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James McCool commited on
Commit
acfed57
·
1 Parent(s): 2457f50

fixing FPPM to be cumulative not exclusive

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Files changed (1) hide show
  1. src/streamlit_app.py +4 -3
src/streamlit_app.py CHANGED
@@ -213,14 +213,15 @@ def seasonlong_build(data_sample):
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  season_long_table['TD'] = data_sample.groupby(['Player', 'Season'], sort=False)['TD'].transform('mean').astype(float)
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  season_long_table['Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('mean').astype(float)
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  season_long_table['FD_Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].transform('mean').astype(float)
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- season_long_table['FPPM'] = data_sample.groupby(['Player', 'Season'], sort=False)['FPPM'].transform('mean').astype(float)
 
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  season_long_table['Rebound%'] = (data_sample.groupby(['Player', 'Season'], sort=False)['REB'].transform('sum').astype(int) /
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  data_sample.groupby(['Player', 'Season'], sort=False)['REB Chance'].transform('sum').astype(int))
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  season_long_table['Assists/Pass'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Assists'].transform('sum').astype(int) /
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  data_sample.groupby(['Player', 'Season'], sort=False)['Passes'].transform('sum').astype(int))
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- season_long_table['Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].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['FD Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].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['TD'] = data_sample.groupby(['Player', 'Season'], sort=False)['TD'].transform('mean').astype(float)
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  season_long_table['Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('mean').astype(float)
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  season_long_table['FD_Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].transform('mean').astype(float)
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+ season_long_table['FPPM'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('sum').astype(float) /
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+ data_sample.groupby(['Player', 'Season'], sort=False)['Min'].transform('sum').astype(int))
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  season_long_table['Rebound%'] = (data_sample.groupby(['Player', 'Season'], sort=False)['REB'].transform('sum').astype(int) /
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  data_sample.groupby(['Player', 'Season'], sort=False)['REB Chance'].transform('sum').astype(int))
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  season_long_table['Assists/Pass'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Assists'].transform('sum').astype(int) /
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  data_sample.groupby(['Player', 'Season'], sort=False)['Passes'].transform('sum').astype(int))
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+ season_long_table['Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('sum').astype(float) /
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  data_sample.groupby(['Player', 'Season'], sort=False)['Touches'].transform('sum').astype(int))
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+ season_long_table['FD Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].transform('sum').astype(float) /
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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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