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Created May 1, 2017 02:04
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Analysis of the largest comebacks in the NBA, 1996-2017
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comeback_analysis.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Analysis of the largest comebacks in the NBA, 1996-2017"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"https://github.com/Jonathan-LeRoux/NBAcomebacks"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"#### Install statsnba-playbyplay module to download and parse play-by-play data from http://stats.nba.com \n",
"More details here: [https://github.com/ethanluoyc/statsnba-playbyplay]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"import sys; sys.executable\n",
"!{sys.executable} -m pip install statsnba-playbyplay"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"In `path_to_your_python_installation/lib/site-packages/statsnba/__init__.py`, comment out the following line:\n",
" #from .models import Game"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"from __future__ import division\n",
"from statsnba.api import Api\n",
"import sys\n",
"import os\n",
"import pandas as pd\n",
"import time\n",
"import cPickle\n",
"import numpy as np\n",
"import plotly\n",
"import plotly.plotly as py\n",
"from plotly import tools\n",
"import plotly.graph_objs as go\n",
"plotly.offline.init_notebook_mode()\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.colors\n",
"import matplotlib.ticker \n",
"%matplotlib nbagg\n",
"import seaborn as sns"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"api = Api()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"def str2diff(s):\n",
" scores = s[0].split(\" - \")\n",
" return int(scores[1]) - int(scores[0])\n",
"def abs_time(s):\n",
" ftr = [60,1]\n",
" return (s[1])*12*60 - sum([a*b for a,b in zip(ftr, map(int,s[2].split(':')))])\n",
"def get_score_times(data):\n",
" return [ (x['SCORE'], x['PERIOD'],x['PCTIMESTRING'],x['GAME_ID']) for x in data['resultSets']['PlayByPlay'] if x['SCORE'] is not None]\n",
"def season_string(seasonstart):\n",
" thisseason=int(seasonstart)\n",
" nextseason=thisseason+1\n",
" return str(thisseason)+\"-\"+str(nextseason)[2:]"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Download the data"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"years=range(1996,2017)\n",
"redo_download = False\n",
"if redo_download:\n",
" score_times_season={}\n",
" for seasonstart in years:\n",
" season = season_string(seasonstart)\n",
" score_times_season[season]={}\n",
" ids=sorted(api.GetSeasonGameIDs(season,'Regular Season'))\n",
" progress = 0\n",
" num_games= len(ids)\n",
" print \"Retrieving \", num_games, \" for season \", season\n",
" for game_id in ids:\n",
" if game_id not in score_times_season[season]:\n",
" this_game_data =api.GetPlayByPlay(game_id)\n",
" score_times_season[season][game_id] = get_score_times(this_game_data)\n",
" time.sleep(.25)\n",
" progress = progress + 1\n",
" sys.stdout.write(\"Progress: %.1f%% \\r\" % (progress/ num_games * 100) )\n",
" sys.stdout.flush()\n",
" with open(\"data/score_data_\" + season + \"_complete.p\",\"wb\") as fid:\n",
" cPickle.dump(score_times_season[season],fid)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Functions to compute the largest comebacks"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"def make_dic_from_data(data):\n",
" # create a dictionary with time as key and score margin as value, \n",
" # keeping the maximum score margin if there are several for a given time.\n",
" # By maximum, we mean the one most opposed to the final score (largest comeback)\n",
" outcome = np.sign(str2diff(data[-1]))\n",
" outdict = {}\n",
" for s in data:\n",
" thiskey = abs_time(s)\n",
" scorediff=str2diff(s) \n",
" gameid = s[3]\n",
" #if scorediff * outcome <= 0:\n",
" if thiskey in outdict:\n",
" if outcome*(scorediff - outdict[thiskey][0]) < 0: \n",
" # e.g., outcome = -1; scorediff=2, outdict[thiskey]=1: new largest comeback\n",
" # or: outcome = 1; scorediff=-2, outdict[thiskey]=-1: new largest comeback\n",
" outdict[thiskey] = (scorediff,set([gameid]))\n",
" else:\n",
" outdict[thiskey] = (scorediff,set([gameid]))\n",
" outdict[0] = (0,set([gameid])) # adding the starting score margin\n",
" return outdict"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"import heapq\n",
"import copy\n",
"def merge_comebacks(maindic,newdic,outcome):\n",
" mainkeys = sorted(maindic.keys())\n",
" newkeys = sorted(newdic.keys())\n",
" allkeys = heapq.merge(mainkeys,newkeys)\n",
" current_largest = (0,set([]))\n",
" main_is_largest = False\n",
" for t in allkeys:\n",
" if t in maindic:\n",
" if outcome*(maindic[t][0] - current_largest[0]) <= 0 or main_is_largest:\n",
" # main is either the new largest, or was already the largest but is moving to a different score (possibly smaller)\n",
" if maindic[t][0] == current_largest[0]: #add maindic[t][1] to current_largest[1]\n",
" maindic[t] = (maindic[t][0],set(maindic[t][1].union(current_largest[1])))\n",
" current_largest = (maindic[t][0],set(maindic[t][1]))\n",
" main_is_largest = True\n",
" else: # whoever was the current largest should overwrite main's value\n",
" maindic[t] = copy.deepcopy(current_largest)\n",
" if t in newdic:\n",
" if main_is_largest:\n",
" if outcome*(newdic[t][0] - current_largest[0]) < 0:\n",
" maindic[t] = copy.deepcopy(newdic[t])\n",
" current_largest = copy.deepcopy(newdic[t])\n",
" main_is_largest = False\n",
" elif newdic[t][0] == current_largest[0]:\n",
" maindic[t] = (current_largest[0],set(current_largest[1].union(newdic[t][1])))\n",
" current_largest = copy.deepcopy(maindic[t])\n",
" main_is_largest = False # to give a chance to newdic at next index\n",
" else: # remove new from main if it was in there\n",
" if t in maindic:\n",
" maindic[t] = (maindic[t][0],set(maindic[t][1].difference(newdic[t][1])))\n",
" current_largest = (current_largest[0],set(current_largest[1].difference(newdic[t][1])))\n",
" else: # largest entry was from newdic, whatever this new score, it is the new largest at this time point\n",
" maindic[t] = copy.deepcopy(newdic[t])\n",
" current_largest = copy.deepcopy(newdic[t])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"def check_data_valid(game_data):\n",
" if len(game_data) > 0:\n",
" first_score=game_data[0][0].split(' - ')\n",
" return int(first_score[0])==0 or int(first_score[1])==0\n",
" else:\n",
" return False"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"total_time=6000\n",
"total_time_show=4*12*60+10\n",
"def full_score(sdic):\n",
" s = np.zeros((total_time,))\n",
" skeys = sorted(sdic.keys())\n",
" for i in range(len(skeys)-1):\n",
" tstart = skeys[i]\n",
" tend = skeys[i+1]\n",
" margin = sdic[skeys[i]][0]\n",
" s[tstart:tend] = margin\n",
" return s\n",
"def full_list(sdic):\n",
" s = []\n",
" skeys = sorted(sdic.keys())\n",
" if skeys[0] > 0:\n",
" list_elem = sdic[skeys[0]][0]\n",
" s.extend([list_elem] * (skeys[0]))\n",
" for i in range(len(skeys)-1):\n",
" tstart = skeys[i]\n",
" tend = skeys[i+1]\n",
" list_elem = sdic[skeys[i]][0]\n",
" s.extend([list_elem] * (tend-tstart))\n",
" return s\n",
"def add_score_counts(S,sdic):\n",
" N,T=S.shape\n",
" C=int(N/2) # center score = 0\n",
" skeys = sorted(sdic.keys())\n",
" for i in range(len(skeys)-1):\n",
" tstart = skeys[i]\n",
" tend = skeys[i+1]\n",
" margin = sdic[skeys[i]][0]\n",
" #print tstart, tend, margin\n",
" S[C+margin,tstart:tend] = S[C+margin,tstart:tend] + 1\n",
" return S"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Compute the largest comebacks for each season"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"data for game 0029600021 appears invalid\n",
"data for game 0029700144 appears invalid\n",
"data for game 0029700804 appears invalid\n",
"data for game 0029701131 appears invalid\n",
"data for game 0020000814 appears invalid\n",
"data for game 0020001001 appears invalid\n",
"data for game 0020001072 appears invalid\n",
"data for game 0020200216 appears invalid\n",
"data for game 0020200222 appears invalid\n",
"data for game 0021201214 appears invalid\n"
]
}
],
"source": [
"years=range(1996,2017)\n",
"comebacks={}\n",
"for seasonstart in years:\n",
" season = season_string(seasonstart)\n",
" with open(\"data/score_data_\"+season+\"_complete.p\",\"rb\") as fid:\n",
" seasonscores=cPickle.load(fid)\n",
" ids = sorted(seasonscores.keys())\n",
"\n",
" comebacks[season]={}\n",
" comebacks[season][1]={}\n",
" comebacks[season][-1]={}\n",
"\n",
" for i in range(len(ids)):\n",
" if check_data_valid(seasonscores[ids[i]]):\n",
" outcome = np.sign(str2diff(seasonscores[ids[i]][-1]))\n",
" merge_comebacks(comebacks[season][outcome],make_dic_from_data(seasonscores[ids[i]]),outcome)\n",
" else:\n",
" print \"data for game \", ids[i], \" appears invalid\"\n",
"with open('data/comebacks_1996-2016_complete.p','wb') as f:\n",
" cPickle.dump(comebacks,f)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### List of games with wrong stats:\n",
"* reverse order play-by-play\n",
" * [http://stats.nba.com/game/#!/0029600021/playbyplay/]\n",
" * [http://stats.nba.com/game/#!/0029700144/playbyplay/]\n",
" * [http://stats.nba.com/game/#!/0029700804/playbyplay/]\n",
" * [http://stats.nba.com/game/#!/0020000814/playbyplay/]\n",
" * [http://stats.nba.com/game/#!/0020001001/playbyplay/]\n",
" * [http://stats.nba.com/game/#!/0020001072/playbyplay/]\n",
" * [http://stats.nba.com/game/#!/0020200216/playbyplay/]\n",
" * [http://stats.nba.com/game/#!/0020200222/playbyplay/] \n",
"* empty stats\n",
" * [http://stats.nba.com/game/#!/0021201214/playbyplay/] \n",
"* score does not start at 0-0\n",
" * [http://stats.nba.com/game/#!/0029701131/playbyplay/]"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Plot the largest comebacks for every NBA season from 1996-97 to 2016-17"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using subplots: nice, but too wide for a blog "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"with open('data/comebacks_1996-2016_complete.p','rb') as f:\n",
" comebacks=cPickle.load(f)\n",
"years=range(1996,2017)\n",
"palette={y:p for y,p in zip(years,sns.husl_palette(len(years), h=.7).as_hex())}\n",
"traces={}\n",
"fig = tools.make_subplots(rows=1, cols=2, subplot_titles=('Home eventually wins', 'Away eventually wins'))\n",
"show_legend_outcome={-1:False,1:True}\n",
"for outcome in [-1,1]:\n",
" traces[outcome]=[]\n",
"for seasonstart in years:\n",
" season = season_string(seasonstart)\n",
" for outcome in [-1,1]:\n",
" traces[outcome].append(go.Scatter(\n",
" x = np.arange(total_time_show)/60,\n",
" y = outcome*full_score(comebacks[season][outcome])[:total_time_show],\n",
" mode = 'lines',\n",
" line = dict(width=2,color = palette[seasonstart]),\n",
" name = season,showlegend=show_legend_outcome[outcome]))\n",
" fig.append_trace(traces[1][-1], 1, 1)\n",
" fig.append_trace(traces[-1][-1], 1, 2)\n",
"\n",
"xtexts=[0,'<br>Q1',12,'<br>Q2',24,'<br>Q3',36,'<br>Q4',48]\n",
"xvals = [q*6 for q in range(len(xtexts))]\n",
"fig['layout']['xaxis1'].update(ticktext=xtexts,tickvals=xvals, title='Time (minutes)')\n",
"fig['layout']['xaxis2'].update(ticktext=xtexts,tickvals=xvals, title='Time (minutes)')\n",
"fig['layout']['yaxis1'].update(title='Largest comeback score')\n",
"fig['layout']['yaxis2'].update(title='Largest comeback score')\n",
"\n",
"fig['layout'].update(height=800, width=1000, \n",
" title='Largest comebacks for every NBA season from 1996-97 to 2016-17')\n",
"plotly.offline.iplot(fig, filename='largest_comebacks_by_season_1996_2016')\n",
"# if you have a plotly account, this command will push the figure to it\n",
"#py.plot(fig, filename='largest_comebacks_by_season_1996_2016')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"#### Output of the previous cell is large, you can check it online here:\n",
"[https://plot.ly/~jonl/12]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using separate plots, tweaking the size to fit the Wordpress theme "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"with open('data/comebacks_1996-2016_complete.p','rb') as f:\n",
" comebacks=cPickle.load(f)\n",
"years=range(1996,2017)\n",
"palette={y:p for y,p in zip(years,sns.husl_palette(len(years), h=.7).as_hex())}\n",
"traces={}\n",
"layouts={}\n",
"titles = {1:'Home eventually wins', -1:'Away eventually wins'}\n",
"title_suffix={1:'_home',-1:'_away'}\n",
"show_legend_outcome={-1:True,1:True}\n",
"for outcome in [-1,1]:\n",
" traces[outcome]=[]\n",
" layouts[outcome]=go.Layout()\n",
"for seasonstart in years:\n",
" season = season_string(seasonstart)\n",
" for outcome in [-1,1]:\n",
" traces[outcome].append(go.Scatter(\n",
" x = np.arange(total_time_show)/60,\n",
" y = outcome*full_score(comebacks[season][outcome])[:total_time_show],\n",
" mode = 'lines',\n",
" line = dict(width=2,color = palette[seasonstart]),\n",
" name = season,showlegend=show_legend_outcome[outcome]))\n",
"xtexts=[0,'<br>Q1',12,'<br>Q2',24,'<br>Q3',36,'<br>Q4',48]\n",
"xvals = [q*6 for q in range(len(xtexts))]\n",
"for outcome in [1,-1]:\n",
" layouts[outcome]['xaxis'].update(ticktext=xtexts,tickvals=xvals, title='Time (minutes)')\n",
" layouts[outcome]['yaxis'].update(title='Largest comeback score')\n",
" \n",
" layouts[outcome].update(height=800, width=540, \n",
" title='Largest comebacks for every NBA season<br>from 1996-97 to 2016-17 ('+titles[outcome]+')')\n",
" plotly.offline.iplot(go.Figure(data=traces[outcome], layout=layouts[outcome]), filename='largest_comebacks_by_season_1996_2016'+title_suffix[outcome])\n",
" # if you have a plotly account, this command will push the figure to it\n",
" #py.plot(go.Figure(data=traces[outcome], layout=layouts[outcome]), filename='largest_comebacks_by_season_1996_2016_wp'+title_suffix[outcome])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Output of the previous cell is large, you can check it online here:\n",
"\n",
"[https://plot.ly/~jonl/16]\n",
"\n",
"[https://plot.ly/~jonl/18]"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Compute the largest comebacks across all seasons"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"years=range(1996,2017)\n",
"with open('data/comebacks_1996-2016_complete.p','rb') as f:\n",
" comebacks=cPickle.load(f)\n",
"overall_comebacks={}\n",
"for seasonstart in years:\n",
" season = season_string(seasonstart)\n",
" for outcome in [-1,1]:\n",
" if outcome not in overall_comebacks:\n",
" overall_comebacks[outcome]=copy.deepcopy(comebacks[season][outcome])\n",
" else:\n",
" merge_comebacks(overall_comebacks[outcome],comebacks[season][outcome],outcome)\n",
"with open('data/overall_comebacks_1996-2016.p','wb') as f:\n",
" cPickle.dump(overall_comebacks,f)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"game_info_dict={}\n",
"def get_info(gid,show_attendance=False):\n",
" if gid not in game_info_dict:\n",
" bb=api.GetBoxscoreSummary(gid)\n",
" game_info_dict[gid] = {}\n",
" game_info_dict[gid]['time'] = bb['resultSets']['GameInfo'][0]['GAME_DATE']\n",
" game_info_dict[gid]['crowd'] = str(bb['resultSets']['GameInfo'][0]['ATTENDANCE'])\n",
" game_info_dict[gid]['home'] = ' '.join([bb['resultSets']['LineScore'][0]['TEAM_CITY_NAME'], bb['resultSets']['LineScore'][0]['TEAM_NICKNAME']])\n",
" game_info_dict[gid]['away'] = ' '.join([bb['resultSets']['LineScore'][1]['TEAM_CITY_NAME'], bb['resultSets']['LineScore'][1]['TEAM_NICKNAME']])\n",
" g_teams = ' '.join([game_info_dict[gid]['away'],'at', game_info_dict[gid]['home']])\n",
" if show_attendance:\n",
" return g_teams + ' (' + game_info_dict[gid]['time'].title() + ', attendance: ' + game_info_dict[gid]['crowd'] + ')'\n",
" else:\n",
" return g_teams + '<br>(' + game_info_dict[gid]['time'].title() + ')'\n",
"def make_chronological_game_id(gid):\n",
" y = gid[:5].replace('0029','199').replace('002','20')\n",
" z = gid[5:]\n",
" return y+z"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"def gamestr(i):\n",
" if i>1:\n",
" return \" games:\"\n",
" else:\n",
" return \" game:\"\n",
"def make_game_list(gid_set,max_num_games=15):\n",
" return \"<br>\".join([str(len(gid_set))+gamestr(len(gid_set))]+[get_info(x) for x in sorted(list(gid_set),key=make_chronological_game_id)[:max_num_games]])"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### List of games at largest comeback score at each time"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"if os.path.exists('data/game_info_dict.p'):\n",
" with open('data/game_info_dict.p','rb') as f:\n",
" game_info_dict=cPickle.load(f)\n",
"game_list_at_comeback={}\n",
"for outcome in [-1,1]:\n",
" sd=sorted(overall_comebacks[outcome].items())\n",
" game_list_at_comeback[outcome] = { a : (make_game_list(c),{}) for a,(b,c) in sd }"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"with open('data/list_of_games_at_overall_comeback_1996-2016.p','wb') as f:\n",
" cPickle.dump(game_list_at_comeback,f)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Plot the largest comebacks in a regular season NBA game between 1996 and 2017"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using subplots: nice, but too wide for a blog "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"with open(\"data/list_of_games_at_overall_comeback_1996-2016.p\",\"rb\") as fid:\n",
" game_list_at_comeback=cPickle.load(fid)\n",
"traces={}\n",
"fig = tools.make_subplots(rows=1, cols=2, subplot_titles=('Home eventually wins', 'Away eventually wins'))\n",
"show_legend_outcome={-1:False,1:False}\n",
"for outcome in [-1,1]:\n",
" traces[outcome]=(go.Scatter(\n",
" x = np.arange(total_time_show)/60,\n",
" y = outcome*full_score(overall_comebacks[outcome])[:total_time_show],\n",
" text = full_list(game_list_at_comeback[outcome])[:total_time_show],\n",
" mode = 'lines',showlegend=show_legend_outcome[outcome]))\n",
"\n",
"fig.append_trace(traces[1], 1, 1)\n",
"fig.append_trace(traces[-1], 1, 2)\n",
"\n",
"xtexts=[0,'<br>Q1',12,'<br>Q2',24,'<br>Q3',36,'<br>Q4',48]\n",
"xvals = [q*6 for q in range(len(xtexts))]\n",
"fig['layout']['xaxis1'].update(ticktext=xtexts,tickvals=xvals, title='Time (minutes)')\n",
"fig['layout']['xaxis2'].update(ticktext=xtexts,tickvals=xvals, title='Time (minutes)')\n",
"fig['layout']['yaxis1'].update(title='Largest comeback score')\n",
"fig['layout']['yaxis2'].update(title='Largest comeback score')\n",
"\n",
"fig['layout'].update(height=700, width=800, \n",
" title='Largest comebacks in a regular season NBA game between 1996 and 2017')\n",
"plotly.offline.iplot(fig, filename='largest_comebacks_overall_1996_2017')\n",
"# if you have a plotly account, this command will push the figure to it\n",
"#py.plot(fig, filename='largest_comebacks_overall_1996_2017')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"#### Output of the previous cell is large, you can check it online here:\n",
"[https://plot.ly/~jonl/10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using separate plots, tweaking the size to fit the Wordpress theme "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"with open('data/list_of_games_at_overall_comeback_1996-2016.p','rb') as f:\n",
" game_list_at_comeback=cPickle.load(f)\n",
"with open('data/overall_comebacks_1996-2016.p','rb') as f:\n",
" overall_comebacks=cPickle.load(f)\n",
"\n",
"titles = {1:'Home eventually wins', -1:'Away eventually wins'}\n",
"title_suffix={1:'_home',-1:'_away'}\n",
"xtexts=[0,'<br>Q1',12,'<br>Q2',24,'<br>Q3',36,'<br>Q4',48]\n",
"xvals = [q*6 for q in range(len(xtexts))]\n",
"\n",
"palette= sns.color_palette().as_hex()# sns.color_palette(\"Paired\").as_hex()\n",
"mycolor={1:palette[0],-1:palette[1]}\n",
"\n",
"layouts={}\n",
"traces={}\n",
"show_legend_outcome={-1:False,1:False}\n",
"for outcome in [1,-1]:\n",
" traces[outcome]=[go.Scatter(\n",
" x = np.arange(total_time_show)/60,\n",
" y = outcome*full_score(overall_comebacks[outcome])[:total_time_show],\n",
" line = dict(color=mycolor[outcome]),\n",
" text = full_list(game_list_at_comeback[outcome])[:total_time_show],\n",
" mode = 'lines',showlegend=show_legend_outcome[outcome])]\n",
" layouts[outcome]=go.Layout()\n",
" layouts[outcome]['xaxis'].update(ticktext=xtexts,tickvals=xvals, title='Time (minutes)')\n",
" layouts[outcome]['yaxis'].update(title='Largest comeback score')\n",
" \n",
" layouts[outcome].update(height=800, width=590, \n",
" title='Largest comebacks in a regular season NBA game<br>between 1996 and 2017 ('+titles[outcome]+')')\n",
" plotly.offline.iplot(go.Figure(data=traces[outcome], layout=layouts[outcome]), filename='largest_comebacks_overall_1996_2017'+title_suffix[outcome])\n",
" # if you have a plotly account, this command will push the figure to it\n",
" #py.plot(go.Figure(data=traces[outcome], layout=layouts[outcome]), filename='largest_comebacks_overall_1996_2017_wp'+title_suffix[outcome])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Output of the previous cell is large, you can check it online here:\n",
"[https://plot.ly/~jonl/22]\n",
"\n",
"[https://plot.ly/~jonl/20]\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Plot the distribution of scores in all regular season NBA games from 1996 to 2017"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1996-97\n",
"data for game 0029600021 appears invalid\n",
"1997-98\n",
"data for game 0029700144 appears invalid\n",
"data for game 0029700804 appears invalid\n",
"data for game 0029701131 appears invalid\n",
"1998-99\n",
"1999-00\n",
"2000-01\n",
"data for game 0020000814 appears invalid\n",
"data for game 0020001001 appears invalid\n",
"data for game 0020001072 appears invalid\n",
"2001-02\n",
"2002-03\n",
"data for game 0020200216 appears invalid\n",
"data for game 0020200222 appears invalid\n",
"2003-04\n",
"2004-05\n",
"2005-06\n",
"2006-07\n",
"2007-08\n",
"2008-09\n",
"2009-10\n",
"2010-11\n",
"2011-12\n",
"2012-13\n",
"data for game 0021201214 appears invalid\n",
"2013-14\n",
"2014-15\n",
"2015-16\n",
"2016-17\n"
]
}
],
"source": [
"sum_all_score_counts={}\n",
"for outcome in [-1,1]:\n",
" sum_all_score_counts[outcome] = np.zeros((200,total_time))\n",
"\n",
"years=range(1996,2017)\n",
"for seasonstart in years:\n",
" season = season_string(seasonstart)\n",
" print season\n",
" with open(\"data/score_data_\"+season+\"_complete.p\",\"rb\") as fid:\n",
" seasonscores=cPickle.load(fid)\n",
" ids = sorted(seasonscores.keys())\n",
"\n",
" score_counts = {}\n",
" score_counts[1] = np.zeros((200,total_time))\n",
" score_counts[-1] = np.zeros((200,total_time))\n",
"\n",
" for i in range(len(ids)):\n",
" if check_data_valid(seasonscores[ids[i]]):\n",
" outcome = np.sign(str2diff(seasonscores[ids[i]][-1]))\n",
" score_counts[outcome] = add_score_counts(score_counts[outcome], make_dic_from_data(seasonscores[ids[i]]))\n",
" else:\n",
" print \"data for game \", ids[i], \" appears invalid\"\n",
" for outcome in [-1,1]:\n",
" sum_all_score_counts[outcome] += score_counts[outcome]\n",
"with open('data/score_counts_overall_1996-2016_complete.p','wb') as f:\n",
" cPickle.dump(sum_all_score_counts,f)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"def set_axis_params(ax):\n",
" ax.xaxis.grid(True)\n",
" ax.set_xticks([q*12*60+6*60 for q in range(4)],minor=True)\n",
" ax.set_xticklabels(['Q %i'%(q+1) for q in range(4)],minor=True)\n",
" ax.set_xticks([q*12*60 for q in range(5)],minor=False)\n",
" ax.set_xticklabels(['%i'%(12*q) for q in range(5)],minor=False)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
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" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
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"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
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" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
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"\n",
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"\n",
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" // almost always do), so we need to clear the canvas so that\n",
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" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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"\n",
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"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
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"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
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"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
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"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
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"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
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"\n",
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"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
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"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
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" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
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"\n",
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" resize: function(event, ui) {\n",
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" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
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"\n",
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" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
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"\n",
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"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
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" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
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"\n",
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" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
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" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
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"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
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width=\"1000\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"vmax = np.fmax(np.max(sum_all_score_counts[1]),np.max(sum_all_score_counts[-1]))\n",
"fig, (ax1,ax2) = plt.subplots(1, 2, figsize=(10,6)) \n",
"fig.suptitle('Distribution of score differences in all regular season NBA games, 1996-2017')\n",
"ax1.set_title(\"Home eventually wins\")\n",
"ax2.set_title(\"Away eventually wins\")\n",
"pc1=ax1.imshow((sum_all_score_counts[1])[60:175,:], aspect='auto',\n",
" norm=matplotlib.colors.LogNorm(vmin=1,vmax=vmax), \n",
" cmap=plt.cm.Reds_r, interpolation='none', extent=[0,6000,74,-40])\n",
"pc2=ax2.imshow((sum_all_score_counts[-1])[26:141,:], aspect='auto',\n",
" norm=matplotlib.colors.LogNorm(vmin=1,vmax=vmax), \n",
" cmap=plt.cm.Reds_r, interpolation='none', extent=[0,6000,40,-74])\n",
"ax1.invert_yaxis()\n",
"for ax,pc in zip([ax1,ax2],[pc1,pc2]):\n",
" ax.set_xlim(0,total_time_show)\n",
" c=fig.colorbar(pc, ax=ax, format=matplotlib.ticker.FormatStrFormatter('%d'))\n",
" c.set_ticks([1,2,5,10,20,50,100,200,500,1000,2000,5000,10000])\n",
" set_axis_params(ax)\n",
" ax.set_xlabel(\"Time\")\n",
" ax.set_ylabel(\"Score difference\")\n",
"fig.canvas.draw()\n",
"fig.savefig('score_difference_distribution_nba_1996-2017.png',dpi=fig.dpi)\n",
"fig.savefig('score_difference_distribution_nba_1996-2017.pdf')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Show the largest home/away comebacks for each season"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"def abstime2Qtime(t):\n",
" if t <= 2880: \n",
" q = t // (12*60)\n",
" qr= t % (12*60)\n",
" #return str(qr//60) + \"'\" + str(qr%60) + \"'' of Q\" + str(q+1)\n",
" return \"Q\" + str(q+1) + ' ' + str(qr//60) + \"'\" + str(qr%60) + \"''\"\n",
"\n",
"def get_game_info_link(gid):\n",
" link_str = '<a href=\"http://stats.nba.com/game/#!/' + gid + '/\">' \\\n",
" + ' '.join([game_info_dict[gid]['away'],'at', game_info_dict[gid]['home']]) \\\n",
" + '</a>'\n",
" return link_str\n",
"\n",
"with open('data/comebacks_1996-2016_complete.p','rb') as f:\n",
" comebacks=cPickle.load(f)\n",
"if os.path.exists('data/game_info_dict.p'):\n",
" with open('data/game_info_dict.p','rb') as f:\n",
" game_info_dict=cPickle.load(f)\n",
"\n",
"home_away={1:'Home',-1:'Away'}\n",
"row_list = []\n",
"for seasonstart in years:\n",
" season = season_string(seasonstart)\n",
" \n",
" for outcome in[1,-1]:\n",
" sd=sorted(comebacks[season][outcome].items())\n",
" allscores=[s[1][0] for s in sd]\n",
" if outcome == 1:\n",
" bc_margin = np.min(allscores)\n",
" else:\n",
" bc_margin = np.max(allscores)\n",
" game_time = {}\n",
" for idx in np.where(allscores==bc_margin)[0]:\n",
" for gid in sd[idx][1][1]:\n",
" if gid not in game_time:\n",
" game_time[gid] = [sd[idx][0]]\n",
" else:\n",
" game_time[gid].append(sd[idx][0])\n",
" for gid in game_time:\n",
" if len(game_time[gid])>1:\n",
" stimes = sorted(game_time[gid])\n",
" tstr = abstime2Qtime(stimes[0]) + ' to ' + abstime2Qtime(stimes[-1])\n",
" else:\n",
" tstr = 'at ' + abstime2Qtime(game_time[gid][0])\n",
" tmp = get_info(gid)\n",
" game_dict = {}\n",
" game_dict.update({'Season': season,\n",
" 'Home/Away':home_away[outcome],\n",
" 'Comeback score': outcome*bc_margin,\n",
" 'Game': get_game_info_link(gid), \n",
" 'Date': game_info_dict[gid]['time'].title(),\n",
" 'Attendance': game_info_dict[gid]['crowd'],\n",
" 'Time of largest score deficit': tstr})\n",
" row_list.append(game_dict)\n",
" \n",
"with open('data/game_info_dict.p','wb') as fid:\n",
" cPickle.dump(game_info_dict,fid)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true,
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>Comeback score</th>\n",
" <th>Game</th>\n",
" <th>Date</th>\n",
" <th>Attendance</th>\n",
" <th>Time of largest score deficit</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Season</th>\n",
" <th>Home/Away</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 rowspan=\"2\" valign=\"top\">1996-97</th>\n",
" <th>Home</th>\n",
" <td>-36</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029600194/\">Denver Nuggets at Utah Jazz</a></td>\n",
" <td>Wednesday, November 27, 1996</td>\n",
" <td>19324</td>\n",
" <td>Q2 11'40'' to Q2 11'56''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-27</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029600830/\">Phoenix Suns at Dallas Mavericks</a></td>\n",
" <td>Sunday, March 2, 1997</td>\n",
" <td>14832</td>\n",
" <td>Q3 8'51'' to Q3 9'32''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">1997-98</th>\n",
" <th>Home</th>\n",
" <td>-24</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029700672/\">Chicago Bulls at Utah Jazz</a></td>\n",
" <td>Wednesday, February 4, 1998</td>\n",
" <td>19911</td>\n",
" <td>Q2 0'47'' to Q2 2'28''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-24</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029700541/\">Minnesota Timberwolves at Dallas Mavericks</a></td>\n",
" <td>Saturday, January 17, 1998</td>\n",
" <td>15327</td>\n",
" <td>Q3 6'7'' to Q3 6'20''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">1998-99</th>\n",
" <th>Home</th>\n",
" <td>-23</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029800582/\">Houston Rockets at San Antonio Spurs</a></td>\n",
" <td>Sunday, April 18, 1999</td>\n",
" <td>24077</td>\n",
" <td>Q2 1'4'' to Q2 1'20''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-28</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029800600/\">Los Angeles Lakers at Golden State Warriors</a></td>\n",
" <td>Tuesday, April 20, 1999</td>\n",
" <td>20108</td>\n",
" <td>Q2 2'22'' to Q2 7'42''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">1999-00</th>\n",
" <th>Home</th>\n",
" <td>-22</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029900965/\">San Antonio Spurs at Dallas Mavericks</a></td>\n",
" <td>Tuesday, March 21, 2000</td>\n",
" <td>15578</td>\n",
" <td>Q2 10'28'' to Q2 11'39''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-23</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0029900945/\">Sacramento Kings at Los Angeles Clippers</a></td>\n",
" <td>Saturday, March 18, 2000</td>\n",
" <td>18964</td>\n",
" <td>Q2 3'29'' to Q2 3'40''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2000-01</th>\n",
" <th>Home</th>\n",
" <td>-24</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020000298/\">Miami Heat at Sacramento Kings</a></td>\n",
" <td>Sunday, December 10, 2000</td>\n",
" <td>17317</td>\n",
" <td>at Q2 0'0''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-28</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020000883/\">Sacramento Kings at Phoenix Suns</a></td>\n",
" <td>Wednesday, March 7, 2001</td>\n",
" <td>19023</td>\n",
" <td>Q2 8'36'' to Q2 8'46''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2001-02</th>\n",
" <th>Home</th>\n",
" <td>-23</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020100791/\">Charlotte Hornets at New Jersey Nets</a></td>\n",
" <td>Sunday, February 24, 2002</td>\n",
" <td>15516</td>\n",
" <td>Q3 3'21'' to Q3 3'25''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020101005/\">Memphis Grizzlies at Portland Trail Blazers</a></td>\n",
" <td>Monday, March 25, 2002</td>\n",
" <td>20441</td>\n",
" <td>Q3 7'14'' to Q3 8'39''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">2002-03</th>\n",
" <th>Home</th>\n",
" <td>-30</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020200278/\">Dallas Mavericks at Los Angeles Lakers</a></td>\n",
" <td>Friday, December 6, 2002</td>\n",
" <td>18997</td>\n",
" <td>Q3 0'40'' to Q3 0'57''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-23</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020201093/\">Los Angeles Lakers at Memphis Grizzlies</a></td>\n",
" <td>Friday, April 4, 2003</td>\n",
" <td>19351</td>\n",
" <td>Q4 0'0'' to Q4 0'13''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-23</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020200585/\">Boston Celtics at Philadelphia 76ers</a></td>\n",
" <td>Monday, January 20, 2003</td>\n",
" <td>20311</td>\n",
" <td>Q3 1'10'' to Q3 1'31''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2003-04</th>\n",
" <th>Home</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020300812/\">New Orleans Hornets at Cleveland Cavaliers</a></td>\n",
" <td>Monday, February 23, 2004</td>\n",
" <td>17093</td>\n",
" <td>Q2 4'15'' to Q2 5'34''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-29</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020300260/\">Phoenix Suns at Boston Celtics</a></td>\n",
" <td>Friday, December 5, 2003</td>\n",
" <td>15116</td>\n",
" <td>Q3 0'23'' to Q3 0'49''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2004-05</th>\n",
" <th>Home</th>\n",
" <td>-22</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020400680/\">Washington Wizards at Toronto Raptors</a></td>\n",
" <td>Friday, February 4, 2005</td>\n",
" <td>15546</td>\n",
" <td>Q3 3'40'' to Q3 4'13''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-24</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020400085/\">Los Angeles Clippers at Chicago Bulls</a></td>\n",
" <td>Saturday, November 13, 2004</td>\n",
" <td>21764</td>\n",
" <td>Q2 5'30'' to Q2 5'41''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">2005-06</th>\n",
" <th>Home</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020500012/\">Charlotte Bobcats at Chicago Bulls</a></td>\n",
" <td>Wednesday, November 2, 2005</td>\n",
" <td>19251</td>\n",
" <td>Q3 3'22'' to Q3 3'28''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Home</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020500960/\">Boston Celtics at Miami Heat</a></td>\n",
" <td>Thursday, March 16, 2006</td>\n",
" <td>20188</td>\n",
" <td>Q2 8'37'' to Q2 9'24''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-19</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020500597/\">Los Angeles Clippers at Golden State Warriors</a></td>\n",
" <td>Monday, January 23, 2006</td>\n",
" <td>17196</td>\n",
" <td>Q3 8'10'' to Q3 8'36''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-19</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020500585/\">Philadelphia 76ers at Minnesota Timberwolves</a></td>\n",
" <td>Sunday, January 22, 2006</td>\n",
" <td>15893</td>\n",
" <td>Q3 10'2'' to Q3 10'20''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2006-07</th>\n",
" <th>Home</th>\n",
" <td>-27</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020600080/\">New Orleans/Oklahoma City Hornets at Portland Trail Blazers</a></td>\n",
" <td>Friday, November 10, 2006</td>\n",
" <td>14122</td>\n",
" <td>Q2 0'20'' to Q2 0'24''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020601056/\">Seattle SuperSonics at Minnesota Timberwolves</a></td>\n",
" <td>Tuesday, March 27, 2007</td>\n",
" <td>15120</td>\n",
" <td>Q3 6'4'' to Q3 6'17''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2007-08</th>\n",
" <th>Home</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020700120/\">Portland Trail Blazers at Philadelphia 76ers</a></td>\n",
" <td>Friday, November 16, 2007</td>\n",
" <td>11483</td>\n",
" <td>Q2 8'20'' to Q2 8'35''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020700080/\">Denver Nuggets at Indiana Pacers</a></td>\n",
" <td>Saturday, November 10, 2007</td>\n",
" <td>12748</td>\n",
" <td>Q2 6'36'' to Q2 6'48''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2008-09</th>\n",
" <th>Home</th>\n",
" <td>-29</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020800463/\">Minnesota Timberwolves at Dallas Mavericks</a></td>\n",
" <td>Tuesday, December 30, 2008</td>\n",
" <td>20264</td>\n",
" <td>Q3 1'34'' to Q3 2'10''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-26</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020800121/\">Philadelphia 76ers at Indiana Pacers</a></td>\n",
" <td>Friday, November 14, 2008</td>\n",
" <td>12742</td>\n",
" <td>Q2 0'26'' to Q2 0'30''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2009-10</th>\n",
" <th>Home</th>\n",
" <td>-24</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020900559/\">Phoenix Suns at Indiana Pacers</a></td>\n",
" <td>Wednesday, January 13, 2010</td>\n",
" <td>10858</td>\n",
" <td>Q2 5'51'' to Q2 5'58''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-35</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0020900402/\">Sacramento Kings at Chicago Bulls</a></td>\n",
" <td>Monday, December 21, 2009</td>\n",
" <td>19631</td>\n",
" <td>Q3 3'10'' to Q3 3'26''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2010-11</th>\n",
" <th>Home</th>\n",
" <td>-23</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021000373/\">Sacramento Kings at New Orleans Hornets</a></td>\n",
" <td>Wednesday, December 15, 2010</td>\n",
" <td>13325</td>\n",
" <td>Q3 3'12'' to Q3 4'8''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021000344/\">Toronto Raptors at Detroit Pistons</a></td>\n",
" <td>Saturday, December 11, 2010</td>\n",
" <td>13343</td>\n",
" <td>Q3 6'9'' to Q3 6'50''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">2011-12</th>\n",
" <th>Home</th>\n",
" <td>-21</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021100096/\">Milwaukee Bucks at Sacramento Kings</a></td>\n",
" <td>Thursday, January 5, 2012</td>\n",
" <td>11813</td>\n",
" <td>Q2 10'1'' to Q3 1'4''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Home</th>\n",
" <td>-21</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021100571/\">Los Angeles Lakers at Washington Wizards</a></td>\n",
" <td>Wednesday, March 7, 2012</td>\n",
" <td>20282</td>\n",
" <td>Q3 4'37'' to Q3 4'49''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-27</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021100270/\">Boston Celtics at Orlando Magic</a></td>\n",
" <td>Thursday, January 26, 2012</td>\n",
" <td>18952</td>\n",
" <td>Q2 8'49'' to Q2 8'57''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">2012-13</th>\n",
" <th>Home</th>\n",
" <td>-27</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021200633/\">Boston Celtics at Atlanta Hawks</a></td>\n",
" <td>Friday, January 25, 2013</td>\n",
" <td>15595</td>\n",
" <td>Q2 5'59'' to Q2 6'14''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-27</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021201009/\">Miami Heat at Cleveland Cavaliers</a></td>\n",
" <td>Wednesday, March 20, 2013</td>\n",
" <td>20562</td>\n",
" <td>Q3 4'16'' to Q3 4'47''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-27</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021200199/\">Milwaukee Bucks at Chicago Bulls</a></td>\n",
" <td>Monday, November 26, 2012</td>\n",
" <td>21485</td>\n",
" <td>at Q3 9'10''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2013-14</th>\n",
" <th>Home</th>\n",
" <td>-27</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021300268/\">Toronto Raptors at Golden State Warriors</a></td>\n",
" <td>Tuesday, December 3, 2013</td>\n",
" <td>19596</td>\n",
" <td>Q3 2'40'' to Q3 2'48''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-25</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021300984/\">Indiana Pacers at Detroit Pistons</a></td>\n",
" <td>Saturday, March 15, 2014</td>\n",
" <td>17440</td>\n",
" <td>Q2 8'36'' to Q2 8'56''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2014-15</th>\n",
" <th>Home</th>\n",
" <td>-26</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021400118/\">Sacramento Kings at Memphis Grizzlies</a></td>\n",
" <td>Thursday, November 13, 2014</td>\n",
" <td>15666</td>\n",
" <td>Q2 1'14'' to Q2 2'1''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-26</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021400880/\">Golden State Warriors at Boston Celtics</a></td>\n",
" <td>Sunday, March 1, 2015</td>\n",
" <td>18624</td>\n",
" <td>Q2 5'7'' to Q2 5'19''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2015-16</th>\n",
" <th>Home</th>\n",
" <td>-26</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021501217/\">Miami Heat at Boston Celtics</a></td>\n",
" <td>Wednesday, April 13, 2016</td>\n",
" <td>18624</td>\n",
" <td>Q2 11'1'' to Q2 11'55''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-24</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021500587/\">Chicago Bulls at Philadelphia 76ers</a></td>\n",
" <td>Thursday, January 14, 2016</td>\n",
" <td>14063</td>\n",
" <td>Q2 5'38'' to Q2 5'55''</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">2016-17</th>\n",
" <th>Home</th>\n",
" <td>-28</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021600957/\">Sacramento Kings at San Antonio Spurs</a></td>\n",
" <td>Wednesday, March 8, 2017</td>\n",
" <td>18418</td>\n",
" <td>Q2 7'18'' to Q2 7'26''</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Away</th>\n",
" <td>-24</td>\n",
" <td><a href=\"http://stats.nba.com/game/#!/0021600550/\">Memphis Grizzlies at Golden State Warriors</a></td>\n",
" <td>Friday, January 6, 2017</td>\n",
" <td>19596</td>\n",
" <td>Q3 6'44'' to Q3 7'19''</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df= pd.DataFrame(row_list,columns=['Season','Home/Away','Comeback score','Game','Date','Attendance','Time of largest score deficit'])\n",
"df2=df.set_index(['Season','Home/Away'])\n",
"from IPython.display import display, HTML\n",
"pd.set_option('display.max_colwidth', -1)\n",
"with open('largest_comebacks_table.html', 'w') as fid:\n",
" fid.write(df2.to_html(escape=False))\n",
"HTML(df2.to_html(escape=False))"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [conda env:py27]",
"language": "python",
"name": "conda-env-py27-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.13"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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