Update app.py

app.py

@@ -50,6 +50,7 @@ channel_filter = st.sidebar.multiselect('Select Channel', options=channel_option
 sentiment_filter = st.sidebar.multiselect('Select Sentiment', options=sentiment_options, default=sentiment_options)
 discrimination_filter = st.sidebar.multiselect('Select Discrimination', options=discrimination_options, default=discrimination_options)
 
+
 # Apply filters
 df_filtered = df[(df['Domain'].isin(domain_filter)) & 
                  (df['Channel'].isin(channel_filter)) & 
@@ -76,9 +77,14 @@ def create_gender_ethnicity_distribution_chart(df):
 
 # Visualization for Sentiment Distribution Across Domains
 def create_sentiment_distribution_chart(df):
-    df['Discrimination'] = df['Discrimination'].replace({"Non Discriminative": "Non-Discriminative"})  # Assuming typo in the original script
     domain_counts = df.groupby(['Domain', 'Sentiment']).size().reset_index(name='counts')
-    fig = px.bar(domain_counts, x='Domain', y='counts', color='Sentiment', title="Sentiment Distribution Across Domains", barmode='stack')
+    domain_counts = domain_counts.sort_values('counts')
+    
+    # Reverse the color scheme
+    color_map = {'Negative': 'red', 'Positive': 'blue', 'Neutral': 'lightblue'}
+    
+    fig = px.bar(domain_counts, x='Domain', y='counts', color='Sentiment', color_discrete_map=color_map,
+                 title="Sentiment Distribution Across Domains", barmode='stack')
     fig.update_layout(margin=dict(l=20, r=20, t=50, b=20), xaxis_title="Domain", yaxis_title="Counts", font=dict(size=10))
     return fig