Update app.py

app.py

@@ -84,11 +84,22 @@ def create_sentiment_distribution_chart(df):
 
 # Visualization for Correlation between Sentiment and Discrimination
 def create_sentiment_discrimination_grouped_chart(df):
-    crosstab_df = pd.crosstab(df['Sentiment'], df['Discrimination']).reset_index()
-    melted_df = pd.melt(crosstab_df, id_vars='Sentiment', value_vars=['Yes', 'No'], var_name='Discrimination', value_name='Count')
-    fig = px.bar(melted_df, x='Sentiment', y='Count', color='Discrimination', barmode='group', title="Sentiment vs. Discrimination")
-    fig.update_layout(margin=dict(l=20, r=20, t=40, b=20), xaxis_title="Sentiment", yaxis_title="Count", font=dict(size=12))
-    return fig
+    # Creating a crosstab of 'Sentiment' and 'Discrimination'
+    crosstab_df = pd.crosstab(df['Sentiment'], df['Discrimination'])
+    
+    # Check if 'Yes' and 'No' are in the columns after the crosstab operation
+    value_vars = crosstab_df.columns.intersection(['Yes', 'No']).tolist()
+    
+    # If 'No' is not in columns, it will not be included in melting
+    melted_df = pd.melt(crosstab_df.reset_index(), id_vars='Sentiment', value_vars=value_vars, var_name='Discrimination', value_name='Count')
+    
+    # Proceeding to plot only if we have data to plot
+    if not melted_df.empty:
+        fig = px.bar(melted_df, x='Sentiment', y='Count', color='Discrimination', barmode='group', title="Sentiment vs. Discrimination")
+        fig.update_layout(margin=dict(l=20, r=20, t=40, b=20), xaxis_title="Sentiment", yaxis_title="Count", font=dict(size=12))
+        return fig
+    else:
+        return "No data to display for the selected filters."
 
 # Function for Top Domains with Negative Sentiment Chart
 def create_top_negative_sentiment_domains_chart(df):
@@ -161,7 +172,11 @@ def render_dashboard(page, df_filtered):
         with col3:
             st.plotly_chart(create_sentiment_distribution_chart(df_filtered))
         with col4:
-            st.plotly_chart(create_sentiment_discrimination_grouped_chart(df_filtered))
+            chart = create_sentiment_discrimination_grouped_chart(df_filtered)
+            if isinstance(chart, str):
+                st.write(chart)
+            else:
+                st.plotly_chart(chart)
 
     elif page == "Sentiment Analysis":
         st.title("Sentiment Analysis Dashboard")
@@ -191,5 +206,6 @@ def render_dashboard(page, df_filtered):
         with col2:
             st.plotly_chart(create_channel_discrimination_chart(df_filtered))
 
+
 # Render the selected dashboard page
 render_dashboard(page, df_filtered)