nba_normalforms.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4b6546a8-f779-4217-b4bb-d4883303af37",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import psycopg\n",
    "from sqlalchemy import create_engine\n",
    "import dotenv\n",
    "import os\n",
    "#import sqlite3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a547cf7f-a8cd-49d1-8875-5becb4aad50e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "nba = pd.read_csv('ASA All NBA Raw Data.csv', low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ba53f03a-b429-40bd-8015-b7d507f66511",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>game_id</th>\n",
       "      <th>game_date</th>\n",
       "      <th>OT</th>\n",
       "      <th>H_A</th>\n",
       "      <th>Team_Abbrev</th>\n",
       "      <th>Team_Score</th>\n",
       "      <th>Team_pace</th>\n",
       "      <th>Team_efg_pct</th>\n",
       "      <th>Team_tov_pct</th>\n",
       "      <th>Team_orb_pct</th>\n",
       "      <th>...</th>\n",
       "      <th>pf_per_minute</th>\n",
       "      <th>ts</th>\n",
       "      <th>last_60_minutes_per_game_starting</th>\n",
       "      <th>last_60_minutes_per_game_bench</th>\n",
       "      <th>PG%</th>\n",
       "      <th>SG%</th>\n",
       "      <th>SF%</th>\n",
       "      <th>PF%</th>\n",
       "      <th>C%</th>\n",
       "      <th>active_position_minutes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.061538</td>\n",
       "      <td>9.00</td>\n",
       "      <td>31.716667</td>\n",
       "      <td>22.017778</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.253586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.099119</td>\n",
       "      <td>7.44</td>\n",
       "      <td>34.324000</td>\n",
       "      <td>18.475954</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>52.152590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>29.820290</td>\n",
       "      <td>16.051693</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>47.021807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.048387</td>\n",
       "      <td>7.88</td>\n",
       "      <td>29.920833</td>\n",
       "      <td>14.603922</td>\n",
       "      <td>90.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.603314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.88</td>\n",
       "      <td>20.095833</td>\n",
       "      <td>14.538095</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>36.472537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.097297</td>\n",
       "      <td>11.76</td>\n",
       "      <td>33.812500</td>\n",
       "      <td>23.658333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.944529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.109756</td>\n",
       "      <td>10.00</td>\n",
       "      <td>20.776017</td>\n",
       "      <td>11.183333</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.083850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036697</td>\n",
       "      <td>15.88</td>\n",
       "      <td>29.610183</td>\n",
       "      <td>15.938596</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>53.836511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.267618</td>\n",
       "      <td>8.32</td>\n",
       "      <td>12.768456</td>\n",
       "      <td>6.873016</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>52.255931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.231362</td>\n",
       "      <td>5.88</td>\n",
       "      <td>20.789815</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>36.472537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        game_id   game_date  OT H_A Team_Abbrev  Team_Score  Team_pace  \\\n",
       "0  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "1  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "2  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "3  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "4  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "5  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "6  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "7  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "8  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "9  202202170BRK  2022-02-17   0   A         WAS         117       94.5   \n",
       "\n",
       "   Team_efg_pct  Team_tov_pct  Team_orb_pct  ...  pf_per_minute     ts  \\\n",
       "0         0.627          13.5          22.9  ...       0.061538   9.00   \n",
       "1         0.627          13.5          22.9  ...       0.099119   7.44   \n",
       "2         0.627          13.5          22.9  ...       0.000000   7.00   \n",
       "3         0.627          13.5          22.9  ...       0.048387   7.88   \n",
       "4         0.627          13.5          22.9  ...       0.000000   6.88   \n",
       "5         0.627          13.5          22.9  ...       0.097297  11.76   \n",
       "6         0.627          13.5          22.9  ...       0.109756  10.00   \n",
       "7         0.627          13.5          22.9  ...       0.036697  15.88   \n",
       "8         0.627          13.5          22.9  ...       0.267618   8.32   \n",
       "9         0.627          13.5          22.9  ...       0.231362   5.88   \n",
       "\n",
       "  last_60_minutes_per_game_starting last_60_minutes_per_game_bench    PG%  \\\n",
       "0                         31.716667                      22.017778    1.0   \n",
       "1                         34.324000                      18.475954    0.0   \n",
       "2                         29.820290                      16.051693    0.0   \n",
       "3                         29.920833                      14.603922   90.0   \n",
       "4                         20.095833                      14.538095    0.0   \n",
       "5                         33.812500                      23.658333    0.0   \n",
       "6                         20.776017                      11.183333  100.0   \n",
       "7                         29.610183                      15.938596    0.0   \n",
       "8                         12.768456                       6.873016    0.0   \n",
       "9                         20.789815                       4.350000    0.0   \n",
       "\n",
       "    SG%   SF%   PF%     C%  active_position_minutes  \n",
       "0  36.0  60.0   4.0    0.0                46.253586  \n",
       "1   0.0   4.0  85.0   11.0                52.152590  \n",
       "2  32.0  67.0   0.0    0.0                47.021807  \n",
       "3  10.0   0.0   0.0    0.0                27.603314  \n",
       "4   0.0   0.0   0.0  100.0                36.472537  \n",
       "5   7.0  62.0  31.0    0.0                54.944529  \n",
       "6   0.0   0.0   0.0    0.0                28.083850  \n",
       "7   0.0  33.0  57.0   10.0                53.836511  \n",
       "8   0.0  16.0  70.0   14.0                52.255931  \n",
       "9   0.0   0.0   0.0  100.0                36.472537  \n",
       "\n",
       "[10 rows x 81 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_rows', 81)\n",
    "nba.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e648164d-5433-4c61-b63a-628e7cbaac7c",
   "metadata": {},
   "source": [
    "## Database Normalization\n",
    "### First normal form:\n",
    "\n",
    "1. **All tables must have a primary key**: In this table, `game_id` and `player_id` together are unique on every row, and so they form primary key.\n",
    "\n",
    "2. **All the data must be atomic**: Inactives is non-atomic.\n",
    "\n",
    "3. **No repeating groups problem**: We can't solve the non-atomicity problem by creating separate columns if this leads to arbitrary ordering language in the column names (for example, `Inactive1`, `Inactive2`, etc.) and if it leads to a lot of missing data (there would be an `Inactive7` which would be missing any time a team has less than 7 inactive players)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "99191f57",
   "metadata": {},
   "outputs": [],
   "source": [
    "nba = nba.drop(['Inactives'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b45adf1e-17e8-4f17-be87-9eeea24426be",
   "metadata": {},
   "source": [
    "### Functional Dependence\n",
    "Let X and Y be columns in a data table. Y is functionally dependent on X if each value of X has exactly one value of Y.\n",
    "\n",
    "That's pretty abstract. So here are some guidelines that help me:\n",
    "\n",
    "1. This use of \"function\" is the exact same as the concept of a function from algebra and pre-calculus. A correspondence f(x)=y is a function if each value of x has only one associated value of y.\n",
    "\n",
    "2. X is either a primary key, or something that should be a primary key in another table.\n",
    "\n",
    "For example, `game_date` (Y) is functionally dependent on `game_id` (X) because one `game_id` takes place on exactly one date.\n",
    "\n",
    "### Second normal form:\n",
    "In this table the primary key is a superkey consisting of two columns: `game_id` and `player_id`. \n",
    "\n",
    "2NF is violated if any columns are functionally dependent on part of the primary key but not the entire primary key. This can only happen if the primary key is a superkey."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cb708ecd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>game_id</th>\n",
       "      <th>game_date</th>\n",
       "      <th>OT</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>202202170CHO</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>2</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>202202170LAC</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>202202170MIL</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>202202170NOP</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>108259</th>\n",
       "      <td>202001080GSW</td>\n",
       "      <td>2020-01-08</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108887</th>\n",
       "      <td>202008020HOU</td>\n",
       "      <td>2020-08-02</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109683</th>\n",
       "      <td>201911060HOU</td>\n",
       "      <td>2019-11-06</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110125</th>\n",
       "      <td>201912250GSW</td>\n",
       "      <td>2019-12-25</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110643</th>\n",
       "      <td>202002200GSW</td>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3197 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             game_id   game_date  OT  season\n",
       "0       202202170BRK  2022-02-17   0    2022\n",
       "26      202202170CHO  2022-02-17   2    2022\n",
       "48      202202170LAC  2022-02-17   0    2022\n",
       "71      202202170MIL  2022-02-17   0    2022\n",
       "95      202202170NOP  2022-02-17   0    2022\n",
       "...              ...         ...  ..     ...\n",
       "108259  202001080GSW  2020-01-08   0    2020\n",
       "108887  202008020HOU  2020-08-02   0    2020\n",
       "109683  201911060HOU  2019-11-06   0    2020\n",
       "110125  201912250GSW  2019-12-25   0    2020\n",
       "110643  202002200GSW  2020-02-20   0    2020\n",
       "\n",
       "[3197 rows x 4 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove columns that violate this\n",
    "games = nba[['game_id', 'game_date', 'OT', 'season']].drop_duplicates()\n",
    "games"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d652b020",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>player_id</th>\n",
       "      <th>player</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>kispeco01</td>\n",
       "      <td>Corey Kispert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>kuzmaky01</td>\n",
       "      <td>Kyle Kuzma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>caldwke01</td>\n",
       "      <td>Kentavious Caldwell-Pope</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>netora01</td>\n",
       "      <td>Raul Neto</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bryanth01</td>\n",
       "      <td>Thomas Bryant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109702</th>\n",
       "      <td>frazimi01</td>\n",
       "      <td>Michael Frazier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110441</th>\n",
       "      <td>howarwi01</td>\n",
       "      <td>William Howard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110913</th>\n",
       "      <td>mbahalu01</td>\n",
       "      <td>Luc Mbah a Moute</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111399</th>\n",
       "      <td>bowmaky01</td>\n",
       "      <td>Ky Bowman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112021</th>\n",
       "      <td>pargoje01</td>\n",
       "      <td>Jeremy Pargo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>812 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        player_id                    player\n",
       "0       kispeco01             Corey Kispert\n",
       "1       kuzmaky01                Kyle Kuzma\n",
       "2       caldwke01  Kentavious Caldwell-Pope\n",
       "3        netora01                 Raul Neto\n",
       "4       bryanth01             Thomas Bryant\n",
       "...           ...                       ...\n",
       "109702  frazimi01           Michael Frazier\n",
       "110441  howarwi01            William Howard\n",
       "110913  mbahalu01          Luc Mbah a Moute\n",
       "111399  bowmaky01                 Ky Bowman\n",
       "112021  pargoje01              Jeremy Pargo\n",
       "\n",
       "[812 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "players = nba[['player_id', 'player']].drop_duplicates()\n",
    "players"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e8be423a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>game_id</th>\n",
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       "      <th>Team_Abbrev</th>\n",
       "      <th>Team_Score</th>\n",
       "      <th>Team_pace</th>\n",
       "      <th>Team_efg_pct</th>\n",
       "      <th>Team_tov_pct</th>\n",
       "      <th>Team_orb_pct</th>\n",
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       "      <th>Team_off_rtg</th>\n",
       "      <th>...</th>\n",
       "      <th>pf_per_minute</th>\n",
       "      <th>ts</th>\n",
       "      <th>last_60_minutes_per_game_starting</th>\n",
       "      <th>last_60_minutes_per_game_bench</th>\n",
       "      <th>PG%</th>\n",
       "      <th>SG%</th>\n",
       "      <th>SF%</th>\n",
       "      <th>PF%</th>\n",
       "      <th>C%</th>\n",
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       "      <th>0</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>0.157</td>\n",
       "      <td>123.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.061538</td>\n",
       "      <td>9.00</td>\n",
       "      <td>31.716667</td>\n",
       "      <td>22.017778</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.253586</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>0.157</td>\n",
       "      <td>123.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.099119</td>\n",
       "      <td>7.44</td>\n",
       "      <td>34.324000</td>\n",
       "      <td>18.475954</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>52.152590</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>0.157</td>\n",
       "      <td>123.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>29.820290</td>\n",
       "      <td>16.051693</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>47.021807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>0.157</td>\n",
       "      <td>123.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.048387</td>\n",
       "      <td>7.88</td>\n",
       "      <td>29.920833</td>\n",
       "      <td>14.603922</td>\n",
       "      <td>90.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.603314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>A</td>\n",
       "      <td>WAS</td>\n",
       "      <td>117</td>\n",
       "      <td>94.5</td>\n",
       "      <td>0.627</td>\n",
       "      <td>13.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>0.157</td>\n",
       "      <td>123.8</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.88</td>\n",
       "      <td>20.095833</td>\n",
       "      <td>14.538095</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>36.472537</td>\n",
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       "    <tr>\n",
       "      <th>112118</th>\n",
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       "      <td>0.263</td>\n",
       "      <td>129.9</td>\n",
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       "      <td>0.107914</td>\n",
       "      <td>13.08</td>\n",
       "      <td>33.110667</td>\n",
       "      <td>19.232562</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>57.207786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112119</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>H</td>\n",
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       "      <td>118</td>\n",
       "      <td>90.9</td>\n",
       "      <td>0.606</td>\n",
       "      <td>7.0</td>\n",
       "      <td>18.9</td>\n",
       "      <td>0.263</td>\n",
       "      <td>129.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036079</td>\n",
       "      <td>6.00</td>\n",
       "      <td>25.470833</td>\n",
       "      <td>20.228571</td>\n",
       "      <td>5.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.202391</td>\n",
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       "    <tr>\n",
       "      <th>112120</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>H</td>\n",
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       "      <td>118</td>\n",
       "      <td>90.9</td>\n",
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       "      <td>7.0</td>\n",
       "      <td>18.9</td>\n",
       "      <td>0.263</td>\n",
       "      <td>129.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.150943</td>\n",
       "      <td>4.00</td>\n",
       "      <td>24.083333</td>\n",
       "      <td>13.228788</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>49.630640</td>\n",
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       "    <tr>\n",
       "      <th>112121</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>H</td>\n",
       "      <td>GSW</td>\n",
       "      <td>118</td>\n",
       "      <td>90.9</td>\n",
       "      <td>0.606</td>\n",
       "      <td>7.0</td>\n",
       "      <td>18.9</td>\n",
       "      <td>0.263</td>\n",
       "      <td>129.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.094340</td>\n",
       "      <td>12.64</td>\n",
       "      <td>34.783333</td>\n",
       "      <td>27.691667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.923515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112122</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>H</td>\n",
       "      <td>GSW</td>\n",
       "      <td>118</td>\n",
       "      <td>90.9</td>\n",
       "      <td>0.606</td>\n",
       "      <td>7.0</td>\n",
       "      <td>18.9</td>\n",
       "      <td>0.263</td>\n",
       "      <td>129.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.76</td>\n",
       "      <td>10.415645</td>\n",
       "      <td>6.050000</td>\n",
       "      <td>81.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.958787</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>112123 rows × 76 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             game_id H_A Team_Abbrev  Team_Score  Team_pace  Team_efg_pct  \\\n",
       "0       202202170BRK   A         WAS         117       94.5         0.627   \n",
       "1       202202170BRK   A         WAS         117       94.5         0.627   \n",
       "2       202202170BRK   A         WAS         117       94.5         0.627   \n",
       "3       202202170BRK   A         WAS         117       94.5         0.627   \n",
       "4       202202170BRK   A         WAS         117       94.5         0.627   \n",
       "...              ...  ..         ...         ...        ...           ...   \n",
       "112118  202003070GSW   H         GSW         118       90.9         0.606   \n",
       "112119  202003070GSW   H         GSW         118       90.9         0.606   \n",
       "112120  202003070GSW   H         GSW         118       90.9         0.606   \n",
       "112121  202003070GSW   H         GSW         118       90.9         0.606   \n",
       "112122  202003070GSW   H         GSW         118       90.9         0.606   \n",
       "\n",
       "        Team_tov_pct  Team_orb_pct  Team_ft_rate  Team_off_rtg  ...  \\\n",
       "0               13.5          22.9         0.157         123.8  ...   \n",
       "1               13.5          22.9         0.157         123.8  ...   \n",
       "2               13.5          22.9         0.157         123.8  ...   \n",
       "3               13.5          22.9         0.157         123.8  ...   \n",
       "4               13.5          22.9         0.157         123.8  ...   \n",
       "...              ...           ...           ...           ...  ...   \n",
       "112118           7.0          18.9         0.263         129.9  ...   \n",
       "112119           7.0          18.9         0.263         129.9  ...   \n",
       "112120           7.0          18.9         0.263         129.9  ...   \n",
       "112121           7.0          18.9         0.263         129.9  ...   \n",
       "112122           7.0          18.9         0.263         129.9  ...   \n",
       "\n",
       "       pf_per_minute     ts  last_60_minutes_per_game_starting  \\\n",
       "0           0.061538   9.00                          31.716667   \n",
       "1           0.099119   7.44                          34.324000   \n",
       "2           0.000000   7.00                          29.820290   \n",
       "3           0.048387   7.88                          29.920833   \n",
       "4           0.000000   6.88                          20.095833   \n",
       "...              ...    ...                                ...   \n",
       "112118      0.107914  13.08                          33.110667   \n",
       "112119      0.036079   6.00                          25.470833   \n",
       "112120      0.150943   4.00                          24.083333   \n",
       "112121      0.094340  12.64                          34.783333   \n",
       "112122      0.000000   2.76                          10.415645   \n",
       "\n",
       "        last_60_minutes_per_game_bench   PG%   SG%   SF%   PF%     C%  \\\n",
       "0                            22.017778   1.0  36.0  60.0   4.0    0.0   \n",
       "1                            18.475954   0.0   0.0   4.0  85.0   11.0   \n",
       "2                            16.051693   0.0  32.0  67.0   0.0    0.0   \n",
       "3                            14.603922  90.0  10.0   0.0   0.0    0.0   \n",
       "4                            14.538095   0.0   0.0   0.0   0.0  100.0   \n",
       "...                                ...   ...   ...   ...   ...    ...   \n",
       "112118                       19.232562   0.0   2.0  77.0  21.0    0.0   \n",
       "112119                       20.228571   5.0  45.0  43.0   7.0    0.0   \n",
       "112120                       13.228788   0.0   0.0   0.0   9.0   91.0   \n",
       "112121                       27.691667   0.0  44.0  48.0   8.0    0.0   \n",
       "112122                        6.050000  81.0  19.0   0.0   0.0    0.0   \n",
       "\n",
       "        active_position_minutes  \n",
       "0                     46.253586  \n",
       "1                     52.152590  \n",
       "2                     47.021807  \n",
       "3                     27.603314  \n",
       "4                     36.472537  \n",
       "...                         ...  \n",
       "112118                57.207786  \n",
       "112119                58.202391  \n",
       "112120                49.630640  \n",
       "112121                58.923515  \n",
       "112122                45.958787  \n",
       "\n",
       "[112123 rows x 76 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba = nba.drop(['game_date', 'OT', 'season', 'player'], axis=1)\n",
    "nba"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fcae511d-6ad2-4fe0-934d-3dd7710ac895",
   "metadata": {},
   "source": [
    "### Third normal form:\n",
    "3NF is violated if there are \"transitive dependencies\", that is, functional dependence between columns when neither column is part of the primary key."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "23970a02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['game_id', 'H_A', 'Team_Abbrev', 'Team_Score', 'Team_pace',\n",
       "       'Team_efg_pct', 'Team_tov_pct', 'Team_orb_pct', 'Team_ft_rate',\n",
       "       'Team_off_rtg', 'Opponent_Abbrev', 'Opponent_Score', 'Opponent_pace',\n",
       "       'Opponent_efg_pct', 'Opponent_tov_pct', 'Opponent_orb_pct',\n",
       "       'Opponent_ft_rate', 'Opponent_off_rtg', 'player_id', 'starter', 'mp',\n",
       "       'fg', 'fga', 'fg_pct', 'fg3', 'fg3a', 'fg3_pct', 'ft', 'fta', 'ft_pct',\n",
       "       'orb', 'drb', 'trb', 'ast', 'stl', 'blk', 'tov', 'pf', 'pts',\n",
       "       'plus_minus', 'did_not_play', 'is_inactive', 'ts_pct', 'efg_pct',\n",
       "       'fg3a_per_fga_pct', 'fta_per_fga_pct', 'orb_pct', 'drb_pct', 'trb_pct',\n",
       "       'ast_pct', 'stl_pct', 'blk_pct', 'tov_pct', 'usg_pct', 'off_rtg',\n",
       "       'def_rtg', 'bpm', 'minutes', 'double_double', 'triple_double', 'DKP',\n",
       "       'FDP', 'SDP', 'DKP_per_minute', 'FDP_per_minute', 'SDP_per_minute',\n",
       "       'pf_per_minute', 'ts', 'last_60_minutes_per_game_starting',\n",
       "       'last_60_minutes_per_game_bench', 'PG%', 'SG%', 'SF%', 'PF%', 'C%',\n",
       "       'active_position_minutes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nba.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a85ce362",
   "metadata": {},
   "outputs": [],
   "source": [
    "team_game_table = nba[['game_id', 'H_A','Team_Abbrev', 'Team_Score', 'Team_pace',\n",
    "       'Team_efg_pct', 'Team_tov_pct', 'Team_orb_pct', 'Team_ft_rate',\n",
    "       'Team_off_rtg', 'Opponent_Abbrev' ]].drop_duplicates()\n",
    "player_game = nba.drop(['H_A','Team_Abbrev', 'Team_Score', 'Team_pace',\n",
    "       'Team_efg_pct', 'Team_tov_pct', 'Team_orb_pct', 'Team_ft_rate',\n",
    "       'Team_off_rtg', 'Opponent_Abbrev','Opponent_Abbrev', 'Opponent_Score', 'Opponent_pace',\n",
    "       'Opponent_efg_pct', 'Opponent_tov_pct', 'Opponent_orb_pct',\n",
    "       'Opponent_ft_rate', 'Opponent_off_rtg' ], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9d332301",
   "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>game_id</th>\n",
       "      <th>player_id</th>\n",
       "      <th>starter</th>\n",
       "      <th>mp</th>\n",
       "      <th>fg</th>\n",
       "      <th>fga</th>\n",
       "      <th>fg_pct</th>\n",
       "      <th>fg3</th>\n",
       "      <th>fg3a</th>\n",
       "      <th>fg3_pct</th>\n",
       "      <th>...</th>\n",
       "      <th>pf_per_minute</th>\n",
       "      <th>ts</th>\n",
       "      <th>last_60_minutes_per_game_starting</th>\n",
       "      <th>last_60_minutes_per_game_bench</th>\n",
       "      <th>PG%</th>\n",
       "      <th>SG%</th>\n",
       "      <th>SF%</th>\n",
       "      <th>PF%</th>\n",
       "      <th>C%</th>\n",
       "      <th>active_position_minutes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>kispeco01</td>\n",
       "      <td>1</td>\n",
       "      <td>32:30</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>0.667</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>0.667</td>\n",
       "      <td>...</td>\n",
       "      <td>0.061538</td>\n",
       "      <td>9.00</td>\n",
       "      <td>31.716667</td>\n",
       "      <td>22.017778</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.253586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>kuzmaky01</td>\n",
       "      <td>1</td>\n",
       "      <td>30:16</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.099119</td>\n",
       "      <td>7.44</td>\n",
       "      <td>34.324000</td>\n",
       "      <td>18.475954</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>52.152590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>caldwke01</td>\n",
       "      <td>1</td>\n",
       "      <td>25:26</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0.429</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.333</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>29.820290</td>\n",
       "      <td>16.051693</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>47.021807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>netora01</td>\n",
       "      <td>1</td>\n",
       "      <td>20:40</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>0.714</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.048387</td>\n",
       "      <td>7.88</td>\n",
       "      <td>29.920833</td>\n",
       "      <td>14.603922</td>\n",
       "      <td>90.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.603314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>bryanth01</td>\n",
       "      <td>1</td>\n",
       "      <td>14:04</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>0.833</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.88</td>\n",
       "      <td>20.095833</td>\n",
       "      <td>14.538095</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>36.472537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112118</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>wiggian01</td>\n",
       "      <td>1</td>\n",
       "      <td>37:04:00</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.107914</td>\n",
       "      <td>13.08</td>\n",
       "      <td>33.110667</td>\n",
       "      <td>19.232562</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>57.207786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112119</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>toscaju01</td>\n",
       "      <td>1</td>\n",
       "      <td>27:43:00</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036079</td>\n",
       "      <td>6.00</td>\n",
       "      <td>25.470833</td>\n",
       "      <td>20.228571</td>\n",
       "      <td>5.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.202391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112120</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>bendedr01</td>\n",
       "      <td>0</td>\n",
       "      <td>13:15</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.150943</td>\n",
       "      <td>4.00</td>\n",
       "      <td>24.083333</td>\n",
       "      <td>13.228788</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>49.630640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112121</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>muldemy01</td>\n",
       "      <td>1</td>\n",
       "      <td>31:48:00</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>0.500</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0.429</td>\n",
       "      <td>...</td>\n",
       "      <td>0.094340</td>\n",
       "      <td>12.64</td>\n",
       "      <td>34.783333</td>\n",
       "      <td>27.691667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.923515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112122</th>\n",
       "      <td>202003070GSW</td>\n",
       "      <td>randlch01</td>\n",
       "      <td>0</td>\n",
       "      <td>13:36</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.76</td>\n",
       "      <td>10.415645</td>\n",
       "      <td>6.050000</td>\n",
       "      <td>81.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.958787</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>112123 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             game_id  player_id  starter        mp  fg  fga  fg_pct  fg3  \\\n",
       "0       202202170BRK  kispeco01        1     32:30   6    9   0.667    4   \n",
       "1       202202170BRK  kuzmaky01        1     30:16   2    7   0.286    0   \n",
       "2       202202170BRK  caldwke01        1     25:26   3    7   0.429    1   \n",
       "3       202202170BRK   netora01        1     20:40   5    7   0.714    1   \n",
       "4       202202170BRK  bryanth01        1     14:04   5    6   0.833    0   \n",
       "...              ...        ...      ...       ...  ..  ...     ...  ...   \n",
       "112118  202003070GSW  wiggian01        1  37:04:00   3   10   0.300    0   \n",
       "112119  202003070GSW  toscaju01        1  27:43:00   3    6   0.500    0   \n",
       "112120  202003070GSW  bendedr01        0     13:15   4    4   1.000    2   \n",
       "112121  202003070GSW  muldemy01        1  31:48:00   5   10   0.500    3   \n",
       "112122  202003070GSW  randlch01        0     13:36   0    1   0.000    0   \n",
       "\n",
       "        fg3a  fg3_pct  ...  pf_per_minute     ts  \\\n",
       "0          6    0.667  ...       0.061538   9.00   \n",
       "1          3    0.000  ...       0.099119   7.44   \n",
       "2          3    0.333  ...       0.000000   7.00   \n",
       "3          1    1.000  ...       0.048387   7.88   \n",
       "4          1    0.000  ...       0.000000   6.88   \n",
       "...      ...      ...  ...            ...    ...   \n",
       "112118     0    0.000  ...       0.107914  13.08   \n",
       "112119     2    0.000  ...       0.036079   6.00   \n",
       "112120     2    1.000  ...       0.150943   4.00   \n",
       "112121     7    0.429  ...       0.094340  12.64   \n",
       "112122     0    0.000  ...       0.000000   2.76   \n",
       "\n",
       "        last_60_minutes_per_game_starting  last_60_minutes_per_game_bench  \\\n",
       "0                               31.716667                       22.017778   \n",
       "1                               34.324000                       18.475954   \n",
       "2                               29.820290                       16.051693   \n",
       "3                               29.920833                       14.603922   \n",
       "4                               20.095833                       14.538095   \n",
       "...                                   ...                             ...   \n",
       "112118                          33.110667                       19.232562   \n",
       "112119                          25.470833                       20.228571   \n",
       "112120                          24.083333                       13.228788   \n",
       "112121                          34.783333                       27.691667   \n",
       "112122                          10.415645                        6.050000   \n",
       "\n",
       "         PG%   SG%   SF%   PF%     C%  active_position_minutes  \n",
       "0        1.0  36.0  60.0   4.0    0.0                46.253586  \n",
       "1        0.0   0.0   4.0  85.0   11.0                52.152590  \n",
       "2        0.0  32.0  67.0   0.0    0.0                47.021807  \n",
       "3       90.0  10.0   0.0   0.0    0.0                27.603314  \n",
       "4        0.0   0.0   0.0   0.0  100.0                36.472537  \n",
       "...      ...   ...   ...   ...    ...                      ...  \n",
       "112118   0.0   2.0  77.0  21.0    0.0                57.207786  \n",
       "112119   5.0  45.0  43.0   7.0    0.0                58.202391  \n",
       "112120   0.0   0.0   0.0   9.0   91.0                49.630640  \n",
       "112121   0.0  44.0  48.0   8.0    0.0                58.923515  \n",
       "112122  81.0  19.0   0.0   0.0    0.0                45.958787  \n",
       "\n",
       "[112123 rows x 59 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_game"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c0c5d826",
   "metadata": {},
   "outputs": [],
   "source": [
    "player_game.columns = [x.lower().replace('%','_pct') for x in player_game.columns]\n",
    "team_game_table.columns = [x.lower().replace('%','_pct') for x in team_game_table.columns]\n",
    "players.columns = [x.lower().replace('%','_pct') for x in players.columns]\n",
    "games.columns = [x.lower().replace('%','_pct') for x in games.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3bd6c72a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['game_id', 'player_id', 'starter', 'mp', 'fg', 'fga', 'fg_pct', 'fg3',\n",
       "       'fg3a', 'fg3_pct', 'ft', 'fta', 'ft_pct', 'orb', 'drb', 'trb', 'ast',\n",
       "       'stl', 'blk', 'tov', 'pf', 'pts', 'plus_minus', 'did_not_play',\n",
       "       'is_inactive', 'ts_pct', 'efg_pct', 'fg3a_per_fga_pct',\n",
       "       'fta_per_fga_pct', 'orb_pct', 'drb_pct', 'trb_pct', 'ast_pct',\n",
       "       'stl_pct', 'blk_pct', 'tov_pct', 'usg_pct', 'off_rtg', 'def_rtg', 'bpm',\n",
       "       'minutes', 'double_double', 'triple_double', 'dkp', 'fdp', 'sdp',\n",
       "       'dkp_per_minute', 'fdp_per_minute', 'sdp_per_minute', 'pf_per_minute',\n",
       "       'ts', 'last_60_minutes_per_game_starting',\n",
       "       'last_60_minutes_per_game_bench', 'pg_pct', 'sg_pct', 'sf_pct',\n",
       "       'pf_pct', 'c_pct', 'active_position_minutes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_game.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f4971d6a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 3197 entries, 0 to 110643\n",
      "Data columns (total 4 columns):\n",
      " #   Column     Non-Null Count  Dtype \n",
      "---  ------     --------------  ----- \n",
      " 0   game_id    3197 non-null   object\n",
      " 1   game_date  3197 non-null   object\n",
      " 2   ot         3197 non-null   int64 \n",
      " 3   season     3197 non-null   int64 \n",
      "dtypes: int64(2), object(2)\n",
      "memory usage: 124.9+ KB\n"
     ]
    }
   ],
   "source": [
    "\n",
    "games.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "72a8211f",
   "metadata": {},
   "outputs": [],
   "source": [
    "dotenv.load_dotenv()\n",
    "postgres_password = os.getenv('POSTGRES_PASSWORD')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fb2460ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Connect to postgres server\n",
    "dbserver = psycopg.connect(\n",
    "    user='postgres',\n",
    "    password = postgres_password,\n",
    "    host='localhost',\n",
    "    port='5432'\n",
    ")\n",
    "dbserver.autocommit = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3e239dff",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create NBA database\n",
    "cursor = dbserver.cursor() # cursor is an entry point to subnit sequel to submit to server\n",
    "\n",
    "try:\n",
    "    cursor.execute('CREATE DATABASE nba')\n",
    "except:\n",
    "    cursor.execute('DROP DATABASE nba')\n",
    "    cursor.execute('CREATE DATABASE nba')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d6ce5de8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'postgresql+psycopg://postgres:1inW1170814302@localhost:5432/nba'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# upload NBA dataframes to nba data base\n",
    "dbms = 'postgresql'\n",
    "connector = 'psycopg'\n",
    "user = 'postgres'\n",
    "password = postgres_password\n",
    "host = 'localhost'\n",
    "port = '5432'\n",
    "database = 'nba'\n",
    "engine_string = f'{dbms}+{connector}://{user}:{password}@{host}:{port}/{database}'\n",
    "engine_string\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b93abc04",
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = create_engine(engine_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9e25aaa3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-113"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_game.to_sql('player_game', con=engine, chunksize=1000, if_exists='replace', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "72b347bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(112123, 59)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_game.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "55f7202d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(112123, 59)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_sql_query('SELECT * FROM player_game', con=engine).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c54e9197",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-4"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_game_table.to_sql('team_game', con=engine, chunksize=1000, if_exists='replace', index=False)\n",
    "players.to_sql('players', con=engine, chunksize=1000, if_exists='replace', index=False)\n",
    "games.to_sql('games', con=engine, chunksize=1000, if_exists='replace', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6c99479d",
   "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>game_id</th>\n",
       "      <th>game_date</th>\n",
       "      <th>ot</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>202202170BRK</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>202202170CHO</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>2</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>202202170LAC</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202202170MIL</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>202202170NOP</td>\n",
       "      <td>2022-02-17</td>\n",
       "      <td>0</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3192</th>\n",
       "      <td>202001080GSW</td>\n",
       "      <td>2020-01-08</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3193</th>\n",
       "      <td>202008020HOU</td>\n",
       "      <td>2020-08-02</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3194</th>\n",
       "      <td>201911060HOU</td>\n",
       "      <td>2019-11-06</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3195</th>\n",
       "      <td>201912250GSW</td>\n",
       "      <td>2019-12-25</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3196</th>\n",
       "      <td>202002200GSW</td>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>0</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3197 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           game_id   game_date  ot  season\n",
       "0     202202170BRK  2022-02-17   0    2022\n",
       "1     202202170CHO  2022-02-17   2    2022\n",
       "2     202202170LAC  2022-02-17   0    2022\n",
       "3     202202170MIL  2022-02-17   0    2022\n",
       "4     202202170NOP  2022-02-17   0    2022\n",
       "...            ...         ...  ..     ...\n",
       "3192  202001080GSW  2020-01-08   0    2020\n",
       "3193  202008020HOU  2020-08-02   0    2020\n",
       "3194  201911060HOU  2019-11-06   0    2020\n",
       "3195  201912250GSW  2019-12-25   0    2020\n",
       "3196  202002200GSW  2020-02-20   0    2020\n",
       "\n",
       "[3197 rows x 4 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myquery = '''\n",
    "SELECT * \n",
    "FROM games\n",
    "'''\n",
    "pd.read_sql_query(myquery, con=engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51259089",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nSELECT * \\nFROM games\\n'"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myquery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b70f0dc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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