CIS3120 Group Project- NBA KNICKS WIN LOSS STATS (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "b98ed9f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from mlxtend.frequent_patterns import apriori\n",
    "from mlxtend.frequent_patterns import association_rules\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "from mlxtend.frequent_patterns import apriori\n",
    "from mlxtend.frequent_patterns import association_rules\n",
    "import time\n",
    "from collections import Counter\n",
    "import collections, re\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "40ceafeb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r--  1 amarisefthimiou  staff  2223684 May  5 22:03 nba_game_stats_1721.csv\r\n"
     ]
    }
   ],
   "source": [
    "! ls -l 'nba_game_stats_1721.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "09ed36ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('nba_game_stats_1721.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eb4a360a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>TEAM_NAME</th>\n",
       "      <th>GAME_ID</th>\n",
       "      <th>GAME_DATE</th>\n",
       "      <th>MATCHUP</th>\n",
       "      <th>WL</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PLUS_MINUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>366</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701214</td>\n",
       "      <td>2018-04-10</td>\n",
       "      <td>ATL vs. PHI</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.692</td>\n",
       "      <td>8.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>27</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
       "      <td>-8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>367</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701202</td>\n",
       "      <td>2018-04-08</td>\n",
       "      <td>ATL @ BOS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.786</td>\n",
       "      <td>5.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>23</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>19</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>368</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701184</td>\n",
       "      <td>2018-04-06</td>\n",
       "      <td>ATL @ WAS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.696</td>\n",
       "      <td>7.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>22</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>369</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701172</td>\n",
       "      <td>2018-04-04</td>\n",
       "      <td>ATL vs. MIA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.647</td>\n",
       "      <td>10.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>20</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>-29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>370</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701158</td>\n",
       "      <td>2018-04-03</td>\n",
       "      <td>ATL @ MIA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.733</td>\n",
       "      <td>12.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>24</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>-3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>371</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701147</td>\n",
       "      <td>2018-04-01</td>\n",
       "      <td>ATL vs. ORL</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>5.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>372</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701130</td>\n",
       "      <td>2018-03-30</td>\n",
       "      <td>ATL vs. PHI</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.667</td>\n",
       "      <td>15.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>24</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>14</td>\n",
       "      <td>-10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>373</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701120</td>\n",
       "      <td>2018-03-28</td>\n",
       "      <td>ATL @ MIN</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.826</td>\n",
       "      <td>4.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>26</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "      <td>22</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>374</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701101</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>ATL @ HOU</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.909</td>\n",
       "      <td>7.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>18</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>-19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>375</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612737</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>21701087</td>\n",
       "      <td>2018-03-23</td>\n",
       "      <td>ATL @ GSW</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.450</td>\n",
       "      <td>5.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>14</td>\n",
       "      <td>-12.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>10 rows × 30 columns</p>\n",
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      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0.1  SEASON_ID     TEAM_ID TEAM_ABBREVIATION  \\\n",
       "0           0           366      22017  1610612737               ATL   \n",
       "1           1           367      22017  1610612737               ATL   \n",
       "2           2           368      22017  1610612737               ATL   \n",
       "3           3           369      22017  1610612737               ATL   \n",
       "4           4           370      22017  1610612737               ATL   \n",
       "5           5           371      22017  1610612737               ATL   \n",
       "6           6           372      22017  1610612737               ATL   \n",
       "7           7           373      22017  1610612737               ATL   \n",
       "8           8           374      22017  1610612737               ATL   \n",
       "9           9           375      22017  1610612737               ATL   \n",
       "\n",
       "       TEAM_NAME   GAME_ID   GAME_DATE      MATCHUP WL  ...  FT_PCT  OREB  \\\n",
       "0  Atlanta Hawks  21701214  2018-04-10  ATL vs. PHI  L  ...   0.692   8.0   \n",
       "1  Atlanta Hawks  21701202  2018-04-08    ATL @ BOS  W  ...   0.786   5.0   \n",
       "2  Atlanta Hawks  21701184  2018-04-06    ATL @ WAS  W  ...   0.696   7.0   \n",
       "3  Atlanta Hawks  21701172  2018-04-04  ATL vs. MIA  L  ...   0.647  10.0   \n",
       "4  Atlanta Hawks  21701158  2018-04-03    ATL @ MIA  L  ...   0.733  12.0   \n",
       "5  Atlanta Hawks  21701147  2018-04-01  ATL vs. ORL  W  ...   1.000   5.0   \n",
       "6  Atlanta Hawks  21701130  2018-03-30  ATL vs. PHI  L  ...   0.667  15.0   \n",
       "7  Atlanta Hawks  21701120  2018-03-28    ATL @ MIN  L  ...   0.826   4.0   \n",
       "8  Atlanta Hawks  21701101  2018-03-25    ATL @ HOU  L  ...   0.909   7.0   \n",
       "9  Atlanta Hawks  21701087  2018-03-23    ATL @ GSW  L  ...   0.450   5.0   \n",
       "\n",
       "   DREB   REB  AST   STL  BLK  TOV  PF  PLUS_MINUS  \n",
       "0  31.0  39.0   27  10.0    3   10  24        -8.0  \n",
       "1  32.0  37.0   23   7.0    4   13  19         6.0  \n",
       "2  43.0  50.0   24   5.0    5   18  22         6.0  \n",
       "3  38.0  48.0   20   5.0    6   15  16       -29.0  \n",
       "4  37.0  49.0   24  10.0    1   15  15        -3.0  \n",
       "5  47.0  52.0   33   0.0    3   14  15         6.0  \n",
       "6  44.0  59.0   24   9.0    4   16  14       -10.0  \n",
       "7  33.0  37.0   26  10.0    2   19  22        -6.0  \n",
       "8  38.0  45.0   18   5.0    2   13  14       -19.0  \n",
       "9  39.0  44.0   24   5.0    5   11  14       -12.0  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d538328d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Unnamed: 0', 'Unnamed: 0.1', 'SEASON_ID', 'TEAM_ID',\n",
      "       'TEAM_ABBREVIATION', 'TEAM_NAME', 'GAME_ID', 'GAME_DATE', 'MATCHUP',\n",
      "       'WL', 'MIN', 'PTS', 'FGM', 'FGA', 'FG_PCT', 'FG3M', 'FG3A', 'FG3_PCT',\n",
      "       'FTM', 'FTA', 'FT_PCT', 'OREB', 'DREB', 'REB', 'AST', 'STL', 'BLK',\n",
      "       'TOV', 'PF', 'PLUS_MINUS'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f8a8b024",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df.TEAM_NAME=='New York Knicks'] #filter df for a specific team by team name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "458618bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>TEAM_NAME</th>\n",
       "      <th>GAME_ID</th>\n",
       "      <th>GAME_DATE</th>\n",
       "      <th>MATCHUP</th>\n",
       "      <th>WL</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PLUS_MINUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1504</th>\n",
       "      <td>1504</td>\n",
       "      <td>340</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701220</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>NYK @ CLE</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.923</td>\n",
       "      <td>8.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>30</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>22</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1505</th>\n",
       "      <td>1505</td>\n",
       "      <td>341</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701207</td>\n",
       "      <td>2018-04-09</td>\n",
       "      <td>NYK vs. CLE</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500</td>\n",
       "      <td>8.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>26</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>-16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1506</th>\n",
       "      <td>1506</td>\n",
       "      <td>342</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701192</td>\n",
       "      <td>2018-04-07</td>\n",
       "      <td>NYK vs. MIL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>13.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>30</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>-13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507</th>\n",
       "      <td>1507</td>\n",
       "      <td>343</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701186</td>\n",
       "      <td>2018-04-06</td>\n",
       "      <td>NYK vs. MIA</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.667</td>\n",
       "      <td>9.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>33</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1508</th>\n",
       "      <td>1508</td>\n",
       "      <td>344</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701159</td>\n",
       "      <td>2018-04-03</td>\n",
       "      <td>NYK vs. ORL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.750</td>\n",
       "      <td>7.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>17</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>-24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1509</th>\n",
       "      <td>1509</td>\n",
       "      <td>345</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701139</td>\n",
       "      <td>2018-03-31</td>\n",
       "      <td>NYK vs. DET</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.833</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>31</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>18</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1510</th>\n",
       "      <td>1510</td>\n",
       "      <td>346</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701118</td>\n",
       "      <td>2018-03-28</td>\n",
       "      <td>NYK @ PHI</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.769</td>\n",
       "      <td>10.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>20</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>22</td>\n",
       "      <td>-17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1511</th>\n",
       "      <td>1511</td>\n",
       "      <td>347</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701103</td>\n",
       "      <td>2018-03-26</td>\n",
       "      <td>NYK @ CHA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>11.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>25</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>27</td>\n",
       "      <td>-9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1512</th>\n",
       "      <td>1512</td>\n",
       "      <td>348</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701098</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>NYK @ WAS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.867</td>\n",
       "      <td>10.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>26</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>19</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1513</th>\n",
       "      <td>1513</td>\n",
       "      <td>349</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701081</td>\n",
       "      <td>2018-03-23</td>\n",
       "      <td>NYK vs. MIN</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.706</td>\n",
       "      <td>10.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>25</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>27</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1  SEASON_ID     TEAM_ID TEAM_ABBREVIATION  \\\n",
       "1504        1504           340      22017  1610612752               NYK   \n",
       "1505        1505           341      22017  1610612752               NYK   \n",
       "1506        1506           342      22017  1610612752               NYK   \n",
       "1507        1507           343      22017  1610612752               NYK   \n",
       "1508        1508           344      22017  1610612752               NYK   \n",
       "1509        1509           345      22017  1610612752               NYK   \n",
       "1510        1510           346      22017  1610612752               NYK   \n",
       "1511        1511           347      22017  1610612752               NYK   \n",
       "1512        1512           348      22017  1610612752               NYK   \n",
       "1513        1513           349      22017  1610612752               NYK   \n",
       "\n",
       "            TEAM_NAME   GAME_ID   GAME_DATE      MATCHUP WL  ...  FT_PCT  \\\n",
       "1504  New York Knicks  21701220  2018-04-11    NYK @ CLE  W  ...   0.923   \n",
       "1505  New York Knicks  21701207  2018-04-09  NYK vs. CLE  L  ...   0.500   \n",
       "1506  New York Knicks  21701192  2018-04-07  NYK vs. MIL  L  ...   1.000   \n",
       "1507  New York Knicks  21701186  2018-04-06  NYK vs. MIA  W  ...   0.667   \n",
       "1508  New York Knicks  21701159  2018-04-03  NYK vs. ORL  L  ...   0.750   \n",
       "1509  New York Knicks  21701139  2018-03-31  NYK vs. DET  L  ...   0.833   \n",
       "1510  New York Knicks  21701118  2018-03-28    NYK @ PHI  L  ...   0.769   \n",
       "1511  New York Knicks  21701103  2018-03-26    NYK @ CHA  L  ...   1.000   \n",
       "1512  New York Knicks  21701098  2018-03-25    NYK @ WAS  W  ...   0.867   \n",
       "1513  New York Knicks  21701081  2018-03-23  NYK vs. MIN  L  ...   0.706   \n",
       "\n",
       "      OREB  DREB   REB  AST   STL  BLK  TOV  PF  PLUS_MINUS  \n",
       "1504   8.0  31.0  39.0   30  10.0    3   15  22        12.0  \n",
       "1505   8.0  29.0  37.0   26   4.0    7   14  20       -16.0  \n",
       "1506  13.0  31.0  44.0   30   3.0    7    8  17       -13.0  \n",
       "1507   9.0  42.0  51.0   33   7.0    5   12  23        24.0  \n",
       "1508   7.0  35.0  42.0   17   5.0    9   11  17       -24.0  \n",
       "1509   9.0  31.0  40.0   31   4.0    1   14  18        -6.0  \n",
       "1510  10.0  36.0  46.0   20   4.0    5   16  22       -17.0  \n",
       "1511  11.0  30.0  41.0   25   6.0    1   10  27        -9.0  \n",
       "1512  10.0  34.0  44.0   26  10.0    6   14  19         4.0  \n",
       "1513  10.0  32.0  42.0   25   9.0    0   10  27        -4.0  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3f316e77",
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df['PLUS_MINUS']) #plus minus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "df3411aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df['AST']) #assists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "92d23b25",
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df['REB']) #rebounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "25fdbced",
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df['TOV']) #tov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "314ed962",
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df['GAME_ID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f234e8a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df['GAME_DATE'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "0e53108b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "L    266\n",
       "W    166\n",
       "Name: WL, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['WL'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1b944483",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(5,5)})\n",
    "plt.hist(df['WL'], bins=5)\n",
    "plt.xlabel(\"WINS V LOSSES KNICKS 2017-2021\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c8dc4f22",
   "metadata": {},
   "outputs": [],
   "source": [
    "#all Knicks games in 2017\n",
    "df_2017 = df.loc[(df['GAME_DATE'] >= '2017-01-01') & (df['GAME_DATE'] <= '2018-01-01')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dd77247a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>TEAM_NAME</th>\n",
       "      <th>GAME_ID</th>\n",
       "      <th>GAME_DATE</th>\n",
       "      <th>MATCHUP</th>\n",
       "      <th>WL</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PLUS_MINUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1550</th>\n",
       "      <td>1550</td>\n",
       "      <td>386</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700532</td>\n",
       "      <td>2017-12-30</td>\n",
       "      <td>NYK @ NOP</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.857</td>\n",
       "      <td>9.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>24</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1551</th>\n",
       "      <td>1551</td>\n",
       "      <td>387</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700519</td>\n",
       "      <td>2017-12-28</td>\n",
       "      <td>NYK @ SAS</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.909</td>\n",
       "      <td>12.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>31</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>26</td>\n",
       "      <td>-12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1552</th>\n",
       "      <td>1552</td>\n",
       "      <td>388</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700509</td>\n",
       "      <td>2017-12-27</td>\n",
       "      <td>NYK @ CHI</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.692</td>\n",
       "      <td>7.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>21</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>17</td>\n",
       "      <td>-5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1553</th>\n",
       "      <td>1553</td>\n",
       "      <td>389</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700493</td>\n",
       "      <td>2017-12-25</td>\n",
       "      <td>NYK vs. PHI</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.643</td>\n",
       "      <td>18.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>18</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>21</td>\n",
       "      <td>-7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1554</th>\n",
       "      <td>1554</td>\n",
       "      <td>390</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700471</td>\n",
       "      <td>2017-12-22</td>\n",
       "      <td>NYK @ DET</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.833</td>\n",
       "      <td>16.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>25</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1555</th>\n",
       "      <td>1555</td>\n",
       "      <td>391</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700468</td>\n",
       "      <td>2017-12-21</td>\n",
       "      <td>NYK vs. BOS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.846</td>\n",
       "      <td>11.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>13</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1556</th>\n",
       "      <td>1556</td>\n",
       "      <td>392</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700441</td>\n",
       "      <td>2017-12-18</td>\n",
       "      <td>NYK @ CHA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.800</td>\n",
       "      <td>10.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>21</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>16</td>\n",
       "      <td>-18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1557</th>\n",
       "      <td>1557</td>\n",
       "      <td>393</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700431</td>\n",
       "      <td>2017-12-16</td>\n",
       "      <td>NYK vs. OKC</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.808</td>\n",
       "      <td>6.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>21</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>22</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1558</th>\n",
       "      <td>1558</td>\n",
       "      <td>394</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700414</td>\n",
       "      <td>2017-12-14</td>\n",
       "      <td>NYK @ BKN</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.864</td>\n",
       "      <td>12.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>23</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>23</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1559</th>\n",
       "      <td>1559</td>\n",
       "      <td>395</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21700399</td>\n",
       "      <td>2017-12-12</td>\n",
       "      <td>NYK vs. LAL</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.727</td>\n",
       "      <td>15.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>25</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>16</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1  SEASON_ID     TEAM_ID TEAM_ABBREVIATION  \\\n",
       "1550        1550           386      22017  1610612752               NYK   \n",
       "1551        1551           387      22017  1610612752               NYK   \n",
       "1552        1552           388      22017  1610612752               NYK   \n",
       "1553        1553           389      22017  1610612752               NYK   \n",
       "1554        1554           390      22017  1610612752               NYK   \n",
       "1555        1555           391      22017  1610612752               NYK   \n",
       "1556        1556           392      22017  1610612752               NYK   \n",
       "1557        1557           393      22017  1610612752               NYK   \n",
       "1558        1558           394      22017  1610612752               NYK   \n",
       "1559        1559           395      22017  1610612752               NYK   \n",
       "\n",
       "            TEAM_NAME   GAME_ID   GAME_DATE      MATCHUP WL  ...  FT_PCT  \\\n",
       "1550  New York Knicks  21700532  2017-12-30    NYK @ NOP  W  ...   0.857   \n",
       "1551  New York Knicks  21700519  2017-12-28    NYK @ SAS  L  ...   0.909   \n",
       "1552  New York Knicks  21700509  2017-12-27    NYK @ CHI  L  ...   0.692   \n",
       "1553  New York Knicks  21700493  2017-12-25  NYK vs. PHI  L  ...   0.643   \n",
       "1554  New York Knicks  21700471  2017-12-22    NYK @ DET  L  ...   0.833   \n",
       "1555  New York Knicks  21700468  2017-12-21  NYK vs. BOS  W  ...   0.846   \n",
       "1556  New York Knicks  21700441  2017-12-18    NYK @ CHA  L  ...   0.800   \n",
       "1557  New York Knicks  21700431  2017-12-16  NYK vs. OKC  W  ...   0.808   \n",
       "1558  New York Knicks  21700414  2017-12-14    NYK @ BKN  W  ...   0.864   \n",
       "1559  New York Knicks  21700399  2017-12-12  NYK vs. LAL  W  ...   0.727   \n",
       "\n",
       "      OREB  DREB   REB  AST   STL  BLK  TOV  PF  PLUS_MINUS  \n",
       "1550   9.0  42.0  51.0   24   6.0    7    6  24         2.0  \n",
       "1551  12.0  32.0  44.0   31   6.0    8    9  26       -12.0  \n",
       "1552   7.0  44.0  51.0   21   6.0    5   12  17        -5.0  \n",
       "1553  18.0  27.0  45.0   18   7.0    5   10  21        -7.0  \n",
       "1554  16.0  35.0  51.0   25   6.0    9   14  20         3.6  \n",
       "1555  11.0  38.0  49.0   13   8.0    3   17  20         9.0  \n",
       "1556  10.0  27.0  37.0   21  10.0    5   17  16       -18.0  \n",
       "1557   6.0  29.0  35.0   21   9.0    3   13  22        15.0  \n",
       "1558  12.0  28.0  40.0   23  11.0    4   13  23         7.0  \n",
       "1559  15.0  34.0  49.0   25   7.0    7   14  16         4.0  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2017.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "54fb3197",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "L    27\n",
       "W    19\n",
       "Name: WL, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2017['WL'].value_counts() #wins vs losses in 2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "54395f31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(5,5)})\n",
    "plt.hist(df_2017['WL'], bins=5)\n",
    "plt.xlabel(\"WINS V LOSSES KNICKS 2017\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2160c515",
   "metadata": {},
   "outputs": [],
   "source": [
    "#all Knicks games in 2018\n",
    "df_2018 = df.loc[(df['GAME_DATE'] >= '2018-01-01') & (df['GAME_DATE'] <= '2019-01-01')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d80ad8f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>TEAM_NAME</th>\n",
       "      <th>GAME_ID</th>\n",
       "      <th>GAME_DATE</th>\n",
       "      <th>MATCHUP</th>\n",
       "      <th>WL</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PLUS_MINUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1504</th>\n",
       "      <td>1504</td>\n",
       "      <td>340</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701220</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>NYK @ CLE</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.923</td>\n",
       "      <td>8.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>30</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>22</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1505</th>\n",
       "      <td>1505</td>\n",
       "      <td>341</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701207</td>\n",
       "      <td>2018-04-09</td>\n",
       "      <td>NYK vs. CLE</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500</td>\n",
       "      <td>8.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>26</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>20</td>\n",
       "      <td>-16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1506</th>\n",
       "      <td>1506</td>\n",
       "      <td>342</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701192</td>\n",
       "      <td>2018-04-07</td>\n",
       "      <td>NYK vs. MIL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>13.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>30</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>-13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507</th>\n",
       "      <td>1507</td>\n",
       "      <td>343</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701186</td>\n",
       "      <td>2018-04-06</td>\n",
       "      <td>NYK vs. MIA</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.667</td>\n",
       "      <td>9.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>33</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1508</th>\n",
       "      <td>1508</td>\n",
       "      <td>344</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701159</td>\n",
       "      <td>2018-04-03</td>\n",
       "      <td>NYK vs. ORL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.750</td>\n",
       "      <td>7.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>17</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>-24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1509</th>\n",
       "      <td>1509</td>\n",
       "      <td>345</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701139</td>\n",
       "      <td>2018-03-31</td>\n",
       "      <td>NYK vs. DET</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.833</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>31</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>18</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1510</th>\n",
       "      <td>1510</td>\n",
       "      <td>346</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701118</td>\n",
       "      <td>2018-03-28</td>\n",
       "      <td>NYK @ PHI</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.769</td>\n",
       "      <td>10.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>20</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>22</td>\n",
       "      <td>-17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1511</th>\n",
       "      <td>1511</td>\n",
       "      <td>347</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701103</td>\n",
       "      <td>2018-03-26</td>\n",
       "      <td>NYK @ CHA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>11.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>25</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>27</td>\n",
       "      <td>-9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1512</th>\n",
       "      <td>1512</td>\n",
       "      <td>348</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701098</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>NYK @ WAS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.867</td>\n",
       "      <td>10.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>26</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>19</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1513</th>\n",
       "      <td>1513</td>\n",
       "      <td>349</td>\n",
       "      <td>22017</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21701081</td>\n",
       "      <td>2018-03-23</td>\n",
       "      <td>NYK vs. MIN</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.706</td>\n",
       "      <td>10.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>25</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>27</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1  SEASON_ID     TEAM_ID TEAM_ABBREVIATION  \\\n",
       "1504        1504           340      22017  1610612752               NYK   \n",
       "1505        1505           341      22017  1610612752               NYK   \n",
       "1506        1506           342      22017  1610612752               NYK   \n",
       "1507        1507           343      22017  1610612752               NYK   \n",
       "1508        1508           344      22017  1610612752               NYK   \n",
       "1509        1509           345      22017  1610612752               NYK   \n",
       "1510        1510           346      22017  1610612752               NYK   \n",
       "1511        1511           347      22017  1610612752               NYK   \n",
       "1512        1512           348      22017  1610612752               NYK   \n",
       "1513        1513           349      22017  1610612752               NYK   \n",
       "\n",
       "            TEAM_NAME   GAME_ID   GAME_DATE      MATCHUP WL  ...  FT_PCT  \\\n",
       "1504  New York Knicks  21701220  2018-04-11    NYK @ CLE  W  ...   0.923   \n",
       "1505  New York Knicks  21701207  2018-04-09  NYK vs. CLE  L  ...   0.500   \n",
       "1506  New York Knicks  21701192  2018-04-07  NYK vs. MIL  L  ...   1.000   \n",
       "1507  New York Knicks  21701186  2018-04-06  NYK vs. MIA  W  ...   0.667   \n",
       "1508  New York Knicks  21701159  2018-04-03  NYK vs. ORL  L  ...   0.750   \n",
       "1509  New York Knicks  21701139  2018-03-31  NYK vs. DET  L  ...   0.833   \n",
       "1510  New York Knicks  21701118  2018-03-28    NYK @ PHI  L  ...   0.769   \n",
       "1511  New York Knicks  21701103  2018-03-26    NYK @ CHA  L  ...   1.000   \n",
       "1512  New York Knicks  21701098  2018-03-25    NYK @ WAS  W  ...   0.867   \n",
       "1513  New York Knicks  21701081  2018-03-23  NYK vs. MIN  L  ...   0.706   \n",
       "\n",
       "      OREB  DREB   REB  AST   STL  BLK  TOV  PF  PLUS_MINUS  \n",
       "1504   8.0  31.0  39.0   30  10.0    3   15  22        12.0  \n",
       "1505   8.0  29.0  37.0   26   4.0    7   14  20       -16.0  \n",
       "1506  13.0  31.0  44.0   30   3.0    7    8  17       -13.0  \n",
       "1507   9.0  42.0  51.0   33   7.0    5   12  23        24.0  \n",
       "1508   7.0  35.0  42.0   17   5.0    9   11  17       -24.0  \n",
       "1509   9.0  31.0  40.0   31   4.0    1   14  18        -6.0  \n",
       "1510  10.0  36.0  46.0   20   4.0    5   16  22       -17.0  \n",
       "1511  11.0  30.0  41.0   25   6.0    1   10  27        -9.0  \n",
       "1512  10.0  34.0  44.0   26  10.0    6   14  19         4.0  \n",
       "1513  10.0  32.0  42.0   25   9.0    0   10  27        -4.0  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2018.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f9d301a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "L    69\n",
       "W    25\n",
       "Name: WL, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2018['WL'].value_counts() #wins vs losses in 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "17698bdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(5,5)})\n",
    "plt.hist(df_2018['WL'], bins=5)\n",
    "plt.xlabel(\"WINS V LOSSES KNICKS 2018\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "deaa51e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#all Knicks games in 2019\n",
    "df_2019 = df.loc[(df['GAME_DATE'] >= '2019-01-01') & (df['GAME_DATE'] <= '2020-01-01')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5b3d3cc1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>TEAM_NAME</th>\n",
       "      <th>GAME_ID</th>\n",
       "      <th>GAME_DATE</th>\n",
       "      <th>MATCHUP</th>\n",
       "      <th>WL</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PLUS_MINUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4437</th>\n",
       "      <td>4437</td>\n",
       "      <td>248</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801223</td>\n",
       "      <td>2019-04-10</td>\n",
       "      <td>NYK vs. DET</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.720</td>\n",
       "      <td>4.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>23</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "      <td>-26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4438</th>\n",
       "      <td>4438</td>\n",
       "      <td>249</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801213</td>\n",
       "      <td>2019-04-09</td>\n",
       "      <td>NYK @ CHI</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.615</td>\n",
       "      <td>11.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>16</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4439</th>\n",
       "      <td>4439</td>\n",
       "      <td>250</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801204</td>\n",
       "      <td>2019-04-07</td>\n",
       "      <td>NYK vs. WAS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.737</td>\n",
       "      <td>7.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>24</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4440</th>\n",
       "      <td>4440</td>\n",
       "      <td>251</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801184</td>\n",
       "      <td>2019-04-05</td>\n",
       "      <td>NYK @ HOU</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.593</td>\n",
       "      <td>5.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>22</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "      <td>-24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4441</th>\n",
       "      <td>4441</td>\n",
       "      <td>252</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801166</td>\n",
       "      <td>2019-04-03</td>\n",
       "      <td>NYK @ ORL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.857</td>\n",
       "      <td>8.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>21</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>18</td>\n",
       "      <td>-14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4442</th>\n",
       "      <td>4442</td>\n",
       "      <td>253</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801155</td>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>NYK vs. CHI</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.840</td>\n",
       "      <td>6.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>24</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9</td>\n",
       "      <td>16</td>\n",
       "      <td>18</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4443</th>\n",
       "      <td>4443</td>\n",
       "      <td>254</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801141</td>\n",
       "      <td>2019-03-30</td>\n",
       "      <td>NYK vs. MIA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.840</td>\n",
       "      <td>8.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>20</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>16</td>\n",
       "      <td>-8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4444</th>\n",
       "      <td>4444</td>\n",
       "      <td>255</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801125</td>\n",
       "      <td>2019-03-28</td>\n",
       "      <td>NYK vs. TOR</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.750</td>\n",
       "      <td>14.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>16</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>16</td>\n",
       "      <td>22</td>\n",
       "      <td>-25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4445</th>\n",
       "      <td>4445</td>\n",
       "      <td>256</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801095</td>\n",
       "      <td>2019-03-24</td>\n",
       "      <td>NYK vs. LAC</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.880</td>\n",
       "      <td>13.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>22</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>24</td>\n",
       "      <td>-11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4446</th>\n",
       "      <td>4446</td>\n",
       "      <td>257</td>\n",
       "      <td>22018</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21801082</td>\n",
       "      <td>2019-03-22</td>\n",
       "      <td>NYK vs. DEN</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.762</td>\n",
       "      <td>8.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>20</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>15</td>\n",
       "      <td>-18.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1  SEASON_ID     TEAM_ID TEAM_ABBREVIATION  \\\n",
       "4437        4437           248      22018  1610612752               NYK   \n",
       "4438        4438           249      22018  1610612752               NYK   \n",
       "4439        4439           250      22018  1610612752               NYK   \n",
       "4440        4440           251      22018  1610612752               NYK   \n",
       "4441        4441           252      22018  1610612752               NYK   \n",
       "4442        4442           253      22018  1610612752               NYK   \n",
       "4443        4443           254      22018  1610612752               NYK   \n",
       "4444        4444           255      22018  1610612752               NYK   \n",
       "4445        4445           256      22018  1610612752               NYK   \n",
       "4446        4446           257      22018  1610612752               NYK   \n",
       "\n",
       "            TEAM_NAME   GAME_ID   GAME_DATE      MATCHUP WL  ...  FT_PCT  \\\n",
       "4437  New York Knicks  21801223  2019-04-10  NYK vs. DET  L  ...   0.720   \n",
       "4438  New York Knicks  21801213  2019-04-09    NYK @ CHI  W  ...   0.615   \n",
       "4439  New York Knicks  21801204  2019-04-07  NYK vs. WAS  W  ...   0.737   \n",
       "4440  New York Knicks  21801184  2019-04-05    NYK @ HOU  L  ...   0.593   \n",
       "4441  New York Knicks  21801166  2019-04-03    NYK @ ORL  L  ...   0.857   \n",
       "4442  New York Knicks  21801155  2019-04-01  NYK vs. CHI  W  ...   0.840   \n",
       "4443  New York Knicks  21801141  2019-03-30  NYK vs. MIA  L  ...   0.840   \n",
       "4444  New York Knicks  21801125  2019-03-28  NYK vs. TOR  L  ...   0.750   \n",
       "4445  New York Knicks  21801095  2019-03-24  NYK vs. LAC  L  ...   0.880   \n",
       "4446  New York Knicks  21801082  2019-03-22  NYK vs. DEN  L  ...   0.762   \n",
       "\n",
       "      OREB  DREB   REB  AST   STL  BLK  TOV  PF  PLUS_MINUS  \n",
       "4437   4.0  29.0  33.0   23   7.0    5   11  17       -26.0  \n",
       "4438  11.0  50.0  61.0   17   0.0   10    9  16        10.0  \n",
       "4439   7.0  36.0  43.0   24   5.0    9   15  14         3.0  \n",
       "4440   5.0  48.0  53.0   22   3.0    6   15  17       -24.0  \n",
       "4441   8.0  31.0  39.0   21  10.0    5   12  18       -14.0  \n",
       "4442   6.0  38.0  44.0   24   2.0    9   16  18         8.0  \n",
       "4443   8.0  34.0  42.0   20  10.0    7   18  16        -8.0  \n",
       "4444  14.0  40.0  54.0   16   3.0    5   16  22       -25.0  \n",
       "4445  13.0  31.0  44.0   22   5.0    7   14  24       -11.0  \n",
       "4446   8.0  37.0  45.0   20   3.0    5    7  15       -18.0  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b435eed8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "L    67\n",
       "W    21\n",
       "Name: WL, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2019['WL'].value_counts() #wins vs losses in 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "eebb88ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(5,5)})\n",
    "plt.hist(df_2019['WL'], bins=5)\n",
    "plt.xlabel(\"WINS V LOSSES KNICKS 2019\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "855cde10",
   "metadata": {},
   "outputs": [],
   "source": [
    "#all Knicks games in 2020\n",
    "df_2020 = df.loc[(df['GAME_DATE'] >= '2020-01-01') & (df['GAME_DATE'] <= '2021-01-01')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1e3269ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>TEAM_NAME</th>\n",
       "      <th>GAME_ID</th>\n",
       "      <th>GAME_DATE</th>\n",
       "      <th>MATCHUP</th>\n",
       "      <th>WL</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PLUS_MINUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7286</th>\n",
       "      <td>7286</td>\n",
       "      <td>173</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900969</td>\n",
       "      <td>2020-03-11</td>\n",
       "      <td>NYK @ ATL</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.735</td>\n",
       "      <td>6.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>32</td>\n",
       "      <td>14.0</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7287</th>\n",
       "      <td>7287</td>\n",
       "      <td>174</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900961</td>\n",
       "      <td>2020-03-10</td>\n",
       "      <td>NYK @ WAS</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.742</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>30</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>29</td>\n",
       "      <td>-7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7288</th>\n",
       "      <td>7288</td>\n",
       "      <td>175</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900955</td>\n",
       "      <td>2020-03-08</td>\n",
       "      <td>NYK vs. DET</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.720</td>\n",
       "      <td>13.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>15</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>16</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7289</th>\n",
       "      <td>7289</td>\n",
       "      <td>176</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900932</td>\n",
       "      <td>2020-03-06</td>\n",
       "      <td>NYK vs. OKC</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.773</td>\n",
       "      <td>13.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>19</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>-23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7290</th>\n",
       "      <td>7290</td>\n",
       "      <td>177</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900921</td>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>NYK vs. UTA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.833</td>\n",
       "      <td>11.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>23</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>-8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7291</th>\n",
       "      <td>7291</td>\n",
       "      <td>178</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900903</td>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>NYK vs. HOU</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.633</td>\n",
       "      <td>20.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>26</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>19</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7292</th>\n",
       "      <td>7292</td>\n",
       "      <td>179</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900887</td>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>NYK vs. CHI</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.697</td>\n",
       "      <td>17.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>29</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>19</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7293</th>\n",
       "      <td>7293</td>\n",
       "      <td>180</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900873</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>NYK @ PHI</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.583</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>28</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>-9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7294</th>\n",
       "      <td>7294</td>\n",
       "      <td>181</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900864</td>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>NYK @ CHA</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.647</td>\n",
       "      <td>13.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>22</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>24</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7295</th>\n",
       "      <td>7295</td>\n",
       "      <td>182</td>\n",
       "      <td>22019</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>21900853</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>NYK @ HOU</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.700</td>\n",
       "      <td>16.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>20</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>-11.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1  SEASON_ID     TEAM_ID TEAM_ABBREVIATION  \\\n",
       "7286        7286           173      22019  1610612752               NYK   \n",
       "7287        7287           174      22019  1610612752               NYK   \n",
       "7288        7288           175      22019  1610612752               NYK   \n",
       "7289        7289           176      22019  1610612752               NYK   \n",
       "7290        7290           177      22019  1610612752               NYK   \n",
       "7291        7291           178      22019  1610612752               NYK   \n",
       "7292        7292           179      22019  1610612752               NYK   \n",
       "7293        7293           180      22019  1610612752               NYK   \n",
       "7294        7294           181      22019  1610612752               NYK   \n",
       "7295        7295           182      22019  1610612752               NYK   \n",
       "\n",
       "            TEAM_NAME   GAME_ID   GAME_DATE      MATCHUP WL  ...  FT_PCT  \\\n",
       "7286  New York Knicks  21900969  2020-03-11    NYK @ ATL  W  ...   0.735   \n",
       "7287  New York Knicks  21900961  2020-03-10    NYK @ WAS  L  ...   0.742   \n",
       "7288  New York Knicks  21900955  2020-03-08  NYK vs. DET  W  ...   0.720   \n",
       "7289  New York Knicks  21900932  2020-03-06  NYK vs. OKC  L  ...   0.773   \n",
       "7290  New York Knicks  21900921  2020-03-04  NYK vs. UTA  L  ...   0.833   \n",
       "7291  New York Knicks  21900903  2020-03-02  NYK vs. HOU  W  ...   0.633   \n",
       "7292  New York Knicks  21900887  2020-02-29  NYK vs. CHI  W  ...   0.697   \n",
       "7293  New York Knicks  21900873  2020-02-27    NYK @ PHI  L  ...   0.583   \n",
       "7294  New York Knicks  21900864  2020-02-26    NYK @ CHA  L  ...   0.647   \n",
       "7295  New York Knicks  21900853  2020-02-24    NYK @ HOU  L  ...   0.700   \n",
       "\n",
       "      OREB  DREB   REB  AST   STL  BLK  TOV  PF  PLUS_MINUS  \n",
       "7286   6.0  41.0  47.0   32  14.0    9   12  23         5.0  \n",
       "7287   8.0  28.0  36.0   30  10.0    3   18  29        -7.0  \n",
       "7288  13.0  38.0  51.0   15  10.0    5    9  16        12.0  \n",
       "7289  13.0  35.0  48.0   19   4.0    8   12  20       -23.0  \n",
       "7290  11.0  31.0  42.0   23   3.0    1   13  18        -8.0  \n",
       "7291  20.0  45.0  65.0   26   6.0    7   17  19         2.0  \n",
       "7292  17.0  33.0  50.0   29   6.0    4   16  19        10.0  \n",
       "7293   9.0  30.0  39.0   28   2.0    3    8  11        -9.0  \n",
       "7294  13.0  29.0  42.0   22   5.0    6   15  24        -6.0  \n",
       "7295  16.0  38.0  54.0   20  12.0    8   17  21       -11.0  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2020.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "74029b57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "L    25\n",
       "W    17\n",
       "Name: WL, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2020['WL'].value_counts() #wins vs losses in 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "db5d72ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(5,5)})\n",
    "plt.hist(df_2020['WL'], bins=5)\n",
    "plt.xlabel(\"WINS V LOSSES KNICKS 2020\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7e822584",
   "metadata": {},
   "outputs": [],
   "source": [
    "#all Knicks games in 2021\n",
    "df_2021 = df.loc[(df['GAME_DATE'] >= '2021-01-01') & (df['GAME_DATE'] <= '2022-01-01')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "69bb18b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>TEAM_NAME</th>\n",
       "      <th>GAME_ID</th>\n",
       "      <th>GAME_DATE</th>\n",
       "      <th>MATCHUP</th>\n",
       "      <th>WL</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PLUS_MINUS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9830</th>\n",
       "      <td>9830</td>\n",
       "      <td>92</td>\n",
       "      <td>42020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>42000135</td>\n",
       "      <td>2021-06-02</td>\n",
       "      <td>NYK vs. ATL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.833</td>\n",
       "      <td>14.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>19</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>22</td>\n",
       "      <td>-14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9831</th>\n",
       "      <td>9831</td>\n",
       "      <td>93</td>\n",
       "      <td>42020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>42000134</td>\n",
       "      <td>2021-05-30</td>\n",
       "      <td>NYK @ ATL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.826</td>\n",
       "      <td>6.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>24</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "      <td>-17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9832</th>\n",
       "      <td>9832</td>\n",
       "      <td>94</td>\n",
       "      <td>42020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>42000133</td>\n",
       "      <td>2021-05-28</td>\n",
       "      <td>NYK @ ATL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.900</td>\n",
       "      <td>13.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>14</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>21</td>\n",
       "      <td>-11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9833</th>\n",
       "      <td>9833</td>\n",
       "      <td>95</td>\n",
       "      <td>42020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>42000132</td>\n",
       "      <td>2021-05-26</td>\n",
       "      <td>NYK vs. ATL</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.739</td>\n",
       "      <td>13.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>15</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9834</th>\n",
       "      <td>9834</td>\n",
       "      <td>96</td>\n",
       "      <td>42020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>42000131</td>\n",
       "      <td>2021-05-23</td>\n",
       "      <td>NYK vs. ATL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.733</td>\n",
       "      <td>13.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>21</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>16</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9835</th>\n",
       "      <td>9835</td>\n",
       "      <td>97</td>\n",
       "      <td>22020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>22001073</td>\n",
       "      <td>2021-05-16</td>\n",
       "      <td>NYK vs. BOS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.789</td>\n",
       "      <td>4.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>16</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>17</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9836</th>\n",
       "      <td>9836</td>\n",
       "      <td>98</td>\n",
       "      <td>22020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>22001064</td>\n",
       "      <td>2021-05-15</td>\n",
       "      <td>NYK vs. CHA</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>0.800</td>\n",
       "      <td>7.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>29</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9837</th>\n",
       "      <td>9837</td>\n",
       "      <td>99</td>\n",
       "      <td>22020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>22000458</td>\n",
       "      <td>2021-05-13</td>\n",
       "      <td>NYK vs. SAS</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>23</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9838</th>\n",
       "      <td>9838</td>\n",
       "      <td>100</td>\n",
       "      <td>22020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>22001041</td>\n",
       "      <td>2021-05-11</td>\n",
       "      <td>NYK @ LAL</td>\n",
       "      <td>L</td>\n",
       "      <td>...</td>\n",
       "      <td>0.913</td>\n",
       "      <td>5.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>19</td>\n",
       "      <td>8.0</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>21</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9839</th>\n",
       "      <td>9839</td>\n",
       "      <td>101</td>\n",
       "      <td>22020</td>\n",
       "      <td>1610612752</td>\n",
       "      <td>NYK</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>22001019</td>\n",
       "      <td>2021-05-09</td>\n",
       "      <td>NYK @ LAC</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000</td>\n",
       "      <td>8.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>25</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>17</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1  SEASON_ID     TEAM_ID TEAM_ABBREVIATION  \\\n",
       "9830        9830            92      42020  1610612752               NYK   \n",
       "9831        9831            93      42020  1610612752               NYK   \n",
       "9832        9832            94      42020  1610612752               NYK   \n",
       "9833        9833            95      42020  1610612752               NYK   \n",
       "9834        9834            96      42020  1610612752               NYK   \n",
       "9835        9835            97      22020  1610612752               NYK   \n",
       "9836        9836            98      22020  1610612752               NYK   \n",
       "9837        9837            99      22020  1610612752               NYK   \n",
       "9838        9838           100      22020  1610612752               NYK   \n",
       "9839        9839           101      22020  1610612752               NYK   \n",
       "\n",
       "            TEAM_NAME   GAME_ID   GAME_DATE      MATCHUP WL  ...  FT_PCT  \\\n",
       "9830  New York Knicks  42000135  2021-06-02  NYK vs. ATL  L  ...   0.833   \n",
       "9831  New York Knicks  42000134  2021-05-30    NYK @ ATL  L  ...   0.826   \n",
       "9832  New York Knicks  42000133  2021-05-28    NYK @ ATL  L  ...   0.900   \n",
       "9833  New York Knicks  42000132  2021-05-26  NYK vs. ATL  W  ...   0.739   \n",
       "9834  New York Knicks  42000131  2021-05-23  NYK vs. ATL  L  ...   0.733   \n",
       "9835  New York Knicks  22001073  2021-05-16  NYK vs. BOS  W  ...   0.789   \n",
       "9836  New York Knicks  22001064  2021-05-15  NYK vs. CHA  W  ...   0.800   \n",
       "9837  New York Knicks  22000458  2021-05-13  NYK vs. SAS  W  ...   1.000   \n",
       "9838  New York Knicks  22001041  2021-05-11    NYK @ LAL  L  ...   0.913   \n",
       "9839  New York Knicks  22001019  2021-05-09    NYK @ LAC  W  ...   1.000   \n",
       "\n",
       "      OREB  DREB   REB  AST  STL  BLK  TOV  PF  PLUS_MINUS  \n",
       "9830  14.0  31.0  45.0   19  5.0    4   16  22       -14.0  \n",
       "9831   6.0  33.0  39.0   24  7.0    2    9  20       -17.0  \n",
       "9832  13.0  32.0  45.0   14  6.0    2   11  21       -11.0  \n",
       "9833  13.0  41.0  54.0   15  8.0    2   10  20         9.0  \n",
       "9834  13.0  36.0  49.0   21  3.0    4   11  16        -2.0  \n",
       "9835   4.0  37.0  41.0   16  7.0    6   10  17         4.0  \n",
       "9836   7.0  43.0  50.0   29  3.0    7    9  20         9.0  \n",
       "9837  10.0  38.0  48.0   23  7.0    8   10  19         4.0  \n",
       "9838   5.0  36.0  41.0   19  8.0    3    9  21        -2.0  \n",
       "9839   8.0  37.0  45.0   25  7.0    5   10  17         6.0  \n",
       "\n",
       "[10 rows x 30 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2021.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "bdac67d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "W    65\n",
       "L    53\n",
       "Name: WL, dtype: int64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2021['WL'].value_counts() #wins vs losses in 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2d191c77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={'figure.figsize':(5,5)})\n",
    "plt.hist(df_2021['WL'], bins=5)\n",
    "plt.xlabel(\"WINS V LOSSES KNICKS 2021\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "a67cb64d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y=[1.4,2.76,3.19,1.4,1.19]\n",
    "x=[2017,2018,2019,2020,2021]\n",
    "\n",
    "plt.plot(x,y,marker=\"o\")\n",
    "plt.xlabel(\"Loss/Win Ratio\")\n",
    "plt.ylabel(\"Years\")\n",
    "plt.title(\"Loss/Win RATIO FROM 2017 to 2021\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c047758b",
   "metadata": {},
   "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
}