fast_facts.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from functools import reduce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>k</th>\n",
       "      <th>Player</th>\n",
       "      <th>WAR/pos</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>Age</th>\n",
       "      <th>G</th>\n",
       "      <th>PA</th>\n",
       "      <th>AB</th>\n",
       "      <th>...</th>\n",
       "      <th>SF</th>\n",
       "      <th>GDP</th>\n",
       "      <th>SB</th>\n",
       "      <th>CS</th>\n",
       "      <th>BA</th>\n",
       "      <th>OBP</th>\n",
       "      <th>SLG</th>\n",
       "      <th>OPS</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Tm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Mike Trout\\troutmi01</td>\n",
       "      <td>68.7</td>\n",
       "      <td>2011</td>\n",
       "      <td>2019</td>\n",
       "      <td>19-27</td>\n",
       "      <td>1130</td>\n",
       "      <td>4962</td>\n",
       "      <td>4087</td>\n",
       "      <td>...</td>\n",
       "      <td>46</td>\n",
       "      <td>56</td>\n",
       "      <td>196</td>\n",
       "      <td>35</td>\n",
       "      <td>0.306</td>\n",
       "      <td>0.419</td>\n",
       "      <td>0.575</td>\n",
       "      <td>0.994</td>\n",
       "      <td>*87/D9H</td>\n",
       "      <td>LAA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Robinson Cano\\canoro01</td>\n",
       "      <td>45.4</td>\n",
       "      <td>2011</td>\n",
       "      <td>2019</td>\n",
       "      <td>28-36</td>\n",
       "      <td>1230</td>\n",
       "      <td>5292</td>\n",
       "      <td>4803</td>\n",
       "      <td>...</td>\n",
       "      <td>32</td>\n",
       "      <td>155</td>\n",
       "      <td>31</td>\n",
       "      <td>15</td>\n",
       "      <td>0.299</td>\n",
       "      <td>0.358</td>\n",
       "      <td>0.492</td>\n",
       "      <td>0.850</td>\n",
       "      <td>*4/D3H56</td>\n",
       "      <td>NYY-SEA-NYM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Joey Votto\\vottojo01</td>\n",
       "      <td>43.6</td>\n",
       "      <td>2011</td>\n",
       "      <td>2019</td>\n",
       "      <td>27-35</td>\n",
       "      <td>1179</td>\n",
       "      <td>5152</td>\n",
       "      <td>4163</td>\n",
       "      <td>...</td>\n",
       "      <td>36</td>\n",
       "      <td>110</td>\n",
       "      <td>47</td>\n",
       "      <td>18</td>\n",
       "      <td>0.307</td>\n",
       "      <td>0.433</td>\n",
       "      <td>0.511</td>\n",
       "      <td>0.944</td>\n",
       "      <td>*3/HD</td>\n",
       "      <td>CIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Adrian Beltre\\beltrad01</td>\n",
       "      <td>43.2</td>\n",
       "      <td>2011</td>\n",
       "      <td>2018</td>\n",
       "      <td>32-39</td>\n",
       "      <td>1098</td>\n",
       "      <td>4612</td>\n",
       "      <td>4194</td>\n",
       "      <td>...</td>\n",
       "      <td>49</td>\n",
       "      <td>101</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>0.304</td>\n",
       "      <td>0.357</td>\n",
       "      <td>0.509</td>\n",
       "      <td>0.865</td>\n",
       "      <td>*5D/H</td>\n",
       "      <td>TEX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Paul Goldschmidt\\goldspa01</td>\n",
       "      <td>41.2</td>\n",
       "      <td>2011</td>\n",
       "      <td>2019</td>\n",
       "      <td>23-31</td>\n",
       "      <td>1159</td>\n",
       "      <td>4998</td>\n",
       "      <td>4230</td>\n",
       "      <td>...</td>\n",
       "      <td>37</td>\n",
       "      <td>103</td>\n",
       "      <td>124</td>\n",
       "      <td>33</td>\n",
       "      <td>0.296</td>\n",
       "      <td>0.395</td>\n",
       "      <td>0.526</td>\n",
       "      <td>0.921</td>\n",
       "      <td>*3/HD</td>\n",
       "      <td>ARI-STL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  k                      Player  WAR/pos  From    To    Age  \\\n",
       "0           0  1        Mike Trout\\troutmi01     68.7  2011  2019  19-27   \n",
       "1           1  2      Robinson Cano\\canoro01     45.4  2011  2019  28-36   \n",
       "2           2  3        Joey Votto\\vottojo01     43.6  2011  2019  27-35   \n",
       "3           3  4     Adrian Beltre\\beltrad01     43.2  2011  2018  32-39   \n",
       "4           4  5  Paul Goldschmidt\\goldspa01     41.2  2011  2019  23-31   \n",
       "\n",
       "      G    PA    AB     ...       SF  GDP   SB  CS     BA    OBP    SLG  \\\n",
       "0  1130  4962  4087     ...       46   56  196  35  0.306  0.419  0.575   \n",
       "1  1230  5292  4803     ...       32  155   31  15  0.299  0.358  0.492   \n",
       "2  1179  5152  4163     ...       36  110   47  18  0.307  0.433  0.511   \n",
       "3  1098  4612  4194     ...       49  101    8   3  0.304  0.357  0.509   \n",
       "4  1159  4998  4230     ...       37  103  124  33  0.296  0.395  0.526   \n",
       "\n",
       "     OPS       Pos           Tm  \n",
       "0  0.994   *87/D9H          LAA  \n",
       "1  0.850  *4/D3H56  NYY-SEA-NYM  \n",
       "2  0.944     *3/HD          CIN  \n",
       "3  0.865     *5D/H          TEX  \n",
       "4  0.921     *3/HD      ARI-STL  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_stats = pd.read_csv(\"libs/unclean_data/mlb_war_ratings/mlb_war_ratings_all.csv\")\n",
    "mlb_stats.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(mlb_stats)):\n",
    "    mlb_stats.iat[i, 2] = mlb_stats.iat[i, 2].split('\\\\')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'k', 'Player', 'WAR/pos', 'From', 'To', 'Age', 'G', 'PA',\n",
       "       'AB', 'R', 'H', '2B', '3B', 'HR', 'RBI', 'BB', 'IBB', 'SO', 'HBP', 'SH',\n",
       "       'SF', 'GDP', 'SB', 'CS', 'BA', 'OBP', 'SLG', 'OPS', 'Pos', 'Tm'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_stats.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>rank</th>\n",
       "      <th>team</th>\n",
       "      <th>name</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\n\\nAlex Rodriguez\\n\\nDesignated Hitter\\n\\n</td>\n",
       "      <td>$32,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\n\\nVernon Wells\\n\\nLeft Field\\n\\n</td>\n",
       "      <td>$26,187,500</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  rank  team                                         name  \\\n",
       "0           0   1.0   NaN  \\n\\nAlex Rodriguez\\n\\nDesignated Hitter\\n\\n   \n",
       "1           1   2.0   NaN           \\n\\nVernon Wells\\n\\nLeft Field\\n\\n   \n",
       "\n",
       "         salary  year  \n",
       "0  $32,000,000   2011  \n",
       "1  $26,187,500   2011  "
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_salary = pd.read_csv(\"libs/unclean_data/mlb_player_salaries/mlb_player_salaries_all.csv\")\n",
    "mlb_salary.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(mlb_salary)):\n",
    "    mlb_salary.iat[i,3] = mlb_salary.iat[i,3].strip().split('\\n')[0].strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>rank</th>\n",
       "      <th>team</th>\n",
       "      <th>name</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$32,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vernon Wells</td>\n",
       "      <td>$26,187,500</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>C.C. Sabathia</td>\n",
       "      <td>$25,571,428</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mark Teixeira</td>\n",
       "      <td>$23,125,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Joe Mauer</td>\n",
       "      <td>$23,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  rank  team            name        salary  year\n",
       "0           0   1.0   NaN  Alex Rodriguez  $32,000,000   2011\n",
       "1           1   2.0   NaN    Vernon Wells  $26,187,500   2011\n",
       "2           2   3.0   NaN   C.C. Sabathia  $25,571,428   2011\n",
       "3           3   4.0   NaN   Mark Teixeira  $23,125,000   2011\n",
       "4           4   5.0   NaN       Joe Mauer  $23,000,000   2011"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_salary.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>rank</th>\n",
       "      <th>team</th>\n",
       "      <th>Player</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$32,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$26,187,500</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$25,571,428</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$23,125,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$23,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$22,500,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$20,171,428</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$20,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$20,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alex Rodriguez</td>\n",
       "      <td>$20,000,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  rank  team          Player        salary  year\n",
       "0           0   1.0   NaN  Alex Rodriguez  $32,000,000   2011\n",
       "1           1   2.0   NaN  Alex Rodriguez  $26,187,500   2011\n",
       "2           2   3.0   NaN  Alex Rodriguez  $25,571,428   2011\n",
       "3           3   4.0   NaN  Alex Rodriguez  $23,125,000   2011\n",
       "4           4   5.0   NaN  Alex Rodriguez  $23,000,000   2011\n",
       "5           5   6.0   NaN  Alex Rodriguez  $22,500,000   2011\n",
       "6           6   7.0   NaN  Alex Rodriguez  $20,171,428   2011\n",
       "7           7   8.0   NaN  Alex Rodriguez  $20,000,000   2011\n",
       "8           8   NaN   NaN  Alex Rodriguez  $20,000,000   2011\n",
       "9           9   NaN   NaN  Alex Rodriguez  $20,000,000   2011"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_salary.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [],
   "source": [
    "mlb_salary = mlb_salary.rename(columns={\"name\":\"Player\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "mlb_merge = pd.merge(mlb_stats, mlb_salary, on='Player')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9000"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(mlb_merge)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>playerID</th>\n",
       "      <th>birthYear</th>\n",
       "      <th>birthMonth</th>\n",
       "      <th>birthDay</th>\n",
       "      <th>birthCountry</th>\n",
       "      <th>birthState</th>\n",
       "      <th>birthCity</th>\n",
       "      <th>deathYear</th>\n",
       "      <th>deathMonth</th>\n",
       "      <th>deathDay</th>\n",
       "      <th>...</th>\n",
       "      <th>nameLast</th>\n",
       "      <th>nameGiven</th>\n",
       "      <th>weight</th>\n",
       "      <th>height</th>\n",
       "      <th>bats</th>\n",
       "      <th>throws</th>\n",
       "      <th>debut</th>\n",
       "      <th>finalGame</th>\n",
       "      <th>retroID</th>\n",
       "      <th>bbrefID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aardsda01</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>CO</td>\n",
       "      <td>Denver</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Aardsma</td>\n",
       "      <td>David Allan</td>\n",
       "      <td>215.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>2004-04-06</td>\n",
       "      <td>2015-08-23</td>\n",
       "      <td>aardd001</td>\n",
       "      <td>aardsda01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>aaronha01</td>\n",
       "      <td>1934.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>AL</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Aaron</td>\n",
       "      <td>Henry Louis</td>\n",
       "      <td>180.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>1954-04-13</td>\n",
       "      <td>1976-10-03</td>\n",
       "      <td>aaroh101</td>\n",
       "      <td>aaronha01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>aaronto01</td>\n",
       "      <td>1939.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>AL</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Aaron</td>\n",
       "      <td>Tommie Lee</td>\n",
       "      <td>190.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>1962-04-10</td>\n",
       "      <td>1971-09-26</td>\n",
       "      <td>aarot101</td>\n",
       "      <td>aaronto01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>aasedo01</td>\n",
       "      <td>1954.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>CA</td>\n",
       "      <td>Orange</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Aase</td>\n",
       "      <td>Donald William</td>\n",
       "      <td>190.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>1977-07-26</td>\n",
       "      <td>1990-10-03</td>\n",
       "      <td>aased001</td>\n",
       "      <td>aasedo01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>abadan01</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>FL</td>\n",
       "      <td>Palm Beach</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Abad</td>\n",
       "      <td>Fausto Andres</td>\n",
       "      <td>184.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>L</td>\n",
       "      <td>L</td>\n",
       "      <td>2001-09-10</td>\n",
       "      <td>2006-04-13</td>\n",
       "      <td>abada001</td>\n",
       "      <td>abadan01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    playerID  birthYear  birthMonth  birthDay birthCountry birthState  \\\n",
       "0  aardsda01     1981.0        12.0      27.0          USA         CO   \n",
       "1  aaronha01     1934.0         2.0       5.0          USA         AL   \n",
       "2  aaronto01     1939.0         8.0       5.0          USA         AL   \n",
       "3   aasedo01     1954.0         9.0       8.0          USA         CA   \n",
       "4   abadan01     1972.0         8.0      25.0          USA         FL   \n",
       "\n",
       "    birthCity  deathYear  deathMonth  deathDay    ...     nameLast  \\\n",
       "0      Denver        NaN         NaN       NaN    ...      Aardsma   \n",
       "1      Mobile        NaN         NaN       NaN    ...        Aaron   \n",
       "2      Mobile     1984.0         8.0      16.0    ...        Aaron   \n",
       "3      Orange        NaN         NaN       NaN    ...         Aase   \n",
       "4  Palm Beach        NaN         NaN       NaN    ...         Abad   \n",
       "\n",
       "        nameGiven weight height bats throws       debut   finalGame   retroID  \\\n",
       "0     David Allan  215.0   75.0    R      R  2004-04-06  2015-08-23  aardd001   \n",
       "1     Henry Louis  180.0   72.0    R      R  1954-04-13  1976-10-03  aaroh101   \n",
       "2      Tommie Lee  190.0   75.0    R      R  1962-04-10  1971-09-26  aarot101   \n",
       "3  Donald William  190.0   75.0    R      R  1977-07-26  1990-10-03  aased001   \n",
       "4   Fausto Andres  184.0   73.0    L      L  2001-09-10  2006-04-13  abada001   \n",
       "\n",
       "     bbrefID  \n",
       "0  aardsda01  \n",
       "1  aaronha01  \n",
       "2  aaronto01  \n",
       "3   aasedo01  \n",
       "4   abadan01  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_unis = pd.read_csv(\"libs/unclean_data/university_info/bb_players.csv\")\n",
    "mlb_unis.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>playerID</th>\n",
       "      <th>birthYear</th>\n",
       "      <th>birthMonth</th>\n",
       "      <th>birthDay</th>\n",
       "      <th>birthCountry</th>\n",
       "      <th>birthState</th>\n",
       "      <th>birthCity</th>\n",
       "      <th>deathYear</th>\n",
       "      <th>deathMonth</th>\n",
       "      <th>deathDay</th>\n",
       "      <th>...</th>\n",
       "      <th>nameLast</th>\n",
       "      <th>Player</th>\n",
       "      <th>weight</th>\n",
       "      <th>height</th>\n",
       "      <th>bats</th>\n",
       "      <th>throws</th>\n",
       "      <th>debut</th>\n",
       "      <th>finalGame</th>\n",
       "      <th>retroID</th>\n",
       "      <th>bbrefID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aardsda01</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>CO</td>\n",
       "      <td>Denver</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Aardsma</td>\n",
       "      <td>David Allan</td>\n",
       "      <td>215.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>2004-04-06</td>\n",
       "      <td>2015-08-23</td>\n",
       "      <td>aardd001</td>\n",
       "      <td>aardsda01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>aaronha01</td>\n",
       "      <td>1934.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>AL</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Aaron</td>\n",
       "      <td>Henry Louis</td>\n",
       "      <td>180.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>1954-04-13</td>\n",
       "      <td>1976-10-03</td>\n",
       "      <td>aaroh101</td>\n",
       "      <td>aaronha01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>aaronto01</td>\n",
       "      <td>1939.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>AL</td>\n",
       "      <td>Mobile</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Aaron</td>\n",
       "      <td>Tommie Lee</td>\n",
       "      <td>190.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>1962-04-10</td>\n",
       "      <td>1971-09-26</td>\n",
       "      <td>aarot101</td>\n",
       "      <td>aaronto01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>aasedo01</td>\n",
       "      <td>1954.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>CA</td>\n",
       "      <td>Orange</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Aase</td>\n",
       "      <td>Donald William</td>\n",
       "      <td>190.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>R</td>\n",
       "      <td>R</td>\n",
       "      <td>1977-07-26</td>\n",
       "      <td>1990-10-03</td>\n",
       "      <td>aased001</td>\n",
       "      <td>aasedo01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>abadan01</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>FL</td>\n",
       "      <td>Palm Beach</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>Abad</td>\n",
       "      <td>Fausto Andres</td>\n",
       "      <td>184.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>L</td>\n",
       "      <td>L</td>\n",
       "      <td>2001-09-10</td>\n",
       "      <td>2006-04-13</td>\n",
       "      <td>abada001</td>\n",
       "      <td>abadan01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    playerID  birthYear  birthMonth  birthDay birthCountry birthState  \\\n",
       "0  aardsda01     1981.0        12.0      27.0          USA         CO   \n",
       "1  aaronha01     1934.0         2.0       5.0          USA         AL   \n",
       "2  aaronto01     1939.0         8.0       5.0          USA         AL   \n",
       "3   aasedo01     1954.0         9.0       8.0          USA         CA   \n",
       "4   abadan01     1972.0         8.0      25.0          USA         FL   \n",
       "\n",
       "    birthCity  deathYear  deathMonth  deathDay    ...     nameLast  \\\n",
       "0      Denver        NaN         NaN       NaN    ...      Aardsma   \n",
       "1      Mobile        NaN         NaN       NaN    ...        Aaron   \n",
       "2      Mobile     1984.0         8.0      16.0    ...        Aaron   \n",
       "3      Orange        NaN         NaN       NaN    ...         Aase   \n",
       "4  Palm Beach        NaN         NaN       NaN    ...         Abad   \n",
       "\n",
       "           Player weight height bats throws       debut   finalGame   retroID  \\\n",
       "0     David Allan  215.0   75.0    R      R  2004-04-06  2015-08-23  aardd001   \n",
       "1     Henry Louis  180.0   72.0    R      R  1954-04-13  1976-10-03  aaroh101   \n",
       "2      Tommie Lee  190.0   75.0    R      R  1962-04-10  1971-09-26  aarot101   \n",
       "3  Donald William  190.0   75.0    R      R  1977-07-26  1990-10-03  aased001   \n",
       "4   Fausto Andres  184.0   73.0    L      L  2001-09-10  2006-04-13  abada001   \n",
       "\n",
       "     bbrefID  \n",
       "0  aardsda01  \n",
       "1  aaronha01  \n",
       "2  aaronto01  \n",
       "3   aasedo01  \n",
       "4   abadan01  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_unis = mlb_unis.rename(columns={\"nameGiven\":\"Player\"})\n",
    "mlb_unis.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "mlb_schools = pd.read_csv(\"libs/unclean_data/university_info/mlb_player_unis.csv\")\n",
    "mlb_schools = mlb_schools.rename(columns={\"nameGiven\":\"Player\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>playerID</th>\n",
       "      <th>name_full</th>\n",
       "      <th>state</th>\n",
       "      <th>Player</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aardsda01</td>\n",
       "      <td>Pennsylvania State University</td>\n",
       "      <td>PA</td>\n",
       "      <td>David Allan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>aardsda01</td>\n",
       "      <td>Rice University</td>\n",
       "      <td>TX</td>\n",
       "      <td>David Allan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>abadan01</td>\n",
       "      <td>Middle Georgia College</td>\n",
       "      <td>GA</td>\n",
       "      <td>Fausto Andres</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>abbeybe01</td>\n",
       "      <td>University of Vermont</td>\n",
       "      <td>VT</td>\n",
       "      <td>Bert Wood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>abbotje01</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>KY</td>\n",
       "      <td>Jeffrey William</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    playerID                      name_full state           Player\n",
       "0  aardsda01  Pennsylvania State University    PA      David Allan\n",
       "1  aardsda01                Rice University    TX      David Allan\n",
       "2   abadan01         Middle Georgia College    GA    Fausto Andres\n",
       "3  abbeybe01          University of Vermont    VT        Bert Wood\n",
       "4  abbotje01         University of Kentucky    KY  Jeffrey William"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mlb_schools.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_merged = data_merged.rename(columns={\"name_full\":\"college\"})\n",
    "data_merged = data_merged.rename(columns={\"WAR/pos\":\"wins_above_replacement\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "#mlb_merged = pd.merge(mlb_merge, mlb_unis, on='Player')\n",
    "data = [mlb_unis, mlb_stats, mlb_salary, mlb_schools]\n",
    "data_merged = reduce(lambda  left,right: pd.merge(left,right,on=['Player'],\n",
    "                                            how='outer'), data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_mlb = data_merged[[\"Player\",\"salary\",\"college\", \"state\",\"wins_above_replacement\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_mlb.to_csv(\"libs/unclean_data/mlb_fast_facts_data1.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Doing same funcitons with NBA files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Rk</th>\n",
       "      <th>Player</th>\n",
       "      <th>Season</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tm</th>\n",
       "      <th>Lg</th>\n",
       "      <th>PER</th>\n",
       "      <th>G</th>\n",
       "      <th>GS</th>\n",
       "      <th>...</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "      <th>FG%</th>\n",
       "      <th>2P%</th>\n",
       "      <th>3P%</th>\n",
       "      <th>eFG%</th>\n",
       "      <th>FT%</th>\n",
       "      <th>TS%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3801</td>\n",
       "      <td>Kalin Lucas\\lucaska01</td>\n",
       "      <td>2014-15</td>\n",
       "      <td>25</td>\n",
       "      <td>MEM</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3802</td>\n",
       "      <td>Matt Williams\\willima05</td>\n",
       "      <td>2017-18</td>\n",
       "      <td>24</td>\n",
       "      <td>MIA</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0.333</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.417</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3803</td>\n",
       "      <td>Jeff Foote\\footeje01</td>\n",
       "      <td>2011-12</td>\n",
       "      <td>24</td>\n",
       "      <td>NOH</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0.333</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3804</td>\n",
       "      <td>Shane Edwards\\edwarsh01</td>\n",
       "      <td>2013-14</td>\n",
       "      <td>26</td>\n",
       "      <td>CLE</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.333</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>3805</td>\n",
       "      <td>Markel Brown\\brownma02</td>\n",
       "      <td>2017-18</td>\n",
       "      <td>26</td>\n",
       "      <td>HOU</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.357</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0    Rk                   Player   Season  Age   Tm   Lg  PER  G  \\\n",
       "0           0  3801    Kalin Lucas\\lucaska01  2014-15   25  MEM  NBA -0.7  1   \n",
       "1           1  3802  Matt Williams\\willima05  2017-18   24  MIA  NBA -0.7  3   \n",
       "2           2  3803     Jeff Foote\\footeje01  2011-12   24  NOH  NBA -0.9  4   \n",
       "3           3  3804  Shane Edwards\\edwarsh01  2013-14   26  CLE  NBA -1.0  2   \n",
       "4           4  3805   Markel Brown\\brownma02  2017-18   26  HOU  NBA -1.2  4   \n",
       "\n",
       "   GS  ...    BLK  TOV  PF  PTS    FG%    2P%  3P%   eFG%  FT%    TS%  \n",
       "0   0  ...      0    0   1    0  0.000  0.000  NaN  0.000  NaN  0.000  \n",
       "1   0  ...      0    1   1    5  0.333  1.000  0.2  0.417  NaN  0.417  \n",
       "2   0  ...      1    2   5    4  0.333  0.333  NaN  0.333  NaN  0.333  \n",
       "3   0  ...      0    1   1    2  0.333  0.333  NaN  0.333  NaN  0.333  \n",
       "4   0  ...      0    2   6    5  0.286  0.500  0.2  0.357  NaN  0.357  \n",
       "\n",
       "[5 rows x 34 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_per = pd.read_csv(\"libs/unclean_data/nba_per_ratings/nba_per_ratings_all.csv\")\n",
    "nba_per.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>rank</th>\n",
       "      <th>team</th>\n",
       "      <th>name</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\r\\r\\nKobe Bryant\\r\\r\\nSmall Forward\\r\\r\\n</td>\n",
       "      <td>$25,244,493</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\r\\r\\nKevin Garnett\\r\\r\\nPower Forward\\r\\r\\n</td>\n",
       "      <td>$21,247,044</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\r\\r\\nTim Duncan\\r\\r\\nPower Forward\\r\\r\\n</td>\n",
       "      <td>$21,164,619</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\r\\r\\nRashard Lewis\\r\\r\\nPower Forward\\r\\r\\n</td>\n",
       "      <td>$21,136,631</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\r\\r\\nDirk Nowitzki\\r\\r\\nPower Forward\\r\\r\\n</td>\n",
       "      <td>$19,092,873</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  rank  team                                          name  \\\n",
       "0           0   1.0   NaN    \\r\\r\\nKobe Bryant\\r\\r\\nSmall Forward\\r\\r\\n   \n",
       "1           1   2.0   NaN  \\r\\r\\nKevin Garnett\\r\\r\\nPower Forward\\r\\r\\n   \n",
       "2           2   3.0   NaN     \\r\\r\\nTim Duncan\\r\\r\\nPower Forward\\r\\r\\n   \n",
       "3           3   4.0   NaN  \\r\\r\\nRashard Lewis\\r\\r\\nPower Forward\\r\\r\\n   \n",
       "4           4   5.0   NaN  \\r\\r\\nDirk Nowitzki\\r\\r\\nPower Forward\\r\\r\\n   \n",
       "\n",
       "          salary  year  \n",
       "0  $25,244,493    2011  \n",
       "1  $21,247,044    2011  \n",
       "2  $21,164,619    2011  \n",
       "3  $21,136,631    2011  \n",
       "4  $19,092,873    2011  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_sal = pd.read_csv(\"libs/unclean_data/nba_player_salaries/nba_player_salaries_all.csv\")\n",
    "nba_sal.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'rank', 'team', 'name', 'salary', 'year'], dtype='object')"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_sal.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(nba_per)):\n",
    "    nba_per.iat[i, 2] = nba_per.iat[i, 2].split('\\\\')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>TOV</th>\n",
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       "      <th>2P%</th>\n",
       "      <th>3P%</th>\n",
       "      <th>eFG%</th>\n",
       "      <th>FT%</th>\n",
       "      <th>TS%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3801</td>\n",
       "      <td>Kalin Lucas</td>\n",
       "      <td>2014-15</td>\n",
       "      <td>25</td>\n",
       "      <td>MEM</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3802</td>\n",
       "      <td>Matt Williams</td>\n",
       "      <td>2017-18</td>\n",
       "      <td>24</td>\n",
       "      <td>MIA</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0.333</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.417</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3803</td>\n",
       "      <td>Jeff Foote</td>\n",
       "      <td>2011-12</td>\n",
       "      <td>24</td>\n",
       "      <td>NOH</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0.333</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3804</td>\n",
       "      <td>Shane Edwards</td>\n",
       "      <td>2013-14</td>\n",
       "      <td>26</td>\n",
       "      <td>CLE</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.333</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>3805</td>\n",
       "      <td>Markel Brown</td>\n",
       "      <td>2017-18</td>\n",
       "      <td>26</td>\n",
       "      <td>HOU</td>\n",
       "      <td>NBA</td>\n",
       "      <td>-1.2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.357</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0    Rk         Player   Season  Age   Tm   Lg  PER  G  GS  ...    \\\n",
       "0           0  3801    Kalin Lucas  2014-15   25  MEM  NBA -0.7  1   0  ...     \n",
       "1           1  3802  Matt Williams  2017-18   24  MIA  NBA -0.7  3   0  ...     \n",
       "2           2  3803     Jeff Foote  2011-12   24  NOH  NBA -0.9  4   0  ...     \n",
       "3           3  3804  Shane Edwards  2013-14   26  CLE  NBA -1.0  2   0  ...     \n",
       "4           4  3805   Markel Brown  2017-18   26  HOU  NBA -1.2  4   0  ...     \n",
       "\n",
       "   BLK  TOV  PF  PTS    FG%    2P%  3P%   eFG%  FT%    TS%  \n",
       "0    0    0   1    0  0.000  0.000  NaN  0.000  NaN  0.000  \n",
       "1    0    1   1    5  0.333  1.000  0.2  0.417  NaN  0.417  \n",
       "2    1    2   5    4  0.333  0.333  NaN  0.333  NaN  0.333  \n",
       "3    0    1   1    2  0.333  0.333  NaN  0.333  NaN  0.333  \n",
       "4    0    2   6    5  0.286  0.500  0.2  0.357  NaN  0.357  \n",
       "\n",
       "[5 rows x 34 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_per.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(nba_sal)):\n",
    "    first = nba_sal['name'][0].strip().split('\\n')[0].strip()\n",
    "    nba_sal[\"name\"] = first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>rank</th>\n",
       "      <th>team</th>\n",
       "      <th>name</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kobe Bryant</td>\n",
       "      <td>$25,244,493</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kobe Bryant</td>\n",
       "      <td>$21,247,044</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kobe Bryant</td>\n",
       "      <td>$21,164,619</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kobe Bryant</td>\n",
       "      <td>$21,136,631</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kobe Bryant</td>\n",
       "      <td>$19,092,873</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  rank  team         name         salary  year\n",
       "0           0   1.0   NaN  Kobe Bryant  $25,244,493    2011\n",
       "1           1   2.0   NaN  Kobe Bryant  $21,247,044    2011\n",
       "2           2   3.0   NaN  Kobe Bryant  $21,164,619    2011\n",
       "3           3   4.0   NaN  Kobe Bryant  $21,136,631    2011\n",
       "4           4   5.0   NaN  Kobe Bryant  $19,092,873    2011"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_sal.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "nba_sal = nba_sal.rename(columns={\"name\":\"Player\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9000"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nba_sal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>index</th>\n",
       "      <th>Player</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Acadia University</td>\n",
       "      <td>Brian Heaney</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Alabama A&amp;M University</td>\n",
       "      <td>Mickell Gladness</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>Kevin Loder</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>Caldwell Jones</td>\n",
       "      <td>GA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>Major Jones</td>\n",
       "      <td>GA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                     index            Player state\n",
       "0           0         Acadia University      Brian Heaney   NaN\n",
       "1           1    Alabama A&M University  Mickell Gladness    AL\n",
       "2           2  Alabama State University       Kevin Loder    AL\n",
       "3           3   Albany State University    Caldwell Jones    GA\n",
       "4           4   Albany State University       Major Jones    GA"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_unis = pd.read_csv(\"libs/unclean_data/university_info/nba_player_unis.csv\")\n",
    "nba_unis.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "nba_df = [nba_unis, nba_sal, nba_per, nba_col] \n",
    "nba_merged = reduce(lambda  left,right: pd.merge(left,right,on=['Player'],\n",
    "                                            how='outer'), nba_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>year</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>...</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "      <th>FG%</th>\n",
       "      <th>2P%</th>\n",
       "      <th>3P%</th>\n",
       "      <th>eFG%</th>\n",
       "      <th>FT%</th>\n",
       "      <th>TS%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>Acadia University</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>Alabama A&amp;M University</td>\n",
       "      <td>Mickell Gladness</td>\n",
       "      <td>AL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2961.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.424</td>\n",
       "      <td>0.424</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.424</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>Alabama A&amp;M University</td>\n",
       "      <td>Mickell Gladness</td>\n",
       "      <td>AL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6561.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.424</td>\n",
       "      <td>0.424</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.424</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.0</td>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>Kevin Loder</td>\n",
       "      <td>AL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>Caldwell Jones</td>\n",
       "      <td>GA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0_x                     index            Player state  \\\n",
       "0           0.0         Acadia University      Brian Heaney   NaN   \n",
       "1           1.0    Alabama A&M University  Mickell Gladness    AL   \n",
       "2           1.0    Alabama A&M University  Mickell Gladness    AL   \n",
       "3           2.0  Alabama State University       Kevin Loder    AL   \n",
       "4           3.0   Albany State University    Caldwell Jones    GA   \n",
       "\n",
       "   Unnamed: 0_y  rank  team salary  year  Unnamed: 0  ...     BLK  TOV    PF  \\\n",
       "0           NaN   NaN   NaN    NaN   NaN         NaN  ...     NaN  NaN   NaN   \n",
       "1           NaN   NaN   NaN    NaN   NaN      2961.0  ...    20.0  7.0  32.0   \n",
       "2           NaN   NaN   NaN    NaN   NaN      6561.0  ...    20.0  7.0  32.0   \n",
       "3           NaN   NaN   NaN    NaN   NaN         NaN  ...     NaN  NaN   NaN   \n",
       "4           NaN   NaN   NaN    NaN   NaN         NaN  ...     NaN  NaN   NaN   \n",
       "\n",
       "    PTS    FG%    2P%  3P%   eFG%  FT%    TS%  \n",
       "0   NaN    NaN    NaN  NaN    NaN  NaN    NaN  \n",
       "1  56.0  0.424  0.424  NaN  0.424  0.5  0.436  \n",
       "2  56.0  0.424  0.424  NaN  0.424  0.5  0.436  \n",
       "3   NaN    NaN    NaN  NaN    NaN  NaN    NaN  \n",
       "4   NaN    NaN    NaN  NaN    NaN  NaN    NaN  \n",
       "\n",
       "[5 rows x 42 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_merged.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "nba_merged.to_csv(\"libs/unclean_data/nba_fast_facts_data.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Doing same for NFL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Rk</th>\n",
       "      <th>Player</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>Draft</th>\n",
       "      <th>Tm</th>\n",
       "      <th>Lg</th>\n",
       "      <th>G</th>\n",
       "      <th>GS</th>\n",
       "      <th>Yrs</th>\n",
       "      <th>PB</th>\n",
       "      <th>AP1</th>\n",
       "      <th>AV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Tom Brady\\BradTo00</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>6-199</td>\n",
       "      <td>NWE</td>\n",
       "      <td>NFL</td>\n",
       "      <td>156.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew Brees\\BreeDr00</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>2-32</td>\n",
       "      <td>NOR</td>\n",
       "      <td>NFL</td>\n",
       "      <td>157.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Aaron Rodgers\\RodgAa00</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>1-24</td>\n",
       "      <td>GNB</td>\n",
       "      <td>NFL</td>\n",
       "      <td>142.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Matt Ryan\\RyanMa00</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>1-3</td>\n",
       "      <td>ATL</td>\n",
       "      <td>NFL</td>\n",
       "      <td>158.0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Philip Rivers\\RivePh00</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>1-4</td>\n",
       "      <td>SDG</td>\n",
       "      <td>NFL</td>\n",
       "      <td>160.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Rk                  Player  From    To  Draft   Tm   Lg      G  \\\n",
       "0           0   1      Tom Brady\\BradTo00  2009  2018  6-199  NWE  NFL  156.0   \n",
       "1           1   2     Drew Brees\\BreeDr00  2009  2018   2-32  NOR  NFL  157.0   \n",
       "2           2   3  Aaron Rodgers\\RodgAa00  2009  2018   1-24  GNB  NFL  142.0   \n",
       "3           3   4      Matt Ryan\\RyanMa00  2009  2018    1-3  ATL  NFL  158.0   \n",
       "4           4   5  Philip Rivers\\RivePh00  2009  2018    1-4  SDG  NFL  160.0   \n",
       "\n",
       "      GS  Yrs  PB  AP1   AV  \n",
       "0  156.0   10  10    2  165  \n",
       "1  157.0   10   9    0  161  \n",
       "2  142.0   10   7    2  155  \n",
       "3  158.0   10   4    1  152  \n",
       "4  160.0   10   7    0  143  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_av = pd.read_csv(\"libs/unclean_data/nfl_av_ratings/nfl_av_ratings_all.csv\")\n",
    "nfl_sal = pd.read_csv(\"libs/unclean_data/nfl_player_salaries/nfl_player_salaries_all.csv\")\n",
    "nfl_av.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(nfl_av)):\n",
    "    nfl_av.iat[i, 2] = nfl_av.iat[i, 2].split('\\\\')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Rk</th>\n",
       "      <th>Player</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>Draft</th>\n",
       "      <th>Tm</th>\n",
       "      <th>Lg</th>\n",
       "      <th>G</th>\n",
       "      <th>GS</th>\n",
       "      <th>Yrs</th>\n",
       "      <th>PB</th>\n",
       "      <th>AP1</th>\n",
       "      <th>AV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>6-199</td>\n",
       "      <td>NWE</td>\n",
       "      <td>NFL</td>\n",
       "      <td>156.0</td>\n",
       "      <td>156.0</td>\n",
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       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew Brees</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>2-32</td>\n",
       "      <td>NOR</td>\n",
       "      <td>NFL</td>\n",
       "      <td>157.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Aaron Rodgers</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>1-24</td>\n",
       "      <td>GNB</td>\n",
       "      <td>NFL</td>\n",
       "      <td>142.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Matt Ryan</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>1-3</td>\n",
       "      <td>ATL</td>\n",
       "      <td>NFL</td>\n",
       "      <td>158.0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Philip Rivers</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>1-4</td>\n",
       "      <td>SDG</td>\n",
       "      <td>NFL</td>\n",
       "      <td>160.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Rk         Player  From    To  Draft   Tm   Lg      G     GS  \\\n",
       "0           0   1      Tom Brady  2009  2018  6-199  NWE  NFL  156.0  156.0   \n",
       "1           1   2     Drew Brees  2009  2018   2-32  NOR  NFL  157.0  157.0   \n",
       "2           2   3  Aaron Rodgers  2009  2018   1-24  GNB  NFL  142.0  142.0   \n",
       "3           3   4      Matt Ryan  2009  2018    1-3  ATL  NFL  158.0  158.0   \n",
       "4           4   5  Philip Rivers  2009  2018    1-4  SDG  NFL  160.0  160.0   \n",
       "\n",
       "   Yrs  PB  AP1   AV  \n",
       "0   10  10    2  165  \n",
       "1   10   9    0  161  \n",
       "2   10   7    2  155  \n",
       "3   10   4    1  152  \n",
       "4   10   7    0  143  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_av.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Richard Seymour</td>\n",
       "      <td>$17,818,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mark Sanchez</td>\n",
       "      <td>$17,228,125</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dwight Freeney</td>\n",
       "      <td>$16,420,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Larry Fitzgerald</td>\n",
       "      <td>$16,250,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mario Williams</td>\n",
       "      <td>$16,200,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               name         salary  year\n",
       "0   Richard Seymour  $17,818,000    2011\n",
       "1      Mark Sanchez  $17,228,125    2011\n",
       "2    Dwight Freeney  $16,420,000    2011\n",
       "3  Larry Fitzgerald  $16,250,000    2011\n",
       "4    Mario Williams  $16,200,000    2011"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_sal.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Richard Seymour</td>\n",
       "      <td>$17,818,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mark Sanchez</td>\n",
       "      <td>$17,228,125</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dwight Freeney</td>\n",
       "      <td>$16,420,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Larry Fitzgerald</td>\n",
       "      <td>$16,250,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mario Williams</td>\n",
       "      <td>$16,200,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Player         salary  year\n",
       "0   Richard Seymour  $17,818,000    2011\n",
       "1      Mark Sanchez  $17,228,125    2011\n",
       "2    Dwight Freeney  $16,420,000    2011\n",
       "3  Larry Fitzgerald  $16,250,000    2011\n",
       "4    Mario Williams  $16,200,000    2011"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_sal = nfl_sal.rename(columns={\"name\":\"Player\"})\n",
    "nfl_sal.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "nfl_merge = pd.merge(nfl_av, nfl_sal, on='Player')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Tm</th>\n",
       "      <th>Lg</th>\n",
       "      <th>G</th>\n",
       "      <th>GS</th>\n",
       "      <th>Yrs</th>\n",
       "      <th>PB</th>\n",
       "      <th>AP1</th>\n",
       "      <th>AV</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>6-199</td>\n",
       "      <td>NWE</td>\n",
       "      <td>NFL</td>\n",
       "      <td>156.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>$12,950,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>6-199</td>\n",
       "      <td>NWE</td>\n",
       "      <td>NFL</td>\n",
       "      <td>156.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>$12,950,000</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>6-199</td>\n",
       "      <td>NWE</td>\n",
       "      <td>NFL</td>\n",
       "      <td>156.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>$8,000,000</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>6-199</td>\n",
       "      <td>NWE</td>\n",
       "      <td>NFL</td>\n",
       "      <td>156.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>$13,800,000</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Tom Brady</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>6-199</td>\n",
       "      <td>NWE</td>\n",
       "      <td>NFL</td>\n",
       "      <td>156.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>$14,800,000</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Rk     Player  From    To  Draft   Tm   Lg      G     GS  Yrs  \\\n",
       "0           0   1  Tom Brady  2009  2018  6-199  NWE  NFL  156.0  156.0   10   \n",
       "1           0   1  Tom Brady  2009  2018  6-199  NWE  NFL  156.0  156.0   10   \n",
       "2           0   1  Tom Brady  2009  2018  6-199  NWE  NFL  156.0  156.0   10   \n",
       "3           0   1  Tom Brady  2009  2018  6-199  NWE  NFL  156.0  156.0   10   \n",
       "4           0   1  Tom Brady  2009  2018  6-199  NWE  NFL  156.0  156.0   10   \n",
       "\n",
       "   PB  AP1   AV         salary  year  \n",
       "0  10    2  165  $12,950,000    2011  \n",
       "1  10    2  165  $12,950,000    2011  \n",
       "2  10    2  165   $8,000,000    2012  \n",
       "3  10    2  165  $13,800,000    2013  \n",
       "4  10    2  165  $14,800,000    2014  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_merge.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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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>index</th>\n",
       "      <th>college</th>\n",
       "      <th>name</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Allegheny College</td>\n",
       "      <td>Allegheny</td>\n",
       "      <td>Ronnie Anderson</td>\n",
       "      <td>PA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Allegheny College</td>\n",
       "      <td>Allegheny</td>\n",
       "      <td>Eddie Wall</td>\n",
       "      <td>PA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Alma College</td>\n",
       "      <td>Alma</td>\n",
       "      <td>Mark Konecny</td>\n",
       "      <td>MI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Amherst College</td>\n",
       "      <td>Amherst</td>\n",
       "      <td>Freddie Scott</td>\n",
       "      <td>MA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Amherst College</td>\n",
       "      <td>Amherst</td>\n",
       "      <td>Kid Hill</td>\n",
       "      <td>MA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0              index    college              name state\n",
       "0           0  Allegheny College  Allegheny  Ronnie Anderson     PA\n",
       "1           1  Allegheny College  Allegheny        Eddie Wall    PA\n",
       "2           2       Alma College       Alma      Mark Konecny    MI\n",
       "3           3    Amherst College    Amherst     Freddie Scott    MA\n",
       "4           4    Amherst College    Amherst          Kid Hill    MA"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_unis = pd.read_csv(\"libs/unclean_data/university_info/nfl_player_unis.csv\")\n",
    "nfl_unis.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>index</th>\n",
       "      <th>college</th>\n",
       "      <th>Player</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Allegheny College</td>\n",
       "      <td>Allegheny</td>\n",
       "      <td>Ronnie Anderson</td>\n",
       "      <td>PA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Allegheny College</td>\n",
       "      <td>Allegheny</td>\n",
       "      <td>Eddie Wall</td>\n",
       "      <td>PA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Alma College</td>\n",
       "      <td>Alma</td>\n",
       "      <td>Mark Konecny</td>\n",
       "      <td>MI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Amherst College</td>\n",
       "      <td>Amherst</td>\n",
       "      <td>Freddie Scott</td>\n",
       "      <td>MA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Amherst College</td>\n",
       "      <td>Amherst</td>\n",
       "      <td>Kid Hill</td>\n",
       "      <td>MA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0              index    college            Player state\n",
       "0           0  Allegheny College  Allegheny  Ronnie Anderson     PA\n",
       "1           1  Allegheny College  Allegheny        Eddie Wall    PA\n",
       "2           2       Alma College       Alma      Mark Konecny    MI\n",
       "3           3    Amherst College    Amherst     Freddie Scott    MA\n",
       "4           4    Amherst College    Amherst          Kid Hill    MA"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_unis = nfl_unis.rename(columns={\"name\":\"Player\"})\n",
    "nfl_unis.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "#nfl_merge = pd.merge(nfl_merge, nfl_unis, on='Player')\n",
    "#nfl_merge.to_csv(\"libs/unclean_data/nfl_fast_facts_data.csv\")\n",
    "nfl_data = pd.read_csv(\"libs/unclean_data/nfl_fast_facts_data1.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0_x</th>\n",
       "      <th>Rk</th>\n",
       "      <th>Player</th>\n",
       "      <th>From</th>\n",
       "      <th>To</th>\n",
       "      <th>Draft</th>\n",
       "      <th>Tm</th>\n",
       "      <th>Lg</th>\n",
       "      <th>G</th>\n",
       "      <th>...</th>\n",
       "      <th>Yrs</th>\n",
       "      <th>PB</th>\n",
       "      <th>AP1</th>\n",
       "      <th>AV</th>\n",
       "      <th>salary</th>\n",
       "      <th>year</th>\n",
       "      <th>Unnamed: 0_y</th>\n",
       "      <th>index</th>\n",
       "      <th>college</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew Brees</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>2-32</td>\n",
       "      <td>NOR</td>\n",
       "      <td>NFL</td>\n",
       "      <td>157.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "      <td>$12,574,700</td>\n",
       "      <td>2011</td>\n",
       "      <td>9398</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>Purdue</td>\n",
       "      <td>IN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew Brees</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>2-32</td>\n",
       "      <td>NOR</td>\n",
       "      <td>NFL</td>\n",
       "      <td>157.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "      <td>$12,574,700</td>\n",
       "      <td>2011</td>\n",
       "      <td>9398</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>Purdue</td>\n",
       "      <td>IN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew Brees</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>2-32</td>\n",
       "      <td>NOR</td>\n",
       "      <td>NFL</td>\n",
       "      <td>157.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "      <td>$10,400,000</td>\n",
       "      <td>2012</td>\n",
       "      <td>9398</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>Purdue</td>\n",
       "      <td>IN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew Brees</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>2-32</td>\n",
       "      <td>NOR</td>\n",
       "      <td>NFL</td>\n",
       "      <td>157.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "      <td>$17,400,000</td>\n",
       "      <td>2013</td>\n",
       "      <td>9398</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>Purdue</td>\n",
       "      <td>IN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Drew Brees</td>\n",
       "      <td>2009</td>\n",
       "      <td>2018</td>\n",
       "      <td>2-32</td>\n",
       "      <td>NOR</td>\n",
       "      <td>NFL</td>\n",
       "      <td>157.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>161</td>\n",
       "      <td>$18,400,000</td>\n",
       "      <td>2014</td>\n",
       "      <td>9398</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>Purdue</td>\n",
       "      <td>IN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  Unnamed: 0_x  Rk      Player  From    To Draft   Tm   Lg  \\\n",
       "0           0             1   2  Drew Brees  2009  2018  2-32  NOR  NFL   \n",
       "1           1             1   2  Drew Brees  2009  2018  2-32  NOR  NFL   \n",
       "2           2             1   2  Drew Brees  2009  2018  2-32  NOR  NFL   \n",
       "3           3             1   2  Drew Brees  2009  2018  2-32  NOR  NFL   \n",
       "4           4             1   2  Drew Brees  2009  2018  2-32  NOR  NFL   \n",
       "\n",
       "       G  ...   Yrs  PB  AP1   AV         salary  year  Unnamed: 0_y  \\\n",
       "0  157.0  ...    10   9    0  161  $12,574,700    2011          9398   \n",
       "1  157.0  ...    10   9    0  161  $12,574,700    2011          9398   \n",
       "2  157.0  ...    10   9    0  161  $10,400,000    2012          9398   \n",
       "3  157.0  ...    10   9    0  161  $17,400,000    2013          9398   \n",
       "4  157.0  ...    10   9    0  161  $18,400,000    2014          9398   \n",
       "\n",
       "               index college state  \n",
       "0  Purdue University  Purdue    IN  \n",
       "1  Purdue University  Purdue    IN  \n",
       "2  Purdue University  Purdue    IN  \n",
       "3  Purdue University  Purdue    IN  \n",
       "4  Purdue University  Purdue    IN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'Unnamed: 0_x', 'Rk', 'Player', 'From', 'To', 'Draft',\n",
       "       'Tm', 'Lg', 'G', 'GS', 'Yrs', 'PB', 'AP1', 'AV', 'salary', 'year',\n",
       "       'Unnamed: 0_y', 'index', 'college', 'state'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfl_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = nfl_data[[\"Player\",\"salary\",\"college\", \"state\",\"AV\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(final_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df.to_csv(\"libs/unclean_data/nfl_fast_facts_data2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0_x', 'index', 'Player', 'state', 'Unnamed: 0_y', 'rank',\n",
       "       'team', 'salary', 'year', 'Unnamed: 0', 'Rk', 'Season', 'Age', 'Tm',\n",
       "       'Lg', 'PER', 'G', 'GS', 'MP', 'FG', 'FGA', '2P', '2PA', '3P', '3PA',\n",
       "       'FT', 'FTA', 'ORB', 'DRB', 'TRB', 'AST', 'STL', 'BLK', 'TOV', 'PF',\n",
       "       'PTS', 'FG%', '2P%', '3P%', 'eFG%', 'FT%', 'TS%'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba_merged.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "nba_col = pd.read_csv(\"libs/unclean_data/university_info/nba_player_universities.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_nba = nba_merged[[\"Player\", \"salary\", \"collage\", \"state\", \"PER\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_nba = final_nba.rename(columns={\"collage\":\"college\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_nba.to_csv(\"libs/unclean_data/nba_fast_facts_data1.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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