DataSetBuild.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5e0a2cbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import os\n",
    "import pickle\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.linear_model import ElasticNet\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.ensemble import AdaBoostRegressor\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from nba_api.stats.endpoints import playercareerstats\n",
    "from nba_api.stats.static import players\n",
    "from nba_api.stats.endpoints import teamyearbyyearstats\n",
    "from nba_api.stats.static import teams\n",
    "from nba_api.stats.endpoints import teamgamelogs\n",
    "\n",
    "\"\"\"This notebook is the second build from the first dataset 'NBA_Dataset' who was build using basketball reference.\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e5c7606a",
   "metadata": {},
   "outputs": [],
   "source": [
    "player_dataset=pd.read_csv('NBA_Dataset.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "32397c28",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>player</th>\n",
       "      <th>pos</th>\n",
       "      <th>age</th>\n",
       "      <th>team_id</th>\n",
       "      <th>g</th>\n",
       "      <th>gs</th>\n",
       "      <th>mp_per_g</th>\n",
       "      <th>fg_per_g</th>\n",
       "      <th>fga_per_g</th>\n",
       "      <th>...</th>\n",
       "      <th>ws</th>\n",
       "      <th>ws_per_48</th>\n",
       "      <th>obpm</th>\n",
       "      <th>dbpm</th>\n",
       "      <th>bpm</th>\n",
       "      <th>vorp</th>\n",
       "      <th>award_share</th>\n",
       "      <th>mov</th>\n",
       "      <th>mov_adj</th>\n",
       "      <th>win_loss_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1982</td>\n",
       "      <td>Kareem Abdul-Jabbar</td>\n",
       "      <td>C</td>\n",
       "      <td>34</td>\n",
       "      <td>LAL</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>35.2</td>\n",
       "      <td>9.9</td>\n",
       "      <td>17.1</td>\n",
       "      <td>...</td>\n",
       "      <td>10.7</td>\n",
       "      <td>0.192</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.37</td>\n",
       "      <td>0.695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1982</td>\n",
       "      <td>Alvan Adams</td>\n",
       "      <td>C</td>\n",
       "      <td>27</td>\n",
       "      <td>PHO</td>\n",
       "      <td>79</td>\n",
       "      <td>75</td>\n",
       "      <td>30.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>13.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.144</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3.45</td>\n",
       "      <td>3.05</td>\n",
       "      <td>0.561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1982</td>\n",
       "      <td>Mark Aguirre</td>\n",
       "      <td>SF</td>\n",
       "      <td>22</td>\n",
       "      <td>DAL</td>\n",
       "      <td>51</td>\n",
       "      <td>20</td>\n",
       "      <td>28.8</td>\n",
       "      <td>7.5</td>\n",
       "      <td>16.1</td>\n",
       "      <td>...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.061</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-4.43</td>\n",
       "      <td>-4.48</td>\n",
       "      <td>0.341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1982</td>\n",
       "      <td>Danny Ainge</td>\n",
       "      <td>SG</td>\n",
       "      <td>22</td>\n",
       "      <td>BOS</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>10.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.042</td>\n",
       "      <td>-3.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-2.7</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6.38</td>\n",
       "      <td>6.35</td>\n",
       "      <td>0.768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1982</td>\n",
       "      <td>Tiny Archibald</td>\n",
       "      <td>PG</td>\n",
       "      <td>33</td>\n",
       "      <td>BOS</td>\n",
       "      <td>68</td>\n",
       "      <td>51</td>\n",
       "      <td>31.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>9.6</td>\n",
       "      <td>...</td>\n",
       "      <td>5.2</td>\n",
       "      <td>0.115</td>\n",
       "      <td>1.4</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6.38</td>\n",
       "      <td>6.35</td>\n",
       "      <td>0.768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17692</th>\n",
       "      <td>2022</td>\n",
       "      <td>Thaddeus Young</td>\n",
       "      <td>PF</td>\n",
       "      <td>33</td>\n",
       "      <td>TOT</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "      <td>16.3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>5.2</td>\n",
       "      <td>...</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.126</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17693</th>\n",
       "      <td>2022</td>\n",
       "      <td>Trae Young</td>\n",
       "      <td>PG</td>\n",
       "      <td>23</td>\n",
       "      <td>ATL</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>34.9</td>\n",
       "      <td>9.4</td>\n",
       "      <td>20.3</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.181</td>\n",
       "      <td>7.1</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1.55</td>\n",
       "      <td>0.524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17694</th>\n",
       "      <td>2022</td>\n",
       "      <td>Omer Yurtseven</td>\n",
       "      <td>C</td>\n",
       "      <td>23</td>\n",
       "      <td>MIA</td>\n",
       "      <td>56</td>\n",
       "      <td>12</td>\n",
       "      <td>12.6</td>\n",
       "      <td>2.3</td>\n",
       "      <td>4.4</td>\n",
       "      <td>...</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.145</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.23</td>\n",
       "      <td>0.646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17695</th>\n",
       "      <td>2022</td>\n",
       "      <td>Cody Zeller</td>\n",
       "      <td>C</td>\n",
       "      <td>29</td>\n",
       "      <td>POR</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>13.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>3.3</td>\n",
       "      <td>...</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.143</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-2.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-8.88</td>\n",
       "      <td>-8.55</td>\n",
       "      <td>0.329</td>\n",
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       "    <tr>\n",
       "      <th>17696</th>\n",
       "      <td>2022</td>\n",
       "      <td>Ivica Zubac</td>\n",
       "      <td>C</td>\n",
       "      <td>24</td>\n",
       "      <td>LAC</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>24.4</td>\n",
       "      <td>4.1</td>\n",
       "      <td>6.5</td>\n",
       "      <td>...</td>\n",
       "      <td>7.2</td>\n",
       "      <td>0.187</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.512</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17697 rows × 55 columns</p>\n",
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      ],
      "text/plain": [
       "       season               player pos  age team_id   g  gs  mp_per_g  \\\n",
       "0        1982  Kareem Abdul-Jabbar   C   34     LAL  76  76      35.2   \n",
       "1        1982          Alvan Adams   C   27     PHO  79  75      30.3   \n",
       "2        1982         Mark Aguirre  SF   22     DAL  51  20      28.8   \n",
       "3        1982          Danny Ainge  SG   22     BOS  53   1      10.6   \n",
       "4        1982       Tiny Archibald  PG   33     BOS  68  51      31.9   \n",
       "...       ...                  ...  ..  ...     ...  ..  ..       ...   \n",
       "17692    2022       Thaddeus Young  PF   33     TOT  52   1      16.3   \n",
       "17693    2022           Trae Young  PG   23     ATL  76  76      34.9   \n",
       "17694    2022       Omer Yurtseven   C   23     MIA  56  12      12.6   \n",
       "17695    2022          Cody Zeller   C   29     POR  27   0      13.1   \n",
       "17696    2022          Ivica Zubac   C   24     LAC  76  76      24.4   \n",
       "\n",
       "       fg_per_g  fga_per_g  ...    ws  ws_per_48  obpm  dbpm  bpm  vorp  \\\n",
       "0           9.9       17.1  ...  10.7      0.192   3.8   1.2  5.0   4.7   \n",
       "1           6.4       13.0  ...   7.2      0.144   1.4   2.2  3.6   3.4   \n",
       "2           7.5       16.1  ...   1.9      0.061   2.3  -1.6  0.7   1.0   \n",
       "3           1.5        4.2  ...   0.5      0.042  -3.7   1.0 -2.7  -0.1   \n",
       "4           4.5        9.6  ...   5.2      0.115   1.4  -1.3  0.1   1.1   \n",
       "...         ...        ...  ...   ...        ...   ...   ...  ...   ...   \n",
       "17692       2.7        5.2  ...   2.2      0.126   0.1   2.1  2.2   0.9   \n",
       "17693       9.4       20.3  ...  10.0      0.181   7.1  -2.0  5.2   4.8   \n",
       "17694       2.3        4.4  ...   2.1      0.145  -1.4   0.4 -1.0   0.2   \n",
       "17695       1.9        3.3  ...   1.1      0.143  -1.2  -1.0 -2.1   0.0   \n",
       "17696       4.1        6.5  ...   7.2      0.187  -0.1   0.8  0.7   1.3   \n",
       "\n",
       "       award_share   mov  mov_adj  win_loss_pct  \n",
       "0            0.045  4.87     4.37         0.695  \n",
       "1            0.000  3.45     3.05         0.561  \n",
       "2            0.000 -4.43    -4.48         0.341  \n",
       "3            0.000  6.38     6.35         0.768  \n",
       "4            0.000  6.38     6.35         0.768  \n",
       "...            ...   ...      ...           ...  \n",
       "17692        0.000  0.00     0.00         0.500  \n",
       "17693        0.000  1.56     1.55         0.524  \n",
       "17694        0.000  4.45     4.23         0.646  \n",
       "17695        0.000 -8.88    -8.55         0.329  \n",
       "17696        0.000  0.02     0.09         0.512  \n",
       "\n",
       "[17697 rows x 55 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7e8bc775",
   "metadata": {},
   "outputs": [],
   "source": [
    "team_data= pd.DataFrame(teams.get_teams())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ea4db3f9",
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>full_name</th>\n",
       "      <th>abbreviation</th>\n",
       "      <th>nickname</th>\n",
       "      <th>city</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1610612737</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>ATL</td>\n",
       "      <td>Hawks</td>\n",
       "      <td>Atlanta</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>1949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1610612738</td>\n",
       "      <td>Boston Celtics</td>\n",
       "      <td>BOS</td>\n",
       "      <td>Celtics</td>\n",
       "      <td>Boston</td>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>1946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1610612739</td>\n",
       "      <td>Cleveland Cavaliers</td>\n",
       "      <td>CLE</td>\n",
       "      <td>Cavaliers</td>\n",
       "      <td>Cleveland</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1610612740</td>\n",
       "      <td>New Orleans Pelicans</td>\n",
       "      <td>NOP</td>\n",
       "      <td>Pelicans</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>2002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1610612741</td>\n",
       "      <td>Chicago Bulls</td>\n",
       "      <td>CHI</td>\n",
       "      <td>Bulls</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>1966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1610612742</td>\n",
       "      <td>Dallas Mavericks</td>\n",
       "      <td>DAL</td>\n",
       "      <td>Mavericks</td>\n",
       "      <td>Dallas</td>\n",
       "      <td>Texas</td>\n",
       "      <td>1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1610612743</td>\n",
       "      <td>Denver Nuggets</td>\n",
       "      <td>DEN</td>\n",
       "      <td>Nuggets</td>\n",
       "      <td>Denver</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>1976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>Golden State Warriors</td>\n",
       "      <td>GSW</td>\n",
       "      <td>Warriors</td>\n",
       "      <td>Golden State</td>\n",
       "      <td>California</td>\n",
       "      <td>1946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1610612745</td>\n",
       "      <td>Houston Rockets</td>\n",
       "      <td>HOU</td>\n",
       "      <td>Rockets</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Texas</td>\n",
       "      <td>1967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1610612746</td>\n",
       "      <td>Los Angeles Clippers</td>\n",
       "      <td>LAC</td>\n",
       "      <td>Clippers</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1610612747</td>\n",
       "      <td>Los Angeles Lakers</td>\n",
       "      <td>LAL</td>\n",
       "      <td>Lakers</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>1948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1610612748</td>\n",
       "      <td>Miami Heat</td>\n",
       "      <td>MIA</td>\n",
       "      <td>Heat</td>\n",
       "      <td>Miami</td>\n",
       "      <td>Florida</td>\n",
       "      <td>1988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1610612749</td>\n",
       "      <td>Milwaukee Bucks</td>\n",
       "      <td>MIL</td>\n",
       "      <td>Bucks</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>1968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1610612750</td>\n",
       "      <td>Minnesota Timberwolves</td>\n",
       "      <td>MIN</td>\n",
       "      <td>Timberwolves</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>1989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1610612751</td>\n",
       "      <td>Brooklyn Nets</td>\n",
       "      <td>BKN</td>\n",
       "      <td>Nets</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "      <td>1976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1610612752</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>NYK</td>\n",
       "      <td>Knicks</td>\n",
       "      <td>New York</td>\n",
       "      <td>New York</td>\n",
       "      <td>1946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1610612753</td>\n",
       "      <td>Orlando Magic</td>\n",
       "      <td>ORL</td>\n",
       "      <td>Magic</td>\n",
       "      <td>Orlando</td>\n",
       "      <td>Florida</td>\n",
       "      <td>1989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1610612754</td>\n",
       "      <td>Indiana Pacers</td>\n",
       "      <td>IND</td>\n",
       "      <td>Pacers</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>1976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1610612755</td>\n",
       "      <td>Philadelphia 76ers</td>\n",
       "      <td>PHI</td>\n",
       "      <td>76ers</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>1949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1610612756</td>\n",
       "      <td>Phoenix Suns</td>\n",
       "      <td>PHX</td>\n",
       "      <td>Suns</td>\n",
       "      <td>Phoenix</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>1968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1610612757</td>\n",
       "      <td>Portland Trail Blazers</td>\n",
       "      <td>POR</td>\n",
       "      <td>Trail Blazers</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>1970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1610612758</td>\n",
       "      <td>Sacramento Kings</td>\n",
       "      <td>SAC</td>\n",
       "      <td>Kings</td>\n",
       "      <td>Sacramento</td>\n",
       "      <td>California</td>\n",
       "      <td>1948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1610612759</td>\n",
       "      <td>San Antonio Spurs</td>\n",
       "      <td>SAS</td>\n",
       "      <td>Spurs</td>\n",
       "      <td>San Antonio</td>\n",
       "      <td>Texas</td>\n",
       "      <td>1976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1610612760</td>\n",
       "      <td>Oklahoma City Thunder</td>\n",
       "      <td>OKC</td>\n",
       "      <td>Thunder</td>\n",
       "      <td>Oklahoma City</td>\n",
       "      <td>Oklahoma</td>\n",
       "      <td>1967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1610612761</td>\n",
       "      <td>Toronto Raptors</td>\n",
       "      <td>TOR</td>\n",
       "      <td>Raptors</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>1995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1610612762</td>\n",
       "      <td>Utah Jazz</td>\n",
       "      <td>UTA</td>\n",
       "      <td>Jazz</td>\n",
       "      <td>Utah</td>\n",
       "      <td>Utah</td>\n",
       "      <td>1974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>Memphis Grizzlies</td>\n",
       "      <td>MEM</td>\n",
       "      <td>Grizzlies</td>\n",
       "      <td>Memphis</td>\n",
       "      <td>Tennessee</td>\n",
       "      <td>1995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1610612764</td>\n",
       "      <td>Washington Wizards</td>\n",
       "      <td>WAS</td>\n",
       "      <td>Wizards</td>\n",
       "      <td>Washington</td>\n",
       "      <td>District of Columbia</td>\n",
       "      <td>1961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1610612765</td>\n",
       "      <td>Detroit Pistons</td>\n",
       "      <td>DET</td>\n",
       "      <td>Pistons</td>\n",
       "      <td>Detroit</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>1948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1610612766</td>\n",
       "      <td>Charlotte Hornets</td>\n",
       "      <td>CHA</td>\n",
       "      <td>Hornets</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>North Carolina</td>\n",
       "      <td>1988</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            id               full_name abbreviation       nickname  \\\n",
       "0   1610612737           Atlanta Hawks          ATL          Hawks   \n",
       "1   1610612738          Boston Celtics          BOS        Celtics   \n",
       "2   1610612739     Cleveland Cavaliers          CLE      Cavaliers   \n",
       "3   1610612740    New Orleans Pelicans          NOP       Pelicans   \n",
       "4   1610612741           Chicago Bulls          CHI          Bulls   \n",
       "5   1610612742        Dallas Mavericks          DAL      Mavericks   \n",
       "6   1610612743          Denver Nuggets          DEN        Nuggets   \n",
       "7   1610612744   Golden State Warriors          GSW       Warriors   \n",
       "8   1610612745         Houston Rockets          HOU        Rockets   \n",
       "9   1610612746    Los Angeles Clippers          LAC       Clippers   \n",
       "10  1610612747      Los Angeles Lakers          LAL         Lakers   \n",
       "11  1610612748              Miami Heat          MIA           Heat   \n",
       "12  1610612749         Milwaukee Bucks          MIL          Bucks   \n",
       "13  1610612750  Minnesota Timberwolves          MIN   Timberwolves   \n",
       "14  1610612751           Brooklyn Nets          BKN           Nets   \n",
       "15  1610612752         New York Knicks          NYK         Knicks   \n",
       "16  1610612753           Orlando Magic          ORL          Magic   \n",
       "17  1610612754          Indiana Pacers          IND         Pacers   \n",
       "18  1610612755      Philadelphia 76ers          PHI          76ers   \n",
       "19  1610612756            Phoenix Suns          PHX           Suns   \n",
       "20  1610612757  Portland Trail Blazers          POR  Trail Blazers   \n",
       "21  1610612758        Sacramento Kings          SAC          Kings   \n",
       "22  1610612759       San Antonio Spurs          SAS          Spurs   \n",
       "23  1610612760   Oklahoma City Thunder          OKC        Thunder   \n",
       "24  1610612761         Toronto Raptors          TOR        Raptors   \n",
       "25  1610612762               Utah Jazz          UTA           Jazz   \n",
       "26  1610612763       Memphis Grizzlies          MEM      Grizzlies   \n",
       "27  1610612764      Washington Wizards          WAS        Wizards   \n",
       "28  1610612765         Detroit Pistons          DET        Pistons   \n",
       "29  1610612766       Charlotte Hornets          CHA        Hornets   \n",
       "\n",
       "             city                 state  year_founded  \n",
       "0         Atlanta               Georgia          1949  \n",
       "1          Boston         Massachusetts          1946  \n",
       "2       Cleveland                  Ohio          1970  \n",
       "3     New Orleans             Louisiana          2002  \n",
       "4         Chicago              Illinois          1966  \n",
       "5          Dallas                 Texas          1980  \n",
       "6          Denver              Colorado          1976  \n",
       "7    Golden State            California          1946  \n",
       "8         Houston                 Texas          1967  \n",
       "9     Los Angeles            California          1970  \n",
       "10    Los Angeles            California          1948  \n",
       "11          Miami               Florida          1988  \n",
       "12      Milwaukee             Wisconsin          1968  \n",
       "13      Minnesota             Minnesota          1989  \n",
       "14       Brooklyn              New York          1976  \n",
       "15       New York              New York          1946  \n",
       "16        Orlando               Florida          1989  \n",
       "17        Indiana               Indiana          1976  \n",
       "18   Philadelphia          Pennsylvania          1949  \n",
       "19        Phoenix               Arizona          1968  \n",
       "20       Portland                Oregon          1970  \n",
       "21     Sacramento            California          1948  \n",
       "22    San Antonio                 Texas          1976  \n",
       "23  Oklahoma City              Oklahoma          1967  \n",
       "24        Toronto               Ontario          1995  \n",
       "25           Utah                  Utah          1974  \n",
       "26        Memphis             Tennessee          1995  \n",
       "27     Washington  District of Columbia          1961  \n",
       "28        Detroit              Michigan          1948  \n",
       "29      Charlotte        North Carolina          1988  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a930d73f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points_per_game = player_dataset['pts_per_g']\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.histplot(points_per_game, kde=True, color='blue', bins=30)\n",
    "plt.title('Points Per Game Distribution')\n",
    "plt.xlabel('Points Per Game')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "26e7870f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points_per_game = player_dataset['age']\n",
    "\n",
    "# Plotting the distribution\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.histplot(points_per_game, kde=True, color='blue', bins=30)\n",
    "plt.title('Points Per Game Distribution')\n",
    "plt.xlabel('Points Per Game')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2812a96a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Read your dataset\n",
    "\n",
    "# Select relevant features for the heatmap\n",
    "selected_features = [\n",
    "    'age', 'g', 'gs', 'mp_per_g', 'fg_per_g', 'fga_per_g', 'fg_pct', 'fg3_per_g', 'fg3a_per_g',\n",
    "    'fg3_pct', 'fg2_per_g', 'fg2a_per_g', 'fg2_pct', 'efg_pct', 'ft_per_g', 'fta_per_g', 'ft_pct',\n",
    "    'orb_per_g', 'drb_per_g', 'trb_per_g', 'ast_per_g', 'stl_per_g', 'blk_per_g', 'tov_per_g',\n",
    "    'pf_per_g', 'pts_per_g', 'per', 'ts_pct', 'fg3a_per_fga_pct', 'fta_per_fga_pct', 'orb_pct',\n",
    "    'drb_pct', 'trb_pct', 'ast_pct', 'stl_pct', 'blk_pct', 'tov_pct', 'usg_pct', 'ows', 'dws',\n",
    "    'ws', 'ws_per_48', 'obpm', 'dbpm', 'bpm', 'vorp', 'award_share', 'mov', 'mov_adj'\n",
    "]\n",
    "\n",
    "# Create a subset of the dataset with selected features\n",
    "subset = player_dataset[selected_features]\n",
    "\n",
    "# Calculate the correlation matrix\n",
    "correlation_matrix = subset.corr()\n",
    "\n",
    "# Set the threshold for correlation\n",
    "correlation_threshold = 0.7  # You can adjust this threshold as needed\n",
    "\n",
    "# Find highly correlated pairs of features\n",
    "highly_correlated_pairs = (correlation_matrix.abs() > correlation_threshold) & (correlation_matrix != 1)\n",
    "\n",
    "# Create a subset of the correlation matrix for highly correlated features\n",
    "subset_corr_matrix = correlation_matrix[highly_correlated_pairs]\n",
    "\n",
    "# Create a heatmap using Seaborn for the subset\n",
    "plt.figure(figsize=(20, 16))\n",
    "sns.heatmap(subset_corr_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
    "plt.title('Correlation Heatmap of Highly Correlated Features')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "dcbe5ebc",
   "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>season</th>\n",
       "      <th>age</th>\n",
       "      <th>g</th>\n",
       "      <th>gs</th>\n",
       "      <th>mp_per_g</th>\n",
       "      <th>fg_per_g</th>\n",
       "      <th>fga_per_g</th>\n",
       "      <th>fg_pct</th>\n",
       "      <th>fg3_per_g</th>\n",
       "      <th>fg3a_per_g</th>\n",
       "      <th>...</th>\n",
       "      <th>ws</th>\n",
       "      <th>ws_per_48</th>\n",
       "      <th>obpm</th>\n",
       "      <th>dbpm</th>\n",
       "      <th>bpm</th>\n",
       "      <th>vorp</th>\n",
       "      <th>award_share</th>\n",
       "      <th>mov</th>\n",
       "      <th>mov_adj</th>\n",
       "      <th>win_loss_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17634.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17694.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "      <td>17697.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2003.785839</td>\n",
       "      <td>26.649489</td>\n",
       "      <td>53.476804</td>\n",
       "      <td>26.040007</td>\n",
       "      <td>20.405086</td>\n",
       "      <td>3.182483</td>\n",
       "      <td>6.992716</td>\n",
       "      <td>0.442370</td>\n",
       "      <td>0.477657</td>\n",
       "      <td>1.383031</td>\n",
       "      <td>...</td>\n",
       "      <td>2.661344</td>\n",
       "      <td>0.072368</td>\n",
       "      <td>-1.489648</td>\n",
       "      <td>-0.187676</td>\n",
       "      <td>-1.677589</td>\n",
       "      <td>0.637345</td>\n",
       "      <td>0.006022</td>\n",
       "      <td>0.000402</td>\n",
       "      <td>0.001414</td>\n",
       "      <td>0.500097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>11.658168</td>\n",
       "      <td>4.107072</td>\n",
       "      <td>25.293578</td>\n",
       "      <td>29.388891</td>\n",
       "      <td>10.111089</td>\n",
       "      <td>2.274591</td>\n",
       "      <td>4.707025</td>\n",
       "      <td>0.093417</td>\n",
       "      <td>0.656515</td>\n",
       "      <td>1.737237</td>\n",
       "      <td>...</td>\n",
       "      <td>3.016477</td>\n",
       "      <td>0.100344</td>\n",
       "      <td>3.985115</td>\n",
       "      <td>1.795641</td>\n",
       "      <td>4.958036</td>\n",
       "      <td>1.370952</td>\n",
       "      <td>0.059277</td>\n",
       "      <td>4.414384</td>\n",
       "      <td>4.264058</td>\n",
       "      <td>0.145315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1982.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.100000</td>\n",
       "      <td>-2.519000</td>\n",
       "      <td>-68.900000</td>\n",
       "      <td>-31.100000</td>\n",
       "      <td>-92.100000</td>\n",
       "      <td>-2.600000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-15.200000</td>\n",
       "      <td>-14.680000</td>\n",
       "      <td>0.106000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1994.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.400000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>0.405000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.038000</td>\n",
       "      <td>-3.200000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-3.500000</td>\n",
       "      <td>-0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-2.820000</td>\n",
       "      <td>-2.620000</td>\n",
       "      <td>0.402000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2004.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>19.800000</td>\n",
       "      <td>2.600000</td>\n",
       "      <td>5.900000</td>\n",
       "      <td>0.446000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.700000</td>\n",
       "      <td>0.081000</td>\n",
       "      <td>-1.300000</td>\n",
       "      <td>-0.200000</td>\n",
       "      <td>-1.400000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2014.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>28.900000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>0.488000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.100000</td>\n",
       "      <td>0.119000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.020000</td>\n",
       "      <td>2.840000</td>\n",
       "      <td>0.610000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2022.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>43.700000</td>\n",
       "      <td>13.400000</td>\n",
       "      <td>27.800000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.300000</td>\n",
       "      <td>13.200000</td>\n",
       "      <td>...</td>\n",
       "      <td>21.200000</td>\n",
       "      <td>2.712000</td>\n",
       "      <td>199.400000</td>\n",
       "      <td>60.700000</td>\n",
       "      <td>242.200000</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.240000</td>\n",
       "      <td>11.800000</td>\n",
       "      <td>0.890000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             season           age             g            gs      mp_per_g  \\\n",
       "count  17697.000000  17697.000000  17697.000000  17697.000000  17697.000000   \n",
       "mean    2003.785839     26.649489     53.476804     26.040007     20.405086   \n",
       "std       11.658168      4.107072     25.293578     29.388891     10.111089   \n",
       "min     1982.000000     18.000000      1.000000      0.000000      0.000000   \n",
       "25%     1994.000000     23.000000     34.000000      1.000000     12.000000   \n",
       "50%     2004.000000     26.000000     61.000000     11.000000     19.800000   \n",
       "75%     2014.000000     29.000000     76.000000     52.000000     28.900000   \n",
       "max     2022.000000     44.000000     85.000000     83.000000     43.700000   \n",
       "\n",
       "           fg_per_g     fga_per_g        fg_pct     fg3_per_g    fg3a_per_g  \\\n",
       "count  17697.000000  17697.000000  17634.000000  17697.000000  17697.000000   \n",
       "mean       3.182483      6.992716      0.442370      0.477657      1.383031   \n",
       "std        2.274591      4.707025      0.093417      0.656515      1.737237   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        1.400000      3.300000      0.405000      0.000000      0.000000   \n",
       "50%        2.600000      5.900000      0.446000      0.100000      0.600000   \n",
       "75%        4.500000      9.800000      0.488000      0.800000      2.300000   \n",
       "max       13.400000     27.800000      1.000000      5.300000     13.200000   \n",
       "\n",
       "       ...            ws     ws_per_48          obpm          dbpm  \\\n",
       "count  ...  17697.000000  17694.000000  17697.000000  17697.000000   \n",
       "mean   ...      2.661344      0.072368     -1.489648     -0.187676   \n",
       "std    ...      3.016477      0.100344      3.985115      1.795641   \n",
       "min    ...     -2.100000     -2.519000    -68.900000    -31.100000   \n",
       "25%    ...      0.300000      0.038000     -3.200000     -1.000000   \n",
       "50%    ...      1.700000      0.081000     -1.300000     -0.200000   \n",
       "75%    ...      4.100000      0.119000      0.400000      0.700000   \n",
       "max    ...     21.200000      2.712000    199.400000     60.700000   \n",
       "\n",
       "                bpm          vorp   award_share           mov       mov_adj  \\\n",
       "count  17697.000000  17697.000000  17697.000000  17697.000000  17697.000000   \n",
       "mean      -1.677589      0.637345      0.006022      0.000402      0.001414   \n",
       "std        4.958036      1.370952      0.059277      4.414384      4.264058   \n",
       "min      -92.100000     -2.600000      0.000000    -15.200000    -14.680000   \n",
       "25%       -3.500000     -0.100000      0.000000     -2.820000     -2.620000   \n",
       "50%       -1.400000      0.100000      0.000000      0.000000      0.000000   \n",
       "75%        0.500000      1.000000      0.000000      3.020000      2.840000   \n",
       "max      242.200000     12.500000      1.000000     12.240000     11.800000   \n",
       "\n",
       "       win_loss_pct  \n",
       "count  17697.000000  \n",
       "mean       0.500097  \n",
       "std        0.145315  \n",
       "min        0.106000  \n",
       "25%        0.402000  \n",
       "50%        0.500000  \n",
       "75%        0.610000  \n",
       "max        0.890000  \n",
       "\n",
       "[8 rows x 52 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_dataset.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1a662434",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      season               player pos  age team_id   g  gs  mp_per_g  \\\n",
      "0       1982  Kareem Abdul-Jabbar   C   34     LAL  76  76      35.2   \n",
      "1       1982          Alvan Adams   C   27     PHO  79  75      30.3   \n",
      "2       1982           Larry Bird  PF   25     BOS  77  58      38.0   \n",
      "3       1982       Michael Cooper  SG   25     LAL  76  14      28.9   \n",
      "4       1982       Adrian Dantley  SF   26     UTA  81  81      39.8   \n",
      "...      ...                  ...  ..  ...     ...  ..  ..       ...   \n",
      "1417    2022   Karl-Anthony Towns   C   26     MIN  74  74      33.5   \n",
      "1418    2022    Jonas Valančiūnas   C   29     NOP  74  74      30.3   \n",
      "1419    2022       Nikola Vučević   C   31     CHI  73  73      33.1   \n",
      "1420    2022       Christian Wood   C   26     HOU  68  67      30.8   \n",
      "1421    2022           Trae Young  PG   23     ATL  76  76      34.9   \n",
      "\n",
      "      fg_per_g  fga_per_g  ...    ws  ws_per_48  obpm  dbpm  bpm  vorp  \\\n",
      "0          9.9       17.1  ...  10.7      0.192   3.8   1.2  5.0   4.7   \n",
      "1          6.4       13.0  ...   7.2      0.144   1.4   2.2  3.6   3.4   \n",
      "2          9.2       18.4  ...  12.5      0.205   4.4   2.3  6.6   6.4   \n",
      "3          5.0        9.8  ...   5.0      0.109  -0.3   1.2  0.9   1.6   \n",
      "4         11.2       19.6  ...  12.6      0.187   5.8  -1.7  4.1   5.0   \n",
      "...        ...        ...  ...   ...        ...   ...   ...  ...   ...   \n",
      "1417       8.7       16.4  ...  10.3      0.199   4.5   0.5  5.0   4.4   \n",
      "1418       6.9       12.7  ...   7.3      0.156   2.0  -0.1  1.9   2.2   \n",
      "1419       7.5       15.8  ...   4.5      0.090   0.8   0.1  0.9   1.8   \n",
      "1420       6.5       12.9  ...   4.9      0.112   2.1  -0.4  1.6   1.9   \n",
      "1421       9.4       20.3  ...  10.0      0.181   7.1  -2.0  5.2   4.8   \n",
      "\n",
      "      award_share   mov  mov_adj  win_loss_pct  \n",
      "0           0.045  4.87     4.37         0.695  \n",
      "1           0.000  3.45     3.05         0.561  \n",
      "2           0.588  6.38     6.35         0.768  \n",
      "3           0.004  4.87     4.37         0.695  \n",
      "4           0.010 -5.66    -5.63         0.305  \n",
      "...           ...   ...      ...           ...  \n",
      "1417        0.000  2.63     2.53         0.561  \n",
      "1418        0.000 -0.99    -0.84         0.439  \n",
      "1419        0.000 -0.39    -0.37         0.561  \n",
      "1420        0.000 -8.48    -8.26         0.244  \n",
      "1421        0.000  1.56     1.55         0.524  \n",
      "\n",
      "[1422 rows x 55 columns]\n"
     ]
    }
   ],
   "source": [
    "filtered_players = player_dataset[\n",
    "    ((player_dataset['g'] > 48) & (player_dataset['pts_per_g'] > 13.5) & (player_dataset['mp_per_g'] > 30) &\n",
    "     (player_dataset['team_id'] != 'TOT') & (player_dataset['fg_pct'] > 0.37) & (player_dataset['fga_per_g'] > 10) &\n",
    "     (player_dataset['per'] > 18)) | (player_dataset['award_share'] > 0)\n",
    "].reset_index(drop=True)\n",
    "\n",
    "print(filtered_players)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d442a151",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      season               player pos  age team_id   g  gs  mp_per_g  \\\n",
      "0       1982  Kareem Abdul-Jabbar   C   34     LAL  76  76      35.2   \n",
      "1       1982          Alvan Adams   C   27     PHO  79  75      30.3   \n",
      "2       1982           Larry Bird  PF   25     BOS  77  58      38.0   \n",
      "3       1982       Michael Cooper  SG   25     LAL  76  14      28.9   \n",
      "4       1982       Adrian Dantley  SF   26     UTA  81  81      39.8   \n",
      "...      ...                  ...  ..  ...     ...  ..  ..       ...   \n",
      "1441    2022   Karl-Anthony Towns   C   26     MIN  74  74      33.5   \n",
      "1442    2022    Jonas Valančiūnas   C   29     NOP  74  74      30.3   \n",
      "1443    2022       Nikola Vučević   C   31     CHI  73  73      33.1   \n",
      "1444    2022       Christian Wood   C   26     HOU  68  67      30.8   \n",
      "1445    2022           Trae Young  PG   23     ATL  76  76      34.9   \n",
      "\n",
      "      fg_per_g  fga_per_g  ...  ws_per_48  obpm  dbpm  bpm  vorp  award_share  \\\n",
      "0          9.9       17.1  ...      0.192   3.8   1.2  5.0   4.7        0.045   \n",
      "1          6.4       13.0  ...      0.144   1.4   2.2  3.6   3.4        0.000   \n",
      "2          9.2       18.4  ...      0.205   4.4   2.3  6.6   6.4        0.588   \n",
      "3          5.0        9.8  ...      0.109  -0.3   1.2  0.9   1.6        0.004   \n",
      "4         11.2       19.6  ...      0.187   5.8  -1.7  4.1   5.0        0.010   \n",
      "...        ...        ...  ...        ...   ...   ...  ...   ...          ...   \n",
      "1441       8.7       16.4  ...      0.199   4.5   0.5  5.0   4.4        0.000   \n",
      "1442       6.9       12.7  ...      0.156   2.0  -0.1  1.9   2.2        0.000   \n",
      "1443       7.5       15.8  ...      0.090   0.8   0.1  0.9   1.8        0.000   \n",
      "1444       6.5       12.9  ...      0.112   2.1  -0.4  1.6   1.9        0.000   \n",
      "1445       9.4       20.3  ...      0.181   7.1  -2.0  5.2   4.8        0.000   \n",
      "\n",
      "       mov  mov_adj  win_loss_pct         id  \n",
      "0     4.87     4.37         0.695    76003.0  \n",
      "1     3.45     3.05         0.561    76011.0  \n",
      "2     6.38     6.35         0.768     1449.0  \n",
      "3     4.87     4.37         0.695    76444.0  \n",
      "4    -5.66    -5.63         0.305    76504.0  \n",
      "...    ...      ...           ...        ...  \n",
      "1441  2.63     2.53         0.561  1626157.0  \n",
      "1442 -0.99    -0.84         0.439        NaN  \n",
      "1443 -0.39    -0.37         0.561        NaN  \n",
      "1444 -8.48    -8.26         0.244  1626174.0  \n",
      "1445  1.56     1.55         0.524  1629027.0  \n",
      "\n",
      "[1446 rows x 56 columns]\n"
     ]
    }
   ],
   "source": [
    "merged_data = pd.merge(filtered_players, df[['full_name', 'id']], how='left', left_on='player', right_on='full_name')\n",
    "\n",
    "# Drop the redundant 'full_name' column\n",
    "merged_data = merged_data.drop(columns=['full_name'])\n",
    "\n",
    "# Display the result\n",
    "print(merged_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5cc5d4b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      season                 player pos  age team_id   g  gs  mp_per_g  \\\n",
      "7       1982          World B. Free  SG   28     GSW  78  78      35.8   \n",
      "75      1984          World B. Free  SG   30     CLE  75  71      31.7   \n",
      "109     1985          World B. Free  SG   31     CLE  71  50      31.7   \n",
      "143     1986          World B. Free  SG   32     CLE  75  75      33.8   \n",
      "156     1986         Cliff Robinson  SF   25     WSB  78  78      32.9   \n",
      "184     1987              Fat Lever  PG   26     DEN  82  82      37.2   \n",
      "212     1988              Fat Lever  SG   27     DEN  82  82      37.3   \n",
      "247     1989              Fat Lever  SG   28     DEN  71  71      38.7   \n",
      "276     1990              Fat Lever  SG   29     DEN  79  79      35.8   \n",
      "429     1994  Clarence Weatherspoon  SF   23     PHI  82  82      38.4   \n",
      "451     1995             Toni Kukoč  SF   26     CHI  81  55      31.9   \n",
      "536     1997            Steve Smith  SG   27     ATL  72  72      39.1   \n",
      "573     1998            Steve Smith  SG   28     ATL  73  73      39.1   \n",
      "606     1999            Steve Smith  SG   29     ATL  36  36      36.5   \n",
      "674     2001        Peja Stojaković  SF   23     SAC  75  75      38.7   \n",
      "710     2002        Peja Stojaković  SF   24     SAC  71  71      37.3   \n",
      "743     2003        Peja Stojaković  SF   25     SAC  72  72      34.0   \n",
      "781     2004        Peja Stojaković  SF   26     SAC  81  81      40.3   \n",
      "922     2008          Manu Ginóbili  SG   30     SAS  74  23      31.1   \n",
      "1000    2010          Manu Ginóbili  SG   32     SAS  75  21      28.7   \n",
      "1034    2011          Manu Ginóbili  SG   33     SAS  80  79      30.3   \n",
      "1128    2013         Nikola Peković   C   27     MIN  62  62      31.6   \n",
      "1145    2014           Goran Dragić  SG   27     PHO  76  75      35.1   \n",
      "1169    2014         Nikola Peković   C   28     MIN  54  54      30.8   \n",
      "1172    2014         Nikola Vučević   C   23     ORL  57  57      31.8   \n",
      "1206    2015         Nikola Vučević   C   24     ORL  74  74      34.2   \n",
      "1244    2016         Nikola Vučević   C   25     ORL  65  60      31.3   \n",
      "1258    2017           Goran Dragić  PG   30     MIA  73  73      33.7   \n",
      "1300    2018           Nikola Jokić   C   22     DEN  75  73      32.6   \n",
      "1322    2019            Luka Dončić  SG   19     DAL  72  72      32.2   \n",
      "1335    2019           Nikola Jokić   C   23     DEN  80  80      31.3   \n",
      "1345    2019         Nikola Vučević   C   28     ORL  80  80      31.4   \n",
      "1356    2020            Luka Dončić  PG   20     DAL  61  61      33.6   \n",
      "1362    2020           Nikola Jokić   C   24     DEN  73  73      32.0   \n",
      "1368    2020     Kristaps Porziņģis   C   24     DAL  57  57      31.8   \n",
      "1373    2020         Nikola Vučević   C   29     ORL  62  62      32.2   \n",
      "1387    2021            Luka Dončić  PG   21     DAL  66  66      34.3   \n",
      "1398    2021           Nikola Jokić   C   25     DEN  72  72      34.6   \n",
      "1424    2022            Luka Dončić  PG   22     DAL  65  65      35.4   \n",
      "1432    2022           Nikola Jokić   C   26     DEN  74  74      33.5   \n",
      "1442    2022      Jonas Valančiūnas   C   29     NOP  74  74      30.3   \n",
      "1443    2022         Nikola Vučević   C   31     CHI  73  73      33.1   \n",
      "\n",
      "      fg_per_g  fga_per_g  ...  ws_per_48  obpm  dbpm   bpm  vorp  \\\n",
      "7          8.3       18.6  ...      0.118   2.4  -1.9   0.5   1.8   \n",
      "75         8.3       18.8  ...      0.107   2.3  -0.9   1.4   2.0   \n",
      "109        8.6       18.7  ...      0.127   3.7  -0.8   3.0   2.8   \n",
      "143        8.7       19.1  ...      0.115   3.2  -0.9   2.3   2.8   \n",
      "156        7.6       16.1  ...      0.104   0.6   0.1   0.7   1.7   \n",
      "184        7.8       16.7  ...      0.153   3.5   1.4   5.0   5.4   \n",
      "212        7.8       16.6  ...      0.163   3.0   2.2   5.1   5.5   \n",
      "247        7.9       17.2  ...      0.161   3.4   1.8   5.2   5.0   \n",
      "276        7.2       16.2  ...      0.149   3.4   1.5   4.9   4.9   \n",
      "429        7.3       15.2  ...      0.091   1.0  -0.6   0.4   1.9   \n",
      "451        6.0       11.9  ...      0.185   3.8   0.5   4.3   4.1   \n",
      "536        6.8       15.9  ...      0.154   2.7  -1.0   1.7   2.7   \n",
      "573        6.7       15.1  ...      0.171   3.9  -0.9   3.0   3.6   \n",
      "606        6.0       15.0  ...      0.162   2.9   0.2   3.1   1.7   \n",
      "674        7.5       15.9  ...      0.168   2.8  -0.3   2.5   3.2   \n",
      "710        7.7       15.9  ...      0.179   3.2  -0.2   3.0   3.3   \n",
      "743        6.9       14.4  ...      0.199   3.6  -0.1   3.5   3.4   \n",
      "781        8.2       17.1  ...      0.198   5.2  -1.3   3.9   4.9   \n",
      "922        6.1       13.3  ...      0.232   5.6   2.7   8.3   6.0   \n",
      "1000       5.3       12.0  ...      0.216   5.1   1.6   6.7   4.7   \n",
      "1034       5.5       12.7  ...      0.195   4.1   1.3   5.4   4.5   \n",
      "1128       6.2       12.0  ...      0.163   1.7  -1.2   0.5   1.2   \n",
      "1145       7.3       14.4  ...      0.186   4.1  -0.2   3.9   4.0   \n",
      "1169       7.0       13.0  ...      0.169   2.2  -1.6   0.6   1.1   \n",
      "1172       6.2       12.2  ...      0.116   0.1   0.0   0.1   1.0   \n",
      "1206       8.5       16.3  ...      0.133   2.0  -1.2   0.9   1.8   \n",
      "1244       8.2       16.1  ...      0.122   1.9   0.0   1.9   2.0   \n",
      "1258       7.3       15.4  ...      0.147   2.7  -0.1   2.6   2.9   \n",
      "1300       6.7       13.5  ...      0.211   5.3   1.6   6.9   5.5   \n",
      "1322       7.0       16.5  ...      0.101   3.6   0.3   3.9   3.4   \n",
      "1335       7.7       15.1  ...      0.226   6.2   2.9   9.1   7.0   \n",
      "1345       8.8       16.9  ...      0.193   5.0   1.7   6.6   5.5   \n",
      "1356       9.5       20.6  ...      0.207   7.4   1.0   8.4   5.4   \n",
      "1362       7.7       14.7  ...      0.202   5.5   2.0   7.4   5.5   \n",
      "1368       7.0       16.4  ...      0.138   1.8   0.1   1.9   1.8   \n",
      "1373       8.0       16.7  ...      0.153   3.7   0.5   4.2   3.1   \n",
      "1387       9.8       20.5  ...      0.163   6.1   0.7   6.8   5.1   \n",
      "1398      10.2       18.0  ...      0.301   9.1   3.0  12.1   8.8   \n",
      "1424       9.9       21.6  ...      0.159   6.4   1.8   8.2   5.9   \n",
      "1432      10.3       17.7  ...      0.296   9.2   4.5  13.7   9.8   \n",
      "1442       6.9       12.7  ...      0.156   2.0  -0.1   1.9   2.2   \n",
      "1443       7.5       15.8  ...      0.090   0.8   0.1   0.9   1.8   \n",
      "\n",
      "      award_share   mov  mov_adj  win_loss_pct  id  \n",
      "7           0.000  1.04     0.80         0.549 NaN  \n",
      "75          0.001 -4.26    -3.71         0.341 NaN  \n",
      "109         0.003 -2.76    -2.27         0.439 NaN  \n",
      "143         0.000 -2.87    -2.19         0.354 NaN  \n",
      "156         0.000 -1.80    -1.28         0.476 NaN  \n",
      "184         0.014 -0.87    -1.14         0.451 NaN  \n",
      "212         0.033  4.07     3.32         0.659 NaN  \n",
      "247         0.000  1.70     0.91         0.537 NaN  \n",
      "276         0.000  1.41     1.56         0.524 NaN  \n",
      "429         0.000 -7.62    -7.37         0.305 NaN  \n",
      "451         0.000  4.83     4.31         0.573 NaN  \n",
      "536         0.001  5.44     5.52         0.683 NaN  \n",
      "573         0.000  3.51     3.85         0.610 NaN  \n",
      "606         0.001  2.90     2.82         0.620 NaN  \n",
      "674         0.000  5.82     6.07         0.671 NaN  \n",
      "710         0.001  7.61     7.61         0.744 NaN  \n",
      "743         0.000  6.50     6.68         0.720 NaN  \n",
      "781         0.228  5.01     5.41         0.671 NaN  \n",
      "922         0.007  4.79     5.10         0.683 NaN  \n",
      "1000        0.002  5.09     5.07         0.610 NaN  \n",
      "1034        0.017  5.71     5.86         0.744 NaN  \n",
      "1128        0.000 -2.37    -1.83         0.378 NaN  \n",
      "1145        0.002  2.63     3.02         0.585 NaN  \n",
      "1169        0.000  2.67     3.10         0.488 NaN  \n",
      "1172        0.000 -5.44    -5.88         0.280 NaN  \n",
      "1206        0.000 -5.72    -5.87         0.305 NaN  \n",
      "1244        0.000 -1.62    -1.68         0.427 NaN  \n",
      "1258        0.000  1.06     0.78         0.500 NaN  \n",
      "1300        0.000  1.48     1.57         0.561 NaN  \n",
      "1322        0.000 -1.28    -0.86         0.402 NaN  \n",
      "1335        0.210  3.95     4.20         0.659 NaN  \n",
      "1345        0.000  0.71     0.28         0.512 NaN  \n",
      "1356        0.198  4.95     4.87         0.573 NaN  \n",
      "1362        0.018  2.11     2.35         0.630 NaN  \n",
      "1368        0.000  4.95     4.87         0.573 NaN  \n",
      "1373        0.000 -1.01    -0.93         0.452 NaN  \n",
      "1387        0.042  2.26     2.26         0.583 NaN  \n",
      "1398        0.961  4.93     4.82         0.653 NaN  \n",
      "1424        0.146  3.30     3.12         0.634 NaN  \n",
      "1432        0.875  2.30     2.16         0.585 NaN  \n",
      "1442        0.000 -0.99    -0.84         0.439 NaN  \n",
      "1443        0.000 -0.39    -0.37         0.561 NaN  \n",
      "\n",
      "[42 rows x 56 columns]\n"
     ]
    }
   ],
   "source": [
    "# Filter rows where player id is NaN\n",
    "players_with_nan_id = merged_data[merged_data['id'].isna()]\n",
    "\n",
    "# Display the result\n",
    "print(players_with_nan_id)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5c03c90e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The ID of World is 76753.\n"
     ]
    }
   ],
   "source": [
    "def find_player_id(player_name, data1):\n",
    "    \"\"\"\n",
    "    Find the player ID based on the player name in data1.\n",
    "    \n",
    "    Parameters:\n",
    "    - player_name (str): The name of the player to search for.\n",
    "    - data1 (pd.DataFrame): The DataFrame containing player information.\n",
    "\n",
    "    Returns:\n",
    "    - int or None: The player ID if found, otherwise None.\n",
    "    \"\"\"\n",
    "    player_id = data1.loc[data1['first_name'] == player_name, 'id'].values\n",
    "    return player_id[0] if len(player_id) > 0 else None\n",
    "# Example usage\n",
    "player_name_to_search = 'World'\n",
    "player_id = find_player_id(player_name_to_search, df)\n",
    "\n",
    "if player_id is not None:\n",
    "    print(f\"The ID of {player_name_to_search} is {player_id}.\")\n",
    "else:\n",
    "    print(f\"Player {player_name_to_search} not found in data1.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "724b1ab0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Manually assigned ID 76753 to World B. Free.\n"
     ]
    }
   ],
   "source": [
    "# Example: Manually add an ID for a specific player\n",
    "player_name_to_add_id = 'World B. Free'\n",
    "manually_assigned_id = 76753 # Replace with the desired ID\n",
    "\n",
    "# Locate all rows corresponding to the player in the merged dataset\n",
    "player_rows = merged_data.index[merged_data['player'] == player_name_to_add_id].tolist()\n",
    "\n",
    "# If the player is found, assign the ID to all corresponding rows\n",
    "if player_rows:\n",
    "    merged_data.loc[player_rows, 'id'] = manually_assigned_id\n",
    "    print(f\"Manually assigned ID {manually_assigned_id} to {player_name_to_add_id}.\")\n",
    "else:\n",
    "    print(f\"Player {player_name_to_add_id} not found in the merged dataset.\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c7d75189",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      season                 player pos  age team_id   g  gs  mp_per_g  \\\n",
      "156     1986         Cliff Robinson  SF   25     WSB  78  78      32.9   \n",
      "184     1987              Fat Lever  PG   26     DEN  82  82      37.2   \n",
      "212     1988              Fat Lever  SG   27     DEN  82  82      37.3   \n",
      "247     1989              Fat Lever  SG   28     DEN  71  71      38.7   \n",
      "276     1990              Fat Lever  SG   29     DEN  79  79      35.8   \n",
      "429     1994  Clarence Weatherspoon  SF   23     PHI  82  82      38.4   \n",
      "451     1995             Toni Kukoč  SF   26     CHI  81  55      31.9   \n",
      "536     1997            Steve Smith  SG   27     ATL  72  72      39.1   \n",
      "573     1998            Steve Smith  SG   28     ATL  73  73      39.1   \n",
      "606     1999            Steve Smith  SG   29     ATL  36  36      36.5   \n",
      "674     2001        Peja Stojaković  SF   23     SAC  75  75      38.7   \n",
      "710     2002        Peja Stojaković  SF   24     SAC  71  71      37.3   \n",
      "743     2003        Peja Stojaković  SF   25     SAC  72  72      34.0   \n",
      "781     2004        Peja Stojaković  SF   26     SAC  81  81      40.3   \n",
      "922     2008          Manu Ginóbili  SG   30     SAS  74  23      31.1   \n",
      "1000    2010          Manu Ginóbili  SG   32     SAS  75  21      28.7   \n",
      "1034    2011          Manu Ginóbili  SG   33     SAS  80  79      30.3   \n",
      "1128    2013         Nikola Peković   C   27     MIN  62  62      31.6   \n",
      "1145    2014           Goran Dragić  SG   27     PHO  76  75      35.1   \n",
      "1169    2014         Nikola Peković   C   28     MIN  54  54      30.8   \n",
      "1172    2014         Nikola Vučević   C   23     ORL  57  57      31.8   \n",
      "1206    2015         Nikola Vučević   C   24     ORL  74  74      34.2   \n",
      "1244    2016         Nikola Vučević   C   25     ORL  65  60      31.3   \n",
      "1258    2017           Goran Dragić  PG   30     MIA  73  73      33.7   \n",
      "1300    2018           Nikola Jokić   C   22     DEN  75  73      32.6   \n",
      "1322    2019            Luka Dončić  SG   19     DAL  72  72      32.2   \n",
      "1335    2019           Nikola Jokić   C   23     DEN  80  80      31.3   \n",
      "1345    2019         Nikola Vučević   C   28     ORL  80  80      31.4   \n",
      "1356    2020            Luka Dončić  PG   20     DAL  61  61      33.6   \n",
      "1362    2020           Nikola Jokić   C   24     DEN  73  73      32.0   \n",
      "1368    2020     Kristaps Porziņģis   C   24     DAL  57  57      31.8   \n",
      "1373    2020         Nikola Vučević   C   29     ORL  62  62      32.2   \n",
      "1387    2021            Luka Dončić  PG   21     DAL  66  66      34.3   \n",
      "1398    2021           Nikola Jokić   C   25     DEN  72  72      34.6   \n",
      "1424    2022            Luka Dončić  PG   22     DAL  65  65      35.4   \n",
      "1432    2022           Nikola Jokić   C   26     DEN  74  74      33.5   \n",
      "1442    2022      Jonas Valančiūnas   C   29     NOP  74  74      30.3   \n",
      "1443    2022         Nikola Vučević   C   31     CHI  73  73      33.1   \n",
      "\n",
      "      fg_per_g  fga_per_g  ...  ws_per_48  obpm  dbpm   bpm  vorp  \\\n",
      "156        7.6       16.1  ...      0.104   0.6   0.1   0.7   1.7   \n",
      "184        7.8       16.7  ...      0.153   3.5   1.4   5.0   5.4   \n",
      "212        7.8       16.6  ...      0.163   3.0   2.2   5.1   5.5   \n",
      "247        7.9       17.2  ...      0.161   3.4   1.8   5.2   5.0   \n",
      "276        7.2       16.2  ...      0.149   3.4   1.5   4.9   4.9   \n",
      "429        7.3       15.2  ...      0.091   1.0  -0.6   0.4   1.9   \n",
      "451        6.0       11.9  ...      0.185   3.8   0.5   4.3   4.1   \n",
      "536        6.8       15.9  ...      0.154   2.7  -1.0   1.7   2.7   \n",
      "573        6.7       15.1  ...      0.171   3.9  -0.9   3.0   3.6   \n",
      "606        6.0       15.0  ...      0.162   2.9   0.2   3.1   1.7   \n",
      "674        7.5       15.9  ...      0.168   2.8  -0.3   2.5   3.2   \n",
      "710        7.7       15.9  ...      0.179   3.2  -0.2   3.0   3.3   \n",
      "743        6.9       14.4  ...      0.199   3.6  -0.1   3.5   3.4   \n",
      "781        8.2       17.1  ...      0.198   5.2  -1.3   3.9   4.9   \n",
      "922        6.1       13.3  ...      0.232   5.6   2.7   8.3   6.0   \n",
      "1000       5.3       12.0  ...      0.216   5.1   1.6   6.7   4.7   \n",
      "1034       5.5       12.7  ...      0.195   4.1   1.3   5.4   4.5   \n",
      "1128       6.2       12.0  ...      0.163   1.7  -1.2   0.5   1.2   \n",
      "1145       7.3       14.4  ...      0.186   4.1  -0.2   3.9   4.0   \n",
      "1169       7.0       13.0  ...      0.169   2.2  -1.6   0.6   1.1   \n",
      "1172       6.2       12.2  ...      0.116   0.1   0.0   0.1   1.0   \n",
      "1206       8.5       16.3  ...      0.133   2.0  -1.2   0.9   1.8   \n",
      "1244       8.2       16.1  ...      0.122   1.9   0.0   1.9   2.0   \n",
      "1258       7.3       15.4  ...      0.147   2.7  -0.1   2.6   2.9   \n",
      "1300       6.7       13.5  ...      0.211   5.3   1.6   6.9   5.5   \n",
      "1322       7.0       16.5  ...      0.101   3.6   0.3   3.9   3.4   \n",
      "1335       7.7       15.1  ...      0.226   6.2   2.9   9.1   7.0   \n",
      "1345       8.8       16.9  ...      0.193   5.0   1.7   6.6   5.5   \n",
      "1356       9.5       20.6  ...      0.207   7.4   1.0   8.4   5.4   \n",
      "1362       7.7       14.7  ...      0.202   5.5   2.0   7.4   5.5   \n",
      "1368       7.0       16.4  ...      0.138   1.8   0.1   1.9   1.8   \n",
      "1373       8.0       16.7  ...      0.153   3.7   0.5   4.2   3.1   \n",
      "1387       9.8       20.5  ...      0.163   6.1   0.7   6.8   5.1   \n",
      "1398      10.2       18.0  ...      0.301   9.1   3.0  12.1   8.8   \n",
      "1424       9.9       21.6  ...      0.159   6.4   1.8   8.2   5.9   \n",
      "1432      10.3       17.7  ...      0.296   9.2   4.5  13.7   9.8   \n",
      "1442       6.9       12.7  ...      0.156   2.0  -0.1   1.9   2.2   \n",
      "1443       7.5       15.8  ...      0.090   0.8   0.1   0.9   1.8   \n",
      "\n",
      "      award_share   mov  mov_adj  win_loss_pct  id  \n",
      "156         0.000 -1.80    -1.28         0.476 NaN  \n",
      "184         0.014 -0.87    -1.14         0.451 NaN  \n",
      "212         0.033  4.07     3.32         0.659 NaN  \n",
      "247         0.000  1.70     0.91         0.537 NaN  \n",
      "276         0.000  1.41     1.56         0.524 NaN  \n",
      "429         0.000 -7.62    -7.37         0.305 NaN  \n",
      "451         0.000  4.83     4.31         0.573 NaN  \n",
      "536         0.001  5.44     5.52         0.683 NaN  \n",
      "573         0.000  3.51     3.85         0.610 NaN  \n",
      "606         0.001  2.90     2.82         0.620 NaN  \n",
      "674         0.000  5.82     6.07         0.671 NaN  \n",
      "710         0.001  7.61     7.61         0.744 NaN  \n",
      "743         0.000  6.50     6.68         0.720 NaN  \n",
      "781         0.228  5.01     5.41         0.671 NaN  \n",
      "922         0.007  4.79     5.10         0.683 NaN  \n",
      "1000        0.002  5.09     5.07         0.610 NaN  \n",
      "1034        0.017  5.71     5.86         0.744 NaN  \n",
      "1128        0.000 -2.37    -1.83         0.378 NaN  \n",
      "1145        0.002  2.63     3.02         0.585 NaN  \n",
      "1169        0.000  2.67     3.10         0.488 NaN  \n",
      "1172        0.000 -5.44    -5.88         0.280 NaN  \n",
      "1206        0.000 -5.72    -5.87         0.305 NaN  \n",
      "1244        0.000 -1.62    -1.68         0.427 NaN  \n",
      "1258        0.000  1.06     0.78         0.500 NaN  \n",
      "1300        0.000  1.48     1.57         0.561 NaN  \n",
      "1322        0.000 -1.28    -0.86         0.402 NaN  \n",
      "1335        0.210  3.95     4.20         0.659 NaN  \n",
      "1345        0.000  0.71     0.28         0.512 NaN  \n",
      "1356        0.198  4.95     4.87         0.573 NaN  \n",
      "1362        0.018  2.11     2.35         0.630 NaN  \n",
      "1368        0.000  4.95     4.87         0.573 NaN  \n",
      "1373        0.000 -1.01    -0.93         0.452 NaN  \n",
      "1387        0.042  2.26     2.26         0.583 NaN  \n",
      "1398        0.961  4.93     4.82         0.653 NaN  \n",
      "1424        0.146  3.30     3.12         0.634 NaN  \n",
      "1432        0.875  2.30     2.16         0.585 NaN  \n",
      "1442        0.000 -0.99    -0.84         0.439 NaN  \n",
      "1443        0.000 -0.39    -0.37         0.561 NaN  \n",
      "\n",
      "[38 rows x 56 columns]\n"
     ]
    }
   ],
   "source": [
    "# Filter rows where player id is NaN\n",
    "players_with_nan_id = merged_data[merged_data['id'].isna()]\n",
    "\n",
    "# Display the result\n",
    "print(players_with_nan_id)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a02b70d4",
   "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>season</th>\n",
       "      <th>player</th>\n",
       "      <th>pos</th>\n",
       "      <th>age</th>\n",
       "      <th>team_id</th>\n",
       "      <th>g</th>\n",
       "      <th>gs</th>\n",
       "      <th>mp_per_g</th>\n",
       "      <th>fg_per_g</th>\n",
       "      <th>fga_per_g</th>\n",
       "      <th>...</th>\n",
       "      <th>ws_per_48</th>\n",
       "      <th>obpm</th>\n",
       "      <th>dbpm</th>\n",
       "      <th>bpm</th>\n",
       "      <th>vorp</th>\n",
       "      <th>award_share</th>\n",
       "      <th>mov</th>\n",
       "      <th>mov_adj</th>\n",
       "      <th>win_loss_pct</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1982</td>\n",
       "      <td>Kareem Abdul-Jabbar</td>\n",
       "      <td>C</td>\n",
       "      <td>34</td>\n",
       "      <td>LAL</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>35.2</td>\n",
       "      <td>9.9</td>\n",
       "      <td>17.1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.192</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.37</td>\n",
       "      <td>0.695</td>\n",
       "      <td>76003.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1982</td>\n",
       "      <td>Alvan Adams</td>\n",
       "      <td>C</td>\n",
       "      <td>27</td>\n",
       "      <td>PHO</td>\n",
       "      <td>79</td>\n",
       "      <td>75</td>\n",
       "      <td>30.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>13.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.144</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3.45</td>\n",
       "      <td>3.05</td>\n",
       "      <td>0.561</td>\n",
       "      <td>76011.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1982</td>\n",
       "      <td>Larry Bird</td>\n",
       "      <td>PF</td>\n",
       "      <td>25</td>\n",
       "      <td>BOS</td>\n",
       "      <td>77</td>\n",
       "      <td>58</td>\n",
       "      <td>38.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>18.4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.205</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>6.6</td>\n",
       "      <td>6.4</td>\n",
       "      <td>0.588</td>\n",
       "      <td>6.38</td>\n",
       "      <td>6.35</td>\n",
       "      <td>0.768</td>\n",
       "      <td>1449.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1982</td>\n",
       "      <td>Michael Cooper</td>\n",
       "      <td>SG</td>\n",
       "      <td>25</td>\n",
       "      <td>LAL</td>\n",
       "      <td>76</td>\n",
       "      <td>14</td>\n",
       "      <td>28.9</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.109</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.004</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.37</td>\n",
       "      <td>0.695</td>\n",
       "      <td>76444.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1982</td>\n",
       "      <td>Adrian Dantley</td>\n",
       "      <td>SF</td>\n",
       "      <td>26</td>\n",
       "      <td>UTA</td>\n",
       "      <td>81</td>\n",
       "      <td>81</td>\n",
       "      <td>39.8</td>\n",
       "      <td>11.2</td>\n",
       "      <td>19.6</td>\n",
       "      <td>...</td>\n",
       "      <td>0.187</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-1.7</td>\n",
       "      <td>4.1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.010</td>\n",
       "      <td>-5.66</td>\n",
       "      <td>-5.63</td>\n",
       "      <td>0.305</td>\n",
       "      <td>76504.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1441</th>\n",
       "      <td>2022</td>\n",
       "      <td>Karl-Anthony Towns</td>\n",
       "      <td>C</td>\n",
       "      <td>26</td>\n",
       "      <td>MIN</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>33.5</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16.4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.199</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2.63</td>\n",
       "      <td>2.53</td>\n",
       "      <td>0.561</td>\n",
       "      <td>1626157.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1442</th>\n",
       "      <td>2022</td>\n",
       "      <td>Jonas Valančiūnas</td>\n",
       "      <td>C</td>\n",
       "      <td>29</td>\n",
       "      <td>NOP</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>30.3</td>\n",
       "      <td>6.9</td>\n",
       "      <td>12.7</td>\n",
       "      <td>...</td>\n",
       "      <td>0.156</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>0.439</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1443</th>\n",
       "      <td>2022</td>\n",
       "      <td>Nikola Vučević</td>\n",
       "      <td>C</td>\n",
       "      <td>31</td>\n",
       "      <td>CHI</td>\n",
       "      <td>73</td>\n",
       "      <td>73</td>\n",
       "      <td>33.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>15.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.39</td>\n",
       "      <td>-0.37</td>\n",
       "      <td>0.561</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1444</th>\n",
       "      <td>2022</td>\n",
       "      <td>Christian Wood</td>\n",
       "      <td>C</td>\n",
       "      <td>26</td>\n",
       "      <td>HOU</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>30.8</td>\n",
       "      <td>6.5</td>\n",
       "      <td>12.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.112</td>\n",
       "      <td>2.1</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-8.48</td>\n",
       "      <td>-8.26</td>\n",
       "      <td>0.244</td>\n",
       "      <td>1626174.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1445</th>\n",
       "      <td>2022</td>\n",
       "      <td>Trae Young</td>\n",
       "      <td>PG</td>\n",
       "      <td>23</td>\n",
       "      <td>ATL</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>34.9</td>\n",
       "      <td>9.4</td>\n",
       "      <td>20.3</td>\n",
       "      <td>...</td>\n",
       "      <td>0.181</td>\n",
       "      <td>7.1</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1.55</td>\n",
       "      <td>0.524</td>\n",
       "      <td>1629027.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1446 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      season               player pos  age team_id   g  gs  mp_per_g  \\\n",
       "0       1982  Kareem Abdul-Jabbar   C   34     LAL  76  76      35.2   \n",
       "1       1982          Alvan Adams   C   27     PHO  79  75      30.3   \n",
       "2       1982           Larry Bird  PF   25     BOS  77  58      38.0   \n",
       "3       1982       Michael Cooper  SG   25     LAL  76  14      28.9   \n",
       "4       1982       Adrian Dantley  SF   26     UTA  81  81      39.8   \n",
       "...      ...                  ...  ..  ...     ...  ..  ..       ...   \n",
       "1441    2022   Karl-Anthony Towns   C   26     MIN  74  74      33.5   \n",
       "1442    2022    Jonas Valančiūnas   C   29     NOP  74  74      30.3   \n",
       "1443    2022       Nikola Vučević   C   31     CHI  73  73      33.1   \n",
       "1444    2022       Christian Wood   C   26     HOU  68  67      30.8   \n",
       "1445    2022           Trae Young  PG   23     ATL  76  76      34.9   \n",
       "\n",
       "      fg_per_g  fga_per_g  ...  ws_per_48  obpm  dbpm  bpm  vorp  award_share  \\\n",
       "0          9.9       17.1  ...      0.192   3.8   1.2  5.0   4.7        0.045   \n",
       "1          6.4       13.0  ...      0.144   1.4   2.2  3.6   3.4        0.000   \n",
       "2          9.2       18.4  ...      0.205   4.4   2.3  6.6   6.4        0.588   \n",
       "3          5.0        9.8  ...      0.109  -0.3   1.2  0.9   1.6        0.004   \n",
       "4         11.2       19.6  ...      0.187   5.8  -1.7  4.1   5.0        0.010   \n",
       "...        ...        ...  ...        ...   ...   ...  ...   ...          ...   \n",
       "1441       8.7       16.4  ...      0.199   4.5   0.5  5.0   4.4        0.000   \n",
       "1442       6.9       12.7  ...      0.156   2.0  -0.1  1.9   2.2        0.000   \n",
       "1443       7.5       15.8  ...      0.090   0.8   0.1  0.9   1.8        0.000   \n",
       "1444       6.5       12.9  ...      0.112   2.1  -0.4  1.6   1.9        0.000   \n",
       "1445       9.4       20.3  ...      0.181   7.1  -2.0  5.2   4.8        0.000   \n",
       "\n",
       "       mov  mov_adj  win_loss_pct         id  \n",
       "0     4.87     4.37         0.695    76003.0  \n",
       "1     3.45     3.05         0.561    76011.0  \n",
       "2     6.38     6.35         0.768     1449.0  \n",
       "3     4.87     4.37         0.695    76444.0  \n",
       "4    -5.66    -5.63         0.305    76504.0  \n",
       "...    ...      ...           ...        ...  \n",
       "1441  2.63     2.53         0.561  1626157.0  \n",
       "1442 -0.99    -0.84         0.439        NaN  \n",
       "1443 -0.39    -0.37         0.561        NaN  \n",
       "1444 -8.48    -8.26         0.244  1626174.0  \n",
       "1445  1.56     1.55         0.524  1629027.0  \n",
       "\n",
       "[1446 rows x 56 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a944a706",
   "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>season</th>\n",
       "      <th>player</th>\n",
       "      <th>pos</th>\n",
       "      <th>age</th>\n",
       "      <th>team_id</th>\n",
       "      <th>g</th>\n",
       "      <th>gs</th>\n",
       "      <th>mp_per_g</th>\n",
       "      <th>fg_per_g</th>\n",
       "      <th>fga_per_g</th>\n",
       "      <th>...</th>\n",
       "      <th>obpm</th>\n",
       "      <th>dbpm</th>\n",
       "      <th>bpm</th>\n",
       "      <th>vorp</th>\n",
       "      <th>award_share</th>\n",
       "      <th>mov</th>\n",
       "      <th>mov_adj</th>\n",
       "      <th>win_loss_pct</th>\n",
       "      <th>id_x</th>\n",
       "      <th>id_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1982</td>\n",
       "      <td>Kareem Abdul-Jabbar</td>\n",
       "      <td>C</td>\n",
       "      <td>34</td>\n",
       "      <td>LAL</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>35.2</td>\n",
       "      <td>9.9</td>\n",
       "      <td>17.1</td>\n",
       "      <td>...</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.045</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.37</td>\n",
       "      <td>0.695</td>\n",
       "      <td>76003.0</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1982</td>\n",
       "      <td>Alvan Adams</td>\n",
       "      <td>C</td>\n",
       "      <td>27</td>\n",
       "      <td>PHO</td>\n",
       "      <td>79</td>\n",
       "      <td>75</td>\n",
       "      <td>30.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>13.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3.45</td>\n",
       "      <td>3.05</td>\n",
       "      <td>0.561</td>\n",
       "      <td>76011.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1982</td>\n",
       "      <td>Larry Bird</td>\n",
       "      <td>PF</td>\n",
       "      <td>25</td>\n",
       "      <td>BOS</td>\n",
       "      <td>77</td>\n",
       "      <td>58</td>\n",
       "      <td>38.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>18.4</td>\n",
       "      <td>...</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>6.6</td>\n",
       "      <td>6.4</td>\n",
       "      <td>0.588</td>\n",
       "      <td>6.38</td>\n",
       "      <td>6.35</td>\n",
       "      <td>0.768</td>\n",
       "      <td>1449.0</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1982</td>\n",
       "      <td>Michael Cooper</td>\n",
       "      <td>SG</td>\n",
       "      <td>25</td>\n",
       "      <td>LAL</td>\n",
       "      <td>76</td>\n",
       "      <td>14</td>\n",
       "      <td>28.9</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.8</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.004</td>\n",
       "      <td>4.87</td>\n",
       "      <td>4.37</td>\n",
       "      <td>0.695</td>\n",
       "      <td>76444.0</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1982</td>\n",
       "      <td>Adrian Dantley</td>\n",
       "      <td>SF</td>\n",
       "      <td>26</td>\n",
       "      <td>UTA</td>\n",
       "      <td>81</td>\n",
       "      <td>81</td>\n",
       "      <td>39.8</td>\n",
       "      <td>11.2</td>\n",
       "      <td>19.6</td>\n",
       "      <td>...</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-1.7</td>\n",
       "      <td>4.1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.010</td>\n",
       "      <td>-5.66</td>\n",
       "      <td>-5.63</td>\n",
       "      <td>0.305</td>\n",
       "      <td>76504.0</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1441</th>\n",
       "      <td>2022</td>\n",
       "      <td>Karl-Anthony Towns</td>\n",
       "      <td>C</td>\n",
       "      <td>26</td>\n",
       "      <td>MIN</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>33.5</td>\n",
       "      <td>8.7</td>\n",
       "      <td>16.4</td>\n",
       "      <td>...</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2.63</td>\n",
       "      <td>2.53</td>\n",
       "      <td>0.561</td>\n",
       "      <td>1626157.0</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1442</th>\n",
       "      <td>2022</td>\n",
       "      <td>Jonas Valančiūnas</td>\n",
       "      <td>C</td>\n",
       "      <td>29</td>\n",
       "      <td>NOP</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>30.3</td>\n",
       "      <td>6.9</td>\n",
       "      <td>12.7</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.99</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>0.439</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1443</th>\n",
       "      <td>2022</td>\n",
       "      <td>Nikola Vučević</td>\n",
       "      <td>C</td>\n",
       "      <td>31</td>\n",
       "      <td>CHI</td>\n",
       "      <td>73</td>\n",
       "      <td>73</td>\n",
       "      <td>33.1</td>\n",
       "      <td>7.5</td>\n",
       "      <td>15.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.9</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.39</td>\n",
       "      <td>-0.37</td>\n",
       "      <td>0.561</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1444</th>\n",
       "      <td>2022</td>\n",
       "      <td>Christian Wood</td>\n",
       "      <td>C</td>\n",
       "      <td>26</td>\n",
       "      <td>HOU</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>30.8</td>\n",
       "      <td>6.5</td>\n",
       "      <td>12.9</td>\n",
       "      <td>...</td>\n",
       "      <td>2.1</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-8.48</td>\n",
       "      <td>-8.26</td>\n",
       "      <td>0.244</td>\n",
       "      <td>1626174.0</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1445</th>\n",
       "      <td>2022</td>\n",
       "      <td>Trae Young</td>\n",
       "      <td>PG</td>\n",
       "      <td>23</td>\n",
       "      <td>ATL</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>34.9</td>\n",
       "      <td>9.4</td>\n",
       "      <td>20.3</td>\n",
       "      <td>...</td>\n",
       "      <td>7.1</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1.55</td>\n",
       "      <td>0.524</td>\n",
       "      <td>1629027.0</td>\n",
       "      <td>1.610613e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1446 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      season               player pos  age team_id   g  gs  mp_per_g  \\\n",
       "0       1982  Kareem Abdul-Jabbar   C   34     LAL  76  76      35.2   \n",
       "1       1982          Alvan Adams   C   27     PHO  79  75      30.3   \n",
       "2       1982           Larry Bird  PF   25     BOS  77  58      38.0   \n",
       "3       1982       Michael Cooper  SG   25     LAL  76  14      28.9   \n",
       "4       1982       Adrian Dantley  SF   26     UTA  81  81      39.8   \n",
       "...      ...                  ...  ..  ...     ...  ..  ..       ...   \n",
       "1441    2022   Karl-Anthony Towns   C   26     MIN  74  74      33.5   \n",
       "1442    2022    Jonas Valančiūnas   C   29     NOP  74  74      30.3   \n",
       "1443    2022       Nikola Vučević   C   31     CHI  73  73      33.1   \n",
       "1444    2022       Christian Wood   C   26     HOU  68  67      30.8   \n",
       "1445    2022           Trae Young  PG   23     ATL  76  76      34.9   \n",
       "\n",
       "      fg_per_g  fga_per_g  ...  obpm  dbpm  bpm  vorp  award_share   mov  \\\n",
       "0          9.9       17.1  ...   3.8   1.2  5.0   4.7        0.045  4.87   \n",
       "1          6.4       13.0  ...   1.4   2.2  3.6   3.4        0.000  3.45   \n",
       "2          9.2       18.4  ...   4.4   2.3  6.6   6.4        0.588  6.38   \n",
       "3          5.0        9.8  ...  -0.3   1.2  0.9   1.6        0.004  4.87   \n",
       "4         11.2       19.6  ...   5.8  -1.7  4.1   5.0        0.010 -5.66   \n",
       "...        ...        ...  ...   ...   ...  ...   ...          ...   ...   \n",
       "1441       8.7       16.4  ...   4.5   0.5  5.0   4.4        0.000  2.63   \n",
       "1442       6.9       12.7  ...   2.0  -0.1  1.9   2.2        0.000 -0.99   \n",
       "1443       7.5       15.8  ...   0.8   0.1  0.9   1.8        0.000 -0.39   \n",
       "1444       6.5       12.9  ...   2.1  -0.4  1.6   1.9        0.000 -8.48   \n",
       "1445       9.4       20.3  ...   7.1  -2.0  5.2   4.8        0.000  1.56   \n",
       "\n",
       "      mov_adj  win_loss_pct       id_x          id_y  \n",
       "0        4.37         0.695    76003.0  1.610613e+09  \n",
       "1        3.05         0.561    76011.0           NaN  \n",
       "2        6.35         0.768     1449.0  1.610613e+09  \n",
       "3        4.37         0.695    76444.0  1.610613e+09  \n",
       "4       -5.63         0.305    76504.0  1.610613e+09  \n",
       "...       ...           ...        ...           ...  \n",
       "1441     2.53         0.561  1626157.0  1.610613e+09  \n",
       "1442    -0.84         0.439        NaN  1.610613e+09  \n",
       "1443    -0.37         0.561        NaN  1.610613e+09  \n",
       "1444    -8.26         0.244  1626174.0  1.610613e+09  \n",
       "1445     1.55         0.524  1629027.0  1.610613e+09  \n",
       "\n",
       "[1446 rows x 57 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df = pd.merge(merged_data, team_data[['id', 'abbreviation']], left_on=['team_id'], right_on=['abbreviation'], how='left')\n",
    "\n",
    "# Drop redundant columns\n",
    "merged_df = merged_df.drop(['abbreviation'], axis=1)\n",
    "\n",
    "\n",
    "\n",
    "# Display the merged dataset\n",
    "merged_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "15e9b546",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['season', 'player', 'pos', 'age', 'team_id', 'g', 'gs', 'mp_per_g',\n",
       "       'fg_per_g', 'fga_per_g', 'fg_pct', 'fg3_per_g', 'fg3a_per_g', 'fg3_pct',\n",
       "       'fg2_per_g', 'fg2a_per_g', 'fg2_pct', 'efg_pct', 'ft_per_g',\n",
       "       'fta_per_g', 'ft_pct', 'orb_per_g', 'drb_per_g', 'trb_per_g',\n",
       "       'ast_per_g', 'stl_per_g', 'blk_per_g', 'tov_per_g', 'pf_per_g',\n",
       "       'pts_per_g', 'mp', 'per', 'ts_pct', 'fg3a_per_fga_pct',\n",
       "       'fta_per_fga_pct', 'orb_pct', 'drb_pct', 'trb_pct', 'ast_pct',\n",
       "       'stl_pct', 'blk_pct', 'tov_pct', 'usg_pct', 'ows', 'dws', 'ws',\n",
       "       'ws_per_48', 'obpm', 'dbpm', 'bpm', 'vorp', 'award_share', 'mov',\n",
       "       'mov_adj', 'win_loss_pct', 'id_x', 'id_y'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "02e07f81",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=merged_df.drop(['id_x'],axis=1)\n",
    "df2=df.drop(['id_y'],axis=1)"
   ]
  }
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