small reorg

app.py

@@ -104,6 +104,20 @@ def format_dataframe(df, show_percentage=False, selected_groups=None, compact_vi
 
         display_df['model_name'] = df.apply(add_model_symbols, axis=1)
 
+    # Format training_set column for clean display
+    if 'training_set' in display_df.columns:
+        def format_training_set(val):
+            if val is None or (isinstance(val, float) and np.isnan(val)):
+                return ''
+            val = str(val).strip()
+            if val in ('[]', '', 'nan', 'None'):
+                return ''
+            # Strip brackets and quotes for list-like strings
+            val = val.strip('[]')
+            val = val.replace("'", "").replace('"', '')
+            return val
+        display_df['training_set'] = display_df['training_set'].apply(format_training_set)
+
     # Convert count-based metrics to percentages if requested
     if show_percentage and 'n_structures' in df.columns:
         n_structures = df['n_structures']
@@ -353,6 +367,7 @@ Generative machine learning models hold great promise for accelerating materials
                             value="Descending",
                             label="Sort Direction"
                         )
+                    with gr.Column(scale=1):
                         training_set_filter = gr.Dropdown(
                             choices=["All"] + TRAINING_DATASETS,
                             value="All",