def get_game_logs(self, season='2016-17', reg_season=True):
import pandas as pd
try:
if (reg_season == True):
player_info = pd.read_pickle('player_game_logs/' +
str(self.player_id) + '-' +
season + '.pckl')
else:
player_info = pd.read_pickle('player_game_logs/' +
str(self.player_id) + '-' +
season + 'p.pckl')
return player_info
except FileNotFoundError:
from nba_py import player
print(
'File not found while retrieving game logs, retrieving now...')
if (reg_season == True):
player_info = player.PlayerGameLogs(self.player_id,
season=season)
player_info = player_info.info()
player_info.to_pickle('player_game_logs/' +
str(self.player_id) + '-' + season +
'.pckl')
else:
player_info = player.PlayerGameLogs(self.player_id,
season=season,
season_type='Playoffs')
player_info = player_info.info()
player_info.to_pickle('player_game_logs/' +
str(self.player_id) + '-' + season +
'p.pckl')
return player_info
def players_and_season(playerid, season):
# season example: "2016-17"
# type example: "Regular Season" or "Playoffs"
player_game_logs = player.PlayerGameLogs(playerid, season=season)
player_games = player_game_logs.info()
playoffs_playergamelogs = player.PlayerGameLogs(playerid,
season=season,
season_type="Playoffs")
playoffs_player_games = playoffs_playergamelogs.info()
player_summary = player.PlayerSummary(playerid)
player_summary_info = player_summary.info()
headline_stats = player_summary.headline_stats()
birth_datestring = player_summary_info[0]["BIRTHDATE"][:10]
birth_date = datetime.datetime.strptime(birth_datestring, "%Y-%m-%d")
pretty_birth_date = birth_date.strftime("%m-%d-%Y")
age = calculate_age(birth_date)
player_headshot = "https://ak-static.cms.nba.com/wp-content/uploads/headshots/nba/latest/260x190/" + playerid + ".png"
if (not test_link(player_headshot)):
player_headshot = False
return render_template("players.html",
title=player_summary_info[0]["DISPLAY_FIRST_LAST"],
player_games=player_games,
playoffs_player_games=playoffs_player_games,
player_summary_info=player_summary_info[0],
headline_stats=headline_stats[0],
age=age,
pretty_birth_date=pretty_birth_date,
season=season,
team_img=TEAM_ID_DATA,
player_headshot=player_headshot)
def gameLog(id):
i=0
player_now = player.PlayerGameLogs(202738, league_id='00', season='2016-17', season_type='Playoffs')
if(player_now):
player_now = player_now.info()
for row, column in player_now.iterrows():
player_now = player.PlayerGameLogs(id, league_id='00', season='2016-17', season_type='Regular Season')
return player_now
def players(playerid):
"""Specific player pages.
"""
player_summary = player.PlayerSummary(playerid)
player_summary_info = player_summary.info()
headline_stats = player_summary.headline_stats()
to_year = int(player_summary_info[0]["TO_YEAR"])
next_year = to_year + 1
season = str(to_year) + "-" + str(next_year)[2:4]
birth_datestring = player_summary_info[0]["BIRTHDATE"][:10]
birth_date = datetime.datetime.strptime(birth_datestring, "%Y-%m-%d")
pretty_birth_date = birth_date.strftime("%m-%d-%Y")
age = calculate_age(birth_date)
player_game_logs = player.PlayerGameLogs(playerid, season=season)
player_games = player_game_logs.info()
playoffs_playergamelogs = player.PlayerGameLogs(playerid,
season=season,
season_type="Playoffs")
playoffs_player_games = playoffs_playergamelogs.info()
player_career = player.PlayerCareer(playerid)
player_career_regular_season_totals = player_career.regular_season_totals()
player_career_post_season_totals = player_career.post_season_totals()
player_headshot = "https://ak-static.cms.nba.com/wp-content/uploads/headshots/nba/latest/260x190/" + playerid + ".png"
if (not test_link(player_headshot)):
player_headshot = False
return render_template(
"players.html",
title=player_summary_info[0]["DISPLAY_FIRST_LAST"],
playerid=playerid,
player_games=player_games,
playoffs_player_games=playoffs_player_games,
player_summary_info=player_summary_info[0],
headline_stats=headline_stats[0],
age=age,
pretty_birth_date=pretty_birth_date,
season=season,
player_career_regular_season_totals=player_career_regular_season_totals,
player_career_post_season_totals=player_career_post_season_totals,
team_img=TEAM_ID_DATA,
player_headshot=player_headshot)
def get_player_log(_pid, _nb_games, _season, _season_type):
games_logs = nba_player.PlayerGameLogs(_pid,
season=_season,
season_type=_season_type).info()
# ---
game_matchup = []
game_date = []
game_fp = []
game_ttfl = []
if _nb_games > len(games_logs.values):
_nb_games = len(games_logs.values)
idx = _nb_games - 1
while idx >= 0:
game_matchup.append(games_logs['MATCHUP'].values[idx])
game_date.append(games_logs['GAME_DATE'].values[idx])
game_fp.append(score.get_fp_score(games_logs.iloc[[idx]]))
game_ttfl.append(score.get_ttfl_score(games_logs.iloc[[idx]]))
idx -= 1
return (game_matchup, game_date, game_fp, game_ttfl)
def testPlayerGameLogs(self):
playergamelogs = player.PlayerGameLogs(self.playerId, self.leagueId,
self.season, self.seasonType)
info = playergamelogs.info()
self.assertTrue((61, 27) == info.shape)
self.assertTrue((12 == info[0:1].PTS).all())
def get_playoff_stats(name):
name_split = name.split()
first = name_split[0]
last = name_split[1]
pid = player.get_player(first, last)
stats = player.PlayerGameLogs(pid, season_type='Playoffs')
return stats.info()
def __init__(self):
#player id is for lebron james
james = player.PlayerGameLogs('2544', '00', '2017-18',
"Regular Season")
#get the json array resultSets
resp = james.json['resultSets']
#store each of the games in a list
for x in resp:
self.games = x['rowSet']
def get_player_game_log(player_name, season='2016-17'):
id = get_player_id(player_name)
try:
player_info = pd.read_pickle('player_game_logs/' + str(id) + '-' +
season + '.pckl')
except FileNotFoundError:
print('File not found')
player_info = player.PlayerGameLogs(id, season=season)
player_info = player_info.info()
player_info.to_pickle('player_game_logs/' + str(id) + '-' + season +
'.pckl')
return player_info
def create_game_log_profile(player_id, player_dict):
"""Creates a file storing game logs of a player given the ID.
:param player_dict: self explanatory
:param player_id: the ID of the player
"""
new_path = os.path.join(PLAYER_BASE_PATH, f'{player_dict[player_id]}.json')
if not os.path.exists(new_path):
print("Retrieving player game log ... Please wait.")
game_log = player.PlayerGameLogs(player_id).json
with open(new_path, 'w') as player_file:
json.dump(game_log, player_file)
def test():
pid = get_player('Tim', 'Duncan')
vs_pid = get_player('Stephen', 'Curry')
assert player.PlayerList()
assert player.PlayerSummary(pid)
# assert player.PlayerGeneralSplits(pid)
# assert player.PlayerOpponentSplits(pid)
assert player.PlayerLastNGamesSplits(pid)
assert player.PlayerInGameSplits(pid)
assert player.PlayerClutchSplits(pid)
# assert player.PlayerShootingSplits(pid)
assert player.PlayerPerformanceSplits(pid)
assert player.PlayerYearOverYearSplits(pid)
assert player.PlayerCareer(pid)
assert player.PlayerProfile(pid)
assert player.PlayerGameLogs(pid)
assert player.PlayerShotTracking(pid)
assert player.PlayerReboundTracking(pid)
assert player.PlayerPassTracking(pid)
assert player.PlayerDefenseTracking(pid)
# assert player.PlayerShotLogTracking(pid)
# assert player.PlayerReboundLogTracking(pid)
assert player.PlayerVsPlayer(pid, vs_pid)
def testAll(self):
assert player.PlayerList()
assert player.PlayerSummary(self.playerId)
# assert player.PlayerGeneralSplits(self.playerId)
# assert player.PlayerOpponentSplits(self.playerId)
assert player.PlayerLastNGamesSplits(self.playerId)
assert player.PlayerInGameSplits(self.playerId)
assert player.PlayerClutchSplits(self.playerId)
# assert player.PlayerShootingSplits(self.playerId)
assert player.PlayerPerformanceSplits(self.playerId)
assert player.PlayerYearOverYearSplits(self.playerId)
assert player.PlayerCareer(self.playerId)
assert player.PlayerProfile(self.playerId)
assert player.PlayerGameLogs(self.playerId)
assert player.PlayerShotTracking(self.playerId)
assert player.PlayerReboundTracking(self.playerId)
assert player.PlayerPassTracking(self.playerId)
assert player.PlayerDefenseTracking(self.playerId)
# assert player.PlayerShotLogTracking(self.playerId)
# assert player.PlayerReboundLogTracking(self.playerId)
assert player.PlayerVsPlayer(self.playerId, self.vs_playerId)
def nba():
body = request.values['Body']
nba_players = player.PlayerList(league_id='00',
season='2018-19',
only_current=1).info()
pid = nba_players[nba_players.DISPLAY_FIRST_LAST == str(body)]['PERSON_ID']
info = player.PlayerGameLogs(pid, season='2018-19').info()
numbers = '\n' + '2018-19 Stats' + '\n' + 'PTS: ' + str(
info.PTS.mean().round(1)) + '\n' + 'AST: ' + str(
info.AST.mean().round(1)) + '\n' + 'REB: ' + str(
info.REB.mean().round(1)) + '\n' + 'STL: ' + str(
info.REB.mean().round(1)) + '\n' + 'BLK: ' + str(
info.STL.mean().round(1))
ps = player.PlayerSummary(pid)
ps = ps.info()
ps = ps.to_dict()
psa = str(body) + '\n' + 'TEAM: ' + str(
ps['TEAM_NAME'][0]) + '\n' + 'HEIGHT: ' + str(
ps['HEIGHT'][0]) + '\n' + 'POSITION: ' + str(ps['POSITION'][0])
fr = str(psa) + str(numbers)
r = MessagingResponse()
res = str(fr)
r.message(res)
return str(r)
from nba_py import player
from nba_py.player import get_player
import json
mvp_name = [("James", "Harden"), ("Russell", "Westbrook"), ("Lebron", "James"),
("Kawhi", "Leonard"), ("Isaiah", "Thomas"), ("John", "Wall"),
("Kevin", "Durant"), ("Stephen", "Curry"), ("Chris", "Paul"),
("DeMar", "DeRozan")]
mvp_id = []
for name in mvp_name:
first, last = name
mvp_id.append(get_player(first, last_name=last))
print(mvp_id)
logs = None
for id in mvp_id:
player_gamelog = player.PlayerGameLogs(id).info()
if not logs:
logs = player_gamelog
else:
logs += player_gamelog
print(logs)
with open('mvp_game.json', 'w') as f:
json.dump(logs, f)
# players = player.PlayerList().info()
# print players
def getData(name, type, season=''):
season = str(season)
if type.lower() == 'shotlog':
id = getPlayerId(name)
year = season + '-' + str(int(season) + 1)[-2:]
shot_data = shotchart.ShotChart(id, season=year).json
data = shot_data['resultSets'][0]['rowSet']
indices = range(0, len(data))
colnames = shot_data['resultSets'][0]['headers']
df = pd.DataFrame(data, index=indices, columns=colnames)
df = df.sort_values(
['GAME_DATE', 'PERIOD', 'MINUTES_REMAINING', 'SECONDS_REMAINING'],
ascending=[1, 1, 0, 0])
return df
elif type.lower() == 'pergame':
id = getPlayerId(name)
df = pd.DataFrame(
player.PlayerCareer(id, 'PerGame').regular_season_totals())
df.columns = list(map(lambda x: x.upper(), df))
if season:
year = season + '-' + str(int(season) + 1)[-2:]
df = df.loc[df['SEASON_ID'] == year]
return df
elif type.lower() == 'gamelog':
id = getPlayerId(name)
try:
season + '-' + str(int(season) + 1)[-2:]
except:
return 'Season is required. Please fill.'
year = season + '-' + str(int(season) + 1)[-2:]
df = player.PlayerGameLogs(id, '00', year, 'Regular Season').info()
df['GAME_DATE'] = pd.to_datetime(pd.to_datetime(
df['GAME_DATE'], infer_datetime_format=True),
format='%Y%m%d')
return df.sort_values(['GAME_DATE'])
elif type.lower() == 'defense':
id = getPlayerId(name)
year = season + '-' + str(int(season) + 1)[-2:]
player.PlayerDefenseTracking(id, 0)
json = player.PlayerDefenseTracking(getPlayerId(name),
0,
measure_type='Base',
per_mode='PerGame',
season=year).json
data = json['resultSets'][0]['rowSet']
indices = [x[3] for x in data] # Set DEFENSE_CATEGORY as index
colnames = json['resultSets'][0]['headers']
df = pd.DataFrame(data, index=indices, columns=colnames)
df = df.drop(['CLOSE_DEF_PERSON_ID', 'DEFENSE_CATEGORY'], axis=1)
return 'PlayerName: ' + name.upper(), 'Season: ' + year, df
elif type.lower() == 'shotmap':
id = getPlayerId(name)
year = season + '-' + str(int(season) + 1)[-2:]
shot_data = shotchart.ShotChart(id, season=year).json
data = shot_data['resultSets'][0]['rowSet']
indices = range(0, len(data))
colnames = shot_data['resultSets'][0]['headers']
df = pd.DataFrame(data, index=indices, columns=colnames)
df = df.sort_values(
['GAME_DATE', 'PERIOD', 'MINUTES_REMAINING', 'SECONDS_REMAINING'],
ascending=[1, 1, 0, 0])
df_size = df.groupby(['SHOT_ZONE_AREA', 'SHOT_ZONE_RANGE']).size()
df_made = df.loc[df['SHOT_MADE_FLAG'] == 1].groupby(
['SHOT_ZONE_AREA', 'SHOT_ZONE_RANGE']).size()
df_pct = df_made / df_size
df_pct = df_pct.fillna(0)
df_size = df_size.to_frame('SHOTS_ATT').reset_index()
df_made = df_made.to_frame('SHOTS_MADE').reset_index()
df_pct = df_pct.to_frame('SHOT_PCT').reset_index()
df = df_made.merge(df_size,
how='right',
on=['SHOT_ZONE_AREA',
'SHOT_ZONE_RANGE']).fillna(int(0)).merge(
df_pct,
on=['SHOT_ZONE_AREA', 'SHOT_ZONE_RANGE'])
df['SHOTS_MADE'] = df['SHOTS_MADE'].astype(int)
return df
def _get_query_results(params={}, flatten_keys=False):
if 'module' not in params or 'sub_module' not in params or 'function' not in params:
return []
if not flatten_keys and 'value_query' not in params:
return []
if params['module'] == 'player':
if 'first_name' not in params:
return []
first = params['first_name']
last = params['last_name'] if 'last_name' in params else None
team_id = params['team_id'] if 'team_id' in params else 0
measure_type = params[
'measure_type'] if 'measure_type' in params else 'Base'
per_mode = params['per_mode'] if 'per_mode' in params else 'PerGame'
plus_minus = params['plus_minus'] if 'plus_minus' in params else 'N'
pace_adjust = params['pace_adjust'] if 'pace_adjust' in params else 'N'
rank = params['rank'] if 'rank' in params else 'N'
league_id = params['league_id'] if 'league_id' in params else '00'
season = params['season'] if 'season' in params else '2016-17'
season_type = params[
'season_type'] if 'season_type' in params else 'Regular Season'
po_round = params['po_round'] if 'po_round' in params else '0'
outcome = params['outcome'] if 'outcome' in params else ''
location = params['location'] if 'location' in params else ''
month = params['month'] if 'month' in params else '0'
season_segment = params[
'season_segment'] if 'season_segment' in params else ''
date_from = params['date_from'] if 'date_from' in params else ''
date_to = params['date_to'] if 'date_to' in params else ''
opponent_team_id = params[
'opponent_team_id'] if 'opponent_team_id' in params else '0'
vs_conference = params[
'vs_conference'] if 'vs_conference' in params else ''
vs_division = params['vs_division'] if 'vs_division' in params else ''
game_segment = params[
'game_segment'] if 'game_segment' in params else ''
period = params['period'] if 'period' in params else '0'
shot_clock_range = params[
'shot_clock_range'] if 'shot_clock_range' in params else ''
last_n_games = params[
'last_n_games'] if 'last_n_games' in params else '0'
only_current = params['only_current'] if 'only_current' in params else 0
just_id = params['just_id'] if 'just_id' in params else True
player_id = player.get_player(first,
last_name=last,
season=season,
only_current=only_current,
just_id=just_id)
if params['sub_module'] == 'player_career':
career = player.PlayerCareer(player_id)
if params['function'] == 'all_star_season_totals':
temp = career.all_star_season_totals()
elif params['function'] == 'career_all_star_season_totals':
temp = career.career_all_star_season_totals()
elif params['function'] == 'college_season_career_totals':
temp = career.college_season_career_totals()
elif params['function'] == 'college_season_totals':
temp = career.college_season_totals()
elif params['function'] == 'post_season_career_totals':
temp = career.post_season_career_totals()
elif params['function'] == 'post_season_rankings':
temp = career.post_season_rankings()
elif params['function'] == 'post_season_totals':
temp = career.post_season_totals()
elif params['function'] == 'preseason_career_totals':
temp = career.preseason_career_totals()
elif params['function'] == 'preseason_season_totals':
temp = career.preseason_season_totals()
elif params['function'] == 'regular_season_career_totals':
temp = career.regular_season_career_totals()
elif params['function'] == 'regular_season_rankings':
temp = career.regular_season_rankings()
elif params['function'] == 'regular_season_totals':
temp = career.regular_season_totals()
else:
return []
elif params['sub_module'] == 'player_clutch_splits':
clutch = player.PlayerClutchSplits(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'last10sec_deficit_3point':
temp = clutch.last10sec_deficit_3point()
elif params['function'] == 'last1min_deficit_5point':
temp = clutch.last1min_deficit_5point()
elif params['function'] == 'last1min_plusminus_5point':
temp = clutch.last1min_plusminus_5point()
elif params['function'] == 'last30sec_deficit_3point':
temp = clutch.last30sec_deficit_3point()
elif params['function'] == 'last30sec_plusminus_5point':
temp = clutch.last30sec_plusminus_5point()
elif params['function'] == 'last3min_deficit_5point':
temp = clutch.last3min_deficit_5point()
elif params['function'] == 'last3min_plusminus_5point':
temp = clutch.last3min_plusminus_5point()
elif params['function'] == 'last5min_deficit_5point':
temp = clutch.last5min_deficit_5point()
elif params['function'] == 'last5min_plusminus_5point':
temp = clutch.last5min_plusminus_5point()
else:
return []
elif params['sub_module'] == 'player_defense_tracking':
temp = player.PlayerDefenseTracking(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
elif params['sub_module'] == 'player_game_logs':
if params['function'] == 'info':
temp = player.PlayerGameLogs(player_id,
league_id=league_id,
season=season,
season_type=season_type)
else:
return []
elif params['sub_module'] == 'player_general_splits':
splits = player.PlayerGeneralSplits(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'days_rest':
temp = splits.days_rest()
elif params['function'] == 'location':
temp = splits.location()
elif params['function'] == 'month':
temp = splits.month()
elif params['function'] == 'pre_post_all_star':
temp = splits.pre_post_all_star()
elif params['function'] == 'starting_position':
temp = splits.starting_position()
elif params['function'] == 'win_losses':
temp = splits.win_losses()
else:
return []
elif params['sub_module'] == 'player_in_game_splits':
if params['function'] == 'by_actual_margin':
temp = splits.by_actual_margin()
elif params['function'] == 'by_half':
temp = splits.by_half()
elif params['function'] == 'by_period':
temp = splits.by_period()
elif params['function'] == 'by_score_margin':
temp = splits.by_score_margin()
else:
return []
elif params['sub_module'] == 'player_last_n_games_splits':
n_splits = player.PlayerLastNGamesSplits(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'game_number':
temp = n_splits.gamenumber()
elif params['function'] == 'last10':
temp = n_splits.last10()
elif params['function'] == 'last15':
temp = n_splits.last15()
elif params['function'] == 'last20':
temp = n_splits.last20()
elif params['function'] == 'last5':
temp = n_splits.last5()
else:
return []
elif params['sub_module'] == 'player_list':
player_list = player.PlayerList(league_id=league_id,
season=season,
only_current=only_current)
if params['function'] == 'info':
temp = player_list.info()
else:
return []
elif params['sub_module'] == 'player_opponent_splits':
op_splits = player.PlayerOpponentSplits(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'by_conference':
temp = op_splits.by_conference()
elif params['function'] == 'by_division':
temp = op_splits.by_division()
elif params['function'] == 'by_opponent':
temp = op_splits.by_opponent()
else:
return []
elif params['sub_module'] == 'player_pass_tracking':
pass_tracking = player.PlayerPassTracking(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'passes_made':
temp = pass_tracking.passes_made()
elif params['function'] == 'passes_received':
temp = pass_tracking.passes_received()
else:
return []
elif params['sub_module'] == 'player_performance_splits':
performance_splits = player.PlayerPerformanceSplits(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'points_against':
temp = performance_splits.points_against()
elif params['function'] == 'points_scored':
temp = performance_splits.points_scored()
elif params['function'] == 'score_differential':
temp = performance_splits.score_differential()
else:
return []
elif params['sub_module'] == 'player_profile':
prof = player.PlayerProfile(per_mode=per_mode, league_id=league_id)
if params['function'] == 'career_highs':
temp = prof.career_highs()
elif params['function'] == 'next_game':
temp = prof.next_game()
elif params['function'] == 'season_highs':
temp = prof.season_highs()
else:
return []
elif params['sub_module'] == 'player_rebound_log_tracking':
temp = player.PlayerReboundLogTracking(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
elif params['sub_module'] == 'player_rebound_tracking':
rb_tracking = player.PlayerReboundTracking(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'num_contested_rebounding':
temp = rb_tracking.num_contested_rebounding()
elif params['function'] == 'rebound_distance_rebounding':
temp = rb_tracking.rebound_distance_rebounding()
elif params['function'] == 'shot_distance_rebounding':
temp = rb_tracking.shot_distance_rebounding()
elif params['function'] == 'shot_type_rebounding':
temp = rb_tracking.shot_type_rebounding()
else:
return []
elif params['sub_module'] == 'player_shooting_splits':
if params['function'] == 'assisted_by':
temp = rb_tracking.assisted_by()
elif params['function'] == 'assisted_shots':
temp = rb_tracking.assisted_shots()
elif params['function'] == 'shot_5ft':
temp = rb_tracking.shot_5ft()
elif params['function'] == 'shot_8ft':
temp = rb_tracking.shot_8ft()
elif params['function'] == 'shot_areas':
temp = rb_tracking.shot_areas()
elif params['function'] == 'shot_types_detail':
temp = rb_tracking.shot_types_detail()
elif params['function'] == 'shot_types_summary':
temp = rb_tracking.shot_types_summary()
else:
return []
elif params['sub_module'] == 'player_shot_log_tracking':
temp = player.PlayerShotLogTracking(player_id, team_id=team_id, measure_type=measure_type, per_mode=per_mode, plus_minus=plus_minus, \
pace_adjust=pace_adjust, rank=rank, league_id=league_id, season=season, season_type=season_type, po_round=po_round, outcome=outcome, \
location=location, month=month, season_segment=season_segment, date_from=date_from, date_to=date_to, opponent_team_id=opponent_team_id, \
vs_conference=vs_conference, vs_division=vs_division, game_segment=game_segment, period=period, shot_clock_range=shot_clock_range, \
last_n_games=last_n_games
)
if params['function'] == 'closest_defender_shooting':
temp = rb_tracking.closest_defender_shooting()
elif params['function'] == 'closest_defender_shooting_long':
temp = rb_tracking.closest_defender_shooting_long()
elif params['function'] == 'dribble_shooting':
temp = rb_tracking.dribble_shooting()
elif params['function'] == 'general_shooting':
temp = rb_tracking.general_shooting()
elif params['function'] == 'shot_clock_shooting':
temp = rb_tracking.shot_clock_shooting()
elif params['function'] == 'touch_time_shooting':
temp = rb_tracking.touch_time_shooting()
else:
return []
# elif params['sub_module'] == 'player_shot_tracking':
# elif params['sub_module'] == 'player_summary':
# elif params['sub_module'] == 'player_vs_player':
# elif params['sub_module'] == 'player_year_over_year_splits':
elif params['module'] == 'game':
pass
elif params['module'] == 'team':
pass
else:
# Failure case.
pass
if flatten_keys:
return [
l for l in list(set([el for o in temp for el in o.keys()]))
if l not in to_remove
]
else:
return {
'data': [o[params['value_query']] for o in temp],
'labels': [o[get_x_axis_key(params['function'])] for o in temp]
}
# # array of players as dictionaries
# p_dict = p_df.T.to_dict().values()
# '''
# {u'GAMES_PLAYED_FLAG': u'Y', u'DISPLAY_FIRST_LAST': u'Alex Abrines', u'TEAM_ABBREVIATION': u'OKC', u'TEAM_ID': 1610612760, u'TO_YEAR': u'2017', u'FROM_YEAR': u'2016', u'PLAYERCODE': u'alex_abrines', u'PERSON_ID': 203518, u'DISPLAY_LAST_COMMA_FIRST': u'Abrines, Alex', u'ROSTERSTATUS': 1, u'TEAM_CODE': u'thunder', u'TEAM_NAME': u'Thunder', u'TEAM_CITY': u'Oklahoma City'}
# '''
# for p in p_dict[4:5]:
# print p['PLAYERCODE']
# p_id = p['PERSON_ID']
# print player.PlayerCareer(p_id, per_mode='PerGame', league_id='00').regular_season_totals()
# print player.PlayerGameLogs(p_id, league_id='00', season='2017-18', season_type='Regular Season').info()
import nba_py
from nba_py import player
from nba_py import game
#
plist = nba_py.player.PlayerList(league_id='00',
season='2017-18',
only_current=1)
p_df = plist.info()
p_dict = p_df.T.to_dict().values()
p = p_dict[10]
p_id = p['PERSON_ID']
#print 'testing'
game_log = player.PlayerGameLogs(p_id,
league_id='00',
season='2017-18',
season_type='Regular Season').info()
colnames = list(game_log.columns.values)
print game_log.to_json(orient='records')
PTS
PLUS_MINUS
'''
bad_cols = ['MATCHUP', 'GAME_DATE', 'VIDEO_AVAILABLE']
print('\nQuerying Player Log Data...')
start_time = time.time()
playergame = pd.DataFrame()
plyrs = player_list.index
# Loop through players
for i in range(plyrs.shape[0]):
plyr = plyrs[i]
data = player.PlayerGameLogs(plyr, season=season).info()
data.drop(bad_cols, axis=1, inplace=True)
playergame = playergame.append(data)
if not i % 50 and i:
print(' %.0f of %.0f Players complete' % (i, plyrs.shape[0]))
print(' Number of rows Queried =', playergame.shape[0])
print(' Runtime (minutes) = %.2f' % ((time.time() - start_time) / 60))
playergame['SEASON_ID'] = seasonid
playergame.to_csv('data/PlayerGameStats_' + str(seasonid) + '.csv',
index=False)
from nba_py import team, player
202738
player.PlayerGameLogs(202738, league_id='00', season='2016-17', season_type='Playoffs')
def gameLog(id):
i=0
player_now = player.PlayerGameLogs(202738, league_id='00', season='2016-17', season_type='Playoffs')
if(player_now):
player_now = player_now.info()
for row, column in player_now.iterrows():
player_now = player.PlayerGameLogs(id, league_id='00', season='2016-17', season_type='Regular Season')
return player_now
team_id = {"Atlanta Hawks":1610612737, "Boston Celtics": 1610612738, "Brooklyn Nets": 1610612751, \
"Charlotte Hornets" : 1610612766, "Chicago Bulls" : 1610612741, "Cleveland Cavaliers": 1610612739, \
"Dallas Mavericks" : 1610612742, "Denver Nuggets" : 1610612743, "Detroit Pistons" : 1610612765, \
"Golden State Warriors" : 1610612744, "Houston Rockets" : 1610612745, "Indiana Pacers": 1610612754, \
"Los Angeles Clippers" : 1610612746, "Los Angeles Lakers": 1610612747, "Memphis Grizzlies" : 1610612763, \
"Miami Heat" :1610612748, "Milwaukee Bucks" : 1610612749, "Minnesota Timberwolves" : 1610612750, \
"New Orleans Pelicans" : 1610612740, "New York Knicks": 1610612752, "Oklahoma City Thunder": 1610612760, \
"Orlando Magic" : 1610612753, "Philadelphia 76ers" : 1610612755, "Phoenix Suns" : 1610612756, \
"Portland Trail Blazers" : 1610612757, "Sacramento Kings" : 1610612758, "San Antonio Spurs" : 1610612759, \
"Toronto Raptors" : 1610612761, "Utah Jazz" : 1610612762, "Washington Wizards" : 1610612764
}
players = player.PlayerList(league_id='00', season='2016-17', only_current=1)
