ipynb/Calculate_PlusMinus.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How to Calculate Plus Minus (+/-) using NBA Play-by-Play Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.set_option('precision', 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>game_id</th>\n",
       "      <th>data_set</th>\n",
       "      <th>date</th>\n",
       "      <th>a1</th>\n",
       "      <th>a2</th>\n",
       "      <th>a3</th>\n",
       "      <th>a4</th>\n",
       "      <th>a5</th>\n",
       "      <th>h1</th>\n",
       "      <th>h2</th>\n",
       "      <th>...</th>\n",
       "      <th>reason</th>\n",
       "      <th>result</th>\n",
       "      <th>steal</th>\n",
       "      <th>type</th>\n",
       "      <th>shot_distance</th>\n",
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       "      <th>original_y</th>\n",
       "      <th>converted_x</th>\n",
       "      <th>converted_y</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21700002</td>\n",
       "      <td>2017-2018 Regular Season</td>\n",
       "      <td>10/17/2017</td>\n",
       "      <td>Trevor Ariza</td>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>Clint Capela</td>\n",
       "      <td>James Harden</td>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>Kevin Durant</td>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>start of period</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>21700002</td>\n",
       "      <td>2017-2018 Regular Season</td>\n",
       "      <td>10/17/2017</td>\n",
       "      <td>Trevor Ariza</td>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>Clint Capela</td>\n",
       "      <td>James Harden</td>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>Kevin Durant</td>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>jump ball</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jump Ball Pachulia vs. Capela: Tip to Anderson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21700002</td>\n",
       "      <td>2017-2018 Regular Season</td>\n",
       "      <td>10/17/2017</td>\n",
       "      <td>Trevor Ariza</td>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>Clint Capela</td>\n",
       "      <td>James Harden</td>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>Kevin Durant</td>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>made</td>\n",
       "      <td>NaN</td>\n",
       "      <td>unknown</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>Harden 2' Driving Layup (2 PTS)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21700002</td>\n",
       "      <td>2017-2018 Regular Season</td>\n",
       "      <td>10/17/2017</td>\n",
       "      <td>Trevor Ariza</td>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>Clint Capela</td>\n",
       "      <td>James Harden</td>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>Kevin Durant</td>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>missed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jump Shot</td>\n",
       "      <td>25.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>25.9</td>\n",
       "      <td>63.6</td>\n",
       "      <td>MISS Green 25' 3PT Jump Shot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21700002</td>\n",
       "      <td>2017-2018 Regular Season</td>\n",
       "      <td>10/17/2017</td>\n",
       "      <td>Trevor Ariza</td>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>Clint Capela</td>\n",
       "      <td>James Harden</td>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>Kevin Durant</td>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>rebound defensive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Capela REBOUND (Off:0 Def:1)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    game_id                  data_set        date            a1  \\\n",
       "0  21700002  2017-2018 Regular Season  10/17/2017  Trevor Ariza   \n",
       "1  21700002  2017-2018 Regular Season  10/17/2017  Trevor Ariza   \n",
       "2  21700002  2017-2018 Regular Season  10/17/2017  Trevor Ariza   \n",
       "3  21700002  2017-2018 Regular Season  10/17/2017  Trevor Ariza   \n",
       "4  21700002  2017-2018 Regular Season  10/17/2017  Trevor Ariza   \n",
       "\n",
       "              a2            a3            a4          a5            h1  \\\n",
       "0  Ryan Anderson  Clint Capela  James Harden  Chris Paul  Kevin Durant   \n",
       "1  Ryan Anderson  Clint Capela  James Harden  Chris Paul  Kevin Durant   \n",
       "2  Ryan Anderson  Clint Capela  James Harden  Chris Paul  Kevin Durant   \n",
       "3  Ryan Anderson  Clint Capela  James Harden  Chris Paul  Kevin Durant   \n",
       "4  Ryan Anderson  Clint Capela  James Harden  Chris Paul  Kevin Durant   \n",
       "\n",
       "               h2  ... reason  result steal               type  shot_distance  \\\n",
       "0  Draymond Green  ...    NaN     NaN   NaN    start of period            NaN   \n",
       "1  Draymond Green  ...    NaN     NaN   NaN          jump ball            NaN   \n",
       "2  Draymond Green  ...    NaN    made   NaN            unknown            2.0   \n",
       "3  Draymond Green  ...    NaN  missed   NaN          Jump Shot           25.0   \n",
       "4  Draymond Green  ...    NaN     NaN   NaN  rebound defensive            NaN   \n",
       "\n",
       "   original_x original_y converted_x converted_y  \\\n",
       "0         NaN        NaN         NaN         NaN   \n",
       "1         NaN        NaN         NaN         NaN   \n",
       "2       -10.0       16.0        26.0         6.6   \n",
       "3         9.0      254.0        25.9        63.6   \n",
       "4         NaN        NaN         NaN         NaN   \n",
       "\n",
       "                                      description  \n",
       "0                                             NaN  \n",
       "1  Jump Ball Pachulia vs. Capela: Tip to Anderson  \n",
       "2                 Harden 2' Driving Layup (2 PTS)  \n",
       "3                    MISS Green 25' 3PT Jump Shot  \n",
       "4                    Capela REBOUND (Off:0 Def:1)  \n",
       "\n",
       "[5 rows x 44 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hou_gsw = '[2017-10-17]-0021700002-HOU@GSW.csv'\n",
    "bos_cle = '[2017-10-17]-0021700001-BOS@CLE.csv'\n",
    "\n",
    "PbP_df = pd.read_csv('../data/2017-18_pbp/{}'.format(hou_gsw))\n",
    "PbP_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(457, 44)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PbP_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 457 entries, 0 to 456\n",
      "Data columns (total 44 columns):\n",
      "game_id           457 non-null int64\n",
      "data_set          457 non-null object\n",
      "date              457 non-null object\n",
      "a1                457 non-null object\n",
      "a2                457 non-null object\n",
      "a3                457 non-null object\n",
      "a4                457 non-null object\n",
      "a5                457 non-null object\n",
      "h1                457 non-null object\n",
      "h2                457 non-null object\n",
      "h3                457 non-null object\n",
      "h4                457 non-null object\n",
      "h5                457 non-null object\n",
      "period            457 non-null int64\n",
      "away_score        457 non-null int64\n",
      "home_score        457 non-null int64\n",
      "remaining_time    457 non-null object\n",
      "elapsed           457 non-null object\n",
      "play_length       457 non-null object\n",
      "play_id           457 non-null int64\n",
      "team              422 non-null object\n",
      "event_type        457 non-null object\n",
      "assist            62 non-null object\n",
      "away              1 non-null object\n",
      "home              1 non-null object\n",
      "block             14 non-null object\n",
      "entered           45 non-null object\n",
      "left              45 non-null object\n",
      "num               40 non-null float64\n",
      "opponent          41 non-null object\n",
      "outof             40 non-null float64\n",
      "player            422 non-null object\n",
      "points            217 non-null float64\n",
      "possession        1 non-null object\n",
      "reason            67 non-null object\n",
      "result            217 non-null object\n",
      "steal             14 non-null object\n",
      "type              457 non-null object\n",
      "shot_distance     177 non-null float64\n",
      "original_x        177 non-null float64\n",
      "original_y        177 non-null float64\n",
      "converted_x       177 non-null float64\n",
      "converted_y       177 non-null float64\n",
      "description       445 non-null object\n",
      "dtypes: float64(8), int64(5), object(31)\n",
      "memory usage: 157.2+ KB\n"
     ]
    }
   ],
   "source": [
    "PbP_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Fill the Null Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Only filling the null values in points for +/-\n",
    "PbP_df.points = PbP_df.points.fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Create the Dummy Player Columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data for players on court are contained in the columns: ['a1', 'a2', 'a3', 'a4', 'a5', 'h1','h2', 'h3', 'h4', 'h5']. This makes it difficult to understand which players are active since any one of the 5 player positions can contain one of the player names. Instead, we will create dummy variables from the player columns and signify their status on court with a '1' or on the bench with a '0'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create dummy variables for the player columns\n",
    "player_dummy_df = pd.get_dummies(PbP_df.filter(regex='a[1-5]|h[1-5]'), prefix='player')\n",
    "\n",
    "# Remove the whitespace in the dummy player columns\n",
    "player_dummy_df.columns = [x.strip().replace(' ', '_') for x in player_dummy_df.columns]\n",
    "\n",
    "# Collapse the duplicate dummy player columns and sum the column values\n",
    "player_dummy_df = player_dummy_df.groupby(lambda x:x, axis=1).sum()\n",
    "\n",
    "# Bring the dummy columns into the main dataframe\n",
    "PbP_df = pd.concat([PbP_df, player_dummy_df], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>3</th>\n",
       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "   player_Chris_Paul  player_Clint_Capela  player_David_West  \\\n",
       "0                  1                    1                  0   \n",
       "1                  1                    1                  0   \n",
       "2                  1                    1                  0   \n",
       "3                  1                    1                  0   \n",
       "4                  1                    1                  0   \n",
       "\n",
       "   player_Draymond_Green  player_Eric_Gordon  player_James_Harden  \\\n",
       "0                      1                   0                    1   \n",
       "1                      1                   0                    1   \n",
       "2                      1                   0                    1   \n",
       "3                      1                   0                    1   \n",
       "4                      1                   0                    1   \n",
       "\n",
       "   player_Jordan_Bell  player_Kevin_Durant  player_Kevon_Looney  \\\n",
       "0                   0                    1                    0   \n",
       "1                   0                    1                    0   \n",
       "2                   0                    1                    0   \n",
       "3                   0                    1                    0   \n",
       "4                   0                    1                    0   \n",
       "\n",
       "   player_Klay_Thompson  player_Luc_Mbah_a_Moute  player_Nick_Young  \\\n",
       "0                     1                        0                  0   \n",
       "1                     1                        0                  0   \n",
       "2                     1                        0                  0   \n",
       "3                     1                        0                  0   \n",
       "4                     1                        0                  0   \n",
       "\n",
       "   player_Omri_Casspi  player_PJ_Tucker  player_Patrick_McCaw  \\\n",
       "0                   0                 0                     0   \n",
       "1                   0                 0                     0   \n",
       "2                   0                 0                     0   \n",
       "3                   0                 0                     0   \n",
       "4                   0                 0                     0   \n",
       "\n",
       "   player_Ryan_Anderson  player_Shaun_Livingston  player_Stephen_Curry  \\\n",
       "0                     1                        0                     1   \n",
       "1                     1                        0                     1   \n",
       "2                     1                        0                     1   \n",
       "3                     1                        0                     1   \n",
       "4                     1                        0                     1   \n",
       "\n",
       "   player_Trevor_Ariza  player_Zaza_Pachulia  \n",
       "0                    1                     1  \n",
       "1                    1                     1  \n",
       "2                    1                     1  \n",
       "3                    1                     1  \n",
       "4                    1                     1  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "player_dummy_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['player_Chris_Paul',\n",
       " 'player_Clint_Capela',\n",
       " 'player_David_West',\n",
       " 'player_Draymond_Green',\n",
       " 'player_Eric_Gordon',\n",
       " 'player_James_Harden',\n",
       " 'player_Jordan_Bell',\n",
       " 'player_Kevin_Durant',\n",
       " 'player_Kevon_Looney',\n",
       " 'player_Klay_Thompson',\n",
       " 'player_Luc_Mbah_a_Moute',\n",
       " 'player_Nick_Young',\n",
       " 'player_Omri_Casspi',\n",
       " 'player_PJ_Tucker',\n",
       " 'player_Patrick_McCaw',\n",
       " 'player_Ryan_Anderson',\n",
       " 'player_Shaun_Livingston',\n",
       " 'player_Stephen_Curry',\n",
       " 'player_Trevor_Ariza',\n",
       " 'player_Zaza_Pachulia']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get list of players\n",
    "player_list = [i for i in list(PbP_df.columns) if re.search(r'player_.+_.+', i)]\n",
    "player_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate Plus Minus (+/-)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**How to:** For a given player, count up points scored by the player’s team and points scored against the player’s team when that player is on the floor. Then simply subtract points against from points for. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 1: Initialize a Dataframe with Player Information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>player</th>\n",
       "      <th>player_unformatted</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>player_Chris_Paul</td>\n",
       "      <td>HOU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Clint Capela</td>\n",
       "      <td>player_Clint_Capela</td>\n",
       "      <td>HOU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>David West</td>\n",
       "      <td>player_David_West</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>player_Draymond_Green</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eric Gordon</td>\n",
       "      <td>player_Eric_Gordon</td>\n",
       "      <td>HOU</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           player     player_unformatted team\n",
       "0      Chris Paul      player_Chris_Paul  HOU\n",
       "1    Clint Capela    player_Clint_Capela  HOU\n",
       "2      David West      player_David_West  GSW\n",
       "3  Draymond Green  player_Draymond_Green  GSW\n",
       "4     Eric Gordon     player_Eric_Gordon  HOU"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create the main +/- dataframe\n",
    "player_df = pd.DataFrame(columns=['player'])\n",
    "player_df['player_unformatted'] = [i for i in player_list]\n",
    "\n",
    "# Format the 'player_unformatted' column to merge later to get the team column\n",
    "player_df['player'] = [i.replace('player_','').replace('_',' ') for i in player_list]\n",
    "\n",
    "# Merge with the PbP dataframe to get team information\n",
    "player_df = player_df.merge(PbP_df[['team', 'player']], on='player').drop_duplicates()\n",
    "player_df = player_df.reset_index(drop=True)\n",
    "player_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 2: Create a For Loop to store the points team/opposing team scored while player is on the floor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a list of players and their respective team for the below for loop\n",
    "p_list = list(player_df.player_unformatted)\n",
    "t_list = list(player_df.team)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "plus = []\n",
    "minus = []\n",
    "\n",
    "for player, team in zip(p_list, t_list):\n",
    "    p_nested = []\n",
    "    plus.append(p_nested)\n",
    "    \n",
    "    m_nested = []\n",
    "    minus.append(m_nested)\n",
    "    \n",
    "    for i, row in PbP_df.iterrows():\n",
    "        if (row[player] == 1) & (row['team'] == team):\n",
    "            p_nested.append(row['points'])\n",
    "        elif (row[player] == 1) & (row['team'] != team):\n",
    "            m_nested.append(row['points'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 2.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 3.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 3.0, 0.0, 2.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 2.0, 3.0, 0.0, 3.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 3.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 2.0, 2.0, 0.0, 0.0, 2.0]\n",
      "\n",
      "[0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 3.0, 2.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 0.0, 3.0, 0.0, 0.0, 2.0, 2.0, 0.0, 3.0, 0.0, 1.0, 1.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 0.0, 1.0, 1.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 2.0, 1.0, 2.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 2.0, 2.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 3.0, 0.0, 0.0, 0.0, 3.0, 2.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 0.0, 0.0, 2.0, 3.0, 0.0, 0.0, 0.0]\n"
     ]
    }
   ],
   "source": [
    "# The plus variable contains a list of lists, which are the points the team scored when the player is active on the court\n",
    "print(plus[0])\n",
    "print()\n",
    "\n",
    "# The minus variable contains a list of lists, which are the points the opposing team scored when the player is active on the court\n",
    "print(minus[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3: Create another For Loop to sum the +/- values into separate lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "p_list = []\n",
    "m_list = []\n",
    "\n",
    "\n",
    "for value in plus:\n",
    "    value = np.sum(value)\n",
    "    p_list.append(value)\n",
    "    \n",
    "for value in minus:\n",
    "    value = np.sum(value)\n",
    "    m_list.append(value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "81.0\n",
      "\n",
      "94.0\n"
     ]
    }
   ],
   "source": [
    "# Here we will sum each list and get a list of the + values\n",
    "print(p_list[0])\n",
    "print()\n",
    "\n",
    "# Here is a sum of each list to get a list of the - values\n",
    "print(m_list[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 4: Create the Final Dataframe"
   ]
  },
  {
   "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>player</th>\n",
       "      <th>team</th>\n",
       "      <th>+/-</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>David West</td>\n",
       "      <td>GSW</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>GSW</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jordan Bell</td>\n",
       "      <td>GSW</td>\n",
       "      <td>-3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kevin Durant</td>\n",
       "      <td>GSW</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kevon Looney</td>\n",
       "      <td>GSW</td>\n",
       "      <td>-7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Klay Thompson</td>\n",
       "      <td>GSW</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Nick Young</td>\n",
       "      <td>GSW</td>\n",
       "      <td>-8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Omri Casspi</td>\n",
       "      <td>GSW</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Patrick McCaw</td>\n",
       "      <td>GSW</td>\n",
       "      <td>-9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Shaun Livingston</td>\n",
       "      <td>GSW</td>\n",
       "      <td>-7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Stephen Curry</td>\n",
       "      <td>GSW</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Zaza Pachulia</td>\n",
       "      <td>GSW</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>HOU</td>\n",
       "      <td>-13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Clint Capela</td>\n",
       "      <td>HOU</td>\n",
       "      <td>-24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Eric Gordon</td>\n",
       "      <td>HOU</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>James Harden</td>\n",
       "      <td>HOU</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Luc Mbah a Moute</td>\n",
       "      <td>HOU</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>PJ Tucker</td>\n",
       "      <td>HOU</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>HOU</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Trevor Ariza</td>\n",
       "      <td>HOU</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Zaza Pachulia</td>\n",
       "      <td>HOU</td>\n",
       "      <td>-9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              player team   +/-\n",
       "0         David West  GSW   0.0\n",
       "1     Draymond Green  GSW   7.0\n",
       "2        Jordan Bell  GSW  -3.0\n",
       "3       Kevin Durant  GSW  11.0\n",
       "4       Kevon Looney  GSW  -7.0\n",
       "5      Klay Thompson  GSW   1.0\n",
       "6         Nick Young  GSW  -8.0\n",
       "7        Omri Casspi  GSW  -4.0\n",
       "8      Patrick McCaw  GSW  -9.0\n",
       "9   Shaun Livingston  GSW  -7.0\n",
       "10     Stephen Curry  GSW   5.0\n",
       "11     Zaza Pachulia  GSW   9.0\n",
       "12        Chris Paul  HOU -13.0\n",
       "13      Clint Capela  HOU -24.0\n",
       "14       Eric Gordon  HOU  16.0\n",
       "15      James Harden  HOU   1.0\n",
       "16  Luc Mbah a Moute  HOU   4.0\n",
       "17         PJ Tucker  HOU  20.0\n",
       "18     Ryan Anderson  HOU   7.0\n",
       "19      Trevor Ariza  HOU  -6.0\n",
       "20     Zaza Pachulia  HOU  -9.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add the columns to the final dataframe\n",
    "player_df['plus'] = p_list\n",
    "player_df['minus'] = m_list\n",
    "\n",
    "# Create the +/- column by subtracting the minus from plus columns\n",
    "player_df['+/-'] = player_df['plus'] - player_df['minus']\n",
    "\n",
    "# Reformat the dataframe for visuals\n",
    "player_df.drop(['plus', 'minus', 'player_unformatted'], axis=1, inplace=True)\n",
    "player_df = player_df.sort_values(by=['team', 'player'], ascending=True)\n",
    "player_df = player_df.reset_index(drop=True)\n",
    "player_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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