Update ui/analytics_plot_generator.py

ui/analytics_plot_generator.py

@@ -290,7 +290,7 @@ def _parse_eb_label(label_data):
     return [] if pd.isna(label_data) else [str(label_data)]
 
 def generate_content_topic_breakdown_plot(df, topics_col='li_eb_labels', **kwargs):
-    title = "Content by Topics (Top 15)"
+    title = "Content by Topics"
     if df is None or df.empty or topics_col not in df.columns:
         return create_placeholder_plot(title=title, message="No data available.")
 
@@ -377,10 +377,12 @@ def update_analytics_plots_figures(token_state_value, date_filter_option, custom
         "content_topic_breakdown_cs": lambda: generate_content_topic_breakdown_plot(filtered_merged_posts_df, topics_col=token_state_value.get("config_eb_labels_col", "li_eb_labels")),
         
         # Analisi Menzioni (Dettaglio)
-        "mention_analysis_volume": lambda: generate_generic_time_series_plot(filtered_mentions_df, token_state_value.get("config_date_col_mentions", "date"), 'mention_id', 'Mentions Volume', 'Number of Mentions', color='#818CF8'),
+        "mention_analysis_volume": lambda: generate_generic_time_series_plot(filtered_mentions_df, token_state_value.get("config_date_col_mentions", "date"), 'id', 'Mentions Volume', 'Number of Mentions', color='#818CF8'),
         "mention_analysis_sentiment": lambda: generate_generic_pie_chart(filtered_mentions_df['sentiment_label'].value_counts().dropna(), "Mention Sentiment Breakdown")
     }
 
+    logging.info(f"colonne posts df {filtered_merged_posts_df.columns}")
+    logging.info(f"colonne mentions df {filtered_mentions_df.columns}")
     plot_figs = []
     for config in current_plot_configs:
         plot_id = config["id"]