Update app.py

app.py

@@ -783,18 +783,20 @@ def server(input, output, session):
         df_dated_score_group[df_dated_score_group.columns[1:]] = df_dated_score_group[df_dated_score_group.columns[1:]].divide(df_dated_score_group.GP,axis=0)
         df_dated_score_group['PP_percent'] = df_dated_score_group.PP_toi / df_dated_score_group.team_pp
         df_dated_score_group = df_dated_score_group.reset_index()
+        df_dated_score_group = df_dated_score_group.merge(test_df[['Team','Off-Night']],left_on=['Team'],right_on=['Team'])
         df_dated_score_group = df_dated_score_group[(df_dated_score_group.Team.isin(team_top))&(df_dated_score_group.percent_owned <= .50 )]
         df_dated_score_group['TOI'] = ["%d:%02d" % (int(x),(x*60)%60) for x in df_dated_score_group['TOI'].astype(float)]
         df_dated_score_group_table = df_dated_score_group[['Player','Team' ,'position', 'percent_owned', 'GP', 'TOI',
-            'Goals', 'ixG', 'Assists', 'Points', 'Shots', 'PP_Points', 'PP_percent']].sort_values(['Points','PP_percent','Goals','Shots'],ascending=False)
+            'Goals', 'ixG', 'Assists', 'Points', 'Shots', 'PP_Points', 'PP_percent','Off-Night']].sort_values(['Points','Off-Night','PP_percent','Goals','Shots'],ascending=False)
 
         df_dated_score_group_table.columns = ['Player','Team' ,'Position', 'Roster%', 'GP', 'TOI/GP',
-            'Goals/GP', 'ixG/GP','Assists/GP', 'Points/GP', 'Shots/GP', 'PPP/GP', 'PP%']
+            'Goals/GP', 'ixG/GP','Assists/GP', 'Points/GP', 'Shots/GP', 'PPP/GP', 'PP%','Off-Night']
         
         
 
-        return df_dated_score_group_table[df_dated_score_group_table.Position != 'D'].head(input.max_head()).style.background_gradient(cmap=cmap_off, subset=['Points/GP']).background_gradient(cmap=cmap_total, subset=['Roster%']).hide_index().set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
-        .set_table_styles([{
+        return df_dated_score_group_table[df_dated_score_group_table.Position != 'D'].head(input.max_head()).style.background_gradient(
+            cmap=cmap_off, subset=['Points/GP']).background_gradient(cmap=cmap_total, subset=['Roster%']).background_gradient(cmap=cmap_off, subset=['Off-Night'],vmin=0,vmax=df_dated_score_group_table['Off-Night'].max()).hide_index().set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
+            .set_table_styles([{
             'selector': 'caption',
             'props': [
                 ('color', ''),
@@ -919,15 +921,20 @@ def server(input, output, session):
         df_dated_score_group[df_dated_score_group.columns[1:]] = df_dated_score_group[df_dated_score_group.columns[1:]].divide(df_dated_score_group.GP,axis=0)
         df_dated_score_group['PP_percent'] = df_dated_score_group.PP_toi / df_dated_score_group.team_pp
         df_dated_score_group = df_dated_score_group.reset_index()
+        df_dated_score_group = df_dated_score_group.merge(test_df[['Team','Off-Night']],left_on=['Team'],right_on=['Team'])
         df_dated_score_group = df_dated_score_group[(df_dated_score_group.Team.isin(team_top))&(df_dated_score_group.percent_owned <= .50 )]
         df_dated_score_group['TOI'] = ["%d:%02d" % (int(x),(x*60)%60) for x in df_dated_score_group['TOI'].astype(float)]
         df_dated_score_group_table = df_dated_score_group[['Player','Team' ,'position', 'percent_owned', 'GP', 'TOI',
-            'Goals', 'ixG', 'Assists', 'Points', 'Shots', 'PP_Points', 'PP_percent']].sort_values(['Points','PP_percent','Goals','Shots'],ascending=False)
+            'Goals', 'ixG', 'Assists', 'Points', 'Shots', 'PP_Points', 'PP_percent','Off-Night']].sort_values(['Points','Off-Night','PP_percent','Goals','Shots'],ascending=False)
 
         df_dated_score_group_table.columns = ['Player','Team' ,'Position', 'Roster%', 'GP', 'TOI/GP',
-            'Goals/GP', 'ixG/GP','Assists/GP', 'Points/GP', 'Shots/GP', 'PPP/GP', 'PP%']
+            'Goals/GP', 'ixG/GP','Assists/GP', 'Points/GP', 'Shots/GP', 'PPP/GP', 'PP%','Off-Night']
 
-        return df_dated_score_group_table[df_dated_score_group_table.Position == 'D'].head(input.max_head()).style.background_gradient(cmap=cmap_off, subset=['Points/GP']).background_gradient(cmap=cmap_total, subset=['Roster%']).hide_index().set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
+        return df_dated_score_group_table[df_dated_score_group_table.Position == 'D'].head(input.max_head()) \
+        .style.background_gradient(cmap=cmap_off, subset=['Points/GP']) \
+        .background_gradient(cmap=cmap_total, subset=['Roster%']) \
+        .background_gradient(cmap=cmap_off, subset=['Off-Night'],vmin=0,vmax=df_dated_score_group_table['Off-Night'].max()) \
+        .hide_index().set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
         .set_table_styles([{
             'selector': 'caption',
             'props': [
@@ -1051,18 +1058,24 @@ def server(input, output, session):
         df_dated_bangers_group[df_dated_bangers_group.columns[1:]] = df_dated_bangers_group[df_dated_bangers_group.columns[1:]].divide(df_dated_bangers_group.GP,axis=0)
         #df_dated_bangers_group['PP_percent'] = df_dated_bangers_group.PP_toi / df_dated_bangers_group.team_pp
         df_dated_bangers_group = df_dated_bangers_group.reset_index()
+        df_dated_bangers_group = df_dated_bangers_group.merge(test_df[['Team','Off-Night']],left_on=['Team'],right_on=['Team'])
         df_dated_bangers_group = df_dated_bangers_group[(df_dated_bangers_group.Team.isin(team_top))&(df_dated_bangers_group.percent_owned <= .50 )]
         df_dated_bangers_group['TOI'] = ["%d:%02d" % (int(x),(x*60)%60) for x in df_dated_bangers_group['TOI'].astype(float)]
         df_dated_bangers_group_table = df_dated_bangers_group[['Player','Team' ,'position', 'percent_owned', 'GP', 'TOI',
-            'Goals', 'Assists', 'Points', 'Shots', 'Hits', 'Blocks','S_H_B']].sort_values(['S_H_B','Shots','Hits','Blocks','Points'],ascending=False)
+            'Goals', 'Assists', 'Points', 'Shots', 'Hits', 'Blocks','S_H_B','Off-Night']].sort_values(['S_H_B','Off-Night','Shots','Hits','Blocks','Points'],ascending=False)
             
         df_dated_bangers_group_table.columns = ['Player','Team' ,'Position', 'Roster%', 'GP', 'TOI/GP',
-            'Goals/GP', 'Assists/GP', 'Points/GP', 'Shots/GP', 'Hits/GP', 'Blocks/GP','S+H+B/GP']
+            'Goals/GP', 'Assists/GP', 'Points/GP', 'Shots/GP', 'Hits/GP', 'Blocks/GP','S+H+B/GP','Off-Night']
 
         #df_dated_bangers_group_table.head(15)
 
-        return df_dated_bangers_group_table[df_dated_bangers_group_table.Position != 'D'].head(input.max_head()).style.background_gradient(cmap=cmap_off, subset=['S+H+B/GP']).background_gradient(cmap=cmap_total, subset=['Roster%']).hide_index().set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
-        .set_table_styles([{
+        return df_dated_bangers_group_table[df_dated_bangers_group_table.Position != 'D'] \
+            .head(input.max_head()).style.background_gradient(cmap=cmap_off, subset=['S+H+B/GP'])\
+            .background_gradient(cmap=cmap_total, subset=['Roster%'])\
+            .background_gradient(cmap=cmap_off, subset=['Off-Night'],vmin=0,vmax=df_dated_bangers_group_table['Off-Night'].max())\
+            .hide_index()\
+            .set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
+            .set_table_styles([{
             'selector': 'caption',
             'props': [
                 ('color', ''),
@@ -1185,18 +1198,24 @@ def server(input, output, session):
         df_dated_bangers_group[df_dated_bangers_group.columns[1:]] = df_dated_bangers_group[df_dated_bangers_group.columns[1:]].divide(df_dated_bangers_group.GP,axis=0)
         #df_dated_bangers_group['PP_percent'] = df_dated_bangers_group.PP_toi / df_dated_bangers_group.team_pp
         df_dated_bangers_group = df_dated_bangers_group.reset_index()
+        df_dated_bangers_group = df_dated_bangers_group.merge(test_df[['Team','Off-Night']],left_on=['Team'],right_on=['Team'])
         df_dated_bangers_group = df_dated_bangers_group[(df_dated_bangers_group.Team.isin(team_top))&(df_dated_bangers_group.percent_owned <= .50 )]
         df_dated_bangers_group['TOI'] = ["%d:%02d" % (int(x),(x*60)%60) for x in df_dated_bangers_group['TOI'].astype(float)]
         df_dated_bangers_group_table = df_dated_bangers_group[['Player','Team' ,'position', 'percent_owned', 'GP', 'TOI',
-            'Goals', 'Assists', 'Points', 'Shots', 'Hits', 'Blocks','S_H_B']].sort_values(['S_H_B','Shots','Hits','Blocks','Points'],ascending=False)
+            'Goals', 'Assists', 'Points', 'Shots', 'Hits', 'Blocks','S_H_B','Off-Night']].sort_values(['S_H_B','Off-Night','Shots','Hits','Blocks','Points'],ascending=False)
             
         df_dated_bangers_group_table.columns = ['Player','Team' ,'Position', 'Roster%', 'GP', 'TOI/GP',
-            'Goals/GP', 'Assists/GP', 'Points/GP', 'Shots/GP', 'Hits/GP', 'Blocks/GP','S+H+B/GP']
+            'Goals/GP', 'Assists/GP', 'Points/GP', 'Shots/GP', 'Hits/GP', 'Blocks/GP','S+H+B/GP','Off-Night']
 
         #df_dated_bangers_group_table.head(15)
 
-        return df_dated_bangers_group_table[df_dated_bangers_group_table.Position == 'D'].head(input.max_head()).style.background_gradient(cmap=cmap_off, subset=['S+H+B/GP']).background_gradient(cmap=cmap_total, subset=['Roster%']).hide_index().set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
-        .set_table_styles([{
+        return df_dated_bangers_group_table[df_dated_bangers_group_table.Position == 'D']\
+            .head(input.max_head()).style.background_gradient(cmap=cmap_off, subset=['S+H+B/GP'])\
+            .background_gradient(cmap=cmap_total, subset=['Roster%'])\
+            .background_gradient(cmap=cmap_off, subset=['Off-Night'],vmin=0,vmax=df_dated_bangers_group_table['Off-Night'].max())\
+            .hide_index()\
+            .set_properties(**{'Height': '12px'},**{'text-align': 'center'})\
+            .set_table_styles([{
             'selector': 'caption',
             'props': [
                 ('color', ''),
@@ -1214,9 +1233,6 @@ def server(input, output, session):
                     **{'min-width':'50px'},subset = ((df_dated_bangers_group_table.columns[1:])),overwrite=False)
 
 
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