf.fit(x_train,Y_train)\n",
    "\n",
    "yhat6=voting_clf.predict(x_test_)\n",
    "\n",
    "(acc(Y_test,yhat6))*100\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Note: As the maximum accuracy is achieved by using Random Forest model, hence using it to train the whole dataset and for final prediction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "### TRAINING ON FULL GIVEN DATASET\n",
    "\n",
    "# WITH Random Forest:\n",
    "\n",
    "rnd.fit(X_,y)\n",
    "\n",
    "\n",
    "yhat_test=rnd.predict_proba(X_test_)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "yhat_test=yhat_test[:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(yhat_test)\n",
    "df.columns=['is_goal']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6268, 1)"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub=pd.read_csv('sample_submission.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub['is_goal']=df['is_goal']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub.to_csv('submission-13.csv')"
   ]
  }
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