Update app.py

app.py

@@ -112,7 +112,7 @@ schedule_df['home_sym'] = 'vs'
 
 
 #if not os.path.isfile('standings/standings_'+str(date.today())+'.csv'):   
-standings_df_old = pd.read_html('https://www.hockey-reference.com/leagues/NHL_2023_standings.html')[0].append(pd.read_html('https://www.hockey-reference.com/leagues/NHL_2023_standings.html')[1])
+standings_df_old = pd.read_html('https://www.hockey-reference.com/leagues/NHL_2024_standings.html')[0].append(pd.read_html('https://www.hockey-reference.com/leagues/NHL_2024_standings.html')[1])
 #    standings_df_old.to_csv('standings/standings_'+str(date.today())+'.csv')
 #standings_df_old = pd.read_csv('standings/standings_'+str(date.today())+'.csv',index_col=[0])
 
@@ -163,15 +163,23 @@ schedule_stack['home_b2b'] = home_b2b
 
 schedule_stack['away_b2b'] = schedule_stack['away_b2b'].replace(1,' 😴')
 schedule_stack['away_b2b'] = schedule_stack['away_b2b'].replace(0,'')
+
+schedule_stack['offnight_score'] = schedule_stack.groupby('date').team.transform('count')
+print('we made it',schedule_stack.offnight_score.max())
+schedule_stack.offnight_score = schedule_stack.offnight_score - 16
+#schedule_stack.loc[schedule_stack['offnight_score'] > 0,'offnight_score'] = 0
+schedule_stack.offnight_score = -1*schedule_stack.offnight_score
+#print(schedule_stack.offnight_score.max())
 schedule_stack.head()
 
 FontProperties(fname='/System/Library/Fonts/Apple Color Emoji.ttc')
+
 try: 
-    data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=3000;sort=rank_season;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
+    data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=3000;sort=percent_owned;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
     key_check = data_r['fantasy_content']['league']['players']
 
 except KeyError:
-    data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=1151;sort=rank_season;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
+    data_r = requests.get("https://pub-api-ro.fantasysports.yahoo.com/fantasy/v2/league/427.l.public;out=settings/players;position=ALL;start=0;count=1151;sort=percent_owned;search=;out=percent_owned;out=auction_values,ranks;ranks=season;ranks_by_position=season;out=expert_ranks;expert_ranks.rank_type=projected_season_remaining/draft_analysis;cut_types=diamond;slices=last7days?format=json_f").json()
     print('key_checked')
 
 total_list = []
@@ -195,7 +203,6 @@ for x in data_r['fantasy_content']['league']['players']:
         single_list.append(0)
     total_list.append(single_list)
 
-
 df_2023 = pd.DataFrame(data=total_list,columns=['player_id','rank_value','full','first','last','average_pick', 'average_cost','display_position','projected_auction_value','editorial_team_abbr','percent_owned'])
 
 week_dict = yahoo_weeks.set_index('Number')['Week'].sort_index().to_dict()
@@ -216,7 +223,11 @@ import matplotlib.image as mpimg
 #     ui.panel_main(ui.output_plot("plot",height = "750px",width="1250px")),
 #     #ui.download_button('test','Download'),
 # )
-app_ui = ui.page_fluid(ui.layout_sidebar(
+import shinyswatch
+app_ui = ui.page_fluid(
+    #shinyswatch.theme.cosmo(),
+    ui.layout_sidebar(
+    
     # Available themes:
     #  cerulean, cosmo, cyborg, darkly, flatly, journal, litera, lumen, lux,
     #  materia, minty, morph, pulse, quartz, sandstone, simplex, sketchy, slate,
@@ -367,7 +378,8 @@ def server(input, output, session):
         test_df = pd.DataFrame()
         test_df['Team'] = list(team_abv['team_abv'])
         test_df['Total'] = test_df.merge(right=weekly_stack.groupby('team_abv')['team_abv'].apply(lambda x: x[x != ''].count()),left_on=['Team'],right_index=True,how='left').fillna(0)['team_abv']
-        test_df['Off-Night'] = test_df.merge(right=weekly_stack.groupby('team_abv').sum()['offnight'],left_on=['Team'],right_index=True,how='left').fillna(0)['offnight']
+
+        test_df['Off-Night'] = test_df.merge(right=weekly_stack.groupby('team_abv').sum()['offnight_score'],left_on=['Team'],right_index=True,how='left').fillna(0)['offnight_score']
         test_df['B2B']= test_df.merge(right=weekly_stack.groupby('team_abv').sum()['b2b'],left_on=['Team'],right_index=True,how='left').fillna(0)['b2b']
 
 
@@ -380,12 +392,14 @@ def server(input, output, session):
 
         games_vs_tired = 0.4*np.array(test_df.merge(right=weekly_stack.groupby('team_abv')['away_b2b'].apply(lambda x: x[x != ''].count()),left_on=['Team'],right_index=True,how='left').fillna(0)['away_b2b'])
 
-
-        team_score = test_df['Total']+test_df['Off-Night']*0.5+test_df['B2B']*-0.2+games_vs_tired*0.3+gf_rank*0.1+ga_rank*0.1
-
+        print('test_df')
+        print(test_df)
+        #team_score = test_df['Total']+test_df['Off-Night']*0.5+test_df['B2B']*-0.2+games_vs_tired*0.3+gf_rank*0.1+ga_rank*0.1
+        team_score = test_df['Total']+test_df['Off-Night']*0.03+test_df['B2B']*-0.2+games_vs_tired*0.3+gf_rank*0.1+ga_rank*0.1
         test_df['Score'] = team_score
 
-
+        test_df['Off-Night'] = test_df.merge(right=weekly_stack.groupby('team_abv').sum()['offnight'],left_on=['Team'],right_index=True,how='left').fillna(0)['offnight']
+        
         cols = test_df.columns.tolist();
         L = len(cols) 
         test_df = test_df[cols[4:]+cols[0:4]]