Update index.py

index.py

@@ -128,10 +128,24 @@ app.layout = dbc.Container([
     dbc.Row([ # row 11
             dbc.Col(dcc.Graph(id='line-graph-4'),
                     )
-    ])
+    ]),
 
-])
+    html.Div(id='pie-container-1')
 
+])
+# # Create a function to generate pie charts
+# def generate_pie_chart(category):
+#     labels = data[category]['labels']
+#     values = data[category]['values']
+#     trace = go.Pie(labels=labels, values=values)
+#     layout = go.Layout(title=f'Pie Chart - {category}')
+#     return dcc.Graph(
+#         figure={
+#             'data': [trace],
+#             'layout': layout
+#         }
+#     )
+    
 # callback decorator
 @app.callback(
     Output('line-graph-1', 'figure'),
@@ -139,6 +153,7 @@ app.layout = dbc.Container([
     Output('line-graph-2', 'figure'),
     Output('line-graph-3', 'figure'),
     Output('line-graph-4', 'figure'),
+    Output('pie-container-1', 'children'),
     Input("topic-selector", "value"),
     Input ("domain-selector", "value"),
     Input('date-range', 'start_date'),
@@ -226,10 +241,63 @@ def update_output(selected_topic, selected_domain, start_date, end_date):
         line_fig_2.update_traces(line_color='#1E88E5')
         line_fig_3.update_traces(line_color='#004D40')
         line_fig_4.update_traces(line_color='#D81B60')
-    
-        return line_fig_1, bar_fig_1, line_fig_2, line_fig_3, line_fig_4
+
+    #
+        # pie_container_1 = generate_pie_chart(category)
+        # Map original labels to their translated versions
+        label_translation = {'positive': 'positivo', 'neutral': 'neutro', 'negative': 'negativo'}
+        df_filtered['FinBERT_label_transformed'] = df_filtered['FinBERT_label'].map(label_translation)
+        
+        # Group by FinBERT_label and count occurrences
+        label_counts_all = df_filtered['FinBERT_label_transformed'].value_counts()
+        
+        # Calculate percentage of each label
+        label_percentages_all = (label_counts_all / label_counts_all.sum()) * 100
+        
+        # Plot general pie chart
+        fig_general = px.pie(
+            values=label_percentages_all,
+            names=label_percentages_all.index,
+            title='Distribuição Geral',
+            color_discrete_sequence=['#039a4d', '#3c03f4', '#ca3919']
+        )
+        
+        
+        # Get unique media categories
+        media_categories = df_filtered['Veículos de notícias'].unique()
+        
+        # Define colors for each label
+        label_colors = {'positivo': '#039a4d', 'neutro': '#3c03f4', 'negativo': '#ca3919'}
+        
+                         
+        pie_container_1 = []
+        for row in range(num_rows):
+            row_content = []
+             # Loop through each media category
+            for media in media_categories:
+                # Filter DataFrame for current media category
+                media_df = df[df['Veículos de notícias'] == media]
+            
+                # Group by FinBERT_label and count occurrences
+                label_counts = media_df['FinBERT_label_transformed'].value_counts()
+            
+                # Calculate percentage of each label
+                label_percentages = (label_counts / label_counts.sum()) * 100
+            
+                # Plot pie chart
+                fig = px.pie(
+                    values=label_percentages,
+                    names=label_percentages.index,
+                    title=f'Distribuição para {media}',
+                    color_discrete_sequence=[label_colors[label] for label in label_percentages.index]
+                )
+                pie_chart = html.Div(fig)
+                row_content.append(pie_chart)
+            pie_container_1.append(html.Div(row_content, className='row'))
+            
+        return line_fig_1, bar_fig_1, line_fig_2, line_fig_3, line_fig_4, pie_container_1
     else:
-        return {'data': []},{'data': []} ,{'data': []} ,{'data': []} , {'data': []} 
+        return {'data': []},{'data': []} ,{'data': []} ,{'data': []} , {'data': []}, {'data':[]} 
     
     # return line_fig_1