ismail_eda.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "57ae5336",
   "metadata": {},
   "source": [
    "# EDA "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5c04d838",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd \n",
    "pd.set_option(\"display.max_columns\", None)\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import cross_val_score, train_test_split\n",
    "from sklearn.metrics import mean_squared_error, accuracy_score\n",
    "\n",
    "from statsmodels.genmod.generalized_linear_model import GLM\n",
    "import statsmodels.api as sm\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b1032ce3",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 30697 entries, 0 to 30696\n",
      "Data columns (total 25 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   action_type         30697 non-null  object \n",
      " 1   combined_shot_type  30697 non-null  object \n",
      " 2   game_event_id       30697 non-null  int64  \n",
      " 3   game_id             30697 non-null  int64  \n",
      " 4   lat                 30697 non-null  float64\n",
      " 5   loc_x               30697 non-null  int64  \n",
      " 6   loc_y               30697 non-null  int64  \n",
      " 7   lon                 30697 non-null  float64\n",
      " 8   minutes_remaining   30697 non-null  int64  \n",
      " 9   period              30697 non-null  int64  \n",
      " 10  playoffs            30697 non-null  int64  \n",
      " 11  season              30697 non-null  object \n",
      " 12  seconds_remaining   30697 non-null  int64  \n",
      " 13  shot_distance       30697 non-null  int64  \n",
      " 14  shot_made_flag      25697 non-null  float64\n",
      " 15  shot_type           30697 non-null  object \n",
      " 16  shot_zone_area      30697 non-null  object \n",
      " 17  shot_zone_basic     30697 non-null  object \n",
      " 18  shot_zone_range     30697 non-null  object \n",
      " 19  team_id             30697 non-null  int64  \n",
      " 20  team_name           30697 non-null  object \n",
      " 21  game_date           30697 non-null  object \n",
      " 22  matchup             30697 non-null  object \n",
      " 23  opponent            30697 non-null  object \n",
      " 24  shot_id             30697 non-null  int64  \n",
      "dtypes: float64(3), int64(11), object(11)\n",
      "memory usage: 5.9+ MB\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('data/data.csv')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b62a55f9",
   "metadata": {},
   "source": [
    "***\n",
    "## SECTION 1: BASIC INSPECTION OF THE DATASET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b61b367b",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(30697, 25)\n"
     ]
    },
    {
     "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>action_type</th>\n",
       "      <th>combined_shot_type</th>\n",
       "      <th>game_event_id</th>\n",
       "      <th>game_id</th>\n",
       "      <th>lat</th>\n",
       "      <th>loc_x</th>\n",
       "      <th>loc_y</th>\n",
       "      <th>lon</th>\n",
       "      <th>minutes_remaining</th>\n",
       "      <th>period</th>\n",
       "      <th>playoffs</th>\n",
       "      <th>season</th>\n",
       "      <th>seconds_remaining</th>\n",
       "      <th>shot_distance</th>\n",
       "      <th>shot_made_flag</th>\n",
       "      <th>shot_type</th>\n",
       "      <th>shot_zone_area</th>\n",
       "      <th>shot_zone_basic</th>\n",
       "      <th>shot_zone_range</th>\n",
       "      <th>team_id</th>\n",
       "      <th>team_name</th>\n",
       "      <th>game_date</th>\n",
       "      <th>matchup</th>\n",
       "      <th>opponent</th>\n",
       "      <th>shot_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>3.069700e+04</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>30697.000000</td>\n",
       "      <td>25697.000000</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>3.069700e+04</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697</td>\n",
       "      <td>30697.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>57</td>\n",
       "      <td>6</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>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1559</td>\n",
       "      <td>74</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</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>2005-06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Center(C)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>Less Than 8 ft.</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Los Angeles Lakers</td>\n",
       "      <td>2016-04-13</td>\n",
       "      <td>LAL @ SAS</td>\n",
       "      <td>SAS</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>18880</td>\n",
       "      <td>23485</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>2318</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24271</td>\n",
       "      <td>13455</td>\n",
       "      <td>12625</td>\n",
       "      <td>9398</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30697</td>\n",
       "      <td>50</td>\n",
       "      <td>1020</td>\n",
       "      <td>1978</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>249.190800</td>\n",
       "      <td>3.562192e+07</td>\n",
       "      <td>33.953192</td>\n",
       "      <td>7.110499</td>\n",
       "      <td>91.107535</td>\n",
       "      <td>-118.262690</td>\n",
       "      <td>4.885624</td>\n",
       "      <td>2.519432</td>\n",
       "      <td>0.146562</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.365085</td>\n",
       "      <td>13.437437</td>\n",
       "      <td>0.446161</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15349.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.003712</td>\n",
       "      <td>1.902401e+09</td>\n",
       "      <td>0.087791</td>\n",
       "      <td>110.124578</td>\n",
       "      <td>87.791361</td>\n",
       "      <td>0.110125</td>\n",
       "      <td>3.449897</td>\n",
       "      <td>1.153665</td>\n",
       "      <td>0.353674</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.478949</td>\n",
       "      <td>9.374189</td>\n",
       "      <td>0.497103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8861.604943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000001e+07</td>\n",
       "      <td>33.253300</td>\n",
       "      <td>-250.000000</td>\n",
       "      <td>-44.000000</td>\n",
       "      <td>-118.519800</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>2.050008e+07</td>\n",
       "      <td>33.884300</td>\n",
       "      <td>-68.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>-118.337800</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7675.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>253.000000</td>\n",
       "      <td>2.090035e+07</td>\n",
       "      <td>33.970300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>-118.269800</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15349.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>368.000000</td>\n",
       "      <td>2.960047e+07</td>\n",
       "      <td>34.040300</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>-118.174800</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23023.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>659.000000</td>\n",
       "      <td>3.333333e+11</td>\n",
       "      <td>34.088300</td>\n",
       "      <td>248.000000</td>\n",
       "      <td>791.000000</td>\n",
       "      <td>-118.021800</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30697.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       action_type combined_shot_type  game_event_id       game_id  \\\n",
       "count        30697              30697   30697.000000  3.069700e+04   \n",
       "unique          57                  6            NaN           NaN   \n",
       "top      Jump Shot          Jump Shot            NaN           NaN   \n",
       "freq         18880              23485            NaN           NaN   \n",
       "mean           NaN                NaN     249.190800  3.562192e+07   \n",
       "std            NaN                NaN     150.003712  1.902401e+09   \n",
       "min            NaN                NaN       2.000000  2.000001e+07   \n",
       "25%            NaN                NaN     110.000000  2.050008e+07   \n",
       "50%            NaN                NaN     253.000000  2.090035e+07   \n",
       "75%            NaN                NaN     368.000000  2.960047e+07   \n",
       "max            NaN                NaN     659.000000  3.333333e+11   \n",
       "\n",
       "                 lat         loc_x         loc_y           lon  \\\n",
       "count   30697.000000  30697.000000  30697.000000  30697.000000   \n",
       "unique           NaN           NaN           NaN           NaN   \n",
       "top              NaN           NaN           NaN           NaN   \n",
       "freq             NaN           NaN           NaN           NaN   \n",
       "mean       33.953192      7.110499     91.107535   -118.262690   \n",
       "std         0.087791    110.124578     87.791361      0.110125   \n",
       "min        33.253300   -250.000000    -44.000000   -118.519800   \n",
       "25%        33.884300    -68.000000      4.000000   -118.337800   \n",
       "50%        33.970300      0.000000     74.000000   -118.269800   \n",
       "75%        34.040300     95.000000    160.000000   -118.174800   \n",
       "max        34.088300    248.000000    791.000000   -118.021800   \n",
       "\n",
       "        minutes_remaining        period      playoffs   season  \\\n",
       "count        30697.000000  30697.000000  30697.000000    30697   \n",
       "unique                NaN           NaN           NaN       20   \n",
       "top                   NaN           NaN           NaN  2005-06   \n",
       "freq                  NaN           NaN           NaN     2318   \n",
       "mean             4.885624      2.519432      0.146562      NaN   \n",
       "std              3.449897      1.153665      0.353674      NaN   \n",
       "min              0.000000      1.000000      0.000000      NaN   \n",
       "25%              2.000000      1.000000      0.000000      NaN   \n",
       "50%              5.000000      3.000000      0.000000      NaN   \n",
       "75%              8.000000      3.000000      0.000000      NaN   \n",
       "max             11.000000      7.000000      1.000000      NaN   \n",
       "\n",
       "        seconds_remaining  shot_distance  shot_made_flag       shot_type  \\\n",
       "count        30697.000000   30697.000000    25697.000000           30697   \n",
       "unique                NaN            NaN             NaN               2   \n",
       "top                   NaN            NaN             NaN  2PT Field Goal   \n",
       "freq                  NaN            NaN             NaN           24271   \n",
       "mean            28.365085      13.437437        0.446161             NaN   \n",
       "std             17.478949       9.374189        0.497103             NaN   \n",
       "min              0.000000       0.000000        0.000000             NaN   \n",
       "25%             13.000000       5.000000        0.000000             NaN   \n",
       "50%             28.000000      15.000000        0.000000             NaN   \n",
       "75%             43.000000      21.000000        1.000000             NaN   \n",
       "max             59.000000      79.000000        1.000000             NaN   \n",
       "\n",
       "       shot_zone_area shot_zone_basic  shot_zone_range       team_id  \\\n",
       "count           30697           30697            30697  3.069700e+04   \n",
       "unique              6               7                5           NaN   \n",
       "top         Center(C)       Mid-Range  Less Than 8 ft.           NaN   \n",
       "freq            13455           12625             9398           NaN   \n",
       "mean              NaN             NaN              NaN  1.610613e+09   \n",
       "std               NaN             NaN              NaN  0.000000e+00   \n",
       "min               NaN             NaN              NaN  1.610613e+09   \n",
       "25%               NaN             NaN              NaN  1.610613e+09   \n",
       "50%               NaN             NaN              NaN  1.610613e+09   \n",
       "75%               NaN             NaN              NaN  1.610613e+09   \n",
       "max               NaN             NaN              NaN  1.610613e+09   \n",
       "\n",
       "                 team_name   game_date    matchup opponent       shot_id  \n",
       "count                30697       30697      30697    30697  30697.000000  \n",
       "unique                   1        1559         74       33           NaN  \n",
       "top     Los Angeles Lakers  2016-04-13  LAL @ SAS      SAS           NaN  \n",
       "freq                 30697          50       1020     1978           NaN  \n",
       "mean                   NaN         NaN        NaN      NaN  15349.000000  \n",
       "std                    NaN         NaN        NaN      NaN   8861.604943  \n",
       "min                    NaN         NaN        NaN      NaN      1.000000  \n",
       "25%                    NaN         NaN        NaN      NaN   7675.000000  \n",
       "50%                    NaN         NaN        NaN      NaN  15349.000000  \n",
       "75%                    NaN         NaN        NaN      NaN  23023.000000  \n",
       "max                    NaN         NaN        NaN      NaN  30697.000000  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df.shape)\n",
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "59c0dfbf",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "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>action_type</th>\n",
       "      <th>combined_shot_type</th>\n",
       "      <th>game_event_id</th>\n",
       "      <th>game_id</th>\n",
       "      <th>lat</th>\n",
       "      <th>loc_x</th>\n",
       "      <th>loc_y</th>\n",
       "      <th>lon</th>\n",
       "      <th>minutes_remaining</th>\n",
       "      <th>period</th>\n",
       "      <th>playoffs</th>\n",
       "      <th>season</th>\n",
       "      <th>seconds_remaining</th>\n",
       "      <th>shot_distance</th>\n",
       "      <th>shot_made_flag</th>\n",
       "      <th>shot_type</th>\n",
       "      <th>shot_zone_area</th>\n",
       "      <th>shot_zone_basic</th>\n",
       "      <th>shot_zone_range</th>\n",
       "      <th>team_id</th>\n",
       "      <th>team_name</th>\n",
       "      <th>game_date</th>\n",
       "      <th>matchup</th>\n",
       "      <th>opponent</th>\n",
       "      <th>shot_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>10</td>\n",
       "      <td>20000012</td>\n",
       "      <td>33.9723</td>\n",
       "      <td>167</td>\n",
       "      <td>72</td>\n",
       "      <td>-118.1028</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>27</td>\n",
       "      <td>18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Right Side(R)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>Los Angeles Lakers</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>12</td>\n",
       "      <td>20000012</td>\n",
       "      <td>34.0443</td>\n",
       "      <td>-157</td>\n",
       "      <td>0</td>\n",
       "      <td>-118.4268</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>22</td>\n",
       "      <td>15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Left Side(L)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>8-16 ft.</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>Los Angeles Lakers</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>35</td>\n",
       "      <td>20000012</td>\n",
       "      <td>33.9093</td>\n",
       "      <td>-101</td>\n",
       "      <td>135</td>\n",
       "      <td>-118.3708</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>45</td>\n",
       "      <td>16</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Left Side Center(LC)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>Los Angeles Lakers</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>43</td>\n",
       "      <td>20000012</td>\n",
       "      <td>33.8693</td>\n",
       "      <td>138</td>\n",
       "      <td>175</td>\n",
       "      <td>-118.1318</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>52</td>\n",
       "      <td>22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Right Side Center(RC)</td>\n",
       "      <td>Mid-Range</td>\n",
       "      <td>16-24 ft.</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>Los Angeles Lakers</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Driving Dunk Shot</td>\n",
       "      <td>Dunk</td>\n",
       "      <td>155</td>\n",
       "      <td>20000012</td>\n",
       "      <td>34.0443</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-118.2698</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2000-01</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2PT Field Goal</td>\n",
       "      <td>Center(C)</td>\n",
       "      <td>Restricted Area</td>\n",
       "      <td>Less Than 8 ft.</td>\n",
       "      <td>1610612747</td>\n",
       "      <td>Los Angeles Lakers</td>\n",
       "      <td>2000-10-31</td>\n",
       "      <td>LAL @ POR</td>\n",
       "      <td>POR</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         action_type combined_shot_type  game_event_id   game_id      lat  \\\n",
       "0          Jump Shot          Jump Shot             10  20000012  33.9723   \n",
       "1          Jump Shot          Jump Shot             12  20000012  34.0443   \n",
       "2          Jump Shot          Jump Shot             35  20000012  33.9093   \n",
       "3          Jump Shot          Jump Shot             43  20000012  33.8693   \n",
       "4  Driving Dunk Shot               Dunk            155  20000012  34.0443   \n",
       "\n",
       "   loc_x  loc_y       lon  minutes_remaining  period  playoffs   season  \\\n",
       "0    167     72 -118.1028                 10       1         0  2000-01   \n",
       "1   -157      0 -118.4268                 10       1         0  2000-01   \n",
       "2   -101    135 -118.3708                  7       1         0  2000-01   \n",
       "3    138    175 -118.1318                  6       1         0  2000-01   \n",
       "4      0      0 -118.2698                  6       2         0  2000-01   \n",
       "\n",
       "   seconds_remaining  shot_distance  shot_made_flag       shot_type  \\\n",
       "0                 27             18             NaN  2PT Field Goal   \n",
       "1                 22             15             0.0  2PT Field Goal   \n",
       "2                 45             16             1.0  2PT Field Goal   \n",
       "3                 52             22             0.0  2PT Field Goal   \n",
       "4                 19              0             1.0  2PT Field Goal   \n",
       "\n",
       "          shot_zone_area  shot_zone_basic  shot_zone_range     team_id  \\\n",
       "0          Right Side(R)        Mid-Range        16-24 ft.  1610612747   \n",
       "1           Left Side(L)        Mid-Range         8-16 ft.  1610612747   \n",
       "2   Left Side Center(LC)        Mid-Range        16-24 ft.  1610612747   \n",
       "3  Right Side Center(RC)        Mid-Range        16-24 ft.  1610612747   \n",
       "4              Center(C)  Restricted Area  Less Than 8 ft.  1610612747   \n",
       "\n",
       "            team_name   game_date    matchup opponent  shot_id  \n",
       "0  Los Angeles Lakers  2000-10-31  LAL @ POR      POR        1  \n",
       "1  Los Angeles Lakers  2000-10-31  LAL @ POR      POR        2  \n",
       "2  Los Angeles Lakers  2000-10-31  LAL @ POR      POR        3  \n",
       "3  Los Angeles Lakers  2000-10-31  LAL @ POR      POR        4  \n",
       "4  Los Angeles Lakers  2000-10-31  LAL @ POR      POR        5  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "525d97ab",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Section 2: Removing Redundant Columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "566a4399",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "There are some columns that have very high corelations with some other columns and some columns that\n",
    "\n",
    "Removing columns:\n",
    "- team_name, team_id - These have only a single value, so it doesn't add any value to the prediction\n",
    "- shot_id "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3bd1134c",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total columns removed: 3\n"
     ]
    }
   ],
   "source": [
    "columns_to_drop = ['team_name', 'team_id', 'shot_id']\n",
    "df = df.drop(labels=columns_to_drop, axis='columns')\n",
    "print(f\"Total columns removed: {len(columns_to_drop)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cf98b2d",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Section 3: Dealing With Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4284caa7",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rows: 30697\n",
      "Number of rows after dropping missing values: 25697\n",
      "Percentage of data removed: 16.28823663550184 %\n"
     ]
    }
   ],
   "source": [
    "def remove_na_rows(df: pd.DataFrame):\n",
    "    \"\"\"\n",
    "    :param pd.DataFrame df:\n",
    "    :return pd.DataFrame\n",
    "    \"\"\"\n",
    "    num_rows_before = len(df)\n",
    "    print(f'Number of rows: {num_rows_before}')\n",
    "    df = df.dropna()\n",
    "    num_rows_after = len(df)\n",
    "    print(f'Number of rows after dropping missing values: {num_rows_after}')\n",
    "    removed_rows = num_rows_before - num_rows_after\n",
    "    print(f'Percentage of data removed: {100 * (removed_rows/num_rows_before)} %')\n",
    "    return df\n",
    "\n",
    "df = remove_na_rows(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "816b47b2",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Section 4: Outlier detection\n",
    "From our analysis of the above data (mostly looking at mean, min, max) we can see that most likely there no outliers. But still we will have a thorough look at all the columns to understand them and confirm that there is no outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "181ba84a",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of the df: (25697, 22)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['action_type', 'combined_shot_type', 'game_event_id', 'game_id', 'lat',\n",
       "       'loc_x', 'loc_y', 'lon', 'minutes_remaining', 'period', 'playoffs',\n",
       "       'season', 'seconds_remaining', 'shot_distance', 'shot_made_flag',\n",
       "       'shot_type', 'shot_zone_area', 'shot_zone_basic', 'shot_zone_range',\n",
       "       'game_date', 'matchup', 'opponent'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f\"Shape of the df: {df.shape}\")\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7b42d10c",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 4]}, figsize=(9,5))\n",
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='game_event_id',ax=axes[0]);\n",
    "df.hist(column='game_event_id', ax=axes[1]);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "6dab8083",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='game_id',ax=axes[0]);\n",
    "df.hist(column='game_id', ax=axes[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27b83cf0",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "These are not outliers, 'game_id' is unique number associated with a single match. In this case it just so happens\n",
    "that in the number system some matches an ID of very high value, but from the overall structre of the above bar chart everything looks good."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "264e4ea1",
   "metadata": {},
   "source": [
    "#### For Column: `lat`, `lon`, `loc_x`, `loc_y`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "fc3a3c6d",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='lat',ax=axes[0]);\n",
    "df.hist(column='lat', ax=axes[1]);\n",
    "\n",
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='loc_y',ax=axes[0]);\n",
    "df.hist(column='loc_y', ax=axes[1]);\n",
    "\n",
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='lon',ax=axes[0]);\n",
    "df.hist(column='lon', ax=axes[1]);\n",
    "\n",
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='loc_x',ax=axes[0]);\n",
    "df.hist(column='loc_x', ax=axes[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5763bc63",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "From this we can see that (`lat`, `lon`) and (`loc_x`, `loc_y`) present the same information just in different encoding. This allows us to drop 2 additional columns as they provide the same information.\n",
    "\n",
    "Also It looks in `lat` and `loc_y` that there might be lot of outliers, but the below diagram tell shows us that, these points are not outliers. In this case these points should be within the court boundry, if that is the case then they are not outliers, as we can see below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e7497aef",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x846.72 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "court_scale, alpha = 7, 0.05\n",
    "plt.figure(figsize=(2 * court_scale, court_scale*(84.0/50.0)))\n",
    "# hit\n",
    "plt.subplot(121)\n",
    "h = df.loc[df.shot_made_flag == 1]\n",
    "plt.scatter(h.loc_x, h.loc_y, color='green', alpha=alpha)\n",
    "plt.title('Shots Made')\n",
    "ax = plt.gca()\n",
    "ax.set_ylim([-50, 900])\n",
    "# miss\n",
    "plt.subplot(122)\n",
    "h = df.loc[df.shot_made_flag == 0]\n",
    "plt.scatter(h.loc_x, h.loc_y, color='red', alpha=alpha)\n",
    "plt.title('Shots missed')\n",
    "ax = plt.gca()\n",
    "ax.set_ylim([-50, 900])\n",
    "plt.savefig('shots_made_and_missed.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04dde5f6",
   "metadata": {},
   "source": [
    "#### For Column: `shot_distance`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2c06b06c",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='shot_distance',ax=axes[0]);\n",
    "df.hist(column='shot_distance', ax=axes[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd78bfe8",
   "metadata": {},
   "source": [
    "As we saw with `lat` and `loc_y`, there are few shots that were made far away from the hoop. So these are not outliers but rather the minority shots. \n",
    "\n",
    "We might need to normalize this column."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65bcf925",
   "metadata": {},
   "source": [
    "#### For Column: `minutes_remaining` & `seconds_remaining`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bf14cc87",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9YAAAF2CAYAAACLagB1AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAArlElEQVR4nO3df5RlZX3n+/cnNCqDjOCvStswNhM7GkwP6C0Rr95JKRFBM4HMGALhamvIdCYLvLrCXUmbO7PUGGdhMmiUMc60QmwjikRl6CsE7BCORidBRJGfOrTYXLptaJUf0hrRxu/94zxtjm3/ONW7qs45Xe/XWrVq7+c8e5/vrqfr9Pmc/exdqSokSZIkSdL++ZlRFyBJkiRJ0iQzWEuSJEmS1IHBWpIkSZKkDgzWkiRJkiR1YLCWJEmSJKkDg7UkSZIkSR0YrCVJksZAkjcn+dCo69gfSc5K8qm57itJkyL+HWtJkqTRS/Jm4BlV9X+OuhZJ0ux4xlqSJOkAkz7f50nSAvEFV5IkLSpJ/iDJliQPJ/lqkhOT/EySNUm+luTbSS5L8sSBbV6U5H8meTDJPUle09qfkOSDSb6Z5O4k/3FnoE3ymiSfTfJfkjyQ5OtJThnY59FJPt3q2AA8eeCxxyX5UKvlwSQ3JJnax3H1krwtyeeA7wH/MsmzkmxIcn871tMH+n8gyZ8n+esk25N8LsnPJvmzVu9XkjxnoP/On8/DSW5P8msDj70myWcH1ivJf0hyZ6v/PUmyH30PSnJBkm+1n9+5rf+S2Yy5JM03g7UkSVo0kjwTOBd4XlUdBrwM2AS8DjgN+CXgacADwHvaNk8H/hq4EHgKcBxwU9vlhcATgH/Ztn018NqBp3w+8FX6oflPgIt2hkbgw8CN7bG3AqsGtlvV9nsU8CTgPwD/OMQhvgpYDRwGfBPY0J7nqcAZwJ8nOWag/+nAf2w1PAL8PfDFtv4x4B0Dfb8G/B+trrcAH0qydC+1/ArwPOBfted52X70/ffAKfR/5s+lP0aSNHYM1pIkaTF5FHgscEySg6tqU1V9jX5w/X+qanNVPQK8GXhlOzP6m8DfVNVHquqHVfXtqropyUH0w+obq+rhqtoEXEA/3O50d1W9r6oeBdYBS4GpJP+CfpD8T1X1SFV9Bvh/B7b7If1A/YyqerSqbqyq7wxxfB+oqtuqagdwMrCpqv6iqnZU1ZeAjwO/PtD/8rbv7wOXA9+vqg+2ej8K/PiMdVX9VVV9o6p+VFUfBe4Ejt9LLedX1YNV9f8B19EPx7PtezrwrjYuDwDnD/EzkKQFZ7CWJEmLRlVtBN5APzhvS3JpkqcBTwcub1ORHwTuoB/Cp+ifNf7abnb3ZOBg4O6BtruBZQPr9w489/fa4uNpZ8Wr6ru7bLvTXwLXAJcm+UaSP0ly8BCHeM/A8tOB5+88pnZcZwE/O9DnvoHlf9zN+uN3riR5dZKbBvb1iwxMX9+NeweWvze4r1n0fdouxzS4LEljw2AtSZIWlar6cFW9iH7wLODt9APbKVV1+MDX46pqS3vs53azq2/RP7P89IG2fwFsGaKMrcARSQ7dZdudNf6wqt5SVccA/zv9qdKvHubwBpbvAT69yzE9vqp+d4j9/IQ2Hf599KfRP6mqDgduBbK37ebAVuDIgfWj5vn5JGm/GKwlSdKikeSZSV6S5LHA9+mflf0R8N+At7UASZKnJDm1bXYJ8MtJTk+yJMmTkhzXpktf1rY7rG37e8A+/xZ1Vd0NfAF4S5LHJHkR8G8G6nxxkpVtuvl36Af4H83ycD8J/HySVyU5uH09L8kvzHI/AIfSD+3fbPW9lv4Z6/l2GfD6JMuSHA78wQI8pyTNmsFakiQtJo+lf53ut+hPP34q8EbgXcB64FNJHgb+gf6Nx2jX/b4cOA+4n/6Ny45t+3sd8F3gLuCz9G8UdvGQtfxme477gTcBHxx47Gfp3zzsO/SnpX+a/vTwoVXVw8BJ9K8D/0Y73rfT/xnMSlXdTv/68b+nP118JfC52e5nP7wP+BRwM/Al4CpgB/1p+pI0NlJV++4lSZIkjVj7c2X/raqevs/OkrSAPGMtSZKksZTkkCQvb1Pwl9E/s3/5qOuSpF15xlqSJGlCJNm+h4dOqaq/W9BiFkCSf0Z/Gvyz6F8PfyXw+iH/9JgkLRiDtSRJkiRJHTgVXJIkSZKkDgzWkiRJkiR1sGQhn+zJT35yLV++fCGfcux997vf5dBDDx11GWPjxhtv/FZVPWXUdWhhjPI1wd+9yeA4TQbHaTI4TpPBcZoMjtNkmOtx2ltWWdBgvXz5cr7whS8s5FOOvV6vx8zMzKjLGBtJ7h51DVo4o3xN8HdvMjhOk8FxmgyO02RwnCaD4zQZ5nqc9pZVnAouSZIkSVIHBmtJkiRJkjowWEuSJEmS1IHBWpIkSZKkDoYK1kkOT/KxJF9JckeSFyR5YpINSe5s34+Y72IlSZIkSRo3w56xfhdwdVU9CzgWuANYA1xbVSuAa9u6JEmSJEmLyj6DdZInAP8auAigqn5QVQ8CpwLrWrd1wGnzU6IkSZIkSeNrmDPWRwPfBP4iyZeSvD/JocBUVW1tfe4FpuarSEmSJEmSxtWSIfs8F3hdVV2f5F3sMu27qipJ7W7jJKuB1QBTU1P0er1uFR9gtm/f7s9EkiRJkibYMMF6M7C5qq5v6x+jH6zvS7K0qrYmWQps293GVbUWWAswPT1dMzMz3as+gPR6PfyZSJIkSdLk2udU8Kq6F7gnyTNb04nA7cB6YFVrWwVcMS8VSpIkSZI0xoY5Yw3wOuCSJI8B7gJeSz+UX5bkbOBu4PT5KVGSJEmSpPE1VLCuqpuA6d08dOKcViNJkiRJ0oQZ9oy1Okoyq/5Vu70XnKQ5csuWh3jNmitHXcZIbDr/FaMuQZIk6YAyzJ/b0hyoqt1+Pf0PPrnbdkmSJEnSZDBYS5IkSZLUgcFakiRJkqQODNaSJEmSJHVgsJYkSZIkqQODtSRJkiRJHRisJUmSJEnqwGAtSZIkSVIHBmtJkiRJkjowWEuSJEmS1IHBWpIkSZKkDgzWkiRJkiR1YLCWJEmSJKkDg7UkSZIkSR0YrCVJkiRJ6sBgLUmSJElSBwZrSZIkSZI6MFhLkiRJktSBwVqSJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKylRS7J45J8PsmXk9yW5C2t/egk1yfZmOSjSR7T2h/b1je2x5cP7OuNrf2rSV42okOSJEmSFpTBWtIjwEuq6ljgOODkJCcAbwfeWVXPAB4Azm79zwYeaO3vbP1IcgxwBvBs4GTgz5MctJAHIkmSJI2CwVpa5Kpve1s9uH0V8BLgY619HXBaWz61rdMePzFJWvulVfVIVX0d2AgcP/9HIEmSJI2WwVoSSQ5KchOwDdgAfA14sKp2tC6bgWVteRlwD0B7/CHgSYPtu9lGkiRJOmAtGXUBkkavqh4FjktyOHA58Kz5eq4kq4HVAFNTU/R6vfl6qr2aOgTOW7lj3x0PQKP6me+P7du3T1S9i5XjNBkcp8ngOE0Gx2kyLOQ4Gawl/VhVPZjkOuAFwOFJlrSz0kcCW1q3LcBRwOYkS4AnAN8eaN9pcJvB51gLrAWYnp6umZmZeTqavbvwkiu44JbF+RK46ayZUZcwtF6vx6j+jWh4jtNkcJwmg+M0GRynybCQ4+RUcGmRS/KUdqaaJIcALwXuAK4DXtm6rQKuaMvr2zrt8b+tqmrtZ7S7hh8NrAA+vyAHIUmSJI3Q4jxdI2nQUmBdu4P3zwCXVdUnk9wOXJrkj4EvARe1/hcBf5lkI3A//TuBU1W3JbkMuB3YAZzTpphLkiRJBzSDtbTIVdXNwHN2034Xu7mrd1V9H/j1PezrbcDb5rpGSZIkaZw5FVySJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKwlSZIkSerAYC1JkiRJUgcGa0mSJEmSOjBYS5IkSZLUgcFakiRJkqQOlgzTKckm4GHgUWBHVU0neSLwUWA5sAk4vaoemJ8yJUmSJEkaT7M5Y/3iqjquqqbb+hrg2qpaAVzb1iVJkiRJWlS6TAU/FVjXltcBp3WuRpIkSZKkCTNssC7gU0luTLK6tU1V1da2fC8wNefVSZIkSZI05oa6xhp4UVVtSfJUYEOSrww+WFWVpHa3YQviqwGmpqbo9Xpd6j0g+TORJEmSpMk1VLCuqi3t+7YklwPHA/clWVpVW5MsBbbtYdu1wFqA6enpmpmZmZPCDxhXX4k/E0mSJEmaXPucCp7k0CSH7VwGTgJuBdYDq1q3VcAV81WkJEmSJEnjapgz1lPA5Ul29v9wVV2d5AbgsiRnA3cDp89fmZIkSZIkjad9Buuqugs4djft3wZOnI+iJEmSJEmaFF3+3JYkSZIkSYuewVqSJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKwlSZIkSerAYC1JkiRJUgcGa0mSJEmSOjBYS5IkSZLUwZJRFyBJkiTNheVrrhx1CZ2dt3IHr9mP49h0/ivmoRpJw/KMtSRJkiRJHRisJUmSJEnqwGAtSZIkSVIHBmtJkiRJkjowWEuSJEmS1IF3BZckSQekA+EO0fvLO0RL0sLyjLUkSZIkSR0YrCVJkiRJ6sBgLUmSJElSBwZrSZIkSZI68OZl0iKX5Cjgg8AUUMDaqnpXkjcD/x74Zuv6h1V1VdvmjcDZwKPA/1VV17T2k4F3AQcB76+q8xfyWCRJfbu7cdt5K3fwmkV8QzdJmk8Ga0k7gPOq6otJDgNuTLKhPfbOqvovg52THAOcATwbeBrwN0l+vj38HuClwGbghiTrq+r2BTkKDW2S7pQ8l0HAuyRLkqT5YrCWFrmq2gpsbcsPJ7kDWLaXTU4FLq2qR4CvJ9kIHN8e21hVdwEkubT1NVhLkiTpgOY11pJ+LMly4DnA9a3p3CQ3J7k4yRGtbRlwz8Bmm1vbntolSZKkA5pnrCUBkOTxwMeBN1TVd5K8F3gr/euu3wpcAPzWHDzPamA1wNTUFL1er+su98vUIf1pxhpvczlOo/q3Ng5u2fLQvO5/6hC48JIr5vU59sd5K0ddwXjxdW8y7O84LebXuFHYvn27P/MJsJDjZLCWRJKD6YfqS6rqEwBVdd/A4+8DPtlWtwBHDWx+ZGtjL+0/VlVrgbUA09PTNTMzMzcHMUsXXnIFF9ziS+C4O2/ljrkbp1u+Ozf7mUjz+299TsdJ88Zxmgz7O06bzpqZ+2K0R71ej1G9h9HwFnKcfHWVFrkkAS4C7qiqdwy0L23XXwP8GnBrW14PfDjJO+jfvGwF8HkgwIokR9MP1GcAv7kwRyFJ0uI2STemnEvemFLjwmAt6YXAq4BbktzU2v4QODPJcfSngm8Cfgegqm5Lchn9m5LtAM6pqkcBkpwLXEP/z21dXFW3LdxhSJIkSaNhsJYWuar6LP2zzbu6ai/bvA14227ar9rbdpIkSdKByLuCS5IkSZLUgWes58Gxb/kUD/3jD4fuP8w1MU845GC+/KaTupQlSZIkSZoHBut58NA//nDoGykMe6e6xXpDCkmSJEkad04FlyRJkiSpA4O1JEmSJEkdGKwlSZIkSerAYC1JkiRJUgcGa0mSJEmSOjBYS5IkSZLUgcFakiRJkqQODNaSJEmSJHVgsJYkSZIkqYMloy5AkiRJkjQ7y9dcOeoSRmLT+a8YdQm7NXSwTnIQ8AVgS1X9SpKjgUuBJwE3Aq+qqh/MT5mSJEmS9JNGFS7PW7mD1yzSYKvdm81U8NcDdwysvx14Z1U9A3gAOHsuC5MkSZIkaRIMFayTHAm8Anh/Ww/wEuBjrcs64LR5qE+SJEmSpLE27FTwPwN+HzisrT8JeLCqdrT1zcCy3W2YZDWwGmBqaoper7e/tU6UYY9z+/btQ/ddLD87SZIkSZok+wzWSX4F2FZVNyaZme0TVNVaYC3A9PR0zczMeheT5+orGfY4e73ecH1nsU9JkiRJ0sIZ5oz1C4FfTfJy4HHAPwfeBRyeZEk7a30ksGX+ypQkSZIkaTzt8xrrqnpjVR1ZVcuBM4C/raqzgOuAV7Zuq4Ar5q1KSZIkSZLG1GzuCr6rPwB+L8lG+tdcXzQ3JUmSJEmSNDmG/jvWAFXVA3pt+S7g+LkvSZIkSZKkydHljLUkSZIkSYuewVqSJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKwlSZIkSerAYC1JkiRJUgcGa0mSJEmSOjBYS5IkSZLUgcFakiRJkqQODNaSJEmSJHVgsJYkSZIkqQODtSRJkiRJHRisJUmSJEnqwGAtSZIkSVIHBmtJkiRJkjowWEuSJEmS1IHBWlrkkhyV5Loktye5LcnrW/sTk2xIcmf7fkRrT5J3J9mY5OYkzx3Y16rW/84kq0Z1TJIkSdJCMlhL2gGcV1XHACcA5yQ5BlgDXFtVK4Br2zrAKcCK9rUaeC/0gzjwJuD5wPHAm3aGcUmSJOlAZrCWFrmq2lpVX2zLDwN3AMuAU4F1rds64LS2fCrwwer7B+DwJEuBlwEbqur+qnoA2ACcvHBHIkmSJI3GklEXIGl8JFkOPAe4Hpiqqq3toXuBqba8DLhnYLPNrW1P7bs+x2r6Z7qZmpqi1+vN3QHMwtQhcN7KHSN5bg3PcZoMjtNkcJwmg+M0GRyn0ZnNe8ft27cv2HtNg7UkAJI8Hvg48Iaq+k6SHz9WVZWk5uJ5qmotsBZgenq6ZmZm5mK3s3bhJVdwwS2+BI6781bucJwmgOM0GRynyeA4TQbHaXQ2nTUzdN9er8dCvdd0KrgkkhxMP1RfUlWfaM33tSnetO/bWvsW4KiBzY9sbXtqlyRJkg5oBmtpkUv/1PRFwB1V9Y6Bh9YDO+/svQq4YqD91e3u4CcAD7Up49cAJyU5ot207KTWJkmSJB3QnL8g6YXAq4BbktzU2v4QOB+4LMnZwN3A6e2xq4CXAxuB7wGvBaiq+5O8Fbih9fujqrp/QY5AkiRJGiGDtbTIVdVngezh4RN307+Ac/awr4uBi+euOkmSJGn8ORVckiRJkqQODNaSJEmSJHVgsJYkSZIkqQODtSRJkiRJHRisJUmSJEnqwGAtSZIkSVIHBmtJkiRJkjowWEuSJEmS1IHBWpIkSZKkDgzWkiRJkiR1YLCWJEmSJKkDg7UkSZIkSR0YrCVJkiRJ6sBgLUmSJElSBwZrSZIkSZI62GewTvK4JJ9P8uUktyV5S2s/Osn1STYm+WiSx8x/uZIkSZIkjZdhzlg/Arykqo4FjgNOTnIC8HbgnVX1DOAB4Ox5q1KSJEmSpDG1z2Bdfdvb6sHtq4CXAB9r7euA0+ajQEmSJEmSxtmSYTolOQi4EXgG8B7ga8CDVbWjddkMLNvDtquB1QBTU1P0er2OJU+GYY9z+/btQ/ddLD87SZIkSZokQwXrqnoUOC7J4cDlwLOGfYKqWgusBZienq6ZmZnZVzlprr6SYY+z1+sN13cW+5QkSZIkLZxZ3RW8qh4ErgNeAByeZGcwPxLYMrelSZIkSZI0/oa5K/hT2plqkhwCvBS4g37AfmXrtgq4Yp5qlCRJkiRpbA0zFXwpsK5dZ/0zwGVV9ckktwOXJvlj4EvARfNYpyRJkiRJY2mfwbqqbgaes5v2u4Dj56MoSZIkSZImxayusZYkSZIkST/JYC1JkiRJUgcGa0mSJEmSOjBYS5IkSZLUwTB3BdcsHfYLa1i5bs3wG6wbZp8Ar9jfkiRJkiRJ88RgPQ8evuN8Np0/XAju9XrMzMzss9/yNVd2rEqSJEmSNB+cCi5JkiRJUgcGa0mSJEmSOjBYS5IkSZLUgcFakiRJkqQODNaSJEmSJHVgsJYkSZIkqQODtSRJkiRJHRisJUmSJEnqwGAtLXJJLk6yLcmtA21vTrIlyU3t6+UDj70xycYkX03ysoH2k1vbxiRrFvo4JEmSpFExWEv6AHDybtrfWVXHta+rAJIcA5wBPLtt8+dJDkpyEPAe4BTgGODM1leSJEk64C0ZdQGSRquqPpNk+ZDdTwUurapHgK8n2Qgc3x7bWFV3ASS5tPW9fa7rlSRJksaNZ6wl7cm5SW5uU8WPaG3LgHsG+mxubXtqlyRJkg54nrGWtDvvBd4KVPt+AfBbc7HjJKuB1QBTU1P0er252O2sTR0C563cMZLn1vAcp8ngOE0Gx2kyOE6TwXEandm8d9y+ffuCvdc0WEv6KVV1387lJO8DPtlWtwBHDXQ9srWxl/Zd970WWAswPT1dMzMzc1P0LF14yRVccIsvgePuvJU7HKcJ4DhNBsdpMjhOk8FxGp1NZ80M3bfX67FQ7zWdCi7ppyRZOrD6a8DOO4avB85I8tgkRwMrgM8DNwArkhyd5DH0b3C2fiFrliRJkkbFj1mkRS7JR4AZ4MlJNgNvAmaSHEd/Kvgm4HcAquq2JJfRvynZDuCcqnq07edc4BrgIODiqrptYY9EkiRJGg2DtbTIVdWZu2m+aC/93wa8bTftVwFXzWFpkiRJ0kRwKrgkSZIkSR0YrCVJkiRJ6sBgLUmSJElSBwZrSZIkSZI6MFhLkiRJktSBwVqSJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKwlSZIkSerAYC1JkiRJUgcGa0mSJEmSOjBYS5IkSZLUgcFakiRJkqQODNaSJEmSJHVgsJYkSZIkqQODtSRJkiRJHRisJUmSJEnqYJ/BOslRSa5LcnuS25K8vrU/McmGJHe270fMf7mSJEmSJI2XYc5Y7wDOq6pjgBOAc5IcA6wBrq2qFcC1bV2SJEmSpEVln8G6qrZW1Rfb8sPAHcAy4FRgXeu2DjhtnmqUJEmSJGlszeoa6yTLgecA1wNTVbW1PXQvMDW3pUmSJEmSNP6WDNsxyeOBjwNvqKrvJPnxY1VVSWoP260GVgNMTU3R6/U6FTwphj3O7du3D913sfzsJEmSJGmSDBWskxxMP1RfUlWfaM33JVlaVVuTLAW27W7bqloLrAWYnp6umZmZ7lWPu6uvZNjj7PV6w/WdxT4lSZIkSQtnmLuCB7gIuKOq3jHw0HpgVVteBVwx9+VJkiRJkjTehjlj/ULgVcAtSW5qbX8InA9cluRs4G7g9HmpUJIkSZKkMbbPYF1VnwWyh4dPnNtyJEmSJEmaLLO6K7gkSZIkSfpJBmtJkiRJkjowWEuSJEmS1IHBWpIkSZKkDgzWkiRJkiR1YLCWJEmSJKkDg7UkSZIkSR0YrCVJkiRJ6sBgLUmSJElSBwZrSZIkSZI6MFhLkiRJktSBwVqSJEmSpA4M1tIil+TiJNuS3DrQ9sQkG5Lc2b4f0dqT5N1JNia5OclzB7ZZ1frfmWTVKI5FkiRJGgWDtaQPACfv0rYGuLaqVgDXtnWAU4AV7Ws18F7oB3HgTcDzgeOBN+0M45IkSdKBzmAtLXJV9Rng/l2aTwXWteV1wGkD7R+svn8ADk+yFHgZsKGq7q+qB4AN/HRYlyRJkg5IS0ZdgKSxNFVVW9vyvcBUW14G3DPQb3Nr21P7T0mymv7Zbqampuj1enNX9SxMHQLnrdwxkufW8BynyeA4TQbHaTI4TpPBcRqd2bx33L59+4K91zRYS9qrqqokNYf7WwusBZienq6ZmZm52vWsXHjJFVxwiy+B4+68lTscpwngOE0Gx2kyOE6TwXEanU1nzQzdt9frsVDvNZ0KLml37mtTvGnft7X2LcBRA/2ObG17apckSZIOeAZrSbuzHth5Z+9VwBUD7a9udwc/AXioTRm/BjgpyRHtpmUntTZJkiTpgOf8BWmRS/IRYAZ4cpLN9O/ufT5wWZKzgbuB01v3q4CXAxuB7wGvBaiq+5O8Fbih9fujqtr1hmiSJEnSAclgLS1yVXXmHh46cTd9CzhnD/u5GLh4DkuTJEmSJoJTwSVJkiRJ6sBgLUmSJElSBwZrSZIkSZI6MFhLkiRJktSBwVqSJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKwlSZIkSepgyagLOFAtX3Pl8J2v3nffJxxycIdqJEmSJEnzxWA9Dzad/4qh+y5fc+Ws+kuSJEmSxotTwSVJkiRJ6sBgLUmSJElSBwZrSZIkSZI6MFhLkiRJktSBwVqSJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKwlSZIkSepgn8E6ycVJtiW5daDtiUk2JLmzfT9ifsuUJEmSJGk8DXPG+gPAybu0rQGuraoVwLVtXZIkSZKkRWefwbqqPgPcv0vzqcC6trwOOG1uy5IkSZIkaTLs7zXWU1W1tS3fC0zNUT2SJEmSJE2UJV13UFWVpPb0eJLVwGqAqakper1e16c84PgzkSRJkqTJtb/B+r4kS6tqa5KlwLY9dayqtcBagOnp6ZqZmdnPpzxAXX0l/kwkSZIkaXLt71Tw9cCqtrwKuGJuypEkSZIkabIM8+e2PgL8PfDMJJuTnA2cD7w0yZ3AL7d1SZIkSZIWnX1OBa+qM/fw0IlzXIskSZIkSRNnf6eCS5IkSZIkDNaSJEmSJHVisJYkSZIkqQODtSRJkiRJHRisJUmSJEnqwGAtSZIkSVIHBmtJkiRJkjowWEuSJEmS1IHBWpIkSZKkDgzWkvYoyaYktyS5KckXWtsTk2xIcmf7fkRrT5J3J9mY5OYkzx1t9ZIkSdLCMFhL2pcXV9VxVTXd1tcA11bVCuDatg5wCrCifa0G3rvglUqSJEkjYLCWNFunAuva8jrgtIH2D1bfPwCHJ1k6gvokSZKkBWWwlrQ3BXwqyY1JVre2qara2pbvBaba8jLgnoFtN7c2SZIk6YC2ZNQFSBprL6qqLUmeCmxI8pXBB6uqktRsdtgC+mqAqakper3enBU7G1OHwHkrd4zkuTU8x2kyOE6TwXGaDI7TZHCcRmc27x23b9++YO81DdaS9qiqtrTv25JcDhwP3JdkaVVtbVO9t7XuW4CjBjY/srXtus+1wFqA6enpmpmZmccj2LMLL7mCC27xJXDcnbdyh+M0ARynyeA4TQbHaTI4TqOz6ayZofv2ej0W6r2mU8El7VaSQ5MctnMZOAm4FVgPrGrdVgFXtOX1wKvb3cFPAB4amDIuSZIkHbD8mEXSnkwBlyeB/mvFh6vq6iQ3AJclORu4Gzi99b8KeDmwEfge8NqFL1mSJElaeAZrSbtVVXcBx+6m/dvAibtpL+CcBShNkiRJGitOBZckSZIkqQODtSRJkiRJHRisJUmSJEnqwGAtSZIkSVIHBmtJkiRJkjowWEuSJEmS1IHBWpIkSZKkDgzWkiRJkiR1YLCWJEmSJKkDg7UkSZIkSR0YrCVJkiRJ6sBgLUmSJElSBwZrSZIkSZI6MFhLkiRJktSBwVqSJEmSpA4M1pIkSZIkdWCwliRJkiSpA4O1JEmSJEkdGKwlSZIkSerAYC1JkiRJUgcGa0mSJEmSOjBYS5IkSZLUgcFakiRJkqQODNaSJEmSJHXQKVgnOTnJV5NsTLJmroqSJEmSJGlS7HewTnIQ8B7gFOAY4Mwkx8xVYZIkSZIkTYIuZ6yPBzZW1V1V9QPgUuDUuSlLkiRJkqTJsKTDtsuAewbWNwPP37VTktXAaoCpqSl6vV6Hp5xcL37xi/f4WN7+023XXXfdPFYjSZIkSZorXYL1UKpqLbAWYHp6umZmZub7KcdSVe22vdfrsVh/JpIkSZJ0IOgyFXwLcNTA+pGtTZIkSZKkRaNLsL4BWJHk6CSPAc4A1s9NWZIkSZIkTYb9ngpeVTuSnAtcAxwEXFxVt81ZZZIkSZIkTYBO11hX1VXAVXNUiyRJkiRJE6fLVHBJkiRJkhY9g7UkSZIkSR0YrCVJkiRJ6sBgLUmSJElSBwZrSZIkSZI6MFhLmjNJTk7y1SQbk6wZdT2SJEnSQjBYS5oTSQ4C3gOcAhwDnJnkmNFWJUmSJM0/g7WkuXI8sLGq7qqqHwCXAqeOuCZJkiRp3hmsJc2VZcA9A+ubW5skSZJ0QEtVLdyTJd8E7l6wJ5wMTwa+NeoixsjTq+opoy5Cs5fklcDJVfXbbf1VwPOr6txd+q0GVrfVZwJfXdBC/4m/e5PBcZoMjtNkcJwmg+M0GRynyTDX47THrLJkDp9knwxMPy3JF6pqetR1SHNgC3DUwPqRre0nVNVaYO1CFbUn/u5NBsdpMjhOk8FxmgyO02RwnCbDQo6TU8ElzZUbgBVJjk7yGOAMYP2Ia5IkSZLm3YKesZZ04KqqHUnOBa4BDgIurqrbRlyWJEmSNO8M1qM38imx0lypqquAq0Zdx5D83ZsMjtNkcJwmg+M0GRynyeA4TYYFG6cFvXmZJEmSJEkHGq+xliRJkiSpA4O1pEUnyclJvppkY5I1o65HfUkuTrItya0DbU9MsiHJne37EaOsUZDkqCTXJbk9yW1JXt/aHasxkuRxST6f5MttnN7S2o9Ocn17/ftou9mkRijJQUm+lOSTbd0xGjNJNiW5JclNSb7Q2nzNGzNJDk/ysSRfSXJHkhcs5DgZrDtKMrPzhXDcJPnVfYWGJE9L8rGFqkkatSQHAe8BTgGOAc5Mcsxoq1LzAeDkXdrWANdW1Qrg2rau0doBnFdVxwAnAOe03yHHarw8Arykqo4FjgNOTnIC8HbgnVX1DOAB4OzRlajm9cAdA+uO0Xh6cVUdN/Cnm3zNGz/vAq6uqmcBx9L/vVqwcTJYj1iSebuBXFWtr6rz99HnG1X1yvmqQRpDxwMbq+quqvoBcClw6ohrElBVnwHu36X5VGBdW14HnLaQNemnVdXWqvpiW36Y/huXZThWY6X6trfVg9tXAS8Bdn6g7jiNWJIjgVcA72/rwTGaFL7mjZEkTwD+NXARQFX9oKoeZAHHaeKDdZJDk1zZpjrdmuQ3kvxvST6d5MYk1yRZ2vo+I8nftL5fTPJz6fvTtu0tSX6j9Z1J0huYTnBJe7HbOY30K0m+CPzbgVp+qU0RualN6TlsDzXPJPm7JOuB29sUoD9NckOSm5P8zkC/Tye5IsldSc5Pclab2nVLkp9r/f5NmzL0pXZ8U639NUn+a1v+QJJ3J/mfbV+vbO3L06Zdtv6fSHJ1my7xJwM1n53kf7Xnft/O/UoTaBlwz8D65tam8TRVVVvb8r3A1CiL0U9Kshx4DnA9jtXYae8vbgK2ARuArwEPVtWO1sXXv9H7M+D3gR+19SfhGI2jAj7VssXq1uZr3ng5Gvgm8BctE70/yaEs4DgdCH9u62TgG1X1CvjxpxV/DZxaVd9sQfltwG8BlwDnV9XlSR5H/4OFf0t/itSxwJOBG5J8pu37OcCzgW8AnwNe2K6reB/9TxM3Ah8dqOX/Bs6pqs8leTzw/b3U/VzgF6vq6+0X9KGqel6SxwKfS/Kp1u9Y4Bfon8W5C3h/VR2f/jVtrwPeAHwWOKGqKslv03+BPm83z7kUeBHwLGA9//Rp6KDj2nE/Anw1yYXAo8B/ajU/DPwt8OW9HJskzbn2GuefshgT7f+5jwNvqKrvtM+eAcdqXFTVo8BxSQ4HLqf//7/GRJJfAbZV1Y1JZkZcjvbuRVW1JclTgQ1JvjL4oK95Y2EJ/azyuqq6Psm72GXa93yP04EQrG8BLkjyduCT9K9F+UX6/+gBDgK2trPHy6rqcoCq+j5AkhcBH2n/+dyX5NPA84DvAJ+vqs2t303AcmA78PWqurO1fwjY+cnV54B3JLkE+MTObffg81X19bZ8EvCvdp5FBp4ArAB+ANyw81OWJF8DdgbuW4AXt+UjgY+2M/OPAXbud1f/o6p+RP8s+Z4+rbm2qh5qz3c78HT6Hzh8uqrub+1/Bfz8Xo5NGmdbgKMG1o9sbRpP9yVZWlVb22vctlEXJEhyMP1QfUlVfaI1O1ZjqqoeTHId8ALg8CRL2hlRX/9G64XAryZ5OfA44J/Tv0bUMRozVbWlfd+W5HL6l5X5mjdeNgObq+r6tv4x+sF6wcZp4qeCV9X/ov/pxC3AHwP/Drit3VzguKpaWVUn7efuHxlYfpR9fBDRrmf+beAQ+med9/bJ8HcHlkP/05WdNR9dVTsD9GANPxpY/9FAPRcC/7WqVgK/Q//FeV/HkyH67POYpQl0A7Ai/buuPgY4g/4MDo2n9cCqtrwKuGKEtYgfXwN6EXBHVb1j4CHHaowkeUo7U02SQ4CX0r8e/jpg5wf5jtMIVdUbq+rIqlpO//+iv62qs3CMxkr6l50etnOZ/gmxW/E1b6xU1b3APUme2ZpOBG5nAcdp4oN1kqcB36uqDwF/CjwfeEqSF7THD07y7HaDlc1JTmvtj03yz4C/A36jXYf0FPoXvX9+L0/5FWD5zuubgTMHavm5qrqlqt5O/837sFOurgF+t50BIMnPt1/cYT2Bf/o0c9XeOu6nG4BfSnJE+jdb+3fz8BzSgmhnAM6l/3t3B3BZVd022qoEkOQjwN8Dz0yyOcnZwPnAS5PcCfxyW9dovRB4FfCS/NN9RV6OYzVulgLXJbmZ/v/jG6rqk8AfAL+XZCP963kvGmGN2j3HaLxMAZ9N8mX6GeHKqroaX/PG0euAS9rr3nHAf2YBx+lAOBu5EvjTJD8Cfgj8Lv0/BfLudr31Evo3hriN/huB/57kj1rfX6d/zdEL6F8zXMDvV9W9ezrbXFXfb9dEX5nke/SD+c6blL0hyYvpn02+jf613sN4P/1p5l9sZwK+yezuWPdm4K+SPED/+uejZ7HtPrVrSv4z/ReT++l/uPDQXD6HtJCq6irgqlHXoZ9UVWfu4aETF7QQ7VVVfZY9z3pyrMZEVd1M/54pu7bfRX8aq8ZIVfWAXlt2jMZIG49jd9P+bXzNGytVdRMwvZuHFmScUuV19tq3JI+vqu3tjPXlwMU7r1eXJEmSpMVs4qeCa8G8ud3A7Vb6N0f7HyOtRpIkSZLGhGes51GSlcBf7tL8SFU9fxT1SJIkSZLmnsFakiRJkqQOnAouSZIkSVIHBmtJkiRJkjowWEuSJEmS1IHBWpIkSZKkDgzWkiRJkiR18P8DDi14ti1cbRQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1224x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='minutes_remaining',ax=axes[0]);\n",
    "df.hist(column='minutes_remaining', ax=axes[1]);\n",
    "\n",
    "fig, axes = plt.subplots(1,2, gridspec_kw={'width_ratios': [1, 5]}, figsize=(17,6))\n",
    "df.boxplot(column='seconds_remaining',ax=axes[0]);\n",
    "df.hist(column='seconds_remaining', ax=axes[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e8c9ef8",
   "metadata": {},
   "source": [
    "#### For Column: `period` & `playoffs`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4c719c34",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3    7002\n",
      "1    6700\n",
      "4    6043\n",
      "2    5635\n",
      "5     280\n",
      "6      30\n",
      "7       7\n",
      "Name: period, dtype: int64\n",
      "0    21939\n",
      "1     3758\n",
      "Name: playoffs, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print( df[\"period\"].value_counts() )\n",
    "print( df[\"playoffs\"].value_counts() )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3071f586",
   "metadata": {},
   "source": [
    "#### For Column: `season`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "83479303",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2005-06    1924\n",
       "2002-03    1852\n",
       "2008-09    1851\n",
       "2007-08    1819\n",
       "2009-10    1772\n",
       "2001-02    1708\n",
       "2006-07    1579\n",
       "2000-01    1575\n",
       "2010-11    1521\n",
       "2011-12    1416\n",
       "2003-04    1371\n",
       "2012-13    1328\n",
       "1999-00    1312\n",
       "2004-05    1127\n",
       "2015-16     932\n",
       "1997-98     810\n",
       "1998-99     765\n",
       "2014-15     593\n",
       "1996-97     383\n",
       "2013-14      59\n",
       "Name: season, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['season'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10421697",
   "metadata": {},
   "source": [
    "#### For Column: `matchup`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "ac2873b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LAL @ SAS      853\n",
       "LAL vs. SAS    765\n",
       "LAL @ PHX      751\n",
       "LAL @ SAC      751\n",
       "LAL vs. HOU    722\n",
       "              ... \n",
       "LAL @ PHO       29\n",
       "LAL vs. NOP     21\n",
       "LAL vs. SAN     20\n",
       "LAL @ UTH       15\n",
       "LAL vs. BKN     13\n",
       "Name: matchup, Length: 74, dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['matchup'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bab19d2",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Dataset distribution\n",
    "Check whether we have a balanced dataset (almost equal number of positive and negative classes) or an imbalanced one. In this case we check distribution of the target label: **shot_made_flag**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "415158f6",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    0.553839\n",
       "1.0    0.446161\n",
       "Name: shot_made_flag, dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['shot_made_flag'].value_counts(normalize = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45a0414f",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "From this we can see that we have a very balanced dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2af3b67",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## === model Run 1 === \n",
    "For this run we are first doing a blind model fitting on the data without any EDA or adjustments. We will just a very basic preprocessing that we learned in the first lab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "5e603e0d",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X = df.loc[:, df.columns != 'shot_made_flag']\n",
    "y = df['shot_made_flag']\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "4346cb6c",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['action_type', 'combined_shot_type', 'season', 'shot_type',\n",
       "       'shot_zone_area', 'shot_zone_basic', 'shot_zone_range',\n",
       "       'game_date', 'opponent'], dtype=object)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.dtypes[X.dtypes == 'object'].index.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "930e6f12",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def minimum_preprocessing(X, y):\n",
    "    print('Original shape:{}'.format(X.shape))\n",
    "    categorical_columns = X.dtypes[X.dtypes == 'object'].index.values\n",
    "    # We kill categorical columns\n",
    "    X = X.drop(columns = categorical_columns)\n",
    "    print('Droped: {}'.format(categorical_columns))\n",
    "    # We remove missing values\n",
    "    X = X.dropna()\n",
    "    y = y[X.index]\n",
    "    print('New shape:{}'.format(X.shape))\n",
    "    return X, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "093c3547",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original shape:(17216, 20)\n",
      "Droped: ['action_type' 'combined_shot_type' 'season' 'shot_type' 'shot_zone_area'\n",
      " 'shot_zone_basic' 'shot_zone_range' 'game_date' 'opponent']\n",
      "New shape:(17216, 11)\n",
      "Original shape:(8481, 20)\n",
      "Droped: ['action_type' 'combined_shot_type' 'season' 'shot_type' 'shot_zone_area'\n",
      " 'shot_zone_basic' 'shot_zone_range' 'game_date' 'opponent']\n",
      "New shape:(8481, 11)\n"
     ]
    }
   ],
   "source": [
    "# We will apply separately our preprocessing to our train and test partitions to avoid generating biases on our data. \n",
    "X_train, y_train = minimum_preprocessing(X_train,y_train)\n",
    "X_test, y_test = minimum_preprocessing(X_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "bc0bb0a8",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "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>game_event_id</th>\n",
       "      <th>game_id</th>\n",
       "      <th>lat</th>\n",
       "      <th>loc_x</th>\n",
       "      <th>loc_y</th>\n",
       "      <th>lon</th>\n",
       "      <th>minutes_remaining</th>\n",
       "      <th>period</th>\n",
       "      <th>playoffs</th>\n",
       "      <th>seconds_remaining</th>\n",
       "      <th>shot_distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>41</td>\n",
       "      <td>20000936</td>\n",
       "      <td>33.9303</td>\n",
       "      <td>132</td>\n",
       "      <td>114</td>\n",
       "      <td>-118.1378</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>57</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17256</th>\n",
       "      <td>207</td>\n",
       "      <td>21000610</td>\n",
       "      <td>33.9623</td>\n",
       "      <td>-2</td>\n",
       "      <td>82</td>\n",
       "      <td>-118.2718</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10436</th>\n",
       "      <td>230</td>\n",
       "      <td>20600598</td>\n",
       "      <td>33.8913</td>\n",
       "      <td>133</td>\n",
       "      <td>153</td>\n",
       "      <td>-118.1368</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24766</th>\n",
       "      <td>414</td>\n",
       "      <td>29800452</td>\n",
       "      <td>34.0443</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-118.2698</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29674</th>\n",
       "      <td>489</td>\n",
       "      <td>41000231</td>\n",
       "      <td>33.8093</td>\n",
       "      <td>102</td>\n",
       "      <td>235</td>\n",
       "      <td>-118.1678</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       game_event_id   game_id      lat  loc_x  loc_y       lon  \\\n",
       "1334              41  20000936  33.9303    132    114 -118.1378   \n",
       "17256            207  21000610  33.9623     -2     82 -118.2718   \n",
       "10436            230  20600598  33.8913    133    153 -118.1368   \n",
       "24766            414  29800452  34.0443      0      0 -118.2698   \n",
       "29674            489  41000231  33.8093    102    235 -118.1678   \n",
       "\n",
       "       minutes_remaining  period  playoffs  seconds_remaining  shot_distance  \n",
       "1334                   6       1         0                 57             17  \n",
       "17256                  3       2         0                 41              8  \n",
       "10436                 11       3         0                 47             20  \n",
       "24766                  0       4         0                 18              0  \n",
       "29674                  0       4         1                  2             25  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8134f41b",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "#### Sklearn linear regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7c78c995",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients: \n",
      " [-2.37981371e-05 -3.48247019e-09 -2.17483761e-07  8.92258391e-06\n",
      "  2.17483761e-04  8.92258394e-09  2.15876770e-03 -6.31502663e-03\n",
      "  6.60814039e-02  5.39761091e-04]\n",
      "Intercept: \n",
      " 0.6620980084339255\n"
     ]
    }
   ],
   "source": [
    "# We instantiate a linear regression. \n",
    "lr = LinearRegression()\n",
    "\n",
    "# Now we train it on train data with fit method\n",
    "lr.fit(X_train,y_train)\n",
    "\n",
    "# We can predict using the predict method\n",
    "y_train_pred = lr.predict(X_train)\n",
    "\n",
    "weights = lr.coef_\n",
    "intercept = lr.intercept_\n",
    "# You can access to some info about the model, like the weights.\n",
    "print('Coefficients: \\n', weights[:10])\n",
    "print('Intercept: \\n', intercept)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5dd3cafe",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Mean Squared Error (MSE): 0.23651704352579284\n",
      "Train MSE with y_pred_bin: 0.400092936802974\n",
      "Test Mean Squared Error (MSE): 0.23782459648806475\n",
      "Test MSE with y_pred_bin: 0.4059662775616083\n"
     ]
    }
   ],
   "source": [
    "#### On train data\n",
    "N = X_train.shape[0]\n",
    "\n",
    "# You can also use sklearn implementation\n",
    "mean_square_error_sk = mean_squared_error(y_train, y_train_pred)\n",
    "print( f\"Train Mean Squared Error (MSE): {mean_square_error_sk}\" )\n",
    "\n",
    "y_train_pred_bin = [1 if y >= 0.5 else 0 for y in y_train_pred]\n",
    "mean_square_error_sk = mean_squared_error(y_train, y_train_pred_bin)\n",
    "print( f\"Train MSE with y_pred_bin: {mean_square_error_sk}\" )\n",
    "\n",
    "#### On test Data\n",
    "y_test_pred = lr.predict(X_test)\n",
    "# You can also use sklearn implementation\n",
    "mean_square_error_sk = mean_squared_error(y_test, y_test_pred)\n",
    "print( f\"Test Mean Squared Error (MSE): {mean_square_error_sk}\" )\n",
    "\n",
    "y_test_pred_bin = [1 if y >= 0.5 else 0 for y in y_test_pred]\n",
    "mean_square_error_sk = mean_squared_error(y_test, y_test_pred_bin)\n",
    "print( f\"Test MSE with y_pred_bin: {mean_square_error_sk}\" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "14c2bbdb",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>     <td>shot_made_flag</td>  <th>  R-squared:         </th> <td>   0.043</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.042</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   85.60</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Sat, 09 Apr 2022</td> <th>  Prob (F-statistic):</th> <td>1.87e-156</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>02:57:33</td>     <th>  Log-Likelihood:    </th> <td> -12018.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td> 17216</td>      <th>  AIC:               </th> <td>2.406e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td> 17206</td>      <th>  BIC:               </th> <td>2.413e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     9</td>      <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "          <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>             <td> 4.371e-05</td> <td> 1.98e-06</td> <td>   22.027</td> <td> 0.000</td> <td> 3.98e-05</td> <td> 4.76e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>game_event_id</th>     <td> -2.38e-05</td> <td>    0.000</td> <td>   -0.174</td> <td> 0.862</td> <td>   -0.000</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>game_id</th>           <td>-3.482e-09</td> <td> 1.22e-09</td> <td>   -2.852</td> <td> 0.004</td> <td>-5.88e-09</td> <td>-1.09e-09</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>lat</th>               <td>    0.0015</td> <td> 6.76e-05</td> <td>   22.024</td> <td> 0.000</td> <td>    0.001</td> <td>    0.002</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>loc_x</th>             <td> 1.409e-05</td> <td> 3.39e-05</td> <td>    0.416</td> <td> 0.677</td> <td>-5.23e-05</td> <td> 8.05e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>loc_y</th>             <td>    0.0002</td> <td> 7.36e-05</td> <td>    2.976</td> <td> 0.003</td> <td> 7.48e-05</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>lon</th>               <td>   -0.0052</td> <td>    0.000</td> <td>  -22.027</td> <td> 0.000</td> <td>   -0.006</td> <td>   -0.005</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>minutes_remaining</th> <td>    0.0022</td> <td>    0.002</td> <td>    1.247</td> <td> 0.212</td> <td>   -0.001</td> <td>    0.006</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>period</th>            <td>   -0.0063</td> <td>    0.017</td> <td>   -0.369</td> <td> 0.712</td> <td>   -0.040</td> <td>    0.027</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>playoffs</th>          <td>    0.0661</td> <td>    0.027</td> <td>    2.478</td> <td> 0.013</td> <td>    0.014</td> <td>    0.118</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>seconds_remaining</th> <td>    0.0005</td> <td>    0.000</td> <td>    2.529</td> <td> 0.011</td> <td>    0.000</td> <td>    0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>shot_distance</th>     <td>   -0.0122</td> <td>    0.001</td> <td>  -17.657</td> <td> 0.000</td> <td>   -0.014</td> <td>   -0.011</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>68240.363</td> <th>  Durbin-Watson:     </th> <td>   1.991</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th>  <td> 0.000</td>   <th>  Jarque-Bera (JB):  </th> <td>2419.226</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>           <td> 0.203</td>   <th>  Prob(JB):          </th> <td>    0.00</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>       <td> 1.209</td>   <th>  Cond. No.          </th> <td>7.15e+23</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The smallest eigenvalue is 2.27e-29. This might indicate that there are<br/>strong multicollinearity problems or that the design matrix is singular."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:         shot_made_flag   R-squared:                       0.043\n",
       "Model:                            OLS   Adj. R-squared:                  0.042\n",
       "Method:                 Least Squares   F-statistic:                     85.60\n",
       "Date:                Sat, 09 Apr 2022   Prob (F-statistic):          1.87e-156\n",
       "Time:                        02:57:33   Log-Likelihood:                -12018.\n",
       "No. Observations:               17216   AIC:                         2.406e+04\n",
       "Df Residuals:                   17206   BIC:                         2.413e+04\n",
       "Df Model:                           9                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "=====================================================================================\n",
       "                        coef    std err          t      P>|t|      [0.025      0.975]\n",
       "-------------------------------------------------------------------------------------\n",
       "const              4.371e-05   1.98e-06     22.027      0.000    3.98e-05    4.76e-05\n",
       "game_event_id      -2.38e-05      0.000     -0.174      0.862      -0.000       0.000\n",
       "game_id           -3.482e-09   1.22e-09     -2.852      0.004   -5.88e-09   -1.09e-09\n",
       "lat                   0.0015   6.76e-05     22.024      0.000       0.001       0.002\n",
       "loc_x              1.409e-05   3.39e-05      0.416      0.677   -5.23e-05    8.05e-05\n",
       "loc_y                 0.0002   7.36e-05      2.976      0.003    7.48e-05       0.000\n",
       "lon                  -0.0052      0.000    -22.027      0.000      -0.006      -0.005\n",
       "minutes_remaining     0.0022      0.002      1.247      0.212      -0.001       0.006\n",
       "period               -0.0063      0.017     -0.369      0.712      -0.040       0.027\n",
       "playoffs              0.0661      0.027      2.478      0.013       0.014       0.118\n",
       "seconds_remaining     0.0005      0.000      2.529      0.011       0.000       0.001\n",
       "shot_distance        -0.0122      0.001    -17.657      0.000      -0.014      -0.011\n",
       "==============================================================================\n",
       "Omnibus:                    68240.363   Durbin-Watson:                   1.991\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             2419.226\n",
       "Skew:                           0.203   Prob(JB):                         0.00\n",
       "Kurtosis:                       1.209   Cond. No.                     7.15e+23\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The smallest eigenvalue is 2.27e-29. This might indicate that there are\n",
       "strong multicollinearity problems or that the design matrix is singular.\n",
       "\"\"\""
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#data_train = X_train.copy()\n",
    "#data_train['life_expectancy'] = y_train\n",
    "#data_train = sm.add_constant(data_train)\n",
    "# Linear regression is called ordinary least squares (OLS) in statsmodels\n",
    "model = sm.OLS(y_train, sm.add_constant(X_train))\n",
    "result = model.fit()\n",
    "result.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d6c4a621",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/teemo/.local/lib/python3.9/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,8))\n",
    "ax.set_xlim([-5,5])\n",
    "sns.distplot(result.resid,bins=100);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "9520774c",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfoAAAHwCAYAAABOjq0vAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAABAj0lEQVR4nO3dd5xU1f3/8dcHBBEQCxCDCqxRo18wagy25Kt0RRQBFUVBEQv2Xn722HtDRRQVGyg2lCpIx+jXROw9oiJKVGyoCCKwn98fZzauuGV2d2bOzJ338/GYx87cuXPvZ9aE955zzz3H3B0RERFJpnqxCxAREZHsUdCLiIgkmIJeREQkwRT0IiIiCaagFxERSTAFvYiISIIp6EWKhJm5mW1Ry88uMLNulby3m5m9V9G+Znaemd1du4prVF8nM/s02+cRKUQKepE8lgrN5Wa21My+MLP7zKxp7LrKc/dn3X2rSt670t2PAjCzktQfG2vV5jxmdriZrU79Lr43s1fNbJ9aHOc+M7u8NjWIFCIFvUj+6+XuTYEdgA7ABWvuUNvwLED/l/pdrA/cAzxqZhvELUkkvynoRQqEuy8Cnga2gf92xZ9gZu8D76e2HW1m883sGzMbb2Ybr3GYnmb2oZl9ZWbXmVm91Oc2N7OZZvZ16r3RZrb+Gp/d0czeNrNvzexeM2uU+myl3eZmdrGZjUq9nJv6uSTVKu+YqvNP5fb/nZktM7OW1fwuSoGRwDrA5hWc93/MbLaZLTGzt8xs39T2IcAA4OxUDROqOo9IEijoRQqEmbUGegKvlNvcB9gZaGdmXYCrgAOBVsDHwJg1DtOX0CuwA9AbOKLs8KnPbgz8D9AauHiNzw4A9iQE6x+poGehGrunfq7v7k3dfU6qvoHl9jkYmOHuX1Z1oFQPxlHAUlJ/5JR7rwEwAXgG+B1wEjDazLZy9xHAaODaVA29avgdRAqOgl4k/z1lZkuAfwBzgCvLvXeVu3/j7ssJQTzS3V929xXAucCuZlZSbv9rUvsvBG4mBCvuPt/dp7n7ilTI3gh0XKOO29z9E3f/Brii7LN1dD9wsJlZ6vWhwINV7L9L6nfxeer8fd39uzX3AZoCV7v7z+4+E5iYoXpFCk6xXNcTKWR93H16Je99Uu75xsDLZS/cfamZfQ1sAiyoYP+PU5/BzDYChgK7AesSGgHfVnGu/362Ltz9n2a2DOhkZp8BWwDjq/jIC+7+v9UcdmPgk1T3fpmPCb8HkaKjFr1IYSu//OR/gLZlL8ysCdAcWFRun9blnrdJfQZCL4EDf3L3ZoTudOPXKvtsbWot7/7U+Q4FHnf3n2p43DX9B2hdNv4gpQ2//B60ZKcUFQW9SHI8DAw2s+3NbG1CeP/T3ReU2+csM9sgdb3/FOCR1PZ1Cde7vzOzTYCzKjj+CWa2qZltCJxf7rPp+hIoBf6wxvZRhLEDA4EHanjMivwTWEYYcNfAzDoBvfhlvMIXFdQgklgKepGESHXvXwg8AXxGGDTXf43dxgEvAa8Ckwi3qAFcQhig911q+9gKTvEQYYDbh8AHQI3uRXf3ZYRr+8+lRsPvktr+CeGSgwPP1uSYlZznZ0Kw7wV8BdwOHObu76Z2uYcweHGJmT1V1/OJ5DtzVy+WiMRlZiOB/7h7TUfyi0g1NBhPRKJK3RWwH/DnyKWIJJK67kUkGjO7DHgTuM7dP4pdj0gSqeteREQkwdSiFxERSTAFvYiISIIlcjBeixYtvKSkJHYZIiIiOfHSSy995e4VLgaVyKAvKSlh3rx5scsQERHJCTP7uLL31HUvIiKSYAp6ERGRBFPQi4iIJJiCXkREJMEU9CIiIgmmoBcREUkwBb2IiEiCKehFREQSTEEvIiKSYAp6ERGRBFPQi4iIJJiCXkREJMEU9CIiIgmmoBcREUkwBb2IiEiCKehFREQSTEEvIiKSS/Png3vOTqegFxERyZXZs2H77eG663J2SgW9iIhILkybBj17Qtu2cNhhOTutgl5ERCTbJk+GXr1gyy1Dq/73v8/ZqRX0IiIi2TRuHPTpA+3bw8yZ0LJlTk+voBcREcmWxx6DAw6AHXaAGTOgefOcl6CgFxERyYaHHoL+/WHnneGZZ2D99aOUoaAXERHJtPvug4EDYffdYcoUaNYsWikKehERkUwaMQIGD4Zu3WDSJGjaNGo5CnoREZFMGTYMjjkm3EY3fjw0bhy7IgW9iIhIRtx4I5x4IvTuDWPHQqNGsSsCFPQiIiJ1d9VVcMYZ0K9fGGm/9tqxK/ovBb2IiEhtucMll8B558Ehh4SR9g0axK7qV9aKXYCIiEhBcocLLoArr4TDD4e774b69WNX9RsKehERkZpyh7POghtugCFDYPhwqJefneQKehERkZpwh1NOgVtvDYPvbrkFzGJXVan8/PNDREQkH5WWwrHHhpA//fS8D3lQ0IuIiKRn9Wo48sgwIc6558L11+d9yIO67kVERKq3alUYcDd6NFx8MVx0UUGEPCjoRUREqrZyJQwYEO6Pv/LK0JovIAp6ERGRyqxYEVage+qp0FV/xhmxK6oxBb2IiEhFfvoprCU/aVIYdHfSSbErqhUFvYiIyJqWLYO+fcM68nfeGe6VL1BRR92b2UgzW2xmb1byficz+87MXk09Lsp1jSIiUmR+/BH22QemTYORIws65CF+i/4+4DbggSr2edbd98lNOSIiUtS+/x723huefx4efDAMwitwUYPe3eeaWUnMGkRERABYsgR69IB582DMmLASXQIUwoQ5u5rZa2b2tJm1j12MiIgk0DffQLdu8PLL8PjjiQl5iN91X52XgbbuvtTMegJPAVtWtKOZDQGGALRp0yZnBYqISIH78kvo3h3efReefDJ03SdIXrfo3f17d1+aej4ZaGBmLSrZd4S7d3D3Di1btsxpnSIiUqA+/xw6d4b33oPx4xMX8pDnQW9mvzcLcwya2U6Eer+OW5WIiCTCokXQqRN89BFMngx77BG7oqyI2nVvZg8DnYAWZvYp8HegAYC73wEcABxnZquA5UB/d/dI5YqISFIsXAhdusAXX8CUKbDbbrEryprYo+4Prub92wi334mIiGTGRx+FkP/223Cv/C67xK4oq/J9MJ6IiEjmzJ8fQn7pUpgxA/7yl9gVZZ2CXkREisO774aQX7kSZs2C7baLXVFOKOhFRCT53nwTunYNa8jPng3ti2dalrwedS8iIlJnr74aRtfXr190IQ8KehERSbJ580J3fePGMHcubL117IpyTkEvIiLJ9MILobt+vfVCyG+xReyKolDQi4hI8jz7bJjWtmXLEPIlJbErikZBLyIiyTJzZliFbpNNQsi3bh27oqgU9CIikhzPPBPmq99sM5gzBzbeOHZF0SnoRUQkGSZNgl69YKutwn3yG20Uu6K8oKAXEZHC9+ST0LcvbLtt6LrXKqb/paAXEZHC9uij0K9fmM52+nTYcMPYFeUVBb2IiBSuUaPg4INh113D9fn11otdUd5R0IuISGG691447DDo2DEsNbvuurEryksKehERKTx33glHHBHulZ84EZo0iV1R3lLQi4hIYbn1Vjj22HAb3bhxYXpbqZSCXkRECsf118PJJ0OfPjB2LDRqFLuivKegFxGRwnDllXDWWXDggWGkfcOGsSsqCAp6ERHJb+5w8cVw/vkwcCCMHg0NGsSuqmCsFbsAERGRSrnDeefB1VfD4MFw111hXXlJm4JeRETykzuccQbcdBMccwzcfjvUU0d0Tek3JiIi+ae0FE46KYT8SSfB8OEK+VrSb01ERPJLaWm4fW7YMDjzTBg6FMxiV1WwFPQiIpI/Vq8OE+HcdVcYfHfttQr5OtI1ehERyQ+rVsGgQfDQQ3DppXDhhbErSgQFvYiIxLdyJRxyCDz+OFx1FZxzTuyKEkNBLyIica1YAQcdFKazvfFGOO202BUlioJeRETi+ekn2H9/mDwZbrsNTjghdkWJo6AXEZE4li2D3r1hxgwYMQKOPjp2RYmkoBcRkdxbuhR69YI5c8K68oMGxa4osRT0IiKSW99/Dz17wgsvwKhRYRCeZI2CXkREcmfJEujRA156CcaMgQMOiF1R4inoRUQkN77+GvbYA954I9xG17t37IqKgoJeRESyb/Fi6N4d3nsv3Ea3116xKyoaCnoREcmuzz6Dbt3go49g4sTwXHJGQS8iItmzaBF06RJ+Tp4MnTrFrqjoKOhFRCQ7Fi4MIb94MUydCn/7W+yKipKCXkREMu/DD0PIL1kC06bBzjvHrqhoKehFRCSz3n8/hPyyZTBzJuywQ+yKipqCXkREMuedd0LIr1oVQn677WJXVPTqxS5AREQS4o03oGNHcIfZsxXyeUJBLyIidffKK9C5MzRoEOavb98+dkWSoqAXEZG6efHF0F3fpAnMnQtbbRW7IilHQS8iIrX3/PNhApwNNggt+c03j12RrEFBLyIitTN3Luy5J2y0UQj5kpLYFUkFFPQiIlJzM2aE+eo33TSEfOvWsSuSSijoRUSkZqZOhX32gT/8IYyub9UqdkVSBQW9iIikb8IE2Hdf2HprmDUrdNtLXlPQi4hIesaOhf32g223DV33LVrErkjSEDXozWykmS02szcred/M7BYzm29mr5uZ5lEUEYnhkUfgwANhxx1h+nTYcMPYFUmaYrfo7wN6VPH+XsCWqccQYHgOahIRkfIefBAOOSSsPjd1Kqy3XuyKpAaiBr27zwW+qWKX3sADHrwArG9mGvUhIpIrI0fCoEFhHfnJk2HddWNXJDUUu0VfnU2AT8q9/jS17TfMbIiZzTOzeV9++WVOihMRSbThw+HII2GPPWDixDDznRScfA/6tLn7CHfv4O4dWrZsGbscEZHCNnQoHH98uI3uqadgnXViVyS1lO9BvwgoPwvDpqltIiKSLdddB6eeGkbYP/EENGoUuyKpg3wP+vHAYanR97sA37n7Z7GLEhFJrMsvh7PPhv79YcwYaNgwdkVSR2vFPLmZPQx0AlqY2afA34EGAO5+BzAZ6AnMB5YBg+NUKiKScO7w97/DZZfBoYeGQXhrRY0IyZCo/xXd/eBq3nfghByVIyJSnNzhnHPg2mvhiCNgxAioXz92VZIh+d51LyIi2eQOp58eQv644+CuuxTyCaOgFxEpVqWlcOKJcPPNcMopMGwY1FMsJI3+i4qIFKPSUjjmGLj99jD47qabwCx2VZIFCnoRkWKzejUMHgx33w0XXABXX62QTzANqRQRKSarVoVR9WPGwKWXwoUXxq5IskxBLyJSLH7+OSxO88QTcM01octeEk9BLyJSDFasgH79YMKEcD3+1FNjVyQ5oqAXEUm65cvDdLZTpoTBd8cdF7siySENxhMRSbIff4RevcI68nffrZCPbPRoKCkJdzGWlITX2aYWvYhIUv3wQ1h97h//gPvug8MOi11RURs9GoYMgWXLwuuPPw6vAQYMyN551aIXEUmi776DHj3guedCwijkozv//F9CvsyyZWF7NqlFLyKSNN9+C3vuCa+8Ao88AvvvH7siARYurNn2TFGLXkQkSb76Crp2hddeg7FjFfJ5pE2bmm3PFAW9iEhSLF4MXbrA22/DuHFhEJ7kjSuugMaNf72tceOwPZsU9CIiSfDZZ9CpE8yfD5MmhevzklcGDAgrALdtG2Ycbts2vM7mQDxQ0IuIFL5PP4WOHcPF3qefDl33khM1vV1uwABYsCCsKbRgQfZDHjQYT0SksH38ceiu/+oreOYZ+OtfY1dUNGLdLldTatGLiBSqDz6A3XeHb76BadMU8llUUcs91u1yNaUWvYhIIfr3v0NLfvlymDEDdtghdkWJVVnLfc2QL5Pt2+VqSi16EZFC8/bb4Zr8zz/D7NkK+Too31Jv0SI81nw+aFDFLff69Ss+ZrZvl6sptehFRArJ669Dt24hZWbPhnbtYldUEMq62j/+OPzqVq8OI9/df9nn668rfr56dcXHXL063B5X/o+AXNwuV1Nq0YuIFIqXX4bOnaFhQ5gzRyFfgbIWullojZuFx8CBIeThl+AuH/K1UXZ7XK5vl6sptehFRArBv/4VprVt1gxmzoTNN49dURTHHw933JFeSNc1yKtS1nIfMCD/gn1NatGLiOS7554L3fUbbghz5yYy5EePhrXX/qUFXtlj+PDsBnhV6tfP75Z7ZdSiFxHJZ3PmwN57wyabhNH1m24au6JqjR4Nhx4aL5CzoXHjwgr38hT0IiL5avp02Hdf2Gyz8LxVq6jltG8fBvwnVZMm0KhRmJZgww3Dtm++CaPoy7rpC5GCXkQkHz39NPTtC3/8Ywj53/0ua6fq1i10FhSLevXCFLRlo+/bti3sIK+Ogl5EJN+MHw/9+oUm9LRp0Lx5rQ9llsG6Clzz5jB0aHIDvTIajCcikk+eeCKsIb/99qGZXUXIt29f/eC1YtW8OYwaFcYJlD2++qr4Qh7UohcRyR8PPxxGse28c+i6b9aMDTaAJUtiF5Z/mjYNt9kVY3DXlFr0IiL54P77WX3IQOas/htNn5+KrdcMs+IM+UaNftsaX/Pxww8K+XQp6EVEIhg9+pfu9aPsbkoPH8wsOtOTyfxI09jlZVS7dlWH9pqP5csV4pmkrnsRkRyp6Jr5cdzO7ZzA0/RgP8byE+vkvrBaatcO3nordhVSHQW9iEgWVTUg7hRu5mZOYxz7ciCP8jNr566wKtSrV/lCLlJ41HUvIpJh6Yx6P5truJnTeJz96cdjOQv56q59uyvkk0YtehGROqrpbWwXcBmXcREPcTCH8QCrM/hPcZKmnZXMUNCLiNRC7e5Rdy7lIi7kcu7nMI5gJKXUr/lRFOZSAwp6EZE01H3yGeca/h9ncx13cRTHcCeextVThbrUlYJeRKQSmZtZzrmJ0ziVoQzjeE7i1gpDXqEu2aCgFxEpJ9PTxhqlDOMEjuMObuQ0zuAG4JeTKNwl2xT0IlL0sjUnfD1WM4IhHMlIrub/cS5XAaZwl5zS7XUiUpTq18/uwi/1WcV9HM6RjOT2FhdxTulVuCvkJfcU9CJSVMrCvbQ0e+dYi5WsOmgghzIKLr+c47+8pLiXkpOo1HUvIkUhFznrDvz8M/TvD488CdddB2eemf0Ti1RBQS8iiZbNgP9NN/xPP0G/fjBxIgwdCiefnL2Ti6RJQS8iiZWNkK/0Gvvy5dC3L0ydCsOHw7HHZv7kIrWgoBeRxMl0wFc7gO7HH2HffWHWLLjnHjjiiMwWIFIHCnoRSZRMhXzao+N/+AH23hueew4eeAAGDsxMASIZEnXUvZn1MLP3zGy+mZ1TwfuHm9mXZvZq6nFUjDpFpDDUNeTLr+CWlu++gz33hOefh4ceUshLXorWojez+sAwoDvwKfCimY1397fX2PURdz8x5wWKSMHIRMDX2DffhJB/7TV47LFwfV4kD8Vs0e8EzHf3D939Z2AM0DtiPSJSgOoS8jVqvZf31VfQtSu8/jqMHauQl7wWM+g3AT4p9/rT1LY17W9mr5vZ42bWOjeliUghqG3I1zrgAb74Ajp3hnffhfHjYZ99ankgkdzI95nxJgAl7r4tMA24v7IdzWyImc0zs3lffvllzgoUkTjqEvK19p//QKdO8OGHMGlS6LoXyXMxg34RUL6Fvmlq23+5+9fuviL18m7gL5UdzN1HuHsHd+/QsmXLjBcrIvmjNiFfp1Y8wCefQMeO8OmnMGUKdOlSh4OJ5E7MoH8R2NLMNjOzhkB/YHz5HcysVbmX+wLv5LA+EclDtQ35OlmwIIT84sXwzDOw2251PKBI7kQLendfBZwITCUE+KPu/paZXWpm+6Z2O9nM3jKz14CTgcPjVCsisdVmpblRozIQ8h98ALvvDt9+C9Onw6671vGAIrllnsA1Ezt06ODz5s2LXYaIZECUa/Fl3nsvdNGvWBFCfvvtM3BQkcwzs5fcvUNF72lmPBHJS3W9ba7O3nor3ELnDrNnwzbbZOCgIrmX76PuRaSIlHXPRw/5114Lo+vr1YM5cxTyUtAU9CISVSbCvUxGQv6ll8J98o0ahZDfeusMHFQkHgW9iORcJsO9TEZC/p//DN31zZrB3Lmw5ZYZOKhIXAp6EcmZTId7mYyE/D/+Ad27Q4sWIeQ32ywDBxWJT0EvIlmXzYDPSMjPng09ekCrVqG7vk2bDBxUJD8o6EUkq/I64AGmTYOePaFt2xDym1S05IZI4VLQi0jWZDrkMxrwAJMnQ69e4Vr87Nnw+99n8OAi+UFBLyJ5rSzcMz6317hx0KcPtG8PM2eC1siQhFLQi0jeyVq4l3nsMTjgANhhB5gxA5o3z9KJROJT0ItIXsh6uJd56CHo3x923jksULP++lk+oUhcCnoRiSZn4V7m/vth4MCwSM2UKeF+eZGEU9CLSBQ5X0/rrrtg8GDo1g0mTYKmTXNcgEgcCnoRyZp27Wq2PWuGDYMhQ2CvvWD8eGjcOMcFiMSjoBeRrHnrrd+Gert2YXvO3HgjnHgi9O4NY8eGOexFikiNlqk1s3pAU3f/Pkv1iEjC5DTU13TVVXDeedCvH4weDQ0aRCxGJI5qW/Rm9pCZNTOzJsCbwNtmdlb2SxMRqSV3uOSSEPKHHBJG2ivkpUil03XfLtWC7wM8DWwGHJrNokREas0dLrgALr4YDj8cHngA1qpR56VIoqQT9A3MrAEh6Me7+0og1+NlRUSq5w5nnQVXXhkG391zD9SvH7sqkajSCfo7gQVAE2CumbUFdI1eRPKLO5xyCtxwQxh8d8cdUE/jjUWq/X+Bu9/i7pu4e08PPgY656A2EZH0lJbCccfBrbfC6afDLbdkZ9k8kQKUzmC8jczsHjN7OvW6HTAo65WJiKRj9Wo46ii4804491y4/nqFvEg56fRr3QdMBTZOvf43cGqW6hERSd+qVTBoENx7bxh8d8UVCnmRNaQT9C3c/VGgFMDdVwGrs1qViEh1Vq4Mt86NHh0G3/397wp5kQqkc8/Jj2bWnNRIezPbBfguq1WJiFRlxYqwAt1TT4Wu+jPOiF2RSN5Kp0V/OjAe2NzMngMeAE7KalUikhijR0NJSRgAX1ISXtfJTz/B/vuHkL/lFoW8SDWqbdG7+8tm1hHYCjDgvdS99CIiVRo9OtzOvmxZeP3xx+E1wIABtTjgsmXQt29YR/7OO385mIhUyryatSLN7LCKtrv7A1mpKAM6dOjg8+bNi12GSNErKQnhvqa2bWHBghoe7McfoVcvmD07TIQzeHDdCxRJCDN7yd07VPReOtfodyz3vBHQFXiZ0IUvIlKpikK+qu2V+v572HtveP55ePDBWnYHiBSndLruf3U93szWB8ZkqyARSY769cNt7hVtT9uSJdCjB8ybBw8/DAcemKnyRIpCbVZ6+JGwsI2ISJUqCvmqtv/GN9/AHnvA66/D449Dnz6ZKk2kaFQb9GY2gV8WsakHtAMezWZRIpIMzZvD119XvL1aX34J3bvDu+/Ck0+GrnsRqbF0WvTXl3u+CvjY3T/NUj0iIvD559CtG3zwAYwfH1r1IlIr6Vyjn5OLQkQkeSpqzVe1HYBFi6BrV/jkE5g8GTprDS2Ruqg06M3sByped94Ad/dmWatKRBKhXr2wsFxF2yu0cCF06QJffAFTpsBuu2W1PpFiUGnQu/u6uSxERJKnopCvdPtHH4WQ//ZbmDYNdtklq7WJFIu0R92b2e8I99ED4O4Ls1KRiBSf+fNDyC9dCjNmwF/+ErsikcRIZz36fc3sfeAjYA6wAHg6y3WJSLF4913YfXdYvhxmzVLIi2RYOovaXAbsAvzb3TcjzIz3QlarEpHi8Oab0LFj6MufNQu22y52RSKJk07Qr3T3r4F6ZlbP3WcBFc6nKyKStldfhU6dwjR5s2fDNttELkgkmdK5Rr/EzJoCc4HRZraYMDueiEiVKpsCd6d686DLHtC0KcycCVtskfviRIpEpS16M+tnZo2A3sAy4DRgCvAB0Cs35YlIIWvU6LfbduYFnintCuutB3PnKuRFsqyqrvtDgIXAHUAPwr3z97v7LamufBGRKv24Rt/f//Is0+jOl7QMIV9SEqUukWJSadC7e19gC2A6cBLwqZndYWYdc1WciCRHJ2YxhR4sYhN2Zy60bh27JJGiUOVgPHf/PtWK3wvYBngFuMXMPslJdSKSCN15hsn05CM2oyNz+IyNY5ckUjTSGXWPmW0A7AccBGwIPJ7NokQkOXoyiQn04j22ojOzWMxGsUsSKSpVzXXfFOgLHAz8GRhPuKd+trtXNAe+iMiv9OFJHuEgXmM79mQq37Jh7JJEik5Vt9ctIIyyvx2Y6u4rc1KRiCTDo4/yGIfwIjvSgyl8z3qxKxIpSlUFfWt3X56zSkQkOUaNgkGD+D/+Sk8msxStkSUSS1Wj7rMe8mbWw8zeM7P5ZnZOBe+vbWaPpN7/p5mVZLsmEamje++Fww6Djh3pwRSFvEhkaQ3GywYzqw8MA/YC2gEHm1m7NXY7EvjW3bcAbgKuyW2VIlIjd94JRxwB3bvDxIkso0nsikSKXrSgB3YC5rv7h+7+MzCGMAtfeb2B+1PPHwe6mpnlsEYRSdett8Kxx8Lee8O4cdC4MU0qyfnKtotI5lU16n4CUOnoenfft47n3gQofz/+p8DOle3j7qvM7DugOfBVBfUOAYYAtGnTpo6liUiN3HADnHkm9OkDjzwCDRvGrkhEUqpq0V8P3EBYh345cFfqsZQw331ecfcR7t7B3Tu0bNkydjkixePKK0PIH3ggPPror0J+zSlwq9suIplXaYve3ecAmNkN7l5+WdoJZjYvA+deBJSfA3PT1LaK9vnUzNYC1gM0z75IPnCHSy4Jj4EDwyC8tdJZEFNEcimda/RNzOwPZS/MbDPIyAibF4EtzWwzM2sI9CdMylPeeGBQ6vkBwExN1iOSB9zhvPNCyA8eDPfdp5AXyVPp/D/zNGC2mX0IGNAWOKauJ05dcz8RmArUB0a6+1tmdikwz93HA/cAD5rZfOAbwh8DIhKTO5xxBtx0ExxzDNx+O9SLOa5XRKpSbdC7+xQz2xLYOrXpXXdfkYmTu/tkYPIa2y4q9/wnoF8mziUiGVBaCiefDMOGwUknwdChUMmNMKNH57g2EalQtX+Gm1lj4CzgRHd/DWhjZvtkvTIRyS+lpeH2uWHDwuC7KkIe4JRTclibiFQqnf62e4GfgV1TrxcBl2etIhHJP6tXh4lw7roLzj8frr22ypAH+LqKYbPNm2e4PhGpVDpBv7m7XwusBHD3ZYRr9SJSDFatClPa3n9/GHx3+eXVhnx1hg7NUG0iUq10BuP9bGbrkJo8x8w2BzJyjV5E8tzKlXDIIfD443DVVXDOb5akqJUBAzJyGBFJQzpB/3fCcrWtzWw08Dfg8GwWJSJ5YMUKOOigMJ3tjTfCaafFrkhEaqHKoDezesAGwH7ALoQu+1Pc/TdT0IpIgvz0E+y/P0yeDLfdBiecELsiEamlKoPe3UvN7Gx3fxSYlKOaRCSmZcugd2+YMQNGjICjj45dkYjUQTqD8aab2Zlm1trMNix7ZL0yEcm9pUvD6nMzZoQpbRXyIgUvnWv0B6V+lu+7c+APFewrIoXq+++hZ0944QUYNSoMwhORgpfOzHib5aIQEYloyRLo0QNeegnGjIEDDohdkYhkSFoz45nZBWY2IvV6S82MJ5IgX38NXbvCyy+H2+gU8iKJUpOZ8f6aeq2Z8USSYvFi6NIF3noLnnoqDMITkUTRzHgixeqzz6BzZ3j/fZgwIVyfF5HE0cx4IsVo0aLQkl+0KNwr36lT7IpEJEs0M55IsVm4MIT84sUwdSr87W+xKxKRLEpn1P00M3sZzYwnUvg+/DCE/JIlMG0a7Lxz7IpEJMsqDXoz22GNTZ+lfrYxszbu/nL2yhKRjHv//RDyy5bBzJmww5r/FxeRJKqqRX9D6mcjoAPwGqFFvy0wj1/WpxeRfPfOO+EWupUrQ8hvt13sikQkRyodde/und29M6Elv4O7d3D3vwB/JtxiJyKF4M03w2C70lKYPVshL1Jk0rm9bit3f6Pshbu/CfxP9koSkYx55ZUQ8mutBXPmQPv2sSsSkRxLZ9T9G2Z2NzAq9XoA8Hr2ShKRjHjxRdhjD2jWLHTXb7557IpEJIJ0gv5w4DjglNTrucDwbBUkIhnw/POw117QvHkI+ZKS2BWJSCRVBr2Z1QeeTl2rvyk3JYlIncydG5aabdUqLDfbunXsikQkoiqv0bv7aqDUzNbLUT0iUhczZoSW/KabhmvykUK+ceMopxWRCqTTdb+UcJ1+GvBj2UZ3PzlrVYlIzU2dCn36wBZbwPTpsNFG0UpZvjzaqUVkDekE/djUQ0Ty1YQJYXnZdu3CjHctWkQrxbTklUheSSfoHwG2SD2f7+4/ZbEeEampsWPhoINg++1Dq37DDaOUoYAXyU+VXqM3s7XM7FrgU+B+4AHgEzO71swa5KpAEanCI4/AgQfCjjuG7voIIW+mkBfJZ1UNxrsO2BDYzN3/4u47AJsD6wPX56A2EanKgw/CIYeE1eemToX1cjdmtizcaxPw7pmvR0QqV1XQ7wMc7e4/lG1w9+8J99T3zHZhIlKFkSNh0KAw693kybDuujk5rVrvIoWnqqB399/+7Z265U5/k4vEMnw4HHlkmPVu4kRo0iSrp6tL631Nas2L5F5VQf+2mR225kYzGwi8m72SRKRSQ4fC8cfDPvvAU0/BOutk7VSZbr0r5EXiqGrU/QnAWDM7Angpta0DsA7QN9uFicgarrsOzj4b9tsPHn4YGjbMymmy0TWvkBeJp9Kgd/dFwM5m1gUoW/JqsrvPyEllIvKLyy+HCy+E/v3hgQegQeZvfFHAiyRTtffRu/tMYGYOahGRNbnD3/8Ol10Ghx4aBuGtlc70F+lTwIskW2b/xRCRzHGHc86Ba6+FI46AESOgfv2MHFrhLlI8FPQi+cgdTj8dbr4ZjjsObrsN6lW5BlW1snVbnAJeJL/V7V8OEcm80lI48cQQ8qecAsOG1TrkR4/Ozr3v7r88RCS/qUUvkk9KS+GYY+Duu8MI+6uvrnFKZ3NCGwW7SOFR0Ivki9Wrw7X4Bx6ACy6ASy9NO7WzPVudAl6kcCnoRfLBqlVhVP2YMSHgL7ywyt1zNQ2tAl6k8CnoRWL7+eewOM0TT8A114Qu+wrkKtzXWQeWLcvNuUQk+xT0IjGtWAH9+sGECXDTTXDqqb/ZRa13EakLBb1ILMuXh+lsp0wJI+uPP/6/byncRSRTFPQiMfz4I/TuDTNnwl13wVFHAbkJeIW7SHHRffQiufbDD9CzJ8yaBffdR/ubjsr6Ou+6712keCnoRXLpu++gRw947jn6l47GBh3G229n/jTrr69wF5FAXfciufLtt7Dnnqx88RX68whj2T+jh1egi0hFogS9mW0IPAKUAAuAA9392wr2Ww28kXq50N33zVWNIhn11Ve83HIP2vMWBzCWifTKyGEV7iJSnVhd9+cAM9x9S2BG6nVFlrv79qmHQl4K0u9sMa+37EI73qY34+oc8uusoy55EUlfrKDvDdyfen4/0CdSHSJZYwat7DNm04ktmM/eTGIqPWp9vLJw12Q2IlITsYJ+I3f/LPX8c2CjSvZrZGbzzOwFM+uTm9JE6qZsBP0mfMocOtKGhezF08yka62Op9a7iNRF1q7Rm9l04PcVvHV++Rfu7mZW2T9jbd19kZn9AZhpZm+4+weVnG8IMASgTZs2dahcpObq1w8Lz5Vpw8fMpAst+Io9eIb/4681Op6CXUQyJWtB7+7dKnvPzL4ws1bu/pmZtQIWV3KMRamfH5rZbODPQIVB7+4jgBEAHTp00D+TkhMV3fv+Bz5gJl1oxvd0ZxovslPax1PAi0imxeq6Hw8MSj0fBIxbcwcz28DM1k49bwH8DcjCHcciNVPWNV9RyG/Jv5lDR5qylK7MSDvk1T0vItkSK+ivBrqb2ftAt9RrzKyDmd2d2ud/gHlm9howC7ja3RX0EkVV4V7mf3ibOXSkIT/Tidm8wg7VHlcBLyLZFuU+enf/Gn47Msnd5wFHpZ4/D/wpx6WJADWfjvZPvM50urGa+nRiNu/Qrsr9Fe4ikiuaAleKXvnWem3mnP8zLzOLzvxMQzoyp8qQVwteRHJNQS9Fo6JAr+tCMjvyL2bQlaU0pSNzeJ8/VrifAl5EYlHQS8Fr3LjyEM9UoFdkV55nOt34hg3Znbl8yOa/el+LyohIPlDQS95q3z69AF++PPe17c4cnmEPPqMVHZnDQtr+9z2Fu4jkE61eJ1m3wQawZEnsKjKnK9MZz758xGZ0Yzqf00rBLiJ5Sy16Scvxx6fXuq7okaSQ78HTTGQfFqy1Be2/mMVnrpAXkfymoE+444+HevVqH9Jlj+HDY3+T+HzceJ5u2IdGf25Hu89nwe9+F7skEZFqKeizbPRoKCkJYVtSEl6X39aiRXiUf24Ga63165+1Devhw3W9uDbKD6RzB3/8Cdh/f9h+e5gxA5o3j12iiEhaFPRVqCika7Lv6NEwZAh8/HEIi48/hsGD4Ygjftn29dfhUf45wOrVv/6psM68446rINArGkj38MNw0EGw004wbVoYdCAiUiA0GK8SZSFdtvb3xx+H1wADBqS37zrr/Hbt8JUrs1u3BBn7w+j++8NfZv/7vzBpEjRtmqEDi4jkhnkCm4odOnTwefPm1ekYJSUhsNfUti0sWJDevpJ5Of2f6913h7/YunSBceOgSZMcnlxEJH1m9pK7d6joPXXdV2LhwvS3V7avVKyqLvPqHjlz++1w9NGw554wYYJCXkQKloK+Em3apL+9sn2bNw+ztpXXoAE0bFi32vJBXcL69ttjV1+Nm2+GE06AffeFp54K12BERAqUgr4SV1zx25Bu3DhsT3ffoUNhxIjQ3W8Wft57L4wc+cu25s3Do/xzgPr1f/2zrlO4Nm0Ko0bVPpwLLqxr65pr4LTTwgj7xx6DtdeOXZGISJ1oMF4lygbcnX9+6Jpv0yYE+poD8dLZt6rPSB657DK46CI4+GB44IFwb6OISIHTYDwR9xDwl18Ohx0WulzKulJERApAVYPx1GSR4uYO/+//wXXXwVFHwZ13hskQREQSQv+iSfFyD9fjr7suzBWskBeRBFKLXopTaWkYWX/HHXDqqXDjjdlZtF5EJDI1X6T4rF4d7pG/447Qba+QF5EEU9BLcVm1Cg4/PAy4u+giuOoqhbyIJJq67qV4rFwJhx4KjzwSRtiff37sikREsk5BL8Xh55+hf3948skw+O7MM2NXJCKSEwp6Sb6ffoJ+/WDixDBd4cknx65IRCRnFPSSbMuXQ9++MHUqDB8Oxx4buyIRkZxS0Ety/fhjWJhm1iy4556wrryISJFR0Esy/fAD7L03PPdcmLd+4MDYFYmIRKGgl+T57jvYay/417/goYfgoINiVyQiEo2CXpLlm29gzz3htdfCMrN9+8auSEQkKgW9JMdXX0H37vD22zB2LOyzT+yKRESiU9BLMnzxBXTrBvPnw/jxoVUvIiIKekmA//wHunaFhQth0iTo0iV2RSIieUNBL4Xtk09CsH/+OUyZArvtFrsiEZG8oqCXwrVgQQj5r7+GZ56BXXeNXZGISN5R0Eth+uCDEPLffw/Tp8OOO8auSEQkLynopfC8914I+RUrwqx3228fuyIRkbyloJfC8tZbYeCdO8yeDdtsE7siEZG8Vi92ASJpe+016NQJ6tWDOXMU8iIiaVDQS2F46SXo3BkaNQohv/XWsSsSESkICnrJf//8Z+iub9YM5s6FLbeMXZGISMFQ0Et++8c/wrS2LVqEkN9ss9gViYgUFAW95K/Zs6FHD2jVKnTXt2kTuyIRkYKjoJf8NG0a9OwJbduGkN9kk9gViYgUJAW95J/Jk6FXr3AtfvZs+P3vY1ckIlKwFPSSX8aNgz59oH17mDkTWraMXZGISEFT0Ev+eOwxOOAA2GEHmDEDmjePXZGISMFT0Et+eOgh6N8fdt45LFCz/vqxKxIRSQQFvcR3//0wcCDsvntYarZZs9gViYgkhoJe4rrrLhg8GLp1g0mToGnT2BWJiCRKlKA3s35m9paZlZpZhyr262Fm75nZfDM7J5c1Sg4MGwZDhsBee8H48dC4ceyKREQSJ1aL/k1gP2BuZTuYWX1gGLAX0A442Mza5aY8ybobb4QTT4TevWHs2DCHvYiIZFyUoHf3d9z9vWp22wmY7+4fuvvPwBigd/ark6y76io444wwwv6xx2DttWNXJCKSWPl8jX4T4JNyrz9NbauQmQ0xs3lmNu/LL7/MenFSC+5wySVw3nlwyCHw8MPQoEHsqkREEm2tbB3YzKYDFU1pdr67j8v0+dx9BDACoEOHDp7p40sducMFF8CVV8Lhh8Pdd0P9+rGrEhFJvKwFvbt3q+MhFgGty73eNLVNCo07nHUW3HBDGHw3fDjUy+fOJBGR5Mjnf21fBLY0s83MrCHQHxgfuSapKXc45ZQQ8ieeCHfcoZAXEcmhWLfX9TWzT4FdgUlmNjW1fWMzmwzg7quAE4GpwDvAo+7+Vox6pZZKS+G44+DWW+H00+GWW8AsdlUiIkUla133VXH3J4EnK9j+H6BnudeTgck5LE0yZfVqOPpouPdeOPdcuOIKhbyISARRgl4SbtWqMOBu9Gi4+GK46CKFvIhIJAp6yayVK2HAgHB//BVXhFvpREQkGgW9ZM6KFWEFuqeeguuvD5PiiIhIVAp6yYyffgoz3U2aFAbdnXRS7IpERAQFvWTCsmXQt29YR/7OO8O98iIikhcU9FI3P/4IvXrB7NkwcmRYclZERPKGgl5q7/vvYe+94fnn4cEHwyA8ERHJKwp6qZ0lS8I68i++GBanOfDA2BWJiEgFFPRSc998A3vsAa+/Do8/Dn36xK5IREQqoaCXmvnyS+jeHd59F558MnTdi4hI3lLQS/o+/xy6dYMPPoDx40OrXkRE8pqCXtKzaBF07QqffAKTJ0PnzrErEhGRNCjopXoLF0KXLvDFFzBlCuy2W+yKREQkTQp6qdpHH4WQ//ZbmDYNdtkldkUiIlIDCnqp3Pz5IeSXLoUZM+Avf4ldkYiI1JCCXir27rsh5FeuhFmzYLvtYlckIiK1UC92AZKH3nwTOnaE0lKFvIhIgVPQy6+9+ip06gT164f567fZJnJBIiJSFwp6+cW8eaG7vnFjmDsXtt46dkUiIlJHCnoJXngh3Ce/3noh5LfYInZFIiKSAQp6gWefDdPatmwZQr6kJHZFIiKSIQr6YjdrFvToAZtsEkK+devYFYmISAYp6IvZM89Az56w2WYwZw5svHHsikREJMMU9MVq0iTo1Qu22iq06jfaKHZFIiKSBQr6YvTkk9C3L/zpTzBzZrg2LyIiiaSgLzaPPgr9+oXpbKdPhw03jF2RiIhkkYK+mIwaBQcfDLvuGq7Pr79+7IpERCTLFPTF4t574bDDwtS2U6bAuuvGrkhERHJAQV8M7rwTjjgi3Cs/cSI0aRK7IhERyREFfdLdeisceyzsvTeMGxemtxURkaKhoE+yG26Ak0+GPn1g7Fho1Ch2RSIikmMK+qS68ko480w48MAw0r5hw9gViYhIBAr6pHGHiy+G88+HgQNh9Gho0CB2VSIiEslasQuQDHKH886Dq6+GwYPhrrvCuvIiIlK0FPRJ4Q5nnAE33QTHHAO33w711GEjIlLslARJUFoKJ50UQv6kk2D4cIW8iIgACvrCV1oabp8bNiwMvhs6FMxiVyUiInlCQV/IVq8OE+HcdVcYfHfttQp5ERH5FV2jL1SrVsGgQfDQQ3DJJXDRRbErEhGRPKSgL0QrV8Ihh8Djj8NVV8E558SuSERE8pSCvtCsWAEHHRSms73xRjjttNgViYhIHlPQF5KffoL994fJk+G22+CEE2JXJCIieU5BXyiWLYPevWHGDBgxAo4+OnZFIiJSABT0hWDpUujVC+bMCevKDxoUuyIRESkQCvp89/330LMnvPACjBoVBuGJiIikSUGfz5YsgR494KWXYMwYOOCA2BWJiEiBUdDnq6+/hj32gDfeCLfR9e4duyIRESlACvp8tHgxdO8O770HTz0Vuu5FRERqIcoUuGbWz8zeMrNSM+tQxX4LzOwNM3vVzOblssZoPv8cOneG99+HCRMU8iIiUiexWvRvAvsBd6axb2d3/yrL9eSHRYugS5fwc/Jk6NQpdkUiIlLgogS9u78DYFqA5RcLF4aQX7wYpk6Fv/0tdkUiIpIA+b56nQPPmNlLZjYkdjFZ8+GHsPvu8NVXMG2aQl5ERDImay16M5sO/L6Ct85393FpHuZ/3X2Rmf0OmGZm77r73ErONwQYAtCmTZta1RzF+++HlvyyZTBzJuywQ+yKREQkQbIW9O7eLQPHWJT6udjMngR2AioMencfAYwA6NChg9f13DnxzjvQtWtYjW7mTNhuu9gViYhIwuRt172ZNTGzdcueA3sQBvElw5tvhsF2paUwe7ZCXkREsiLW7XV9zexTYFdgkplNTW3f2Mwmp3bbCPiHmb0G/AuY5O5TYtSbca+8EkJ+rbXC/PXt28euSEREEirWqPsngScr2P4foGfq+YdA8pq5L74YZrxr1ix012++eeyKREQkwfK26z6Rnn8eunWDDTYILXmFvIiIZJmCPlfmzoU994SNNgohX1ISuyIRESkCCvpcmDED9toLNt00hHzr1rErEhGRIqGgz7apU2GffeAPfwij61u1il2RiIgUEQV9Nk2YAPvuC1tvDbNmhW57ERGRHFLQZ8vYsbDffrDttqHrvkWL2BWJiEgRUtBnwyOPwIEHwo47wvTpsOGGsSsSEZEipaDPtAcfhEMOCQvTTJ0K660XuyIRESliCvpMGjkSBg0Ks95Nngzrrhu7IhERKXIK+kwZPhyOPDLMejdxIjRpErsiERERBX1GDB0Kxx8fbqN76ilYZ53YFYmIiAAK+rq77jo49dQwwv6JJ6BRo9gViYiI/JeCvi4uvxzOPhv694cxY6Bhw9gViYiI/IqCvjbc4aKL4MIL4dBDw0j7Bg1iVyUiIvIbUZapLWjucO65cM01cMQRMGIE1K8fuyoREZEKKehrwh1OPx1uvhmOOw5uuw3qqVNERETyl1IqXaWlcOKJIeRPOQWGDVPIi4hI3lNSpaO0FI45Bm6/PQy+u+kmMItdlYiISLUU9NVZvRoGD4a774YLLoCrr1bIi4hIwdA1+qqsWhVG1Y8ZA5deGkbZi4iIFBAFfVVKS+GHH8II+7PPjl2NiIhIjSnoq9KwIYwbp9vnRESkYOkafXUU8iIiUsAU9CIiIgmmoBcREUkwBb2IiEiCKehFREQSTEEvIiKSYAp6ERGRBFPQi4iIJJiCXkREJMEU9CIiIgmmoBcREUkwBb2IiEiCKehFREQSTEEvIiKSYAp6ERGRBFPQi4iIJJiCXkREJMEU9CIiIglm7h67howzsy+Bj+t4mBbAVxkoJx8k6btAsr5Pkr4LJOv7JOm7QLK+T5K+C2Tm+7R195YVvZHIoM8EM5vn7h1i15EJSfoukKzvk6TvAsn6Pkn6LpCs75Ok7wLZ/z7quhcREUkwBb2IiEiCKegrNyJ2ARmUpO8Cyfo+SfoukKzvk6TvAsn6Pkn6LpDl76Nr9CIiIgmmFr2IiEiCKejTYGZnmJmbWYvYtdSWmV1mZq+b2atm9oyZbRy7prows+vM7N3Ud3rSzNaPXVNtmVk/M3vLzErNrCBHEptZDzN7z8zmm9k5seupCzMbaWaLzezN2LXUlZm1NrNZZvZ26n9jp8SuqS7MrJGZ/cvMXkt9n0ti11RXZlbfzF4xs4nZOoeCvhpm1hrYA1gYu5Y6us7dt3X37YGJwEWR66mracA27r4t8G/g3Mj11MWbwH7A3NiF1IaZ1QeGAXsB7YCDzaxd3Krq5D6gR+wiMmQVcIa7twN2AU4o8P82K4Au7r4dsD3Qw8x2iVtSnZ0CvJPNEyjoq3cTcDZQ0IMZ3P37ci+bUPjf5xl3X5V6+QKwacx66sLd33H392LXUQc7AfPd/UN3/xkYA/SOXFOtuftc4JvYdWSCu3/m7i+nnv9ACJRN4lZVex4sTb1skHoU7L9lZrYpsDdwdzbPo6Cvgpn1Bha5+2uxa8kEM7vCzD4BBlD4LfryjgCejl1EEdsE+KTc608p4DBJKjMrAf4M/DNyKXWS6up+FVgMTHP3Qv4+NxMakqXZPMla2Tx4ITCz6cDvK3jrfOA8Qrd9Qajqu7j7OHc/HzjfzM4FTgT+ntMCa6i675Pa53xC9+ToXNZWU+l8F5FsMbOmwBPAqWv07hUcd18NbJ8al/OkmW3j7gU3nsLM9gEWu/tLZtYpm+cq+qB3924VbTezPwGbAa+ZGYSu4ZfNbCd3/zyHJaatsu9SgdHAZPI86Kv7PmZ2OLAP0NXz/D7RGvy3KUSLgNblXm+a2iZ5wMwaEEJ+tLuPjV1Pprj7EjObRRhPUXBBD/wN2NfMegKNgGZmNsrdB2b6ROq6r4S7v+Huv3P3EncvIXRH7pCvIV8dM9uy3MvewLuxaskEM+tB6PLa192Xxa6nyL0IbGlmm5lZQ6A/MD5yTQJYaKXcA7zj7jfGrqeuzKxl2R02ZrYO0J0C/bfM3c91901T+dIfmJmNkAcFfTG52szeNLPXCZcjCvo2G+A2YF1gWuqWwTtiF1RbZtbXzD4FdgUmmdnU2DXVRGpQ5InAVMJgr0fd/a24VdWemT0M/B+wlZl9amZHxq6pDv4GHAp0Sf3/5NVUC7JQtQJmpf4de5FwjT5rt6UlhWbGExERSTC16EVERBJMQS8iIpJgCnoREZEEU9CLiIgkmIJeREQkwRT0IpGYWfNytzx9bmaLUs+XmNnbOa6lT/nFTszsUjOr8SQ/ZlYSc9U3MztvjdfPp35GrUskJgW9SCTu/rW7b59aUfAO4KbU8+3JwtzXZlbVTJh9CCvPldV2kbtPz3QNOfCroHf3v8YqRCRfKOhF8lN9M7srteb2M6lZwDCzzc1sipm9ZGbPmtnWqe0lZjbTzF43sxlm1ia1/T4zu8PM/glcW9HnzeyvwL7Adakehc1TnzsgdYwdzez51Brg/zKzdVPne9bMXk49qgxUC26zsGb9dDObXO74C8ysRep5BzObnXq+k5n9n4W1up83s61S2w83s7Gp7/G+mV2b2n41sE7qO4xObVtaQS31zew6M3sx9fs6JrW9lZnNTX3+TTPbrY7/DUXyQtHPdS+Sp7YEDnb3o83sUWB/YBQwAjjW3d83s52B24EuwK3A/e5+v5kdAdxCaKVDmHv+r+6+2sxmrPl5d+9iZuOBie7+OECYORVSU9o+Ahzk7i+aWTNgOWHlsO7u/pOF6ZUfBjpU8X36AlsReg02At4GRlbzO3gX2M3dV6UuI1yZ+j1A6PX4M2F98vfM7FZ3P8fMTkz1ilTlSOA7d9/RzNYGnjOzZ4D9gKnufoWZ1QcaV3MckYKgoBfJTx+5+6up5y8BJRZWIPsr8FhZEANrp37uSggqgAeBa8sd67FUyFf1+cpsBXzm7i8ClK18ZmZNgNvMbHtgNfDHao6zO/BwauWx/5jZzGr2B1gPuD/1h4QT1h4vM8Pdv0vV8jbQll8vlVuVPYBty3oUUufZkjCl6kgLi8A8Ve73L1LQFPQi+WlFueergXUIl9qWpNFiXdOPqZ+1/XxFTgO+ALZLHfenOhxrFb9cRmxUbvtlwCx372thLfXZ5d5b8/dTk3/LDDjJ3X+zpoCZ7Q7sDdxnZje6+wM1OK5IXtI1epECkWpNf2Rm/eC/1723S739PGEFLIABwLM1/PwPhEWC1vQe0MrMdkx9Zt3UoL71CC39UsKiKfWrKX8ucFDq+ngroHO59xYAf0k937/c9vX4Zbnbw6s5fpmVqRZ5VaYCx5XtZ2Z/NLMmZtYW+MLd7wLuBnZI85wieU1BL1JYBgBHmtlrwFuEJYcBTgIGW1jV61AqX52wss+PAc5KDXzbvGxnd/8ZOAi4NfWZaYRW9+3AoNS2rfml16AyTwLvE67NP0BYHa7MJcBQM5tHaJ2XuRa4ysxeIf0W+wjg9bLBeJW4O1XHyxZuubszdfxOwGup8x0EDE3znCJ5TavXiUjOmdl9lBv8JyLZoxa9iIhIgqlFLyIikmBq0YuIiCSYgl5ERCTBFPQiIiIJpqAXERFJMAW9iIhIginoRUREEuz/A70240i4kSrdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,8))\n",
    "stats.probplot(result.resid, plot=plt);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5519d91",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## === model Run 2 === \n",
    "In this we will do some preprocessing, converting categorical attributes into numerical.\n",
    "\n",
    "-- del -- below line\n",
    "For this run we are first doing a blind model fitting on the data without any EDA or adjustments. We will just a very basic preprocessing that we learned in the first lab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "a352d519",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['action_type', 'combined_shot_type', 'game_event_id', 'game_id', 'lat',\n",
       "       'loc_x', 'loc_y', 'lon', 'minutes_remaining', 'period', 'playoffs',\n",
       "       'season', 'seconds_remaining', 'shot_distance', 'shot_made_flag',\n",
       "       'shot_type', 'shot_zone_area', 'shot_zone_basic', 'shot_zone_range',\n",
       "       'game_date', 'opponent'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c00c0811",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20ceaa3a",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}