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Multichem commited on Nov 12, 2023

Commit

6034111

1 Parent(s): 279ff8e

Update app.py

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Files changed (1) hide show

app.py +5 -5

app.py CHANGED Viewed

@@ -112,13 +112,13 @@ def seasonlong_build(data_sample):
     season_long_table['Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('mean').astype(float)
     season_long_table['FD_Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].transform('mean').astype(float)
     season_long_table['Rebound%'] = (data_sample.groupby(['Player', 'Season'], sort=False)['REB'].transform('sum').astype(int) /
-                                     data_sample.groupby(['Player', 'Season'], sort=False)['reboundChancesTotal'].transform('sum').astype(int))
-    season_long_table['Assists/Pass'] = (data_sample.groupby(['Player', 'Season'], sort=False)['assists'].transform('sum').astype(int) /
-                                             data_sample.groupby(['Player', 'Season'], sort=False)['passes'].transform('sum').astype(int))
     season_long_table['Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('sum').astype(int) /
-                                              data_sample.groupby(['Player', 'Season'], sort=False)['touches'].transform('sum').astype(int))
     season_long_table['FD Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].transform('sum').astype(int) /
-                                                 data_sample.groupby(['Player', 'Season'], sort=False)['touches'].transform('sum').astype(int))
     season_long_table = season_long_table.drop_duplicates(subset='Player')
     season_long_table = season_long_table.set_axis(['Player', 'Team', 'Season', 'Date', 'Matchup', 'Min', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M', 'FG3A',

     season_long_table['Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('mean').astype(float)
     season_long_table['FD_Fantasy'] = data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].transform('mean').astype(float)
     season_long_table['Rebound%'] = (data_sample.groupby(['Player', 'Season'], sort=False)['REB'].transform('sum').astype(int) /
+                                     data_sample.groupby(['Player', 'Season'], sort=False)['REB Chance'].transform('sum').astype(int))
+    season_long_table['Assists/Pass'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Assists'].transform('sum').astype(int) /
+                                             data_sample.groupby(['Player', 'Season'], sort=False)['Passes'].transform('sum').astype(int))
     season_long_table['Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['Fantasy'].transform('sum').astype(int) /
+                                              data_sample.groupby(['Player', 'Season'], sort=False)['Touches'].transform('sum').astype(int))
     season_long_table['FD Fantasy/Touch'] = (data_sample.groupby(['Player', 'Season'], sort=False)['FD_Fantasy'].transform('sum').astype(int) /
+                                                 data_sample.groupby(['Player', 'Season'], sort=False)['Touches'].transform('sum').astype(int))
     season_long_table = season_long_table.drop_duplicates(subset='Player')
     season_long_table = season_long_table.set_axis(['Player', 'Team', 'Season', 'Date', 'Matchup', 'Min', 'Touches', 'Pts', 'FGM', 'FGA', 'FG%', 'FG3M', 'FG3A',