def custom_boxscore(roster_id):
game_logs = team.TeamGameLogs(roster_id)
df_game_logs = game_logs.info()
df_game_logs['GAME_DATE'] = pd.to_datetime(df_game_logs['GAME_DATE'])
df_game_logs['DAYS_REST'] = df_game_logs['GAME_DATE'] - df_game_logs[
'GAME_DATE'].shift(-1)
df_game_logs['DAYS_REST'] = df_game_logs['DAYS_REST'].astype(
'timedelta64[D]')
df_all = pd.DataFrame() ##blank dataframe
dates = df_game_logs['GAME_DATE']
for date in dates:
game_info = team.TeamPassTracking(roster_id,
date_from=date,
date_to=date).passes_made()
game_info[
'GAME_DATE'] = date ## We need to append the date to this so we can join back
temp_df = game_info.groupby(['GAME_DATE']).sum()
temp_df.reset_index(level=0, inplace=True)
##now to get the shot info. For the most part, we're just reusing code we've already written
open_info = team.TeamShotTracking(
roster_id, date_from=date,
date_to=date).closest_defender_shooting()
open_info['OPEN'] = open_info['CLOSE_DEF_DIST_RANGE'].map(
lambda x: True if 'Open' in x else False)
temp_df['OPEN_SHOTS'] = open_info.loc[open_info['OPEN'] == True,
'FGA'].sum()
temp_df['OPEN_EFG'] = (
open_info.loc[open_info['OPEN'] == True, 'FGM'].sum() +
(.5 * open_info.loc[open_info['OPEN'] == True, 'FG3M'].sum())) / (
open_info.loc[open_info['OPEN'] == True, 'FGA'].sum())
temp_df['COVERED_EFG'] = (
open_info.loc[open_info['OPEN'] == False, 'FGM'].sum() +
(.5 * open_info.loc[open_info['OPEN'] == False, 'FG3M'].sum())) / (
open_info.loc[open_info['OPEN'] == False, 'FGA'].sum())
##append this to our bigger dataframe
df_all = df_all.append(temp_df)
df_boxscore = pd.merge(df_game_logs,
df_all[[
'PASS', 'FG2M', 'FG2_PCT', 'OPEN_SHOTS',
'OPEN_EFG', 'COVERED_EFG'
]],
how='left',
left_on=df_game_logs['GAME_DATE'],
right_on=df_all['GAME_DATE'])
df_boxscore['PASS_AST'] = df_boxscore['PASS'] / df_boxscore['AST']
df_boxscore['RESULT'] = df_boxscore['WL'].map(lambda x: 1
if 'W' in x else 0)
return df_boxscore
def test():
team_id = TEAMS['ATL']['id']
player_id = get_player('Lebron', 'James')
assert team.TeamList()
assert team.TeamSummary(team_id)
team_details = team.TeamDetails(team_id)
assert team_details
assert team_details.background()
assert team_details.history()
assert team.TeamCommonRoster(team_id)
assert team.TeamGeneralSplits(team_id)
assert team.TeamOpponentSplits(team_id)
assert team.TeamLastNGamesSplits(team_id)
assert team.TeamInGameSplits(team_id)
assert team.TeamClutchSplits(team_id)
assert team.TeamShootingSplits(team_id)
assert team.TeamPerformanceSplits(team_id)
assert team.TeamLineups(team_id)
assert team.TeamPlayers(team_id)
assert team.TeamPlayerOnOffDetail(team_id)
assert team.TeamPlayerOnOffSummary(team_id)
assert team.TeamGameLogs(team_id)
assert team.TeamShotTracking(team_id)
assert team.TeamReboundTracking(team_id)
assert team.TeamPassTracking(team_id)
assert team.TeamVsPlayer(team_id, player_id)
def test():
if os.path.exists(TEAMS_FILE):
teams = pd.DataFrame.from_csv(TEAMS_FILE)
else:
teams = team.TeamList().info().dropna()
teams.to_csv(TEAMS_FILE)
all = None
for index, row in teams.iterrows():
data = team.TeamPassTracking(team_id=row['TEAM_ID'])
passes_made = data.passes_made().drop([u'PASS_TYPE'], 1)
passes_made.rename(columns={'PASS_FROM': 'PLAYER_NAME'}, inplace=True)
passes_recieved = data.passes_recieved().drop([u'PASS_TYPE'], 1)
passes_recieved.rename(columns={'PASS_TO': 'PLAYER_NAME'},
inplace=True)
overall = passes_made.merge(
passes_recieved,
left_on=PRIMARY_KEYS,
right_on=PRIMARY_KEYS,
how='outer',
suffixes=['_ON_MADE', '_ON_RECEIVED'
]).dropna().drop(['TEAM_ID', 'PASS_TEAMMATE_PLAYER_ID'],
1)
if all is not None:
all = pd.concat([all, overall])
else:
all = overall
print overall
all.to_csv('data/passdash.csv', index=False)
def testAll(self):
assert team.TeamList()
assert team.TeamSummary(self.teamId)
team_details = team.TeamDetails(self.teamId)
assert team_details
# assert team_details.background()
# assert team_details.history()
assert team.TeamCommonRoster(self.teamId)
assert team.TeamGeneralSplits(self.teamId)
assert team.TeamOpponentSplits(self.teamId)
assert team.TeamLastNGamesSplits(self.teamId)
assert team.TeamInGameSplits(self.teamId)
assert team.TeamClutchSplits(self.teamId)
assert team.TeamShootingSplits(self.teamId)
assert team.TeamPerformanceSplits(self.teamId)
assert team.TeamLineups(self.teamId)
assert team.TeamPlayers(self.teamId)
assert team.TeamPlayerOnOffDetail(self.teamId)
assert team.TeamPlayerOnOffSummary(self.teamId)
assert team.TeamGameLogs(self.teamId)
assert team.TeamShotTracking(self.teamId)
assert team.TeamReboundTracking(self.teamId)
assert team.TeamPassTracking(self.teamId)
assert team.TeamVsPlayer(self.teamId, self.playerId)
def nba_main():
raptors = team.TeamPassTracking(raptors_id)
rp = raptors.passes_made().head()
print(rp)
def nba_passes():
raptors_last_game = team.TeamPassTracking(raptors_id,last_n_games=2)
raptors_last_game.passes_made().head()
import os
import pandas as pd
TEAMS_FILE = 'teams.csv'
PRIMARY_KEYS = [
u'TEAM_ID', u'TEAM_NAME', u'PASS_TEAMMATE_PLAYER_ID', u'PLAYER_NAME'
]
if __name__ == '__main__':
if os.path.exists(TEAMS_FILE):
teams = pd.DataFrame.from_csv(TEAMS_FILE)
else:
teams = team.TeamList().info().dropna()
teams.to_csv(TEAMS_FILE)
all = None
for index, row in teams.iterrows():
data = team.TeamPassTracking(team_id=row['TEAM_ID'])
passes_made = data.passes_made().drop([u'PASS_TYPE'], 1)
passes_made.rename(columns={'PASS_FROM': 'PLAYER_NAME'}, inplace=True)
passes_recieved = data.passes_recieved().drop([u'PASS_TYPE'], 1)
passes_recieved.rename(columns={'PASS_TO': 'PLAYER_NAME'},
inplace=True)
overall = passes_made.merge(
passes_recieved,
left_on=PRIMARY_KEYS,
right_on=PRIMARY_KEYS,
how='outer',
suffixes=['_ON_MADE', '_ON_RECEIVED'
]).dropna().drop(['TEAM_ID', 'PASS_TEAMMATE_PLAYER_ID'],
1)