Update app.py

app.py

@@ -223,21 +223,25 @@ if fetch_data:
             return pd.isna(value) or value in ["", "N/A", "null", None]
         
         if not metadata_df.empty:
-            # Incomplete record detection
-            incomplete_mask = metadata_df.apply(lambda row: row.map(is_incomplete), axis=1).any(axis=1)
-            incomplete_count = incomplete_mask.sum()
-        
-            # Overall completeness
-            total_fields = metadata_df.size
-            filled_fields = metadata_df.apply(lambda row: row.map(lambda x: not is_incomplete(x)), axis=1).sum().sum()
-            overall_percent = (filled_fields / total_fields) * 100
-        
-            # Field-by-field completeness
-            completeness = metadata_df.map(lambda x: not is_incomplete(x)).mean() * 100
-            completeness_table = completeness.round(1).to_frame(name="Completeness (%)")
-        
-            # Render stats summary in sidebar
+        ...
+            stats_html = f"""
+            <div class="sidebar-stats">
+                <h3 style="color: lightgray;">📊 Quick Stats</h3>
+                <p style="color:lightgray;">Total Records: <b>{len(metadata_df)}</b></p>
+                <p style="color:lightgray;">Incomplete Records: <b>{incomplete_count}</b></p>
+                <p style="color:lightgray;">Overall Metadata Completeness: <b>{overall_percent:.1f}%</b></p>
+            </div>
+            """
             stats_placeholder.markdown(stats_html, unsafe_allow_html=True)
+    
+            # ✅ Then show this right after
+            with st.sidebar.expander("📊 Field Completeness Breakdown", expanded=True):
+                st.dataframe(
+                    completeness_table.style.background_gradient(cmap="Greens").format("{:.1f}%"),
+                    use_container_width=True,
+                    height=240
+                )
+
 
             # Render collapsible green completeness table in sidebar
             with st.sidebar.expander("📊 Field Completeness Breakdown", expanded=True):