'AST', 'TOV', 'STL', 'BLK', 'PF', '+/-'] preds=[] data=pd.read_csv(path2data+'whole_raw.csv') for game in list(range(len(games))): b=pd.DataFrame() team_home=games.at[game,'home'] team_away=games.at[game,'away'] teams=[team_home,team_away] date=games.at[game,'date'] x,teams_avgs=0,pd.DataFrame() for team in teams: past=f.get_past_games(data,date,team,20) for c in c2_avg: b.at[x,c]=f.get_avgs(past,c) b.at[x,'winrate 20']=f.create_winrate(past,20) b.at[x,'winrate 10']=f.create_winrate(past,10) b.at[x,'winrate 5']=f.create_winrate(past,5) b.at[x,'fatigue']=f.fatigue(past) teams_avgs=teams_avgs.append(b) x=x+1 home=teams_avgs.iloc[[1]] away=teams_avgs.iloc[[2]] home=home.reset_index(drop=True) away=away.reset_index(drop=True) b=home.join(away,lsuffix='_home',rsuffix='_away') pred=clf.predict(b) print(games.loc[[game]],pred) preds.append(pred)
data = pd.read_csv('raw.csv') #data=data.dropna() data.pop('Unnamed: 24') data = data.astype('object') #data=data[:1000] c2_avg = [ 'PTS', 'FGM', 'FGA', 'FG%', '3PM', '3PA', '3P%', 'FTM', 'FTA', 'FT%', 'OREB', 'DREB', 'REB', 'AST', 'TOV', 'STL', 'BLK', 'PF', '+/-' ] for ix in range(len(data)): print(ix) data1 = data.loc[ix, 'Game Date'] team = data.loc[ix, 'Team'] ixs = f.get_past_games(data, data1, team, 30) past = data.loc[ixs] data.at[ix, 'winrate 30'] = f.create_winrate(past, 30) data.at[ix, 'winrate 6'] = f.create_winrate(past, 6) for c in c2_avg: data.at[ix, c] = f.get_avgs(past, c) data.to_csv('data.csv', index=False) b = f.append2for1(data) b['Result'] = f.result(b) b['Location'] = f.location(b) b.to_csv('train.csv', index=False)
'AST', 'TOV', 'STL', 'BLK', 'PF', '+/-'] # get avgs of recent data toappend=toappend.reset_index(drop=True) toappend=toappend.astype('object') for ix in range(len(toappend)): print(ix) data1=toappend.at[ix,'Game Date'] team=toappend.at[ix,'Team'] past=f.get_past_games(whole_data,data1,team,20) toappend.at[ix,'winrate 20']=f.create_winrate(past,20) toappend.at[ix,'winrate 10']=f.create_winrate(past,10) toappend.at[ix,'winrate 5']=f.create_winrate(past,5) toappend.at[ix,'fatigue']=f.fatigue(past) for c in c2_avg: toappend.at[ix,c]=f.get_avgs(past,c) """ # update data.csv data=pd.read_csv('data.csv') data=data.dropna() data=data.iloc[::-1] data=data.append(toappend,sort=False) data=data.iloc[::-1] data=data.reset_index(drop=True) data.to_csv('data.csv',index=False) """ # update train.csv train=pd.read_csv('train.csv') toappend=f.append2for1(toappend) toappend['Result']=f.result(toappend) train=train.iloc[::-1]