Update main.py

main.py

@@ -573,8 +573,7 @@ def get_team_standings_brscraper(year):
         logging.info(f"Scraping team standings for {year} (cache stale or not found).")
         df = _scrape_team_standings_brscraper(year)
         if not df.empty:
-            # Apply clean_df_for_firebase before saving to cache
-            df_cleaned_for_firebase = clean_df_for_firebase(df.copy()) # Use a copy to avoid modifying original df if it's used later
+            df_cleaned_for_firebase = clean_df_for_firebase(df.copy())
             db_ref.set({
                 'last_updated': datetime.utcnow().isoformat(),
                 'data': df_cleaned_for_firebase.to_dict(orient='records')
@@ -729,6 +728,8 @@ def get_dashboard_info_brscraper():
         logging.info("Scraping dashboard info (cache stale or not found).")
         data = _scrape_dashboard_info_brscraper()
         if data:
+            # Apply clean_df_for_firebase to the dataframes before saving to cache
+            # This is done inside _scrape_dashboard_info_brscraper now
             db_ref.set({
                 'last_updated': datetime.utcnow().isoformat(),
                 'data': data
@@ -741,6 +742,13 @@ def _scrape_dashboard_info_brscraper():
     try:
         mvp_2025_df = nba.get_award_votings('mvp', 2025)
         if not mvp_2025_df.empty:
+            # Rename 'Share' to 'Votes' for frontend consistency
+            if 'Share' in mvp_2025_df.columns:
+                mvp_2025_df = mvp_2025_df.rename(columns={'Share': 'Votes'})
+            # Ensure 'Votes' is numeric, convert percentage strings if necessary
+            if 'Votes' in mvp_2025_df.columns:
+                mvp_2025_df['Votes'] = mvp_2025_df['Votes'].astype(str).str.replace('%', '').astype(float) * 100 # Convert share to percentage points
+            
             mvp_2025_df = clean_df_for_firebase(mvp_2025_df)
             dashboard_data['mvp_2025_votings'] = mvp_2025_df.replace({np.nan: None}).to_dict(orient='records')
         else:
@@ -749,6 +757,16 @@ def _scrape_dashboard_info_brscraper():
 
         east_probs_df = nba.get_playoffs_probs('east')
         if not east_probs_df.empty:
+            # Rename the team column to 'Team' for consistency
+            if 'Eastern Conference' in east_probs_df.columns: # BRScraper might return this
+                east_probs_df = east_probs_df.rename(columns={'Eastern Conference': 'Team'})
+            elif 'Tm' in east_probs_df.columns: # Or this
+                east_probs_df = east_probs_df.rename(columns={'Tm': 'Team'})
+            
+            # Clean team names (remove playoff seeds)
+            if 'Team' in east_probs_df.columns:
+                east_probs_df['Team'] = east_probs_df['Team'].astype(str).apply(clean_team_name)
+
             east_probs_df = clean_df_for_firebase(east_probs_df)
             dashboard_data['playoff_probs_east'] = east_probs_df.replace({np.nan: None}).to_dict(orient='records')
         else:
@@ -757,6 +775,16 @@ def _scrape_dashboard_info_brscraper():
 
         west_probs_df = nba.get_playoffs_probs('west')
         if not west_probs_df.empty:
+            # Rename the team column to 'Team' for consistency
+            if 'Western Conference' in west_probs_df.columns: # BRScraper might return this
+                west_probs_df = west_probs_df.rename(columns={'Western Conference': 'Team'})
+            elif 'Tm' in west_probs_df.columns: # Or this
+                west_probs_df = west_probs_df.rename(columns={'Tm': 'Team'})
+
+            # Clean team names (remove playoff seeds)
+            if 'Team' in west_probs_df.columns:
+                west_probs_df['Team'] = west_probs_df['Team'].astype(str).apply(clean_team_name)
+
             west_probs_df = clean_df_for_firebase(west_probs_df)
             dashboard_data['playoff_probs_west'] = west_probs_df.replace({np.nan: None}).to_dict(orient='records')
         else: