Multichem commited on
Commit
ce3bf55
·
1 Parent(s): 6034111

Update app.py

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Files changed (1) hide show
  1. app.py +2 -1
app.py CHANGED
@@ -81,6 +81,7 @@ def seasonlong_build(data_sample):
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  season_long_table = data_sample[['Player', 'Team']]
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  season_long_table['Min'] = data_sample.groupby(['Player', 'Season'], sort=False)['Min'].transform('mean').astype(float)
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  season_long_table['Touches'] = data_sample.groupby(['Player', 'Season'], sort=False)['Touches'].transform('mean').astype(float)
 
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  season_long_table['FGM'] = data_sample.groupby(['Player', 'Season'], sort=False)['FGM'].transform('mean').astype(float)
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  season_long_table['FGA'] = data_sample.groupby(['Player', 'Season'], sort=False)['FGA'].transform('mean').astype(float)
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  season_long_table['FG%'] = (data_sample.groupby(['Player', 'Season'], sort=False)['FGM'].transform('sum').astype(int) /
@@ -121,7 +122,7 @@ def seasonlong_build(data_sample):
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  data_sample.groupby(['Player', 'Season'], sort=False)['Touches'].transform('sum').astype(int))
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  season_long_table = season_long_table.drop_duplicates(subset='Player')
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- season_long_table = season_long_table.set_axis(['Player', 'Team', 'Season', 'Date', 'Matchup', 'Min', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M', 'FG3A',
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  'FG3%', 'FTM', 'FTA', 'FT%', 'OREB Chance', 'OREB', 'DREB Chance', 'DREB', 'REB Chance', 'REB',
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  'Passes', 'Alt Assists', 'FT Assists', 'Assists', 'Stl', 'Blk', 'Tov', 'PF', 'DD', 'TD', 'Fantasy', 'FD_Fantasy',
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  'Rebound%', 'Assists/Pass', 'Fantasy/Touch', 'FD Fantasy/Touch'], axis=1)
 
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  season_long_table = data_sample[['Player', 'Team']]
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  season_long_table['Min'] = data_sample.groupby(['Player', 'Season'], sort=False)['Min'].transform('mean').astype(float)
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  season_long_table['Touches'] = data_sample.groupby(['Player', 'Season'], sort=False)['Touches'].transform('mean').astype(float)
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+ season_long_table['Pts'] = data_sample.groupby(['Player', 'Season'], sort=False)['Pts'].transform('mean').astype(float)
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  season_long_table['FGM'] = data_sample.groupby(['Player', 'Season'], sort=False)['FGM'].transform('mean').astype(float)
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  season_long_table['FGA'] = data_sample.groupby(['Player', 'Season'], sort=False)['FGA'].transform('mean').astype(float)
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  season_long_table['FG%'] = (data_sample.groupby(['Player', 'Season'], sort=False)['FGM'].transform('sum').astype(int) /
 
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  data_sample.groupby(['Player', 'Season'], sort=False)['Touches'].transform('sum').astype(int))
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  season_long_table = season_long_table.drop_duplicates(subset='Player')
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+ season_long_table = season_long_table.set_axis(['Player', 'Team', 'Min', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M', 'FG3A',
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  'FG3%', 'FTM', 'FTA', 'FT%', 'OREB Chance', 'OREB', 'DREB Chance', 'DREB', 'REB Chance', 'REB',
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  'Passes', 'Alt Assists', 'FT Assists', 'Assists', 'Stl', 'Blk', 'Tov', 'PF', 'DD', 'TD', 'Fantasy', 'FD_Fantasy',
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  'Rebound%', 'Assists/Pass', 'Fantasy/Touch', 'FD Fantasy/Touch'], axis=1)