def getTotalAve(lis, GTBP):
df = pd.DataFrame()
for x in range(len(lis)):
df = df.append(pfp.PlayerFantasyProfile(lis[x]).get_data_frames()[0], ignore_index=True)
Time.sleep(delay)
df = df.drop(columns=['GROUP_SET',
'GROUP_VALUE',
'W',
'L',
'W_PCT',
'MIN',
'OREB',
'DREB',
'BLKA',
'PF',
'PFD',
'PLUS_MINUS',
'DD2',
'TD3',
'FAN_DUEL_PTS',
'NBA_FANTASY_PTS',
'FG3A',
'FG3_PCT',
'FG_PCT',
'FT_PCT'
])
df.insert(1, 'FGMPG', df.FGM / df.GP)
df.insert(2, 'FGAPG', df.FGA / df.GP)
df.insert(3, 'FTMPG', df.FTM / df.GP)
df.insert(4, 'FTAPG', df.FTA / df.GP)
df.insert(7, '3PTMPG', df.FG3M / df.GP)
df.insert(9, 'PPG', df.PTS / df.GP)
df.insert(10, 'RPG', df.REB / df.GP)
df.insert(11, 'APG', df.AST / df.GP)
df.insert(16, 'TOPG', df.TOV / df.GP)
df.insert(13, 'SPG', df.STL / df.GP)
df.insert(15, 'BPG', df.BLK / df.GP)
df.insert(0, 'GTBP', GTBP)
df = df.drop(columns=['PTS',
'AST',
'REB',
'BLK',
'STL',
'TOV',
'FGA',
'FG3M',
'GP',
'FTA',
'FTM',
'FGM'
])
return df
def main():
df_final = pd.DataFrame()
df_opponent = pd.DataFrame()
for x in range(len(lis)):
df_final = df_final.append(cleanse(pfp.PlayerFantasyProfile(lis[x]).get_data_frames()[0]), ignore_index=True)
time.sleep(.5)
print('My lineup stas: ')
print('')
print(df_final)
print('')
df_final = cleanseSomeMore(df_final)
print('This is my total stats:')
print('')
print(df_final)
print('')
if len(lis2):
for x in range(len(lis2)):
df_opponent = df_opponent.append(cleanse(pfp.PlayerFantasyProfile(lis2[x]).get_data_frames()[0]), ignore_index=True)
print('My Opponent\'s lineup stas: ')
print('')
print(df_opponent)
print('')
df_opponent = cleanseSomeMore(df_opponent)
print('This is my opponent\'s total stats:')
print('')
print(df_opponent)
print('')
def main():
df_final = pd.DataFrame()
df_opponent = pd.DataFrame()
for x in range(len(lis)):
df_final = df_final.append(cleanse(
pfp.PlayerFantasyProfile(lis[x]).get_data_frames()[0]),
ignore_index=True)
for x in range(len(lis2)):
df_opponent = df_opponent.append(cleanse(
pfp.PlayerFantasyProfile(lis2[x]).get_data_frames()[0]),
ignore_index=True)
print(df_final)
print(df_opponent)
df_final = cleanseSomeMore(df_final)
df_opponent = cleanseSomeMore(df_opponent)
print(df_final)
print(df_opponent)
def getFantasyProfileDict(self,
mode="PerGame",
type_season="Regular Season",
id="201939",
my_season="2018-19"):
fantasy_obj = playerfantasyprofile.PlayerFantasyProfile(
player_id=id,
measure_type_base="Base",
pace_adjust_no="N",
per_mode36=mode,
plus_minus_no="N",
rank_no="N",
season=my_season,
season_type_playoffs=type_season,
league_id_nullable="00")
fantasy_dict = fantasy_obj.get_dict()
with open('season_stats.json', 'w') as fp:
json.dump(fantasy_dict, fp, indent=3)
return fantasy_dict
from nba_api.stats.endpoints import commonplayerinfo, playerfantasyprofile
from nba_api.stats.static import players
import pandas
playerName = 'Lebron James'
seasonYear = '2015-16'
statCategory = 'GROUP_VALUE'
playerId = players.find_players_by_full_name(playerName)[0]['id']
print(playerId)
player_info = commonplayerinfo.CommonPlayerInfo(player_id=playerId)
playerInfo = player_info.common_player_info.get_data_frame()
# print (avaliableSeasonDF.at[0, 'SEASON_ID'])
print(playerInfo)
# team_id =
seasonInfo = playerfantasyprofile.PlayerFantasyProfile(player_id=playerId,
season=seasonYear)
seasonInfoByGame = seasonInfo.opponent.get_data_frame()
print(seasonInfoByGame)
statDF = seasonInfoByGame.loc[:, statCategory]
print(statDF)