Update app.py

app.py

@@ -721,7 +721,8 @@ with st.sidebar:
             # Create a mapping from username to Spaces and Models rankings
             spaces_rank = {owner: idx+1 for idx, (owner, _) in enumerate(top_owners_spaces)}
             models_rank = {owner: idx+1 for idx, (owner, _) in enumerate(top_owners_models)}
-
+            
+            # Create the overall ranking dataframe with trophies for top 3
             overall_data = []
             for idx, username in enumerate(trending_accounts[:100]):
                 # Add trophy emojis for top 3
@@ -729,21 +730,20 @@ with st.sidebar:
                 if idx == 0:
                     rank_display = "🏆 "  # Gold trophy for 1st place
                 elif idx == 1:
-                    rank_display = "🥈 "  # Silver trophy for 2nd place
+                    rank_display = "🏆 "  # Silver trophy for 2nd place
                 elif idx == 2:
-                    rank_display = "🥉 "  # Bronze trophy for 3rd place
-    
+                    rank_display = "🏆 "  # Bronze trophy for 3rd place
+                
+                # Use strings for all rankings to avoid type conversion issues
                 spaces_position = str(spaces_rank.get(username, "-"))
                 models_position = str(models_rank.get(username, "-"))
                 overall_data.append([f"{rank_display}{username}", spaces_position, models_position])
-
+            
             ranking_data_overall = pd.DataFrame(
                 overall_data, 
                 columns=["Contributor", "Spaces Rank", "Models Rank"]
             )
             ranking_data_overall.index = ranking_data_overall.index + 1  # Start index from 1 for ranking
-
-
             
             st.dataframe(
                 ranking_data_overall,
@@ -760,9 +760,22 @@ with st.sidebar:
         # Show trending accounts by Spaces & Models
         st.markdown('<div class="subheader"><h3>🚀 Spaces Leaders</h3></div>', unsafe_allow_html=True)
         
-        # Create a data frame for the table
+        # Create a data frame for the Spaces table with medals for top 3
         if top_owners_spaces:
-            ranking_data_spaces = pd.DataFrame(top_owners_spaces[:50], columns=["Contributor", "Spaces Count"])
+            spaces_data = []
+            for idx, (owner, count) in enumerate(top_owners_spaces[:50]):
+                # Add medal emojis for top 3
+                rank_display = ""
+                if idx == 0:
+                    rank_display = "🥇 "  # Gold medal for 1st place
+                elif idx == 1:
+                    rank_display = "🥈 "  # Silver medal for 2nd place
+                elif idx == 2:
+                    rank_display = "🥉 "  # Bronze medal for 3rd place
+                
+                spaces_data.append([f"{rank_display}{owner}", count])
+            
+            ranking_data_spaces = pd.DataFrame(spaces_data, columns=["Contributor", "Spaces Count"])
             ranking_data_spaces.index = ranking_data_spaces.index + 1  # Start index from 1 for ranking
             
             st.dataframe(
@@ -775,12 +788,25 @@ with st.sidebar:
                 hide_index=False
             )
         
-        # Display the top Models accounts list
+        # Display the top Models accounts list with medals for top 3
         st.markdown('<div class="subheader"><h3>🧠 Models Leaders</h3></div>', unsafe_allow_html=True)
         
-        # Create a data frame for the Models table
+        # Create a data frame for the Models table with medals for top 3
         if top_owners_models:
-            ranking_data_models = pd.DataFrame(top_owners_models[:50], columns=["Contributor", "Models Count"])
+            models_data = []
+            for idx, (owner, count) in enumerate(top_owners_models[:50]):
+                # Add medal emojis for top 3
+                rank_display = ""
+                if idx == 0:
+                    rank_display = "🥇 "  # Gold medal for 1st place
+                elif idx == 1:
+                    rank_display = "🥈 "  # Silver medal for 2nd place
+                elif idx == 2:
+                    rank_display = "🥉 "  # Bronze medal for 3rd place
+                
+                models_data.append([f"{rank_display}{owner}", count])
+            
+            ranking_data_models = pd.DataFrame(models_data, columns=["Contributor", "Models Count"])
             ranking_data_models.index = ranking_data_models.index + 1  # Start index from 1 for ranking
             
             st.dataframe(
@@ -1150,4 +1176,4 @@ else:
               f'<img src="https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.svg" style="width: 200px; margin-bottom: 30px;">'
               f'<h2>Welcome to Hugging Face Contributions Dashboard</h2>'
               f'<p style="font-size: 1.2rem;">Please select a contributor from the sidebar to view their activity.</p>'
-              f'</div>', unsafe_allow_html=True)            
+              f'</div>', unsafe_allow_html=True)