Update app.py

app.py

@@ -1506,33 +1506,45 @@ def update_grid_rows(*args):
     if not show_na_filter:
         if active_preset == 'Writing':
             filtered_df.dropna(subset=['Writing ✍️'], inplace=True)
+        if active_preset == 'Politics':
+            filtered_df = filtered_df[filtered_df['Political Lean 📋'] != -99999]
 
     # 6. Apply context-aware "NA Models" filter
     if show_na_filter:
-        all_selections = set(uncensored_cols + intelligence_cols + writing_cols + politics_cols)
         if active_preset == 'Overview':
-             all_selections.update(PRESET_COLUMNS['Overview'].keys())
-
-        is_writing_visible = 'Writing ✍️' in all_selections
-        is_politics_visible = 'Political Lean 📋' in all_selections
-        # Now correctly checks if the "World Model Tests" checkbox is ticked
-        is_pred_reasoning_visible = 'world_model_group' in intelligence_cols
-        
-        na_conditions = []
-        if is_writing_visible:
-            na_conditions.append(filtered_df['Writing ✍️'].isna())
-        if is_pred_reasoning_visible:
-            na_conditions.append(filtered_df['Show Rec Score'] == -99999)
-        if is_politics_visible:
-            na_conditions.append(filtered_df['Political Lean 📋'].isna())
-
-        if na_conditions:
-            final_na_mask = pd.Series(False, index=filtered_df.index)
-            for condition in na_conditions:
-                final_na_mask |= condition
-            filtered_df = filtered_df[final_na_mask]
+            # Special logic for Overview: show rows if EITHER Writing OR Politics is NA
+            writing_na_mask = filtered_df['Writing ✍️'].isna()
+            politics_na_mask = filtered_df['Political Lean 📋'] == -99999
+            filtered_df = filtered_df[writing_na_mask | politics_na_mask]
+            
+        elif active_preset == 'Politics':
+            # Special logic for Politics: ONLY show rows where Political Lean is NA
+            filtered_df = filtered_df[filtered_df['Political Lean 📋'] == -99999]
+            
         else:
-            filtered_df = filtered_df.iloc[0:0]
+            # Existing logic for all other presets (Uncensored, Intelligence, Writing)
+            all_selections = set(uncensored_cols + intelligence_cols + writing_cols + politics_cols)
+            
+            is_writing_visible = 'Writing ✍️' in all_selections
+            is_politics_visible = 'Political Lean 📋' in all_selections
+            is_pred_reasoning_visible = 'world_model_group' in intelligence_cols
+            
+            na_conditions = []
+            if is_writing_visible:
+                na_conditions.append(filtered_df['Writing ✍️'].isna())
+            if is_pred_reasoning_visible:
+                na_conditions.append(filtered_df['Show Rec Score'] == -99999)
+            if is_politics_visible:
+                na_conditions.append(filtered_df['Political Lean 📋'] == -99999)
+
+            if na_conditions:
+                final_na_mask = pd.Series(False, index=filtered_df.index)
+                for condition in na_conditions:
+                    final_na_mask |= condition
+                filtered_df = filtered_df[final_na_mask]
+            else:
+                # If no NA-able columns are selected, show nothing.
+                filtered_df = filtered_df.iloc[0:0]
 
     return filtered_df.to_dict('records')