Change category distribution from table to horizontal bar plot

- Replace DataFrame with BarPlot component for category distribution
- Display categories on y-axis with count bars extending horizontally
- Cleaner visualization of classification results

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

app.py

@@ -556,18 +556,16 @@ is the key and a 1 if the category is present and a 0 if not.'''
             python_version=python_version
         )
 
-        # Build distribution summary DataFrame for display
+        # Build distribution summary DataFrame for bar plot
         dist_data = []
         total_rows = len(result)
         for i, cat in enumerate(categories, 1):
             col_name = f"category_{i}"
             if col_name in result.columns:
                 count = int(result[col_name].sum())
-                pct = (count / total_rows) * 100 if total_rows > 0 else 0
                 dist_data.append({
                     "Category": cat,
-                    "Count": count,
-                    "Percentage": f"{pct:.1f}%"
+                    "Count": count
                 })
         distribution_df = pd.DataFrame(dist_data)
 
@@ -627,7 +625,7 @@ def reset_all():
         "",  # api_key
         "**Free tier** - no API key required! We cover the cost while CatLLM is in review.",  # api_key_status
         "Ready to classify",  # status
-        gr.update(value=None, visible=False),  # distribution_df
+        gr.update(value=None, visible=False),  # distribution_plot
         gr.update(value=None, visible=False),  # sample_results
         gr.update(value=None, visible=False),  # results
         None,  # download_file
@@ -793,7 +791,13 @@ https://github.com/chrissoria/cat-llm
 
         with gr.Column():
             status = gr.Markdown("Ready to classify")
-            distribution_df = gr.DataFrame(label="Category Distribution Summary", visible=False)
+            distribution_plot = gr.BarPlot(
+                x="Count",
+                y="Category",
+                title="Category Distribution",
+                horizontal=True,
+                visible=False
+            )
             sample_results = gr.DataFrame(label="Sample Results (First 5 Rows)", visible=False)
             results = gr.DataFrame(label="Full Classification Results", visible=False)
             download_file = gr.File(label="Download Results (CSV + Codebook PDF)", file_count="multiple")
@@ -840,7 +844,7 @@ https://github.com/chrissoria/cat-llm
     classify_btn.click(
         fn=classify_data,
         inputs=[spreadsheet_file, spreadsheet_column] + category_inputs + [model_tier, model, model_source, api_key],
-        outputs=[distribution_df, sample_results, results, download_file, status]
+        outputs=[distribution_plot, sample_results, results, download_file, status]
     )
 
     see_code_btn.click(
@@ -852,7 +856,7 @@ https://github.com/chrissoria/cat-llm
     reset_btn.click(
         fn=reset_all,
         inputs=[],
-        outputs=[spreadsheet_file, spreadsheet_column] + category_inputs + [add_category_btn, category_count, model_tier, model, model_source, api_key, api_key_status, status, distribution_df, sample_results, results, download_file, code_output]
+        outputs=[spreadsheet_file, spreadsheet_column] + category_inputs + [add_category_btn, category_count, model_tier, model, model_source, api_key, api_key_status, status, distribution_plot, sample_results, results, download_file, code_output]
     )