Update app.py

app.py

@@ -19,11 +19,16 @@ def load_and_clean_data():
 
     # Concatenate dataframes and clean data
     df_combined = pd.concat([df1, df2, df3, df4])
+    
+    # Replace 'nan' and 'None' with numpy NaN for removal
     df_combined['Domain'] = df_combined['Domain'].replace({"MUSLIM": "Muslim", "nan": pd.NA, "None": pd.NA, "Other-Ethnic": "Other-Ethnicity"})
+    
+    # Specific replacements for 'Sentiment' and 'Discrimination'
     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'])
+    df_combined['Discrimination'] = df_combined['Discrimination'].replace({"nan": pd.NA, "None": pd.NA, "No": pd.NA})
+    
+    # Drop rows with NA values in 'Domain', 'Sentiment', and 'Discrimination'
+    df_combined.dropna(subset=['Domain', 'Sentiment', 'Discrimination'], inplace=True)
 
     return df_combined
 
@@ -129,11 +134,10 @@ def create_top_discriminatory_domains_chart(df):
     return fig
 
 # Function for Channel-wise Sentiment Over Time Chart
-def create_channel_sentiment_over_time_chart(df):
-    df['Date'] = pd.to_datetime(df['Date'])
-    timeline = df.groupby([df['Date'].dt.to_period('M'), 'Channel', 'Sentiment']).size().unstack(fill_value=0)
-    fig = px.line(timeline, x=timeline.index.levels[1].to_timestamp(), y=['Positive', 'Negative', 'Neutral'], color='Channel')
-    fig.update_layout(title='Channel-wise Sentiment Over Time', margin=dict(l=20, r=20, t=40, b=20))
+def create_sentiment_distribution_by_channel_chart(df):
+    sentiment_by_channel = df.groupby(['Channel', 'Sentiment']).size().reset_index(name='counts')
+    fig = px.bar(sentiment_by_channel, x='Channel', y='counts', color='Sentiment', title="Sentiment Distribution by Channel", barmode='group')
+    fig.update_layout(margin=dict(l=20, r=20, t=40, b=20), xaxis_title="Channel", yaxis_title="Counts", font=dict(size=12))
     return fig
 
 # Function for Channel-wise Distribution of Discriminative Content Chart
@@ -183,7 +187,7 @@ def render_dashboard(page, df_filtered):
         st.title("Channel Analysis Dashboard")
         col1, col2 = st.columns(2)
         with col1:
-            st.plotly_chart(create_channel_sentiment_over_time_chart(df_filtered))
+            st.plotly_chart(create_sentiment_distribution_by_channel_chart(df_filtered))
         with col2:
             st.plotly_chart(create_channel_discrimination_chart(df_filtered))