Update app.py

app.py

@@ -106,39 +106,35 @@ def create_stats_html():
         type_dist['model_type'] = type_dist['model_type'].str.capitalize()
         
         # Create bar chart with better formatting
-        fig_types = go.Figure()
-        
-        # Add bars
-        fig_types.add_trace(go.Bar(
-            x=type_dist['model_type'],
-            y=type_dist['downloads_30d'],
-            text=type_dist['downloads_30d'].apply(format_number),
-            textposition='outside',
-        ))
+        fig_types = px.bar(
+            type_dist, 
+            x='model_type',    # x-axis: model types
+            y='downloads_30d', # y-axis: number of downloads
+            title='Downloads by Model Type',
+            labels={'downloads_30d': 'Downloads', 'model_type': 'Model Type'},
+            text=type_dist['downloads_30d'].apply(format_number)
+        )
         
-        # Update layout
+        # Update layout for log scale and better appearance
         fig_types.update_layout(
-            title='Downloads by Model Type',
-            yaxis_type="log",  # Set y-axis to log scale
             yaxis=dict(
-                title="Downloads",
                 type='log',
-                dtick=1,  # This controls the tick spacing
-                tickformat=".1s"  # Format ticks with K, M suffix
-            ),
-            xaxis=dict(
-                title="Model Type"
+                title='Downloads (log scale)'
             ),
-            plot_bgcolor='white',
-            bargap=0.3,
-            height=600,
             showlegend=False,
-            margin=dict(t=100, b=50)  # Add margin for labels
+            plot_bgcolor='white',
+            height=500,
+            width=800
+        )
+        
+        # Update bars and text
+        fig_types.update_traces(
+            textposition='outside',
+            cliponaxis=False
         )
         
     else:
-        # Create empty figure if no data
-        fig_types = go.Figure()
+        fig_types = px.bar(title='No data available')
     
     # Create top models table
     if len(derivative_df) > 0: