diff --git a/03_quant_report.script.py b/03_quant_report.script.py
index bef3975..ea0f1ca 100644
--- a/03_quant_report.script.py
+++ b/03_quant_report.script.py
@@ -257,17 +257,17 @@ mo.md(r"""
 """)
 
 # %%
-_pairwise_df, _meta = S.compute_ranking_significance(char_rank)
+# _pairwise_df, _meta = S.compute_ranking_significance(char_rank)
 
-# print(_pairwise_df.columns)
+# # print(_pairwise_df.columns)
 
-mo.md(f"""
+# mo.md(f"""
 
 
-{mo.ui.altair_chart(S.plot_significance_heatmap(_pairwise_df, metadata=_meta))}
+# {mo.ui.altair_chart(S.plot_significance_heatmap(_pairwise_df, metadata=_meta))}
 
-{mo.ui.altair_chart(S.plot_significance_summary(_pairwise_df, metadata=_meta))}
-""")
+# {mo.ui.altair_chart(S.plot_significance_summary(_pairwise_df, metadata=_meta))}
+# """)
 
 # %%
 mo.md(r"""
@@ -463,34 +463,34 @@ mo.md(r"""
 
 # %%
 # Compute pairwise significance tests
-pairwise_df, metadata = S.compute_pairwise_significance(
-    voice_1_10,
-    test_type="mannwhitney",  # or "ttest", "chi2", "auto"
-    alpha=0.05,
-    correction="bonferroni"   # or "holm", "none"
-)
+# pairwise_df, metadata = S.compute_pairwise_significance(
+#     voice_1_10,
+#     test_type="mannwhitney",  # or "ttest", "chi2", "auto"
+#     alpha=0.05,
+#     correction="bonferroni"   # or "holm", "none"
+# )
 
-# View significant pairs
-# print(pairwise_df.filter(pl.col('significant') == True))
+# # View significant pairs
+# # print(pairwise_df.filter(pl.col('significant') == True))
 
-# Create heatmap visualization
-_heatmap = S.plot_significance_heatmap(
-    pairwise_df, 
-    metadata=metadata,
-    title="Voice Rating Significance<br>(Pairwise Comparisons)"
-)
+# # Create heatmap visualization
+# _heatmap = S.plot_significance_heatmap(
+#     pairwise_df, 
+#     metadata=metadata,
+#     title="Voice Rating Significance<br>(Pairwise Comparisons)"
+# )
 
-# Create summary bar chart
-_summary = S.plot_significance_summary(
-    pairwise_df,
-    metadata=metadata
-)
+# # Create summary bar chart
+# _summary = S.plot_significance_summary(
+#     pairwise_df,
+#     metadata=metadata
+# )
 
-mo.md(f"""
-{mo.ui.altair_chart(_heatmap)}
+# mo.md(f"""
+# {mo.ui.altair_chart(_heatmap)}
 
-{mo.ui.altair_chart(_summary)}
-""")
+# {mo.ui.altair_chart(_summary)}
+# """)
 
 # %%
 
diff --git a/plots.py b/plots.py
index 76cb41f..2321c68 100644
--- a/plots.py
+++ b/plots.py
@@ -1305,6 +1305,16 @@ class QualtricsPlotsMixin:
         # Create frequency dictionary
         trait_freq = Counter(traits_list)
         
+        # Handle empty data gracefully - return empty figure with message
+        if not trait_freq:
+            fig, ax = plt.subplots(figsize=(width/100, height/100), dpi=100)
+            ax.text(0.5, 0.5, "No trait data available for current filter", 
+                    ha='center', va='center', fontsize=14, color='gray',
+                    transform=ax.transAxes)
+            ax.axis('off')
+            ax.set_title(title, fontsize=16, pad=20, color=ColorPalette.TEXT)
+            return fig
+        
         # Set random seed for color selection
         random.seed(random_state)
         
@@ -1335,7 +1345,15 @@ class QualtricsPlotsMixin:
         fig, ax = plt.subplots(figsize=(width/100, height/100), dpi=100)
         ax.imshow(wordcloud, interpolation='bilinear')
         ax.axis('off')
-        ax.set_title(title, fontsize=16, pad=20, color=ColorPalette.TEXT)
+        
+        # Add title with filter subtitle (similar to _add_filter_footnote for Altair charts)
+        filter_text = self._get_filter_description()
+        if filter_text:
+            # Title on top, filter subtitle below in light grey
+            fig.suptitle(title, fontsize=16, y=0.98, color=ColorPalette.TEXT)
+            ax.set_title(filter_text, fontsize=10, pad=10, color='lightgrey', loc='left')
+        else:
+            ax.set_title(title, fontsize=16, pad=20, color=ColorPalette.TEXT)
         
         plt.tight_layout(pad=0)