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mra1385/2015 NBA Finals - Points and Salaries.ipynb

Last active November 10, 2015 03:23
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2015 NBA Finals - Points and Salaries
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2015 NBA Finals - Points and Salaries.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# import libraries \n",
"from os import listdir\n",
"import numpy as np\n",
"import pandas as pd\n",
"%matplotlib inline\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"from bs4 import BeautifulSoup\n",
"import requests"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# local path for data sets downloaded from nba reference \n",
"folder_path = '/Users/MRA/Desktop/admin/chart-it/NBA Finals 2015/raw'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# file names in directory\n",
"files = listdir(folder_path)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"tmp_lst = []"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create dataframe with data set\n",
"for item in files:\n",
" file_path = folder_path +\"\\{}\".format(item)\n",
" frame = pd.read_csv(file_path)\n",
" frame['Team'] = item\n",
" tmp_lst.append(frame)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# remove column 'Rk' \n",
"nba_finals = (pd.concat(tmp_lst, ignore_index = True)).drop('Rk', 1)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# rename columns\n",
"nba_finals = nba_finals.rename(columns = {'Player ':'Player', 'Age ': 'Age'})"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# set index to be player name\n",
"nba_finals = nba_finals.set_index('Player')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# nba_finals_GSW.iloc[:,'% asd Pts'] = 'test'"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# remove team totals from dataframe to avoid double counting\n",
"nba_finals = nba_finals[nba_finals.index != 'Team Totals']"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# calculate total team points\n",
"CLE_pts = nba_finals.groupby('Team')['PTS Totals'].sum()[0]\n",
"GSW_pts = nba_finals.groupby('Team')['PTS Totals'].sum()[1]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# produce dataframe subset based on needed information\n",
"nba_finals = nba_finals[['Team', 'FG Totals', 'FGA Totals', '3P Totals', '3PA Totals', 'FT Totals', 'FTA Totals', 'AST Totals', 'PTS Totals']]"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create dataframe for CLE only\n",
"nba_finals_CLE = nba_finals[nba_finals['Team'].str.find('CLE.csv') == 33]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create dataframe for GSW only\n",
"nba_finals_GSW = nba_finals[nba_finals['Team'].str.find('GSW.csv') == 33]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" from IPython.kernel.zmq import kernelapp as app\n",
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:3: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" app.launch_new_instance()\n"
]
}
],
"source": [
"# add new column for player points as % of total team points\n",
"nba_finals_GSW['% Team Pts'] = nba_finals_GSW['PTS Totals'] / GSW_pts\n",
"nba_finals_CLE['% Team Pts'] = nba_finals_CLE['PTS Totals'] / CLE_pts"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" from IPython.kernel.zmq import kernelapp as app\n",
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:3: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" app.launch_new_instance()\n"
]
}
],
"source": [
"# add new column for player points + assist points\n",
"nba_finals_GSW['PTS + AST'] = nba_finals_GSW['PTS Totals'] + ( nba_finals_GSW['AST Totals'] * 2 )\n",
"nba_finals_CLE['PTS + AST'] = nba_finals_CLE['PTS Totals'] + ( nba_finals_CLE['AST Totals'] * 2 )"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" from IPython.kernel.zmq import kernelapp as app\n",
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:3: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" app.launch_new_instance()\n"
]
}
],
"source": [
"# add new column for player points + assist points as % of total team points\n",
"nba_finals_CLE['% Team Pts + AST'] = nba_finals_CLE['PTS + AST'] / CLE_pts\n",
"nba_finals_GSW['% Team Pts + AST'] = nba_finals_GSW['PTS + AST'] / GSW_pts"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# web scraping CLE player salaries\n",
"url = \"http://www.basketball-reference.com/teams/CLE/2015.html?lid=playoff_series_team\"\n",
"soup = BeautifulSoup(requests.get(url).content)\n",
"tmp_cle_salaries = soup.find(id=\"div_salaries\").find_all('td')\n",
"\n",
"cle_salaries = dict()\n",
"for i in range(1, len(tmp_cle_salaries), 3):\n",
" cle_salaries[tmp_cle_salaries[i].text] = tmp_cle_salaries[i + 1].text"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# web scraping GSW player salaries\n",
"url = \"http://www.basketball-reference.com/teams/GSW/2015.html?lid=playoff_series_team\"\n",
"soup = BeautifulSoup(requests.get(url).content)\n",
"tmp_gsw_salaries = soup.find(id=\"div_salaries\").find_all('td')\n",
"\n",
"gsw_salaries = dict()\n",
"for i in range(1, len(tmp_gsw_salaries), 3):\n",
" gsw_salaries[tmp_gsw_salaries[i].text] = tmp_gsw_salaries[i + 1].text"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create dataframes with player salaries\n",
"cle_salaries_df = pd.DataFrame.from_dict(cle_salaries, orient='index')\n",
"cle_salaries_df.columns = ['Salary']\n",
"cle_salaries_df.index.name = 'Player'\n",
"\n",
"gsw_salaries_df = pd.DataFrame.from_dict(gsw_salaries, orient='index')\n",
"gsw_salaries_df.columns = ['Salary']\n",
"gsw_salaries_df.index.name = 'Player'"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# join salaries to main dataframe with player data\n",
"nba_finals_CLE = pd.merge(nba_finals_CLE, cle_salaries_df, left_index=True, right_index=True)\n",
"nba_finals_GSW = pd.merge(nba_finals_GSW, gsw_salaries_df, left_index=True, right_index=True)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# remove '$' from salary data in order to convert salary string to integer data type\n",
"nba_finals_CLE['Salary'] = nba_finals_CLE['Salary'].str.replace(\"$\",\"\")\n",
"nba_finals_CLE['Salary'] = nba_finals_CLE['Salary'].str.replace(\",\",\"\")\n",
"\n",
"nba_finals_GSW['Salary'] = nba_finals_GSW['Salary'].str.replace(\"$\",\"\")\n",
"nba_finals_GSW['Salary'] = nba_finals_GSW['Salary'].str.replace(\",\",\"\")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: convert_objects is deprecated. Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.\n",
" from IPython.kernel.zmq import kernelapp as app\n",
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:3: FutureWarning: convert_objects is deprecated. Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.\n",
" app.launch_new_instance()\n"
]
}
],
"source": [
"# convert salary data from string to integer\n",
"nba_finals_CLE['Salary'] = nba_finals_CLE.Salary.convert_objects(convert_numeric=True)\n",
"nba_finals_GSW['Salary'] = nba_finals_GSW.Salary.convert_objects(convert_numeric=True)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add column with salary as % of total\n",
"nba_finals_GSW['% Team Salary'] = nba_finals_GSW['Salary'] /nba_finals_GSW['Salary'].sum()\n",
"nba_finals_CLE['% Team Salary'] = nba_finals_CLE['Salary'] / nba_finals_CLE['Salary'].sum()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(61, 48)"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# total team assists\n",
"nba_finals_GSW['AST Totals'].sum(), \\\n",
"nba_finals_CLE['AST Totals'].sum()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Team</th>\n",
" <th>FG Totals</th>\n",
" <th>FGA Totals</th>\n",
" <th>3P Totals</th>\n",
" <th>3PA Totals</th>\n",
" <th>FT Totals</th>\n",
" <th>FTA Totals</th>\n",
" <th>AST Totals</th>\n",
" <th>PTS Totals</th>\n",
" <th>% Team Pts</th>\n",
" <th>PTS + AST</th>\n",
" <th>% Team Pts + AST</th>\n",
" <th>Salary</th>\n",
" <th>% Team Salary</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Player</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Draymond Green</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>8</td>\n",
" <td>30</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" <td>12</td>\n",
" <td>13</td>\n",
" <td>8</td>\n",
" <td>29</td>\n",
" <td>0.099315</td>\n",
" <td>45</td>\n",
" <td>0.154110</td>\n",
" <td>915243</td>\n",
" <td>0.013175</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Shaun Livingston</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>5</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>6</td>\n",
" <td>11</td>\n",
" <td>0.037671</td>\n",
" <td>23</td>\n",
" <td>0.078767</td>\n",
" <td>5305000</td>\n",
" <td>0.076365</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Andrew Bogut</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>4</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>5</td>\n",
" <td>10</td>\n",
" <td>0.034247</td>\n",
" <td>20</td>\n",
" <td>0.068493</td>\n",
" <td>12972973</td>\n",
" <td>0.186746</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Leandro Barbosa</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>5</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" <td>0.037671</td>\n",
" <td>13</td>\n",
" <td>0.044521</td>\n",
" <td>1448490</td>\n",
" <td>0.020851</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Festus Ezeli</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>4</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>6</td>\n",
" <td>2</td>\n",
" <td>12</td>\n",
" <td>0.041096</td>\n",
" <td>16</td>\n",
" <td>0.054795</td>\n",
" <td>1112880</td>\n",
" <td>0.016020</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Marreese Speights</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>4</td>\n",
" <td>11</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" <td>0.027397</td>\n",
" <td>10</td>\n",
" <td>0.034247</td>\n",
" <td>3657500</td>\n",
" <td>0.052650</td>\n",
" </tr>\n",
" <tr>\n",
" <th>David Lee</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>11</td>\n",
" <td>0.037671</td>\n",
" <td>15</td>\n",
" <td>0.051370</td>\n",
" <td>15012000</td>\n",
" <td>0.216097</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Klay Thompson</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>25</td>\n",
" <td>58</td>\n",
" <td>9</td>\n",
" <td>28</td>\n",
" <td>10</td>\n",
" <td>11</td>\n",
" <td>4</td>\n",
" <td>69</td>\n",
" <td>0.236301</td>\n",
" <td>77</td>\n",
" <td>0.263699</td>\n",
" <td>3075880</td>\n",
" <td>0.044277</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Harrison Barnes</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>9</td>\n",
" <td>27</td>\n",
" <td>3</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" <td>0.075342</td>\n",
" <td>24</td>\n",
" <td>0.082192</td>\n",
" <td>3049920</td>\n",
" <td>0.043904</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Andre Iguodala</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>15</td>\n",
" <td>25</td>\n",
" <td>5</td>\n",
" <td>13</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>12</td>\n",
" <td>37</td>\n",
" <td>0.126712</td>\n",
" <td>61</td>\n",
" <td>0.208904</td>\n",
" <td>12289544</td>\n",
" <td>0.176908</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Stephen Curry</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_GSW.csv</td>\n",
" <td>25</td>\n",
" <td>63</td>\n",
" <td>11</td>\n",
" <td>34</td>\n",
" <td>11</td>\n",
" <td>12</td>\n",
" <td>19</td>\n",
" <td>72</td>\n",
" <td>0.246575</td>\n",
" <td>110</td>\n",
" <td>0.376712</td>\n",
" <td>10629213</td>\n",
" <td>0.153007</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Team FG Totals \\\n",
"Player \n",
"Draymond Green playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 8 \n",
"Shaun Livingston playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 5 \n",
"Andrew Bogut playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 4 \n",
"Leandro Barbosa playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 5 \n",
"Festus Ezeli playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 4 \n",
"Marreese Speights playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 4 \n",
"David Lee playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 4 \n",
"Klay Thompson playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 25 \n",
"Harrison Barnes playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 9 \n",
"Andre Iguodala playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 15 \n",
"Stephen Curry playoffs_NBA_2015_finals_CLE-GSW_GSW.csv 25 \n",
"\n",
" FGA Totals 3P Totals 3PA Totals FT Totals FTA Totals \\\n",
"Player \n",
"Draymond Green 30 1 8 12 13 \n",
"Shaun Livingston 12 0 1 1 2 \n",
"Andrew Bogut 9 0 0 2 4 \n",
"Leandro Barbosa 13 1 2 0 0 \n",
"Festus Ezeli 9 0 0 4 6 \n",
"Marreese Speights 11 0 0 0 0 \n",
"David Lee 4 0 0 3 5 \n",
"Klay Thompson 58 9 28 10 11 \n",
"Harrison Barnes 27 3 10 1 1 \n",
"Andre Iguodala 25 5 13 2 5 \n",
"Stephen Curry 63 11 34 11 12 \n",
"\n",
" AST Totals PTS Totals % Team Pts PTS + AST \\\n",
"Player \n",
"Draymond Green 8 29 0.099315 45 \n",
"Shaun Livingston 6 11 0.037671 23 \n",
"Andrew Bogut 5 10 0.034247 20 \n",
"Leandro Barbosa 1 11 0.037671 13 \n",
"Festus Ezeli 2 12 0.041096 16 \n",
"Marreese Speights 1 8 0.027397 10 \n",
"David Lee 2 11 0.037671 15 \n",
"Klay Thompson 4 69 0.236301 77 \n",
"Harrison Barnes 1 22 0.075342 24 \n",
"Andre Iguodala 12 37 0.126712 61 \n",
"Stephen Curry 19 72 0.246575 110 \n",
"\n",
" % Team Pts + AST Salary % Team Salary \n",
"Player \n",
"Draymond Green 0.154110 915243 0.013175 \n",
"Shaun Livingston 0.078767 5305000 0.076365 \n",
"Andrew Bogut 0.068493 12972973 0.186746 \n",
"Leandro Barbosa 0.044521 1448490 0.020851 \n",
"Festus Ezeli 0.054795 1112880 0.016020 \n",
"Marreese Speights 0.034247 3657500 0.052650 \n",
"David Lee 0.051370 15012000 0.216097 \n",
"Klay Thompson 0.263699 3075880 0.044277 \n",
"Harrison Barnes 0.082192 3049920 0.043904 \n",
"Andre Iguodala 0.208904 12289544 0.176908 \n",
"Stephen Curry 0.376712 10629213 0.153007 "
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# results for GSW\n",
"nba_finals_GSW"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Team</th>\n",
" <th>FG Totals</th>\n",
" <th>FGA Totals</th>\n",
" <th>3P Totals</th>\n",
" <th>3PA Totals</th>\n",
" <th>FT Totals</th>\n",
" <th>FTA Totals</th>\n",
" <th>AST Totals</th>\n",
" <th>PTS Totals</th>\n",
" <th>% Team Pts</th>\n",
" <th>PTS + AST</th>\n",
" <th>% Team Pts + AST</th>\n",
" <th>Salary</th>\n",
" <th>% Team Salary</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Player</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Timofey Mozgov</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>13</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>13</td>\n",
" <td>20</td>\n",
" <td>3</td>\n",
" <td>39</td>\n",
" <td>0.134021</td>\n",
" <td>45</td>\n",
" <td>0.154639</td>\n",
" <td>4650000</td>\n",
" <td>0.090058</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Tristan Thompson</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>5</td>\n",
" <td>15</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>8</td>\n",
" <td>2</td>\n",
" <td>14</td>\n",
" <td>0.048110</td>\n",
" <td>18</td>\n",
" <td>0.061856</td>\n",
" <td>5138430</td>\n",
" <td>0.099517</td>\n",
" </tr>\n",
" <tr>\n",
" <th>J.R. Smith</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>12</td>\n",
" <td>35</td>\n",
" <td>7</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" <td>0.109966</td>\n",
" <td>34</td>\n",
" <td>0.116838</td>\n",
" <td>6516000</td>\n",
" <td>0.126197</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Mike Miller</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
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" <td>2732000</td>\n",
" <td>0.052911</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LeBron James</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>43</td>\n",
" <td>107</td>\n",
" <td>7</td>\n",
" <td>20</td>\n",
" <td>30</td>\n",
" <td>40</td>\n",
" <td>25</td>\n",
" <td>123</td>\n",
" <td>0.422680</td>\n",
" <td>173</td>\n",
" <td>0.594502</td>\n",
" <td>20644400</td>\n",
" <td>0.399826</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Iman Shumpert</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>5</td>\n",
" <td>19</td>\n",
" <td>4</td>\n",
" <td>11</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" <td>0.054983</td>\n",
" <td>18</td>\n",
" <td>0.061856</td>\n",
" <td>2616975</td>\n",
" <td>0.050684</td>\n",
" </tr>\n",
" <tr>\n",
" <th>James Jones</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>5</td>\n",
" <td>10</td>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>15</td>\n",
" <td>0.051546</td>\n",
" <td>19</td>\n",
" <td>0.065292</td>\n",
" <td>1448490</td>\n",
" <td>0.028053</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Matthew Dellavedova</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>10</td>\n",
" <td>27</td>\n",
" <td>3</td>\n",
" <td>12</td>\n",
" <td>6</td>\n",
" <td>7</td>\n",
" <td>8</td>\n",
" <td>29</td>\n",
" <td>0.099656</td>\n",
" <td>45</td>\n",
" <td>0.154639</td>\n",
" <td>816482</td>\n",
" <td>0.015813</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Kyrie Irving</th>\n",
" <td>playoffs_NBA_2015_finals_CLE-GSW_CLE.csv</td>\n",
" <td>10</td>\n",
" <td>22</td>\n",
" <td>2</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" <td>23</td>\n",
" <td>0.079038</td>\n",
" <td>35</td>\n",
" <td>0.120275</td>\n",
" <td>7070730</td>\n",
" <td>0.136941</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Team FG Totals \\\n",
"Player \n",
"Timofey Mozgov playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 13 \n",
"Tristan Thompson playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 5 \n",
"J.R. Smith playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 12 \n",
"Mike Miller playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 0 \n",
"LeBron James playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 43 \n",
"Iman Shumpert playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 5 \n",
"James Jones playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 5 \n",
"Matthew Dellavedova playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 10 \n",
"Kyrie Irving playoffs_NBA_2015_finals_CLE-GSW_CLE.csv 10 \n",
"\n",
" FGA Totals 3P Totals 3PA Totals FT Totals FTA Totals \\\n",
"Player \n",
"Timofey Mozgov 24 0 0 13 20 \n",
"Tristan Thompson 15 0 0 4 8 \n",
"J.R. Smith 35 7 20 1 2 \n",
"Mike Miller 1 0 1 0 0 \n",
"LeBron James 107 7 20 30 40 \n",
"Iman Shumpert 19 4 11 2 4 \n",
"James Jones 10 4 7 1 1 \n",
"Matthew Dellavedova 27 3 12 6 7 \n",
"Kyrie Irving 22 2 8 1 1 \n",
"\n",
" AST Totals PTS Totals % Team Pts PTS + AST \\\n",
"Player \n",
"Timofey Mozgov 3 39 0.134021 45 \n",
"Tristan Thompson 2 14 0.048110 18 \n",
"J.R. Smith 1 32 0.109966 34 \n",
"Mike Miller 0 0 0.000000 0 \n",
"LeBron James 25 123 0.422680 173 \n",
"Iman Shumpert 1 16 0.054983 18 \n",
"James Jones 2 15 0.051546 19 \n",
"Matthew Dellavedova 8 29 0.099656 45 \n",
"Kyrie Irving 6 23 0.079038 35 \n",
"\n",
" % Team Pts + AST Salary % Team Salary \n",
"Player \n",
"Timofey Mozgov 0.154639 4650000 0.090058 \n",
"Tristan Thompson 0.061856 5138430 0.099517 \n",
"J.R. Smith 0.116838 6516000 0.126197 \n",
"Mike Miller 0.000000 2732000 0.052911 \n",
"LeBron James 0.594502 20644400 0.399826 \n",
"Iman Shumpert 0.061856 2616975 0.050684 \n",
"James Jones 0.065292 1448490 0.028053 \n",
"Matthew Dellavedova 0.154639 816482 0.015813 \n",
"Kyrie Irving 0.120275 7070730 0.136941 "
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# results for CLW\n",
"nba_finals_CLE"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.4.3"
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"nbformat": 4,
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