dashboard.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook uses Viola to render the notebook as a dashboard. It's hosted on the cloud for free using mybinder.org. \n",
    "\n",
    "### NBA Player Stats and Salary\n",
    "\n",
    "For this article, we will be using two separate a dataset from kaggle, The salary data that can be found <a href=\"https://www.kaggle.com/koki25ando/salary\"> here </a> and the player stats can be found <a href=\"https://www.kaggle.com/mcamli/nba17-18#nba.csv\"> here. </a> Both dataset are from the season 2017 - 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "!pip install -U altair vega_datasets notebook vega"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "outputs": [],
   "source": [
    "%%capture\n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "import seaborn as sns\n",
    "import warnings\n",
    "import matplotlib.pyplot as plt\n",
    "from ipywidgets import interact\n",
    "import altair as alt\n",
    "\n",
    "%matplotlib inline\n",
    "warnings.filterwarnings('ignore')\n",
    "pd.set_option('display.max_columns',False)\n",
    "pd.set_option('display.max_rows',100)\n",
    "sns.set(style='ticks')\n",
    "alt.renderers.enable('kaggle')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "salary = pd.read_csv('NBA_season1718_salary.csv')\n",
    "stats = pd.read_csv('nba_extra.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we will transform the ```Player``` column in the stats data, so we can match in with the salary data. We'll also drop the first column in the salary data.\n",
    "\n",
    "\n",
    "\n",
    "##### The first few rows of the Salary Data:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Player</th>\n",
       "      <th>Tm</th>\n",
       "      <th>season17_18</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Stephen Curry</td>\n",
       "      <td>GSW</td>\n",
       "      <td>34682550.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>LeBron James</td>\n",
       "      <td>CLE</td>\n",
       "      <td>33285709.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Paul Millsap</td>\n",
       "      <td>DEN</td>\n",
       "      <td>31269231.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Gordon Hayward</td>\n",
       "      <td>BOS</td>\n",
       "      <td>29727900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Blake Griffin</td>\n",
       "      <td>DET</td>\n",
       "      <td>29512900.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0          Player   Tm  season17_18\n",
       "0           1   Stephen Curry  GSW   34682550.0\n",
       "1           2    LeBron James  CLE   33285709.0\n",
       "2           3    Paul Millsap  DEN   31269231.0\n",
       "3           4  Gordon Hayward  BOS   29727900.0\n",
       "4           5   Blake Griffin  DET   29512900.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### The first few rows of the Stats Data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Rk</th>\n",
       "      <th>Player</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tm</th>\n",
       "      <th>G</th>\n",
       "      <th>GS</th>\n",
       "      <th>MP</th>\n",
       "      <th>FG</th>\n",
       "      <th>FGA</th>\n",
       "      <th>FG%</th>\n",
       "      <th>3P</th>\n",
       "      <th>3PA</th>\n",
       "      <th>3P%</th>\n",
       "      <th>2P</th>\n",
       "      <th>2PA</th>\n",
       "      <th>2P%</th>\n",
       "      <th>eFG%</th>\n",
       "      <th>FT</th>\n",
       "      <th>FTA</th>\n",
       "      <th>FT%</th>\n",
       "      <th>ORB</th>\n",
       "      <th>DRB</th>\n",
       "      <th>TRB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Alex Abrines\\abrinal01</td>\n",
       "      <td>SG</td>\n",
       "      <td>24</td>\n",
       "      <td>OKC</td>\n",
       "      <td>75</td>\n",
       "      <td>8</td>\n",
       "      <td>1134</td>\n",
       "      <td>115</td>\n",
       "      <td>291</td>\n",
       "      <td>0.395</td>\n",
       "      <td>84</td>\n",
       "      <td>221</td>\n",
       "      <td>0.380</td>\n",
       "      <td>31</td>\n",
       "      <td>70</td>\n",
       "      <td>0.443</td>\n",
       "      <td>0.540</td>\n",
       "      <td>39</td>\n",
       "      <td>46</td>\n",
       "      <td>0.848</td>\n",
       "      <td>26</td>\n",
       "      <td>88</td>\n",
       "      <td>114</td>\n",
       "      <td>28</td>\n",
       "      <td>38</td>\n",
       "      <td>8</td>\n",
       "      <td>25</td>\n",
       "      <td>124</td>\n",
       "      <td>353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Quincy Acy\\acyqu01</td>\n",
       "      <td>PF</td>\n",
       "      <td>27</td>\n",
       "      <td>BRK</td>\n",
       "      <td>70</td>\n",
       "      <td>8</td>\n",
       "      <td>1359</td>\n",
       "      <td>130</td>\n",
       "      <td>365</td>\n",
       "      <td>0.356</td>\n",
       "      <td>102</td>\n",
       "      <td>292</td>\n",
       "      <td>0.349</td>\n",
       "      <td>28</td>\n",
       "      <td>73</td>\n",
       "      <td>0.384</td>\n",
       "      <td>0.496</td>\n",
       "      <td>49</td>\n",
       "      <td>60</td>\n",
       "      <td>0.817</td>\n",
       "      <td>40</td>\n",
       "      <td>217</td>\n",
       "      <td>257</td>\n",
       "      <td>57</td>\n",
       "      <td>33</td>\n",
       "      <td>29</td>\n",
       "      <td>60</td>\n",
       "      <td>149</td>\n",
       "      <td>411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Steven Adams\\adamsst01</td>\n",
       "      <td>C</td>\n",
       "      <td>24</td>\n",
       "      <td>OKC</td>\n",
       "      <td>76</td>\n",
       "      <td>76</td>\n",
       "      <td>2487</td>\n",
       "      <td>448</td>\n",
       "      <td>712</td>\n",
       "      <td>0.629</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000</td>\n",
       "      <td>448</td>\n",
       "      <td>710</td>\n",
       "      <td>0.631</td>\n",
       "      <td>0.629</td>\n",
       "      <td>160</td>\n",
       "      <td>286</td>\n",
       "      <td>0.559</td>\n",
       "      <td>384</td>\n",
       "      <td>301</td>\n",
       "      <td>685</td>\n",
       "      <td>88</td>\n",
       "      <td>92</td>\n",
       "      <td>78</td>\n",
       "      <td>128</td>\n",
       "      <td>215</td>\n",
       "      <td>1056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Bam Adebayo\\adebaba01</td>\n",
       "      <td>C</td>\n",
       "      <td>20</td>\n",
       "      <td>MIA</td>\n",
       "      <td>69</td>\n",
       "      <td>19</td>\n",
       "      <td>1368</td>\n",
       "      <td>174</td>\n",
       "      <td>340</td>\n",
       "      <td>0.512</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.000</td>\n",
       "      <td>174</td>\n",
       "      <td>333</td>\n",
       "      <td>0.523</td>\n",
       "      <td>0.512</td>\n",
       "      <td>129</td>\n",
       "      <td>179</td>\n",
       "      <td>0.721</td>\n",
       "      <td>118</td>\n",
       "      <td>263</td>\n",
       "      <td>381</td>\n",
       "      <td>101</td>\n",
       "      <td>32</td>\n",
       "      <td>41</td>\n",
       "      <td>66</td>\n",
       "      <td>138</td>\n",
       "      <td>477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Arron Afflalo\\afflaar01</td>\n",
       "      <td>SG</td>\n",
       "      <td>32</td>\n",
       "      <td>ORL</td>\n",
       "      <td>53</td>\n",
       "      <td>3</td>\n",
       "      <td>682</td>\n",
       "      <td>65</td>\n",
       "      <td>162</td>\n",
       "      <td>0.401</td>\n",
       "      <td>27</td>\n",
       "      <td>70</td>\n",
       "      <td>0.386</td>\n",
       "      <td>38</td>\n",
       "      <td>92</td>\n",
       "      <td>0.413</td>\n",
       "      <td>0.485</td>\n",
       "      <td>22</td>\n",
       "      <td>26</td>\n",
       "      <td>0.846</td>\n",
       "      <td>4</td>\n",
       "      <td>62</td>\n",
       "      <td>66</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>21</td>\n",
       "      <td>56</td>\n",
       "      <td>179</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Rk                   Player Pos  Age   Tm   G  ...  AST  STL  BLK  TOV   PF   PTS\n",
       "0   1   Alex Abrines\\abrinal01  SG   24  OKC  75  ...   28   38    8   25  124   353\n",
       "1   2       Quincy Acy\\acyqu01  PF   27  BRK  70  ...   57   33   29   60  149   411\n",
       "2   3   Steven Adams\\adamsst01   C   24  OKC  76  ...   88   92   78  128  215  1056\n",
       "3   4    Bam Adebayo\\adebaba01   C   20  MIA  69  ...  101   32   41   66  138   477\n",
       "4   5  Arron Afflalo\\afflaar01  SG   32  ORL  53  ...   30    4    9   21   56   179\n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "salary.drop('Unnamed: 0',axis=1,inplace=True)\n",
    "salary.columns = ['Player','Tm','salary']\n",
    "stats.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "new=[]\n",
    "for i in range(0,len(stats.Player)):\n",
    "    x=stats.Player[i].split(\"\\\\\")\n",
    "    new.append(x[0])\n",
    "stats[\"Player\"]=new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.merge(salary,stats,on=['Player','Tm'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Note that this dataset contains duplicate rows, because players can switch teams in a single season. We've also renamed the ```salary``` column.\n",
    "- Also notice that for the missing values, this can be easily obtained (i.e. FG% = FG/GA) except for eFG%.\n",
    "- For the missing values in eFG%, we'll replace them by the average of their respective ```Position```.\n",
    "- For duplicate rows, we'll keep the most recent team.\n",
    "\n",
    "#### Handling Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>% of missing</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FG%</th>\n",
       "      <td>0.004107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3P%</th>\n",
       "      <td>0.090349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2P%</th>\n",
       "      <td>0.024641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eFG%</th>\n",
       "      <td>0.004107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FT%</th>\n",
       "      <td>0.073922</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "      % of missing\n",
       "FG%       0.004107\n",
       "3P%       0.090349\n",
       "2P%       0.024641\n",
       "eFG%      0.004107\n",
       "FT%       0.073922"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing = pd.DataFrame(data.isnull().sum())\n",
    "missing.columns = ['% of missing']\n",
    "missing['% of missing'] = missing['% of missing']/data.shape[0]\n",
    "missing[missing['% of missing']>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>eFGRate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pos</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>0.544529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PF</th>\n",
       "      <td>0.511559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>0.475516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SF</th>\n",
       "      <td>0.479988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG</th>\n",
       "      <td>0.505589</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "      eFGRate\n",
       "Pos          \n",
       "C    0.544529\n",
       "PF   0.511559\n",
       "PG   0.475516\n",
       "SF   0.479988\n",
       "SG   0.505589"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.rename(columns={'eFG%': 'eFGRate',}, inplace=True)\n",
    "def show_average_by_pos(metric):\n",
    "    guide = pd.pivot_table(index='Pos',values=metric,aggfunc=np.mean,data=data[['Pos',metric]])\n",
    "    return guide\n",
    "\n",
    "show_average_by_pos('eFGRate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def imputer(cols):\n",
    "    eFGRate = cols[0]\n",
    "    Pos = cols[1]\n",
    "    \n",
    "    if pd.isnull(eFGRate):\n",
    "\n",
    "        if Pos == 'C':\n",
    "            return 0.544529\n",
    "        elif Pos == 'PF':\n",
    "            return 0.511559\n",
    "        elif Pos == 'PG':\n",
    "            return 0.475516\n",
    "        elif Pos == 'SF':\n",
    "            return 0.479988\n",
    "        else:\n",
    "            return 0.505589\n",
    "    else:\n",
    "        return eFGRate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Uppon further investigation, it seems that the missing values are caused by 0 ``FGA``, 0 ```3PA``` and so on. It's best to impute them by 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "    .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>% of missing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FG%</th>\n",
       "      <td>0.004107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3P%</th>\n",
       "      <td>0.090349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2P%</th>\n",
       "      <td>0.024641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FT%</th>\n",
       "      <td>0.073922</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     % of missing\n",
       "FG%      0.004107\n",
       "3P%      0.090349\n",
       "2P%      0.024641\n",
       "FT%      0.073922"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['eFGRate'] = data[['eFGRate','Pos']].apply(imputer,axis=1)\n",
    "data['FG%'] = data['FG'] / data['FGA']\n",
    "data['3P%'] = data['3P'] / data['3PA']\n",
    "data['2P%'] = data['2P'] / data['2PA']\n",
    "data['FT%'] = data['FT'] / data['FTA']\n",
    "missing = pd.DataFrame(data.isnull().sum())\n",
    "missing.columns = ['% of missing']\n",
    "missing['% of missing'] = missing['% of missing']/data.shape[0]\n",
    "missing[missing['% of missing']>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>% of missing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [% of missing]\n",
       "Index: []"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.fillna(0,inplace=True)\n",
    "missing = pd.DataFrame(data.isnull().sum())\n",
    "missing.columns = ['% of missing']\n",
    "missing['% of missing'] = missing['% of missing']/data.shape[0]\n",
    "missing[missing['% of missing']>0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Handling Duplicate ```Player```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 36 duplicate players.\n"
     ]
    }
   ],
   "source": [
    "ids = data[\"Player\"]\n",
    "print('There are',data[ids.isin(ids[ids.duplicated()])].sort_values(by=\"Player\").shape[0],'duplicate players.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Duplicate Players"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Player</th>\n",
       "      <th>Tm</th>\n",
       "      <th>salary</th>\n",
       "      <th>Rk</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Age</th>\n",
       "      <th>G</th>\n",
       "      <th>GS</th>\n",
       "      <th>MP</th>\n",
       "      <th>FG</th>\n",
       "      <th>FGA</th>\n",
       "      <th>FG%</th>\n",
       "      <th>3P</th>\n",
       "      <th>3PA</th>\n",
       "      <th>3P%</th>\n",
       "      <th>2P</th>\n",
       "      <th>2PA</th>\n",
       "      <th>2P%</th>\n",
       "      <th>eFGRate</th>\n",
       "      <th>FT</th>\n",
       "      <th>FTA</th>\n",
       "      <th>FT%</th>\n",
       "      <th>ORB</th>\n",
       "      <th>DRB</th>\n",
       "      <th>TRB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>Antonius Cleveland</td>\n",
       "      <td>DAL</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>100</td>\n",
       "      <td>SG</td>\n",
       "      <td>23</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>0.307692</td>\n",
       "      <td>0.286</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>Antonius Cleveland</td>\n",
       "      <td>ATL</td>\n",
       "      <td>92160.0</td>\n",
       "      <td>100</td>\n",
       "      <td>SG</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>0.571429</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.786</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>460</th>\n",
       "      <td>Briante Weber</td>\n",
       "      <td>MEM</td>\n",
       "      <td>83129.0</td>\n",
       "      <td>506</td>\n",
       "      <td>PG</td>\n",
       "      <td>25</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>119</td>\n",
       "      <td>10</td>\n",
       "      <td>21</td>\n",
       "      <td>0.476190</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>0.526316</td>\n",
       "      <td>0.476</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>Briante Weber</td>\n",
       "      <td>HOU</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>506</td>\n",
       "      <td>PG</td>\n",
       "      <td>25</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>118</td>\n",
       "      <td>9</td>\n",
       "      <td>22</td>\n",
       "      <td>0.409091</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>0.444444</td>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>0.384615</td>\n",
       "      <td>0.500</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>DeAndre Liggins</td>\n",
       "      <td>NOP</td>\n",
       "      <td>172238.0</td>\n",
       "      <td>297</td>\n",
       "      <td>SG</td>\n",
       "      <td>29</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>244</td>\n",
       "      <td>18</td>\n",
       "      <td>41</td>\n",
       "      <td>0.439024</td>\n",
       "      <td>8</td>\n",
       "      <td>17</td>\n",
       "      <td>0.470588</td>\n",
       "      <td>10</td>\n",
       "      <td>24</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>0.537</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>20</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>DeAndre Liggins</td>\n",
       "      <td>MIL</td>\n",
       "      <td>1577230.0</td>\n",
       "      <td>297</td>\n",
       "      <td>SG</td>\n",
       "      <td>29</td>\n",
       "      <td>31</td>\n",
       "      <td>1</td>\n",
       "      <td>480</td>\n",
       "      <td>22</td>\n",
       "      <td>65</td>\n",
       "      <td>0.338462</td>\n",
       "      <td>11</td>\n",
       "      <td>36</td>\n",
       "      <td>0.305556</td>\n",
       "      <td>11</td>\n",
       "      <td>29</td>\n",
       "      <td>0.379310</td>\n",
       "      <td>0.423</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>5</td>\n",
       "      <td>44</td>\n",
       "      <td>49</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "      <td>61</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>Demetrius Jackson</td>\n",
       "      <td>HOU</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>244</td>\n",
       "      <td>PG</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>63</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>461</th>\n",
       "      <td>Demetrius Jackson</td>\n",
       "      <td>HOU</td>\n",
       "      <td>74159.0</td>\n",
       "      <td>244</td>\n",
       "      <td>PG</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>63</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>0.285714</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>Ersan Ilyasova</td>\n",
       "      <td>ATL</td>\n",
       "      <td>6000000.0</td>\n",
       "      <td>235</td>\n",
       "      <td>PF</td>\n",
       "      <td>30</td>\n",
       "      <td>46</td>\n",
       "      <td>40</td>\n",
       "      <td>1175</td>\n",
       "      <td>184</td>\n",
       "      <td>401</td>\n",
       "      <td>0.458853</td>\n",
       "      <td>61</td>\n",
       "      <td>170</td>\n",
       "      <td>0.358824</td>\n",
       "      <td>123</td>\n",
       "      <td>231</td>\n",
       "      <td>0.532468</td>\n",
       "      <td>0.535</td>\n",
       "      <td>72</td>\n",
       "      <td>90</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>74</td>\n",
       "      <td>177</td>\n",
       "      <td>251</td>\n",
       "      <td>51</td>\n",
       "      <td>44</td>\n",
       "      <td>17</td>\n",
       "      <td>43</td>\n",
       "      <td>92</td>\n",
       "      <td>501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>Ersan Ilyasova</td>\n",
       "      <td>PHI</td>\n",
       "      <td>502328.0</td>\n",
       "      <td>235</td>\n",
       "      <td>PF</td>\n",
       "      <td>30</td>\n",
       "      <td>23</td>\n",
       "      <td>3</td>\n",
       "      <td>554</td>\n",
       "      <td>93</td>\n",
       "      <td>212</td>\n",
       "      <td>0.438679</td>\n",
       "      <td>30</td>\n",
       "      <td>83</td>\n",
       "      <td>0.361446</td>\n",
       "      <td>63</td>\n",
       "      <td>129</td>\n",
       "      <td>0.488372</td>\n",
       "      <td>0.509</td>\n",
       "      <td>33</td>\n",
       "      <td>45</td>\n",
       "      <td>0.733333</td>\n",
       "      <td>44</td>\n",
       "      <td>110</td>\n",
       "      <td>154</td>\n",
       "      <td>39</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>65</td>\n",
       "      <td>249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>SAC</td>\n",
       "      <td>2301360.0</td>\n",
       "      <td>389</td>\n",
       "      <td>C</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>118</td>\n",
       "      <td>17</td>\n",
       "      <td>41</td>\n",
       "      <td>0.414634</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17</td>\n",
       "      <td>41</td>\n",
       "      <td>0.414634</td>\n",
       "      <td>0.415</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12</td>\n",
       "      <td>24</td>\n",
       "      <td>36</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>463</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>POR</td>\n",
       "      <td>74159.0</td>\n",
       "      <td>389</td>\n",
       "      <td>C</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Greg Monroe</td>\n",
       "      <td>PHO</td>\n",
       "      <td>17884176.0</td>\n",
       "      <td>346</td>\n",
       "      <td>C</td>\n",
       "      <td>27</td>\n",
       "      <td>20</td>\n",
       "      <td>14</td>\n",
       "      <td>465</td>\n",
       "      <td>97</td>\n",
       "      <td>155</td>\n",
       "      <td>0.625806</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>97</td>\n",
       "      <td>155</td>\n",
       "      <td>0.625806</td>\n",
       "      <td>0.626</td>\n",
       "      <td>31</td>\n",
       "      <td>46</td>\n",
       "      <td>0.673913</td>\n",
       "      <td>50</td>\n",
       "      <td>110</td>\n",
       "      <td>160</td>\n",
       "      <td>50</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Greg Monroe</td>\n",
       "      <td>BOS</td>\n",
       "      <td>5000000.0</td>\n",
       "      <td>346</td>\n",
       "      <td>C</td>\n",
       "      <td>27</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>496</td>\n",
       "      <td>105</td>\n",
       "      <td>198</td>\n",
       "      <td>0.530303</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>105</td>\n",
       "      <td>198</td>\n",
       "      <td>0.530303</td>\n",
       "      <td>0.530</td>\n",
       "      <td>55</td>\n",
       "      <td>69</td>\n",
       "      <td>0.797101</td>\n",
       "      <td>53</td>\n",
       "      <td>112</td>\n",
       "      <td>165</td>\n",
       "      <td>59</td>\n",
       "      <td>28</td>\n",
       "      <td>17</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>Isaiah Canaan</td>\n",
       "      <td>PHO</td>\n",
       "      <td>1069308.0</td>\n",
       "      <td>84</td>\n",
       "      <td>PG</td>\n",
       "      <td>26</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>418</td>\n",
       "      <td>52</td>\n",
       "      <td>136</td>\n",
       "      <td>0.382353</td>\n",
       "      <td>22</td>\n",
       "      <td>66</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>30</td>\n",
       "      <td>70</td>\n",
       "      <td>0.428571</td>\n",
       "      <td>0.463</td>\n",
       "      <td>46</td>\n",
       "      <td>51</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>6</td>\n",
       "      <td>38</td>\n",
       "      <td>44</td>\n",
       "      <td>76</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>36</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>Isaiah Canaan</td>\n",
       "      <td>HOU</td>\n",
       "      <td>53465.0</td>\n",
       "      <td>84</td>\n",
       "      <td>SG</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>459</th>\n",
       "      <td>Jarell Eddie</td>\n",
       "      <td>CHI</td>\n",
       "      <td>17224.0</td>\n",
       "      <td>144</td>\n",
       "      <td>SF</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458</th>\n",
       "      <td>Jarell Eddie</td>\n",
       "      <td>CHI</td>\n",
       "      <td>83129.0</td>\n",
       "      <td>144</td>\n",
       "      <td>SF</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457</th>\n",
       "      <td>Jarell Eddie</td>\n",
       "      <td>BOS</td>\n",
       "      <td>83129.0</td>\n",
       "      <td>144</td>\n",
       "      <td>SF</td>\n",
       "      <td>26</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>Kyle Collinsworth</td>\n",
       "      <td>DAL</td>\n",
       "      <td>92160.0</td>\n",
       "      <td>103</td>\n",
       "      <td>SF</td>\n",
       "      <td>26</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>480</td>\n",
       "      <td>38</td>\n",
       "      <td>99</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>34</td>\n",
       "      <td>82</td>\n",
       "      <td>0.414634</td>\n",
       "      <td>0.404</td>\n",
       "      <td>21</td>\n",
       "      <td>40</td>\n",
       "      <td>0.525000</td>\n",
       "      <td>32</td>\n",
       "      <td>75</td>\n",
       "      <td>107</td>\n",
       "      <td>56</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>24</td>\n",
       "      <td>44</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>Kyle Collinsworth</td>\n",
       "      <td>DAL</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>103</td>\n",
       "      <td>SF</td>\n",
       "      <td>26</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>480</td>\n",
       "      <td>38</td>\n",
       "      <td>99</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>34</td>\n",
       "      <td>82</td>\n",
       "      <td>0.414634</td>\n",
       "      <td>0.404</td>\n",
       "      <td>21</td>\n",
       "      <td>40</td>\n",
       "      <td>0.525000</td>\n",
       "      <td>32</td>\n",
       "      <td>75</td>\n",
       "      <td>107</td>\n",
       "      <td>56</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>24</td>\n",
       "      <td>44</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>Marco Belinelli</td>\n",
       "      <td>ATL</td>\n",
       "      <td>6306060.0</td>\n",
       "      <td>40</td>\n",
       "      <td>SG</td>\n",
       "      <td>31</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "      <td>1210</td>\n",
       "      <td>199</td>\n",
       "      <td>485</td>\n",
       "      <td>0.410309</td>\n",
       "      <td>92</td>\n",
       "      <td>247</td>\n",
       "      <td>0.372470</td>\n",
       "      <td>107</td>\n",
       "      <td>238</td>\n",
       "      <td>0.449580</td>\n",
       "      <td>0.505</td>\n",
       "      <td>101</td>\n",
       "      <td>109</td>\n",
       "      <td>0.926606</td>\n",
       "      <td>14</td>\n",
       "      <td>86</td>\n",
       "      <td>100</td>\n",
       "      <td>103</td>\n",
       "      <td>46</td>\n",
       "      <td>3</td>\n",
       "      <td>54</td>\n",
       "      <td>41</td>\n",
       "      <td>591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>Marco Belinelli</td>\n",
       "      <td>PHI</td>\n",
       "      <td>776217.0</td>\n",
       "      <td>40</td>\n",
       "      <td>SG</td>\n",
       "      <td>31</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>737</td>\n",
       "      <td>138</td>\n",
       "      <td>279</td>\n",
       "      <td>0.494624</td>\n",
       "      <td>57</td>\n",
       "      <td>148</td>\n",
       "      <td>0.385135</td>\n",
       "      <td>81</td>\n",
       "      <td>131</td>\n",
       "      <td>0.618321</td>\n",
       "      <td>0.597</td>\n",
       "      <td>47</td>\n",
       "      <td>54</td>\n",
       "      <td>0.870370</td>\n",
       "      <td>6</td>\n",
       "      <td>45</td>\n",
       "      <td>51</td>\n",
       "      <td>45</td>\n",
       "      <td>20</td>\n",
       "      <td>9</td>\n",
       "      <td>40</td>\n",
       "      <td>50</td>\n",
       "      <td>380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>Naz Mitrou-Long</td>\n",
       "      <td>UTA</td>\n",
       "      <td>92160.0</td>\n",
       "      <td>344</td>\n",
       "      <td>SG</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>Naz Mitrou-Long</td>\n",
       "      <td>UTA</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>344</td>\n",
       "      <td>SG</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>481</th>\n",
       "      <td>Nigel Hayes</td>\n",
       "      <td>TOR</td>\n",
       "      <td>46080.0</td>\n",
       "      <td>206</td>\n",
       "      <td>SF</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>Nigel Hayes</td>\n",
       "      <td>LAL</td>\n",
       "      <td>46080.0</td>\n",
       "      <td>206</td>\n",
       "      <td>SF</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.333</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>Ramon Sessions</td>\n",
       "      <td>WAS</td>\n",
       "      <td>263124.0</td>\n",
       "      <td>446</td>\n",
       "      <td>PG</td>\n",
       "      <td>31</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>225</td>\n",
       "      <td>25</td>\n",
       "      <td>64</td>\n",
       "      <td>0.390625</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>19</td>\n",
       "      <td>49</td>\n",
       "      <td>0.387755</td>\n",
       "      <td>0.438</td>\n",
       "      <td>32</td>\n",
       "      <td>42</td>\n",
       "      <td>0.761905</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>20</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>Ramon Sessions</td>\n",
       "      <td>NYK</td>\n",
       "      <td>2328652.0</td>\n",
       "      <td>446</td>\n",
       "      <td>PG</td>\n",
       "      <td>31</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>167</td>\n",
       "      <td>17</td>\n",
       "      <td>53</td>\n",
       "      <td>0.320755</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>0.181818</td>\n",
       "      <td>15</td>\n",
       "      <td>42</td>\n",
       "      <td>0.357143</td>\n",
       "      <td>0.340</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "      <td>27</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>Sean Kilpatrick</td>\n",
       "      <td>MIL</td>\n",
       "      <td>789725.0</td>\n",
       "      <td>274</td>\n",
       "      <td>SG</td>\n",
       "      <td>28</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>205</td>\n",
       "      <td>31</td>\n",
       "      <td>82</td>\n",
       "      <td>0.378049</td>\n",
       "      <td>13</td>\n",
       "      <td>46</td>\n",
       "      <td>0.282609</td>\n",
       "      <td>18</td>\n",
       "      <td>36</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.457</td>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "      <td>0.947368</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>15</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>337</th>\n",
       "      <td>Sean Kilpatrick</td>\n",
       "      <td>BRK</td>\n",
       "      <td>1524305.0</td>\n",
       "      <td>274</td>\n",
       "      <td>SG</td>\n",
       "      <td>28</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>183</td>\n",
       "      <td>25</td>\n",
       "      <td>87</td>\n",
       "      <td>0.287356</td>\n",
       "      <td>11</td>\n",
       "      <td>43</td>\n",
       "      <td>0.255814</td>\n",
       "      <td>14</td>\n",
       "      <td>44</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>0.351</td>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "      <td>0.947368</td>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "      <td>35</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>8</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>Sean Kilpatrick</td>\n",
       "      <td>LAC</td>\n",
       "      <td>172238.0</td>\n",
       "      <td>274</td>\n",
       "      <td>SG</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>0.388889</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0.428571</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>0.363636</td>\n",
       "      <td>0.472</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351</th>\n",
       "      <td>Troy Williams</td>\n",
       "      <td>HOU</td>\n",
       "      <td>1471382.0</td>\n",
       "      <td>523</td>\n",
       "      <td>SF</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.222</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>Troy Williams</td>\n",
       "      <td>NYK</td>\n",
       "      <td>148318.0</td>\n",
       "      <td>523</td>\n",
       "      <td>SF</td>\n",
       "      <td>23</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>290</td>\n",
       "      <td>49</td>\n",
       "      <td>100</td>\n",
       "      <td>0.490000</td>\n",
       "      <td>11</td>\n",
       "      <td>33</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>38</td>\n",
       "      <td>67</td>\n",
       "      <td>0.567164</td>\n",
       "      <td>0.545</td>\n",
       "      <td>19</td>\n",
       "      <td>27</td>\n",
       "      <td>0.703704</td>\n",
       "      <td>21</td>\n",
       "      <td>38</td>\n",
       "      <td>59</td>\n",
       "      <td>15</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>18</td>\n",
       "      <td>32</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>Tyler Cavanaugh</td>\n",
       "      <td>ATL</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>92</td>\n",
       "      <td>PF</td>\n",
       "      <td>23</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>518</td>\n",
       "      <td>67</td>\n",
       "      <td>152</td>\n",
       "      <td>0.440789</td>\n",
       "      <td>32</td>\n",
       "      <td>89</td>\n",
       "      <td>0.359551</td>\n",
       "      <td>35</td>\n",
       "      <td>63</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.546</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>0.809524</td>\n",
       "      <td>45</td>\n",
       "      <td>82</td>\n",
       "      <td>127</td>\n",
       "      <td>27</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>61</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>Tyler Cavanaugh</td>\n",
       "      <td>ATL</td>\n",
       "      <td>679919.0</td>\n",
       "      <td>92</td>\n",
       "      <td>PF</td>\n",
       "      <td>23</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>518</td>\n",
       "      <td>67</td>\n",
       "      <td>152</td>\n",
       "      <td>0.440789</td>\n",
       "      <td>32</td>\n",
       "      <td>89</td>\n",
       "      <td>0.359551</td>\n",
       "      <td>35</td>\n",
       "      <td>63</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>0.546</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>0.809524</td>\n",
       "      <td>45</td>\n",
       "      <td>82</td>\n",
       "      <td>127</td>\n",
       "      <td>27</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>61</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Player   Tm      salary   Rk Pos  ...  STL  BLK  TOV  PF  PTS\n",
       "478    Antonius Cleveland  DAL     50000.0  100  SG  ...    6    4    2  11   10\n",
       "454    Antonius Cleveland  ATL     92160.0  100  SG  ...    1    1    5  12   13\n",
       "460         Briante Weber  MEM     83129.0  506  PG  ...    8    2    8  10   24\n",
       "475         Briante Weber  HOU     50000.0  506  PG  ...   10    3    7  18   26\n",
       "441       DeAndre Liggins  NOP    172238.0  297  SG  ...   10    4    7  20   44\n",
       "331       DeAndre Liggins  MIL   1577230.0  297  SG  ...   27   10   13  61   57\n",
       "462     Demetrius Jackson  HOU     50000.0  244  PG  ...    4    1    9   6    8\n",
       "461     Demetrius Jackson  HOU     74159.0  244  PG  ...    4    1    9   6    8\n",
       "171        Ersan Ilyasova  ATL   6000000.0  235  PF  ...   44   17   43  92  501\n",
       "436        Ersan Ilyasova  PHI    502328.0  235  PF  ...   17    9   29  65  249\n",
       "285  Georgios Papagiannis  SAC   2301360.0  389   C  ...    2    6    8  12   34\n",
       "463  Georgios Papagiannis  POR     74159.0  389   C  ...    2    0    0   0    2\n",
       "48            Greg Monroe  PHO  17884176.0  346   C  ...   16    6   40  40  225\n",
       "190           Greg Monroe  BOS   5000000.0  346   C  ...   28   17   48  48  265\n",
       "406         Isaiah Canaan  PHO   1069308.0   84  PG  ...   16    1   29  36  172\n",
       "466         Isaiah Canaan  HOU     53465.0   84  SG  ...    0    0    0   0    0\n",
       "459          Jarell Eddie  CHI     17224.0  144  SF  ...    0    0    0   0    0\n",
       "458          Jarell Eddie  CHI     83129.0  144  SF  ...    0    0    0   0    0\n",
       "457          Jarell Eddie  BOS     83129.0  144  SF  ...    1    0    0   0    0\n",
       "448     Kyle Collinsworth  DAL     92160.0  103  SF  ...   17    9   24  44  101\n",
       "449     Kyle Collinsworth  DAL     50000.0  103  SF  ...   17    9   24  44  101\n",
       "158       Marco Belinelli  ATL   6306060.0   40  SG  ...   46    3   54  41  591\n",
       "431       Marco Belinelli  PHI    776217.0   40  SG  ...   20    9   40  50  380\n",
       "451       Naz Mitrou-Long  UTA     92160.0  344  SG  ...    0    0    0   0    3\n",
       "452       Naz Mitrou-Long  UTA     50000.0  344  SG  ...    0    0    0   0    3\n",
       "481           Nigel Hayes  TOR     46080.0  206  SF  ...    0    0    1   0    6\n",
       "480           Nigel Hayes  LAL     46080.0  206  SF  ...    0    0    0   0    3\n",
       "437        Ramon Sessions  WAS    263124.0  446  PG  ...    7    1   15  15   88\n",
       "275        Ramon Sessions  NYK   2328652.0  446  PG  ...    7    1   15  14   48\n",
       "428       Sean Kilpatrick  MIL    789725.0  274  SG  ...    5    1    9  15   93\n",
       "337       Sean Kilpatrick  BRK   1524305.0  274  SG  ...    2    1   16   8   79\n",
       "442       Sean Kilpatrick  LAC    172238.0  274  SG  ...    0    0    1   2   19\n",
       "351         Troy Williams  HOU   1471382.0  523  SF  ...    1    0    1   2    5\n",
       "444         Troy Williams  NYK    148318.0  523  SF  ...   19    4   18  32  128\n",
       "435       Tyler Cavanaugh  ATL     50000.0   92  PF  ...    9    4   14  61  183\n",
       "434       Tyler Cavanaugh  ATL    679919.0   92  PF  ...    9    4   14  61  183\n",
       "\n",
       "[36 rows x 31 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[ids.isin(ids[ids.duplicated()])].sort_values(by=\"Player\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop_duplicates(subset =\"Player\", keep = 'first', inplace = True) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Visualization\n",
    "\n",
    "### Interactive Cross Filter of Player Salary, FG% and FT%.\n",
    "\n",
    "- Brushing on one histogram, affects the other histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\"datasets\": {\"data-0da967c8d457f4b33fb8ffa2f5e67c7a\": [{\"Player\": \"Stephen Curry\", \"Tm\": \"GSW\", \"salary\": 34682550.0, \"Rk\": 120, \"Pos\": \"PG\", \"Age\": 29, \"G\": 51, \"GS\": 51, \"MP\": 1631, \"FG\": 428, \"FGA\": 864, \"FG%\": 0.49537037037037035, \"3P\": 212, \"3PA\": 501, \"3P%\": 0.4231536926147705, \"2P\": 216, \"2PA\": 363, \"2P%\": 0.5950413223140496, \"eFGRate\": 0.618, \"FT\": 278, \"FTA\": 302, \"FT%\": 0.9205298013245033, \"ORB\": 36, \"DRB\": 225, \"TRB\": 261, \"AST\": 310, \"STL\": 80, \"BLK\": 8, \"TOV\": 153, \"PF\": 114, \"PTS\": 1346}, {\"Player\": \"LeBron James\", \"Tm\": \"CLE\", \"salary\": 33285709.0, \"Rk\": 248, \"Pos\": \"PF\", \"Age\": 33, \"G\": 82, \"GS\": 82, \"MP\": 3026, \"FG\": 857, \"FGA\": 1580, \"FG%\": 0.5424050632911392, \"3P\": 149, \"3PA\": 406, \"3P%\": 0.3669950738916256, \"2P\": 708, \"2PA\": 1174, \"2P%\": 0.6030664395229983, \"eFGRate\": 0.59, \"FT\": 388, \"FTA\": 531, \"FT%\": 0.7306967984934086, \"ORB\": 97, \"DRB\": 612, \"TRB\": 709, \"AST\": 747, \"STL\": 116, \"BLK\": 71, \"TOV\": 347, \"PF\": 136, \"PTS\": 2251}, {\"Player\": \"Paul Millsap\", \"Tm\": \"DEN\", \"salary\": 31269231.0, \"Rk\": 341, \"Pos\": \"PF\", \"Age\": 32, \"G\": 38, \"GS\": 37, \"MP\": 1143, \"FG\": 202, \"FGA\": 435, \"FG%\": 0.46436781609195404, \"3P\": 39, \"3PA\": 113, \"3P%\": 0.34513274336283184, \"2P\": 163, \"2PA\": 322, \"2P%\": 0.5062111801242236, \"eFGRate\": 0.509, \"FT\": 112, \"FTA\": 161, \"FT%\": 0.6956521739130435, \"ORB\": 65, \"DRB\": 180, \"TRB\": 245, \"AST\": 105, \"STL\": 39, \"BLK\": 44, \"TOV\": 73, \"PF\": 99, \"PTS\": 555}, {\"Player\": \"Gordon Hayward\", \"Tm\": \"BOS\", \"salary\": 29727900.0, \"Rk\": 207, \"Pos\": \"SF\", \"Age\": 27, \"G\": 1, \"GS\": 1, \"MP\": 5, \"FG\": 1, \"FGA\": 2, \"FG%\": 0.5, \"3P\": 0, \"3PA\": 1, \"3P%\": 0.0, \"2P\": 1, \"2PA\": 1, \"2P%\": 1.0, \"eFGRate\": 0.5, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 0, \"DRB\": 1, \"TRB\": 1, \"AST\": 0, \"STL\": 0, 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\"PTS\": 30}, {\"Player\": \"Matt Williams\", \"Tm\": \"MIA\", \"salary\": 50000.0, \"Rk\": 522, \"Pos\": \"SG\", \"Age\": 24, \"G\": 3, \"GS\": 0, \"MP\": 11, \"FG\": 2, \"FGA\": 6, \"FG%\": 0.3333333333333333, \"3P\": 1, \"3PA\": 5, \"3P%\": 0.2, \"2P\": 1, \"2PA\": 1, \"2P%\": 1.0, \"eFGRate\": 0.41700000000000004, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 0, \"DRB\": 1, \"TRB\": 1, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 1, \"PF\": 1, \"PTS\": 5}, {\"Player\": \"Vince Hunter\", \"Tm\": \"MEM\", \"salary\": 50000.0, \"Rk\": 232, \"Pos\": \"PF\", \"Age\": 23, \"G\": 4, \"GS\": 0, \"MP\": 7, \"FG\": 3, \"FGA\": 5, \"FG%\": 0.6, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 3, \"2PA\": 5, \"2P%\": 0.6, \"eFGRate\": 0.6, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 2, \"DRB\": 1, \"TRB\": 3, \"AST\": 0, \"STL\": 0, \"BLK\": 1, \"TOV\": 1, \"PF\": 0, \"PTS\": 6}, {\"Player\": \"Vander Blue\", \"Tm\": \"LAL\", \"salary\": 50000.0, \"Rk\": 53, \"Pos\": \"SG\", \"Age\": 25, \"G\": 5, \"GS\": 0, \"MP\": 45, \"FG\": 1, \"FGA\": 5, \"FG%\": 0.2, \"3P\": 0, \"3PA\": 2, \"3P%\": 0.0, \"2P\": 1, \"2PA\": 3, \"2P%\": 0.3333333333333333, \"eFGRate\": 0.2, \"FT\": 1, \"FTA\": 2, \"FT%\": 0.5, \"ORB\": 0, \"DRB\": 1, \"TRB\": 1, \"AST\": 3, \"STL\": 1, \"BLK\": 0, \"TOV\": 3, \"PF\": 2, \"PTS\": 3}, {\"Player\": \"Jamil Wilson\", \"Tm\": \"LAC\", \"salary\": 50000.0, \"Rk\": 525, \"Pos\": \"SF\", \"Age\": 27, \"G\": 15, \"GS\": 10, \"MP\": 274, \"FG\": 38, \"FGA\": 81, \"FG%\": 0.4691358024691358, \"3P\": 27, \"3PA\": 63, \"3P%\": 0.42857142857142855, \"2P\": 11, \"2PA\": 18, \"2P%\": 0.6111111111111112, \"eFGRate\": 0.636, \"FT\": 2, \"FTA\": 4, \"FT%\": 0.5, \"ORB\": 3, \"DRB\": 29, \"TRB\": 32, \"AST\": 10, \"STL\": 5, \"BLK\": 8, \"TOV\": 8, \"PF\": 34, \"PTS\": 105}, {\"Player\": \"Luis Montero\", \"Tm\": \"DET\", \"salary\": 50000.0, \"Rk\": 347, \"Pos\": \"SG\", \"Age\": 24, \"G\": 2, \"GS\": 0, \"MP\": 8, \"FG\": 0, \"FGA\": 1, \"FG%\": 0.0, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 0, \"2PA\": 1, \"2P%\": 0.0, \"eFGRate\": 0.0, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 0, \"DRB\": 2, \"TRB\": 2, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 2, \"PF\": 0, \"PTS\": 0}, {\"Player\": \"Gian Clavell\", \"Tm\": \"DAL\", \"salary\": 50000.0, \"Rk\": 99, \"Pos\": \"SG\", \"Age\": 24, \"G\": 7, \"GS\": 0, \"MP\": 64, \"FG\": 6, \"FGA\": 18, \"FG%\": 0.3333333333333333, \"3P\": 6, \"3PA\": 15, \"3P%\": 0.4, \"2P\": 0, \"2PA\": 3, \"2P%\": 0.0, \"eFGRate\": 0.5, \"FT\": 2, \"FTA\": 2, \"FT%\": 1.0, \"ORB\": 1, \"DRB\": 6, \"TRB\": 7, \"AST\": 3, \"STL\": 2, \"BLK\": 0, \"TOV\": 2, \"PF\": 8, \"PTS\": 20}, {\"Player\": \"Jeremy Evans\", \"Tm\": \"ATL\", \"salary\": 50000.0, \"Rk\": 151, \"Pos\": \"SF\", \"Age\": 30, \"G\": 1, \"GS\": 0, \"MP\": 5, \"FG\": 1, \"FGA\": 1, \"FG%\": 1.0, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 1, \"2PA\": 1, \"2P%\": 1.0, \"eFGRate\": 1.0, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 1, \"DRB\": 0, \"TRB\": 1, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 1, \"PF\": 1, \"PTS\": 2}, {\"Player\": \"Nigel Hayes\", \"Tm\": \"LAL\", \"salary\": 46080.0, \"Rk\": 206, \"Pos\": \"SF\", \"Age\": 23, \"G\": 2, \"GS\": 0, \"MP\": 11, \"FG\": 1, \"FGA\": 3, \"FG%\": 0.3333333333333333, \"3P\": 0, \"3PA\": 2, \"3P%\": 0.0, \"2P\": 1, \"2PA\": 1, \"2P%\": 1.0, \"eFGRate\": 0.33299999999999996, \"FT\": 1, \"FTA\": 1, \"FT%\": 1.0, \"ORB\": 0, \"DRB\": 0, \"TRB\": 0, \"AST\": 2, \"STL\": 0, \"BLK\": 0, \"TOV\": 0, \"PF\": 0, \"PTS\": 3}, {\"Player\": \"Rodney Purvis\", \"Tm\": \"ORL\", \"salary\": 46080.0, \"Rk\": 416, \"Pos\": \"SG\", \"Age\": 23, \"G\": 16, \"GS\": 2, \"MP\": 290, \"FG\": 35, \"FGA\": 107, \"FG%\": 0.32710280373831774, \"3P\": 13, \"3PA\": 52, \"3P%\": 0.25, \"2P\": 22, \"2PA\": 55, \"2P%\": 0.4, \"eFGRate\": 0.38799999999999996, \"FT\": 13, \"FTA\": 15, \"FT%\": 0.8666666666666667, \"ORB\": 1, \"DRB\": 26, \"TRB\": 27, \"AST\": 17, \"STL\": 3, \"BLK\": 3, \"TOV\": 10, \"PF\": 26, \"PTS\": 96}, {\"Player\": \"Xavier Rathan-Mayes\", \"Tm\": \"MEM\", \"salary\": 46080.0, \"Rk\": 422, \"Pos\": \"SG\", \"Age\": 23, \"G\": 5, \"GS\": 0, \"MP\": 118, \"FG\": 12, \"FGA\": 42, \"FG%\": 0.2857142857142857, \"3P\": 1, \"3PA\": 14, \"3P%\": 0.07142857142857142, \"2P\": 11, \"2PA\": 28, \"2P%\": 0.39285714285714285, \"eFGRate\": 0.298, \"FT\": 4, \"FTA\": 9, \"FT%\": 0.4444444444444444, \"ORB\": 0, \"DRB\": 5, \"TRB\": 5, \"AST\": 18, \"STL\": 6, \"BLK\": 3, \"TOV\": 11, \"PF\": 18, \"PTS\": 29}, {\"Player\": \"Trey McKinney-Jones\", \"Tm\": \"IND\", \"salary\": 46080.0, \"Rk\": 329, \"Pos\": \"SG\", \"Age\": 27, \"G\": 1, \"GS\": 0, \"MP\": 1, \"FG\": 0, \"FGA\": 0, \"FG%\": 0.0, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 0, \"2PA\": 0, \"2P%\": 0.0, \"eFGRate\": 0.505589, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 0, \"DRB\": 0, \"TRB\": 0, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 0, \"PF\": 0, \"PTS\": 0}, {\"Player\": \"Jameel Warney\", \"Tm\": \"DAL\", \"salary\": 46080.0, \"Rk\": 502, \"Pos\": \"PF\", \"Age\": 24, \"G\": 3, \"GS\": 0, \"MP\": 27, \"FG\": 7, \"FGA\": 12, \"FG%\": 0.5833333333333334, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 7, \"2PA\": 12, \"2P%\": 0.5833333333333334, \"eFGRate\": 0.583, \"FT\": 3, \"FTA\": 5, \"FT%\": 0.6, \"ORB\": 4, \"DRB\": 5, \"TRB\": 9, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 1, \"PF\": 2, \"PTS\": 17}, {\"Player\": \"Joel Bolomboy\", \"Tm\": \"MIL\", \"salary\": 22248.0, \"Rk\": 57, \"Pos\": \"PF\", \"Age\": 24, \"G\": 6, \"GS\": 0, \"MP\": 38, \"FG\": 3, \"FGA\": 6, \"FG%\": 0.5, \"3P\": 0, \"3PA\": 1, \"3P%\": 0.0, \"2P\": 3, \"2PA\": 5, \"2P%\": 0.6, \"eFGRate\": 0.5, \"FT\": 3, \"FTA\": 6, \"FT%\": 0.5, \"ORB\": 6, \"DRB\": 4, \"TRB\": 10, \"AST\": 0, \"STL\": 2, \"BLK\": 0, \"TOV\": 2, \"PF\": 3, \"PTS\": 9}]}};\n",
       "      var embedOpt = {\"mode\": \"vega-lite\"};\n",
       "\n",
       "      function showError(el, error){\n",
       "          el.innerHTML = ('<div class=\"error\" style=\"color:red;\">'\n",
       "                          + '<p>JavaScript Error: ' + error.message + '</p>'\n",
       "                          + \"<p>This usually means there's a typo in your chart specification. \"\n",
       "                          + \"See the javascript console for the full traceback.</p>\"\n",
       "                          + '</div>');\n",
       "          throw error;\n",
       "      }\n",
       "      const el = document.getElementById('altair-viz-1');\n",
       "      vegaEmbed(\"#altair-viz-1\", spec, embedOpt)\n",
       "        .catch(error => showError(el, error));\n",
       "    });\n",
       "\n",
       "  </script>"
      ],
      "text/plain": [
       "alt.RepeatChart(...)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datat = data.copy()\n",
    "brush = alt.selection(type='interval', encodings=['x'])\n",
    "\n",
    "# Define the base chart, with the common parts of the\n",
    "# background and highlights\n",
    "base = alt.Chart().mark_bar().encode(\n",
    "    x=alt.X(alt.repeat('column'), type='quantitative', bin=alt.Bin(maxbins=30)),\n",
    "    y='count()'\n",
    ").properties(\n",
    "    width=250,\n",
    "    height=250\n",
    ")\n",
    "\n",
    "# blue background with selection\n",
    "background = base.add_selection(brush)\n",
    "\n",
    "# yellow highlights on the transformed data\n",
    "highlight = base.encode(\n",
    "    color=alt.value('goldenrod')\n",
    ").transform_filter(brush)\n",
    "\n",
    "# layer the two charts & repeat\n",
    "alt.layer(\n",
    "    background,\n",
    "    highlight,\n",
    "    data=datat\n",
    ").repeat(column=[\"salary\", \"FG%\", \"FT%\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cross filter of any columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cross_filter(column1='FG%',column2='Age',column3='3P'):\n",
    "    brush = alt.selection(type='interval', encodings=['x'])\n",
    "\n",
    "    # Define the base chart, with the common parts of the\n",
    "    # background and highlights\n",
    "    base = alt.Chart().mark_bar().encode(\n",
    "        x=alt.X(alt.repeat('column'), type='quantitative', bin=alt.Bin(maxbins=30)),\n",
    "        y='count()'\n",
    "    ).properties(\n",
    "        width=250,\n",
    "        height=250\n",
    "    )\n",
    "\n",
    "    # blue background with selection\n",
    "    background = base.add_selection(brush)\n",
    "\n",
    "    # yellow highlights on the transformed data\n",
    "    highlight = base.encode(\n",
    "        color=alt.value('goldenrod')\n",
    "    ).transform_filter(brush)\n",
    "\n",
    "    # layer the two charts & repeat\n",
    "    plot = alt.layer(\n",
    "        background,\n",
    "        highlight,\n",
    "        data=datat\n",
    "    ).repeat(column=[column1,column2,column3])\n",
    "    return plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5980afb264264e309f331d2e6af4dba6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', index=9, options=('salary', 'Rk', 'Pos', 'Age', 'G', 'GS…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interactive = interact(cross_filter,column1=list(data.columns[2:]),column2=list(data.columns[2:]),column3=list(data.columns[2:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scatter_plot(metric='PTS'):\n",
    "    scatter = alt.Chart(datat).mark_circle().encode(\n",
    "        x = metric,\n",
    "        y = 'salary',\n",
    "        color = 'Pos',\n",
    "        tooltip = 'Player'\n",
    "    )\n",
    "    \n",
    "    return scatter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### This plot is an Interactive Scatter Plot with Player Name Tooltip."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4cc920f959ed457abcfc7982dca9ac4d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='metric', index=25, options=('Age', 'G', 'GS', 'MP', 'FG', 'FGA', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interactive_scatter = interact(scatter_plot,metric=list(data.columns[5:]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Average Salary Per Team\n",
    "\n",
    "#### Cleveland has the highest Average Salary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <style>\n",
       "    .vega-actions a {\n",
       "        margin-right: 12px;\n",
       "        color: #757575;\n",
       "        font-weight: normal;\n",
       "        font-size: 13px;\n",
       "    }\n",
       "    .error {\n",
       "        color: red;\n",
       "    }\n",
       "  </style>\n",
       "  <div id=\"altair-viz-4\"></div>\n",
       "  <script>\n",
       "    requirejs.config({\n",
       "        \"paths\": {\n",
       "            \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "            \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "            \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@3.4.0?noext\",\n",
       "            \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@4?noext\",\n",
       "        }\n",
       "    });\n",
       "    \n",
       "    require(['vega-embed'],function(vegaEmbed) {\n",
       "      var spec = {\"config\": {\"view\": {\"width\": 400, \"height\": 300}, \"mark\": {\"tooltip\": null}}, \"data\": {\"name\": \"data-0da967c8d457f4b33fb8ffa2f5e67c7a\"}, \"mark\": \"bar\", \"encoding\": {\"color\": {\"condition\": {\"value\": \"orange\", \"test\": \"(datum.Tm === 'CLE')\"}, \"value\": \"steelblue\"}, \"tooltip\": [{\"type\": \"quantitative\", \"aggregate\": \"average\", \"field\": \"salary\"}], \"x\": {\"type\": \"nominal\", \"field\": \"Tm\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"average\", \"field\": \"salary\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v3.4.0.json\", \"datasets\": {\"data-0da967c8d457f4b33fb8ffa2f5e67c7a\": [{\"Player\": \"Stephen Curry\", \"Tm\": \"GSW\", \"salary\": 34682550.0, \"Rk\": 120, \"Pos\": \"PG\", \"Age\": 29, \"G\": 51, \"GS\": 51, \"MP\": 1631, \"FG\": 428, \"FGA\": 864, \"FG%\": 0.49537037037037035, \"3P\": 212, \"3PA\": 501, \"3P%\": 0.4231536926147705, \"2P\": 216, \"2PA\": 363, \"2P%\": 0.5950413223140496, \"eFGRate\": 0.618, \"FT\": 278, \"FTA\": 302, \"FT%\": 0.9205298013245033, \"ORB\": 36, \"DRB\": 225, \"TRB\": 261, \"AST\": 310, \"STL\": 80, \"BLK\": 8, \"TOV\": 153, \"PF\": 114, \"PTS\": 1346}, {\"Player\": \"LeBron James\", \"Tm\": \"CLE\", \"salary\": 33285709.0, \"Rk\": 248, \"Pos\": \"PF\", \"Age\": 33, \"G\": 82, \"GS\": 82, \"MP\": 3026, \"FG\": 857, \"FGA\": 1580, \"FG%\": 0.5424050632911392, \"3P\": 149, \"3PA\": 406, \"3P%\": 0.3669950738916256, \"2P\": 708, \"2PA\": 1174, \"2P%\": 0.6030664395229983, \"eFGRate\": 0.59, \"FT\": 388, \"FTA\": 531, \"FT%\": 0.7306967984934086, \"ORB\": 97, \"DRB\": 612, \"TRB\": 709, \"AST\": 747, \"STL\": 116, \"BLK\": 71, \"TOV\": 347, \"PF\": 136, \"PTS\": 2251}, {\"Player\": \"Paul Millsap\", \"Tm\": \"DEN\", \"salary\": 31269231.0, \"Rk\": 341, \"Pos\": \"PF\", \"Age\": 32, \"G\": 38, \"GS\": 37, \"MP\": 1143, \"FG\": 202, \"FGA\": 435, \"FG%\": 0.46436781609195404, \"3P\": 39, \"3PA\": 113, \"3P%\": 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0, \"STL\": 0, \"BLK\": 0, \"TOV\": 1, \"PF\": 0, \"PTS\": 2}, {\"Player\": \"James Michael McAdoo\", \"Tm\": \"PHI\", \"salary\": 50000.0, \"Rk\": 320, \"Pos\": \"PF\", \"Age\": 25, \"G\": 3, \"GS\": 0, \"MP\": 18, \"FG\": 2, \"FGA\": 7, \"FG%\": 0.2857142857142857, \"3P\": 2, \"3PA\": 7, \"3P%\": 0.2857142857142857, \"2P\": 0, \"2PA\": 0, \"2P%\": 0.0, \"eFGRate\": 0.429, \"FT\": 2, \"FTA\": 2, \"FT%\": 1.0, \"ORB\": 0, \"DRB\": 2, \"TRB\": 2, \"AST\": 0, \"STL\": 0, \"BLK\": 1, \"TOV\": 1, \"PF\": 1, \"PTS\": 8}, {\"Player\": \"Gary Payton\", \"Tm\": \"MIL\", \"salary\": 50000.0, \"Rk\": 400, \"Pos\": \"PG\", \"Age\": 25, \"G\": 12, \"GS\": 6, \"MP\": 106, \"FG\": 13, \"FGA\": 33, \"FG%\": 0.3939393939393939, \"3P\": 2, \"3PA\": 12, \"3P%\": 0.16666666666666666, \"2P\": 11, \"2PA\": 21, \"2P%\": 0.5238095238095238, \"eFGRate\": 0.424, \"FT\": 2, \"FTA\": 3, \"FT%\": 0.6666666666666666, \"ORB\": 4, \"DRB\": 13, \"TRB\": 17, \"AST\": 9, \"STL\": 3, \"BLK\": 1, \"TOV\": 3, \"PF\": 17, \"PTS\": 30}, {\"Player\": \"Matt Williams\", \"Tm\": \"MIA\", \"salary\": 50000.0, \"Rk\": 522, \"Pos\": \"SG\", \"Age\": 24, \"G\": 3, \"GS\": 0, \"MP\": 11, \"FG\": 2, \"FGA\": 6, \"FG%\": 0.3333333333333333, \"3P\": 1, \"3PA\": 5, \"3P%\": 0.2, \"2P\": 1, \"2PA\": 1, \"2P%\": 1.0, \"eFGRate\": 0.41700000000000004, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 0, \"DRB\": 1, \"TRB\": 1, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 1, \"PF\": 1, \"PTS\": 5}, {\"Player\": \"Vince Hunter\", \"Tm\": \"MEM\", \"salary\": 50000.0, \"Rk\": 232, \"Pos\": \"PF\", \"Age\": 23, \"G\": 4, \"GS\": 0, \"MP\": 7, \"FG\": 3, \"FGA\": 5, \"FG%\": 0.6, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 3, \"2PA\": 5, \"2P%\": 0.6, \"eFGRate\": 0.6, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 2, \"DRB\": 1, \"TRB\": 3, \"AST\": 0, \"STL\": 0, \"BLK\": 1, \"TOV\": 1, \"PF\": 0, \"PTS\": 6}, {\"Player\": \"Vander Blue\", \"Tm\": \"LAL\", \"salary\": 50000.0, \"Rk\": 53, \"Pos\": \"SG\", \"Age\": 25, \"G\": 5, \"GS\": 0, \"MP\": 45, \"FG\": 1, \"FGA\": 5, \"FG%\": 0.2, \"3P\": 0, \"3PA\": 2, \"3P%\": 0.0, \"2P\": 1, \"2PA\": 3, \"2P%\": 0.3333333333333333, \"eFGRate\": 0.2, \"FT\": 1, \"FTA\": 2, \"FT%\": 0.5, \"ORB\": 0, \"DRB\": 1, \"TRB\": 1, \"AST\": 3, \"STL\": 1, \"BLK\": 0, \"TOV\": 3, \"PF\": 2, \"PTS\": 3}, {\"Player\": \"Jamil Wilson\", \"Tm\": \"LAC\", \"salary\": 50000.0, \"Rk\": 525, \"Pos\": \"SF\", \"Age\": 27, \"G\": 15, \"GS\": 10, \"MP\": 274, \"FG\": 38, \"FGA\": 81, \"FG%\": 0.4691358024691358, \"3P\": 27, \"3PA\": 63, \"3P%\": 0.42857142857142855, \"2P\": 11, \"2PA\": 18, \"2P%\": 0.6111111111111112, \"eFGRate\": 0.636, \"FT\": 2, \"FTA\": 4, \"FT%\": 0.5, \"ORB\": 3, \"DRB\": 29, \"TRB\": 32, \"AST\": 10, \"STL\": 5, \"BLK\": 8, \"TOV\": 8, \"PF\": 34, \"PTS\": 105}, {\"Player\": \"Luis Montero\", \"Tm\": \"DET\", \"salary\": 50000.0, \"Rk\": 347, \"Pos\": \"SG\", \"Age\": 24, \"G\": 2, \"GS\": 0, \"MP\": 8, \"FG\": 0, \"FGA\": 1, \"FG%\": 0.0, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 0, \"2PA\": 1, \"2P%\": 0.0, \"eFGRate\": 0.0, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 0, \"DRB\": 2, \"TRB\": 2, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 2, \"PF\": 0, \"PTS\": 0}, {\"Player\": \"Gian Clavell\", \"Tm\": \"DAL\", \"salary\": 50000.0, \"Rk\": 99, \"Pos\": \"SG\", \"Age\": 24, \"G\": 7, \"GS\": 0, \"MP\": 64, \"FG\": 6, \"FGA\": 18, \"FG%\": 0.3333333333333333, \"3P\": 6, \"3PA\": 15, \"3P%\": 0.4, \"2P\": 0, \"2PA\": 3, \"2P%\": 0.0, \"eFGRate\": 0.5, \"FT\": 2, \"FTA\": 2, \"FT%\": 1.0, \"ORB\": 1, \"DRB\": 6, \"TRB\": 7, \"AST\": 3, \"STL\": 2, \"BLK\": 0, \"TOV\": 2, \"PF\": 8, \"PTS\": 20}, {\"Player\": \"Jeremy Evans\", \"Tm\": \"ATL\", \"salary\": 50000.0, \"Rk\": 151, \"Pos\": \"SF\", \"Age\": 30, \"G\": 1, \"GS\": 0, \"MP\": 5, \"FG\": 1, \"FGA\": 1, \"FG%\": 1.0, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 1, \"2PA\": 1, \"2P%\": 1.0, \"eFGRate\": 1.0, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 1, \"DRB\": 0, \"TRB\": 1, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 1, \"PF\": 1, \"PTS\": 2}, {\"Player\": \"Nigel Hayes\", \"Tm\": \"LAL\", \"salary\": 46080.0, \"Rk\": 206, \"Pos\": \"SF\", \"Age\": 23, \"G\": 2, \"GS\": 0, \"MP\": 11, \"FG\": 1, \"FGA\": 3, \"FG%\": 0.3333333333333333, \"3P\": 0, \"3PA\": 2, \"3P%\": 0.0, \"2P\": 1, \"2PA\": 1, \"2P%\": 1.0, \"eFGRate\": 0.33299999999999996, \"FT\": 1, \"FTA\": 1, \"FT%\": 1.0, \"ORB\": 0, \"DRB\": 0, \"TRB\": 0, \"AST\": 2, \"STL\": 0, \"BLK\": 0, \"TOV\": 0, \"PF\": 0, \"PTS\": 3}, {\"Player\": \"Rodney Purvis\", \"Tm\": \"ORL\", \"salary\": 46080.0, \"Rk\": 416, \"Pos\": \"SG\", \"Age\": 23, \"G\": 16, \"GS\": 2, \"MP\": 290, \"FG\": 35, \"FGA\": 107, \"FG%\": 0.32710280373831774, \"3P\": 13, \"3PA\": 52, \"3P%\": 0.25, \"2P\": 22, \"2PA\": 55, \"2P%\": 0.4, \"eFGRate\": 0.38799999999999996, \"FT\": 13, \"FTA\": 15, \"FT%\": 0.8666666666666667, \"ORB\": 1, \"DRB\": 26, \"TRB\": 27, \"AST\": 17, \"STL\": 3, \"BLK\": 3, \"TOV\": 10, \"PF\": 26, \"PTS\": 96}, {\"Player\": \"Xavier Rathan-Mayes\", \"Tm\": \"MEM\", \"salary\": 46080.0, \"Rk\": 422, \"Pos\": \"SG\", \"Age\": 23, \"G\": 5, \"GS\": 0, \"MP\": 118, \"FG\": 12, \"FGA\": 42, \"FG%\": 0.2857142857142857, \"3P\": 1, \"3PA\": 14, \"3P%\": 0.07142857142857142, \"2P\": 11, \"2PA\": 28, \"2P%\": 0.39285714285714285, \"eFGRate\": 0.298, \"FT\": 4, \"FTA\": 9, \"FT%\": 0.4444444444444444, \"ORB\": 0, \"DRB\": 5, \"TRB\": 5, \"AST\": 18, \"STL\": 6, \"BLK\": 3, \"TOV\": 11, \"PF\": 18, \"PTS\": 29}, {\"Player\": \"Trey McKinney-Jones\", \"Tm\": \"IND\", \"salary\": 46080.0, \"Rk\": 329, \"Pos\": \"SG\", \"Age\": 27, \"G\": 1, \"GS\": 0, \"MP\": 1, \"FG\": 0, \"FGA\": 0, \"FG%\": 0.0, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 0, \"2PA\": 0, \"2P%\": 0.0, \"eFGRate\": 0.505589, \"FT\": 0, \"FTA\": 0, \"FT%\": 0.0, \"ORB\": 0, \"DRB\": 0, \"TRB\": 0, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 0, \"PF\": 0, \"PTS\": 0}, {\"Player\": \"Jameel Warney\", \"Tm\": \"DAL\", \"salary\": 46080.0, \"Rk\": 502, \"Pos\": \"PF\", \"Age\": 24, \"G\": 3, \"GS\": 0, \"MP\": 27, \"FG\": 7, \"FGA\": 12, \"FG%\": 0.5833333333333334, \"3P\": 0, \"3PA\": 0, \"3P%\": 0.0, \"2P\": 7, \"2PA\": 12, \"2P%\": 0.5833333333333334, \"eFGRate\": 0.583, \"FT\": 3, \"FTA\": 5, \"FT%\": 0.6, \"ORB\": 4, \"DRB\": 5, \"TRB\": 9, \"AST\": 0, \"STL\": 0, \"BLK\": 0, \"TOV\": 1, \"PF\": 2, \"PTS\": 17}, {\"Player\": \"Joel Bolomboy\", \"Tm\": \"MIL\", \"salary\": 22248.0, \"Rk\": 57, \"Pos\": \"PF\", \"Age\": 24, \"G\": 6, \"GS\": 0, \"MP\": 38, \"FG\": 3, \"FGA\": 6, \"FG%\": 0.5, \"3P\": 0, \"3PA\": 1, \"3P%\": 0.0, \"2P\": 3, \"2PA\": 5, \"2P%\": 0.6, \"eFGRate\": 0.5, \"FT\": 3, \"FTA\": 6, \"FT%\": 0.5, \"ORB\": 6, \"DRB\": 4, \"TRB\": 10, \"AST\": 0, \"STL\": 2, \"BLK\": 0, \"TOV\": 2, \"PF\": 3, \"PTS\": 9}]}};\n",
       "      var embedOpt = {\"mode\": \"vega-lite\"};\n",
       "\n",
       "      function showError(el, error){\n",
       "          el.innerHTML = ('<div class=\"error\" style=\"color:red;\">'\n",
       "                          + '<p>JavaScript Error: ' + error.message + '</p>'\n",
       "                          + \"<p>This usually means there's a typo in your chart specification. \"\n",
       "                          + \"See the javascript console for the full traceback.</p>\"\n",
       "                          + '</div>');\n",
       "          throw error;\n",
       "      }\n",
       "      const el = document.getElementById('altair-viz-4');\n",
       "      vegaEmbed(\"#altair-viz-4\", spec, embedOpt)\n",
       "        .catch(error => showError(el, error));\n",
       "    });\n",
       "\n",
       "  </script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alt.Chart(data).mark_bar().encode(\n",
    "    x = 'Tm',\n",
    "    y = 'average(salary)',\n",
    "    tooltip = ['average(salary)'],\n",
    "    color=alt.condition(\n",
    "    alt.datum.Tm == 'CLE',  # If the year is 1810 this test returns True,\n",
    "    alt.value('orange'),     # which sets the bar orange.\n",
    "    alt.value('steelblue')   # And if it's not true it sets the bar steelblue.\n",
    ")\n",
    ")\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Stephen Curry Makes More Money than LeBron James, despite making significantly smaller Points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <style>\n",
       "    .vega-actions a {\n",
       "        margin-right: 12px;\n",
       "        color: #757575;\n",
       "        font-weight: normal;\n",
       "        font-size: 13px;\n",
       "    }\n",
       "    .error {\n",
       "        color: red;\n",
       "    }\n",
       "  </style>\n",
       "  <div id=\"altair-viz-5\"></div>\n",
       "  <script>\n",
       "    requirejs.config({\n",
       "        \"paths\": {\n",
       "            \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
       "            \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
       "            \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@3.4.0?noext\",\n",
       "            \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@4?noext\",\n",
       "        }\n",
       "    });\n",
       "    \n",
       "    require(['vega-embed'],function(vegaEmbed) {\n",
       "      var spec = {\"config\": {\"view\": {\"width\": 400, \"height\": 300}, \"mark\": {\"tooltip\": null}}, \"vconcat\": [{\"data\": {\"name\": \"data-a3493c7264c87538ec088c066c10d834\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"salary\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Player\"}}}, {\"data\": {\"name\": \"data-a3493c7264c87538ec088c066c10d834\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"PTS\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Player\"}}}], \"$schema\": \"https://vega.github.io/schema/vega-lite/v3.4.0.json\", \"datasets\": {\"data-a3493c7264c87538ec088c066c10d834\": [{\"Player\": \"Stephen Curry\", \"Tm\": \"GSW\", \"salary\": 34682550.0, \"Rk\": 120, \"Pos\": \"PG\", \"Age\": 29, \"G\": 51, \"GS\": 51, \"MP\": 1631, \"FG\": 428, \"FGA\": 864, \"FG%\": 0.49537037037037035, \"3P\": 212, \"3PA\": 501, \"3P%\": 0.4231536926147705, \"2P\": 216, \"2PA\": 363, \"2P%\": 0.5950413223140496, \"eFGRate\": 0.618, \"FT\": 278, \"FTA\": 302, \"FT%\": 0.9205298013245033, \"ORB\": 36, \"DRB\": 225, \"TRB\": 261, \"AST\": 310, \"STL\": 80, \"BLK\": 8, \"TOV\": 153, \"PF\": 114, \"PTS\": 1346}, {\"Player\": \"LeBron James\", \"Tm\": \"CLE\", \"salary\": 33285709.0, \"Rk\": 248, \"Pos\": \"PF\", \"Age\": 33, \"G\": 82, \"GS\": 82, \"MP\": 3026, \"FG\": 857, \"FGA\": 1580, \"FG%\": 0.5424050632911392, \"3P\": 149, \"3PA\": 406, \"3P%\": 0.3669950738916256, \"2P\": 708, \"2PA\": 1174, \"2P%\": 0.6030664395229983, \"eFGRate\": 0.59, \"FT\": 388, \"FTA\": 531, \"FT%\": 0.7306967984934086, \"ORB\": 97, \"DRB\": 612, \"TRB\": 709, \"AST\": 747, \"STL\": 116, \"BLK\": 71, \"TOV\": 347, \"PF\": 136, \"PTS\": 2251}]}};\n",
       "      var embedOpt = {\"mode\": \"vega-lite\"};\n",
       "\n",
       "      function showError(el, error){\n",
       "          el.innerHTML = ('<div class=\"error\" style=\"color:red;\">'\n",
       "                          + '<p>JavaScript Error: ' + error.message + '</p>'\n",
       "                          + \"<p>This usually means there's a typo in your chart specification. \"\n",
       "                          + \"See the javascript console for the full traceback.</p>\"\n",
       "                          + '</div>');\n",
       "          throw error;\n",
       "      }\n",
       "      const el = document.getElementById('altair-viz-5');\n",
       "      vegaEmbed(\"#altair-viz-5\", spec, embedOpt)\n",
       "        .catch(error => showError(el, error));\n",
       "    });\n",
       "\n",
       "  </script>"
      ],
      "text/plain": [
       "alt.VConcatChart(...)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar = alt.Chart(data[(data['Player']=='LeBron James')|(data['Player']=='Stephen Curry')]).mark_bar().encode(\n",
    "    y = 'Player:N',\n",
    "    x = 'salary',\n",
    "\n",
    ")\n",
    "bar2 = alt.Chart(data[(data['Player']=='LeBron James')|(data['Player']=='Stephen Curry')]).mark_bar().encode(\n",
    "    y = 'Player:N',\n",
    "    x = 'PTS',\n",
    "\n",
    ")\n",
    "\n",
    "bar&bar2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Machine Learning\n",
    "\n",
    "- We'll consider the columns that are rates as features, and we'll keep all other metrics.\n",
    "- We'll also drop ```Player``` and ```Tm``` so that our model only pick up patterns from metrics themselves.\n",
    "- We'll do a one hot encodinig on the ```Pos``` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>salary</th>\n",
       "      <th>Rk</th>\n",
       "      <th>Age</th>\n",
       "      <th>G</th>\n",
       "      <th>GS</th>\n",
       "      <th>MP</th>\n",
       "      <th>FG%</th>\n",
       "      <th>3P%</th>\n",
       "      <th>2P%</th>\n",
       "      <th>eFGRate</th>\n",
       "      <th>FT%</th>\n",
       "      <th>ORB</th>\n",
       "      <th>DRB</th>\n",
       "      <th>TRB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34682550.0</td>\n",
       "      <td>120</td>\n",
       "      <td>29</td>\n",
       "      <td>51</td>\n",
       "      <td>51</td>\n",
       "      <td>1631</td>\n",
       "      <td>0.495370</td>\n",
       "      <td>0.423154</td>\n",
       "      <td>0.595041</td>\n",
       "      <td>0.618</td>\n",
       "      <td>0.920530</td>\n",
       "      <td>36</td>\n",
       "      <td>225</td>\n",
       "      <td>261</td>\n",
       "      <td>310</td>\n",
       "      <td>80</td>\n",
       "      <td>8</td>\n",
       "      <td>153</td>\n",
       "      <td>114</td>\n",
       "      <td>1346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>33285709.0</td>\n",
       "      <td>248</td>\n",
       "      <td>33</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>3026</td>\n",
       "      <td>0.542405</td>\n",
       "      <td>0.366995</td>\n",
       "      <td>0.603066</td>\n",
       "      <td>0.590</td>\n",
       "      <td>0.730697</td>\n",
       "      <td>97</td>\n",
       "      <td>612</td>\n",
       "      <td>709</td>\n",
       "      <td>747</td>\n",
       "      <td>116</td>\n",
       "      <td>71</td>\n",
       "      <td>347</td>\n",
       "      <td>136</td>\n",
       "      <td>2251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31269231.0</td>\n",
       "      <td>341</td>\n",
       "      <td>32</td>\n",
       "      <td>38</td>\n",
       "      <td>37</td>\n",
       "      <td>1143</td>\n",
       "      <td>0.464368</td>\n",
       "      <td>0.345133</td>\n",
       "      <td>0.506211</td>\n",
       "      <td>0.509</td>\n",
       "      <td>0.695652</td>\n",
       "      <td>65</td>\n",
       "      <td>180</td>\n",
       "      <td>245</td>\n",
       "      <td>105</td>\n",
       "      <td>39</td>\n",
       "      <td>44</td>\n",
       "      <td>73</td>\n",
       "      <td>99</td>\n",
       "      <td>555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>29727900.0</td>\n",
       "      <td>207</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>29512900.0</td>\n",
       "      <td>191</td>\n",
       "      <td>28</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>831</td>\n",
       "      <td>0.433014</td>\n",
       "      <td>0.348148</td>\n",
       "      <td>0.473498</td>\n",
       "      <td>0.489</td>\n",
       "      <td>0.783784</td>\n",
       "      <td>27</td>\n",
       "      <td>139</td>\n",
       "      <td>166</td>\n",
       "      <td>155</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>61</td>\n",
       "      <td>496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>28703704.0</td>\n",
       "      <td>305</td>\n",
       "      <td>31</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>2510</td>\n",
       "      <td>0.426907</td>\n",
       "      <td>0.399329</td>\n",
       "      <td>0.474138</td>\n",
       "      <td>0.553</td>\n",
       "      <td>0.854406</td>\n",
       "      <td>66</td>\n",
       "      <td>368</td>\n",
       "      <td>434</td>\n",
       "      <td>537</td>\n",
       "      <td>85</td>\n",
       "      <td>19</td>\n",
       "      <td>183</td>\n",
       "      <td>192</td>\n",
       "      <td>1267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>28530608.0</td>\n",
       "      <td>508</td>\n",
       "      <td>29</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>2914</td>\n",
       "      <td>0.448726</td>\n",
       "      <td>0.297546</td>\n",
       "      <td>0.484938</td>\n",
       "      <td>0.477</td>\n",
       "      <td>0.736749</td>\n",
       "      <td>152</td>\n",
       "      <td>652</td>\n",
       "      <td>804</td>\n",
       "      <td>820</td>\n",
       "      <td>147</td>\n",
       "      <td>20</td>\n",
       "      <td>381</td>\n",
       "      <td>200</td>\n",
       "      <td>2028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>28530608.0</td>\n",
       "      <td>106</td>\n",
       "      <td>30</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>373</td>\n",
       "      <td>0.380952</td>\n",
       "      <td>0.311688</td>\n",
       "      <td>0.439560</td>\n",
       "      <td>0.452</td>\n",
       "      <td>0.803030</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>49</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>24</td>\n",
       "      <td>205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>28299399.0</td>\n",
       "      <td>194</td>\n",
       "      <td>28</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>2551</td>\n",
       "      <td>0.449275</td>\n",
       "      <td>0.367036</td>\n",
       "      <td>0.530949</td>\n",
       "      <td>0.541</td>\n",
       "      <td>0.858322</td>\n",
       "      <td>41</td>\n",
       "      <td>348</td>\n",
       "      <td>389</td>\n",
       "      <td>630</td>\n",
       "      <td>126</td>\n",
       "      <td>50</td>\n",
       "      <td>315</td>\n",
       "      <td>169</td>\n",
       "      <td>2191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>27739975.0</td>\n",
       "      <td>130</td>\n",
       "      <td>28</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>2711</td>\n",
       "      <td>0.456476</td>\n",
       "      <td>0.310105</td>\n",
       "      <td>0.493783</td>\n",
       "      <td>0.488</td>\n",
       "      <td>0.824687</td>\n",
       "      <td>59</td>\n",
       "      <td>256</td>\n",
       "      <td>315</td>\n",
       "      <td>417</td>\n",
       "      <td>85</td>\n",
       "      <td>22</td>\n",
       "      <td>175</td>\n",
       "      <td>151</td>\n",
       "      <td>1840</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       salary   Rk  Age   G  GS    MP  ...  AST  STL  BLK  TOV   PF   PTS\n",
       "0  34682550.0  120   29  51  51  1631  ...  310   80    8  153  114  1346\n",
       "1  33285709.0  248   33  82  82  3026  ...  747  116   71  347  136  2251\n",
       "2  31269231.0  341   32  38  37  1143  ...  105   39   44   73   99   555\n",
       "3  29727900.0  207   27   1   1     5  ...    0    0    0    0    1     2\n",
       "4  29512900.0  191   28  25  25   831  ...  155   11    9   66   61   496\n",
       "5  28703704.0  305   31  78  78  2510  ...  537   85   19  183  192  1267\n",
       "6  28530608.0  508   29  80  80  2914  ...  820  147   20  381  200  2028\n",
       "7  28530608.0  106   30  12  12   373  ...   49   12    3   18   24   205\n",
       "8  28299399.0  194   28  72  72  2551  ...  630  126   50  315  169  2191\n",
       "9  27739975.0  130   28  80  80  2711  ...  417   85   22  175  151  1840\n",
       "\n",
       "[10 rows x 20 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = data.drop(['Player','Tm','FG','FGA','3P','3PA','2P','2PA','FT','FTA','Pos'],axis=1)\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a base model, you can never go wrong with a linear model. We'll do a train-test split, then 3- Fold cross validate on the training set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split, cross_val_score, GridSearchCV\n",
    "from sklearn import metrics\n",
    "X = data.drop('salary',axis=1)\n",
    "X = pd.get_dummies(X)\n",
    "y = data[['salary']]\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linear Regression RMSE with 3 cross validation : 5592997.5461236555\n",
      "Linear Regression Test RMSE 5194095.922658304\n",
      "Average Salary in the Dataset 6696803.098290598\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "model = LinearRegression(normalize=True)\n",
    "model.fit(X_train,y_train)\n",
    "cv = np.mean(cross_val_score(model, X_train, y_train, cv=3,scoring='neg_mean_squared_error'))\n",
    "print (\"Linear Regression RMSE with 3 cross validation :\",np.sqrt(-cv))\n",
    "y_predict_test = model.predict(X_test)\n",
    "score_test = np.sqrt(metrics.mean_squared_error(y_test, y_predict_test))\n",
    "print('Linear Regression Test RMSE',score_test)\n",
    "print('Average Salary in the Dataset',data['salary'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below is the performance of Random Forest. This is  achieved by running a GridSearch. Stay tuned. We'll update this notebook soon, and will employ better feature engineering techniques!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model RMSE with 3 cross validation : 4941272.855393014\n",
      "Test RMSE 5593990.843845949\n",
      "Average Salary in the Dataset 6696803.098290598\n"
     ]
    }
   ],
   "source": [
    "model = RandomForestRegressor(max_depth=9,max_features='auto',n_estimators=500)\n",
    "model.fit(X_train,y_train)\n",
    "cv = np.mean(cross_val_score(model, X_train, y_train, cv=3,scoring='neg_mean_squared_error'))\n",
    "print (\"Model RMSE with 3 cross validation :\",np.sqrt(-cv))\n",
    "y_predict_test = model.predict(X_test)\n",
    "score_test = np.sqrt(metrics.mean_squared_error(y_test, y_predict_test))\n",
    "print('Test RMSE',score_test)\n",
    "print('Average Salary in the Dataset',data['salary'].mean())"
   ]
  }
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