Update app.py

app.py

@@ -19,21 +19,21 @@ def load_and_clean_data():
 
     # Concatenate dataframes and clean data
     df_combined = pd.concat([df1, df2, df3, df4])
-    df_combined['Domain'] = df_combined['Domain'].replace("MUSLIM", "Muslim")
-    df_combined = df_combined[df_combined['Domain'] != 'Not relevant']
-    df_combined = df_combined[df_combined['Domain'] != 'None']
-    df_combined = df_combined[df_combined['Discrimination'] != 'None']
-    df_combined = df_combined[df_combined['Sentiment'] != 'None']
+    df_combined['Domain'] = df_combined['Domain'].replace({"MUSLIM": "Muslim", "nan": pd.NA, "None": pd.NA, "Other-Ethnic": "Other-Ethnicity"})
+    df_combined['Sentiment'] = df_combined['Sentiment'].replace({"nan": pd.NA, "None": pd.NA, "No": pd.NA})
+
+    # Drop rows with NA values in 'Domain' and 'Sentiment'
+    df_combined = df_combined.dropna(subset=['Domain', 'Sentiment'])
 
     return df_combined
 
 df = load_and_clean_data()
 
-# Define Sidebar Filters
-domain_options = df['Domain'].unique()
-channel_options = df['Channel'].unique()
-sentiment_options = df['Sentiment'].unique()
-discrimination_options = df['Discrimination'].unique()
+# Sidebar Filters
+domain_options = df['Domain'].dropna().unique()
+channel_options = df['Channel'].dropna().unique()
+sentiment_options = df['Sentiment'].dropna().unique()
+discrimination_options = df['Discrimination'].dropna().unique()
 
 domain_filter = st.sidebar.multiselect('Select Domain', options=domain_options, default=domain_options)
 channel_filter = st.sidebar.multiselect('Select Channel', options=channel_options, default=channel_options)
@@ -97,6 +97,7 @@ def create_channel_discrimination_chart(df):
     fig.update_layout(title='Channel-wise Distribution of Discriminative Content', margin=dict(l=20, r=20, t=40, b=20))
     return fig
 
+# Function for rendering dashboard
 def render_dashboard(page, df_filtered):
     if page == "Overview":
         st.title("Overview Dashboard")
@@ -115,13 +116,11 @@ def render_dashboard(page, df_filtered):
 
     elif page == "Sentiment Analysis":
         st.title("Sentiment Analysis Dashboard")
-        # Implementation for the "Sentiment Analysis" page...
-        # Example: st.plotly_chart(create_some_other_chart(df_filtered))
+        # Implement sentiment analysis visualizations here
 
     elif page == "Discrimination Analysis":
         st.title("Discrimination Analysis Dashboard")
-        # Implementation for the "Discrimination Analysis" page...
-        # Example: st.plotly_chart(create_another_chart(df_filtered))
+        # Implement discrimination analysis visualizations here
 
     elif page == "Channel Analysis":
         st.title("Channel Analysis Dashboard")
@@ -132,5 +131,5 @@ def render_dashboard(page, df_filtered):
         with col2:
             st.plotly_chart(create_channel_discrimination_chart(df_filtered))
 
-# Render the dashboard with filtered data
+# Render the selected dashboard page
 render_dashboard(page, df_filtered)