Update ui_generators.py

ui_generators.py

@@ -94,9 +94,9 @@ def display_main_dashboard(token_state):
             try:
                 monthly_gains.loc[:, FOLLOWER_STATS_CATEGORY_COLUMN_DT] = pd.to_datetime(monthly_gains[FOLLOWER_STATS_CATEGORY_COLUMN], errors='coerce')
                 monthly_gains_display = monthly_gains.sort_values(by=FOLLOWER_STATS_CATEGORY_COLUMN_DT, ascending=False)
-                latest_gain = monthly_gains_display.head(1).copy() 
+                latest_gain = monthly_gains_display.head(1).copy()
                 if not latest_gain.empty:
-                    latest_gain.loc[:, FOLLOWER_STATS_CATEGORY_COLUMN] = latest_gain[FOLLOWER_STATS_CATEGORY_COLUMN_DT].dt.strftime(UI_DATE_FORMAT) 
+                    latest_gain.loc[:, FOLLOWER_STATS_CATEGORY_COLUMN] = latest_gain[FOLLOWER_STATS_CATEGORY_COLUMN_DT].dt.strftime(UI_DATE_FORMAT)
                     html_parts.append("<h5>Latest Monthly Follower Gain:</h5>")
                     html_parts.append(latest_gain[[FOLLOWER_STATS_CATEGORY_COLUMN, FOLLOWER_STATS_ORGANIC_COLUMN, FOLLOWER_STATS_PAID_COLUMN]].to_html(escape=True, index=False, classes="table table-sm"))
                 else:
@@ -147,25 +147,28 @@ def run_mentions_tab_display(token_state):
         html_parts.append(mentions_df_display[display_columns].head(20).to_html(escape=False, index=False, classes="table table-sm"))
 
     mentions_html_output = "\n".join(html_parts)
-    fig = None 
+    fig = None
     if not mentions_df.empty and "sentiment_label" in mentions_df.columns:
         try:
             fig_plot, ax = plt.subplots(figsize=(6,4))
             sentiment_counts = mentions_df["sentiment_label"].value_counts()
             sentiment_counts.plot(kind='bar', ax=ax, color=['#4CAF50', '#FFC107', '#F44336', '#9E9E9E', '#2196F3'])
-            ax.set_title("Mention Sentiment Distribution")
+            ax.set_title("Mention Sentiment Distribution", y=1.03) # MODIFIED: Added y parameter
             ax.set_ylabel("Count")
             plt.xticks(rotation=45, ha='right')
-            plt.tight_layout()
-            fig = fig_plot 
+            plt.tight_layout() # Ensure tight_layout is called
+            fig = fig_plot
             logging.info("Mentions tab: Sentiment distribution plot generated.")
         except Exception as e:
             logging.error(f"Error generating mentions plot: {e}", exc_info=True)
+            fig = None # Ensure fig is None on error
         finally:
-            if fig is not None and fig is not plt: 
-                 plt.close(fig) 
-            elif fig is None and plt.get_fignums(): 
-                 plt.close('all')
+            # Only close if fig_plot was successfully created and is not the global plt context
+            if fig_plot and fig_plot is not plt: # fig_plot is the figure object from subplots
+                 plt.close(fig_plot)
+            # Fallback if somehow a global figure was left open without being assigned to fig_plot
+            # elif fig is None and plt.get_fignums():
+            #     plt.close('all') # This might be too aggressive if other plots are intended to be open
     return mentions_html_output, fig
 
 
@@ -188,15 +191,17 @@ def run_follower_stats_tab_display(token_state):
     plot_seniority_dist = None
     plot_industry_dist = None
 
-    monthly_gains_df = follower_stats_df[
-        (follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] == 'follower_gains_monthly') &
-        (follower_stats_df[FOLLOWER_STATS_CATEGORY_COLUMN].notna()) &
-        (follower_stats_df[FOLLOWER_STATS_ORGANIC_COLUMN].notna()) &
-        (follower_stats_df[FOLLOWER_STATS_PAID_COLUMN].notna())
-    ].copy()
-
-    if not monthly_gains_df.empty:
-        try:
+    # Monthly Gains Plot
+    fig_gains_local = None # Use local var for figure to manage closing
+    try:
+        monthly_gains_df = follower_stats_df[
+            (follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] == 'follower_gains_monthly') &
+            (follower_stats_df[FOLLOWER_STATS_CATEGORY_COLUMN].notna()) &
+            (follower_stats_df[FOLLOWER_STATS_ORGANIC_COLUMN].notna()) &
+            (follower_stats_df[FOLLOWER_STATS_PAID_COLUMN].notna())
+        ].copy()
+
+        if not monthly_gains_df.empty:
             monthly_gains_df.loc[:, FOLLOWER_STATS_CATEGORY_COLUMN_DT] = pd.to_datetime(monthly_gains_df[FOLLOWER_STATS_CATEGORY_COLUMN], errors='coerce')
             monthly_gains_df_sorted_table = monthly_gains_df.sort_values(by=FOLLOWER_STATS_CATEGORY_COLUMN_DT, ascending=False)
 
@@ -210,96 +215,103 @@ def run_follower_stats_tab_display(token_state):
             plot_data = monthly_gains_df_sorted_plot.groupby('_plot_month').agg(
                 organic=(FOLLOWER_STATS_ORGANIC_COLUMN, 'sum'),
                 paid=(FOLLOWER_STATS_PAID_COLUMN, 'sum')
-            ).reset_index().sort_values(by='_plot_month') 
+            ).reset_index()
+            # Ensure months are sorted correctly for plotting after groupby
+            plot_data['_plot_month_dt'] = pd.to_datetime(plot_data['_plot_month'], format=UI_MONTH_FORMAT)
+            plot_data = plot_data.sort_values(by='_plot_month_dt')
 
-            fig_gains, ax_gains = plt.subplots(figsize=(10,5))
+
+            fig_gains_local, ax_gains = plt.subplots(figsize=(10,5))
             ax_gains.plot(plot_data['_plot_month'], plot_data['organic'], marker='o', linestyle='-', label='Organic Gain')
             ax_gains.plot(plot_data['_plot_month'], plot_data['paid'], marker='x', linestyle='--', label='Paid Gain')
-            ax_gains.set_title("Monthly Follower Gains Over Time")
+            ax_gains.set_title("Monthly Follower Gains Over Time", y=1.03) # MODIFIED
             ax_gains.set_ylabel("Follower Count")
             ax_gains.set_xlabel("Month (YYYY-MM)")
             plt.xticks(rotation=45, ha='right')
             ax_gains.legend()
             plt.grid(True, linestyle='--', alpha=0.7)
             plt.tight_layout()
-            plot_monthly_gains = fig_gains
+            plot_monthly_gains = fig_gains_local # Assign to the return variable
             logging.info("Follower stats tab: Monthly gains plot generated.")
-        except Exception as e:
-            logging.error(f"Error processing or plotting monthly gains: {e}", exc_info=True)
-            html_parts.append("<p>Error displaying monthly follower gain data.</p>")
-        finally:
-            if plot_monthly_gains is not None and plot_monthly_gains is not plt:
-                 plt.close(plot_monthly_gains)
-            elif plot_monthly_gains is None and plt.get_fignums():
-                 plt.close('all')
-    else:
-        html_parts.append("<p>No monthly follower gain data available or required columns missing.</p>")
+        else:
+            html_parts.append("<p>No monthly follower gain data available or required columns missing.</p>")
+    except Exception as e:
+        logging.error(f"Error processing or plotting monthly gains: {e}", exc_info=True)
+        html_parts.append("<p>Error displaying monthly follower gain data.</p>")
+        plot_monthly_gains = None # Ensure it's None on error
+    finally:
+        if fig_gains_local and fig_gains_local is not plt: # Check local var
+             plt.close(fig_gains_local)
     html_parts.append("<hr/>")
 
-    seniority_df = follower_stats_df[
-        (follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] == 'follower_seniority') &
-        (follower_stats_df[FOLLOWER_STATS_CATEGORY_COLUMN].notna()) &
-        (follower_stats_df[FOLLOWER_STATS_ORGANIC_COLUMN].notna())
-    ].copy()
-    if not seniority_df.empty:
-        try:
+
+    # Seniority Plot
+    fig_seniority_local = None
+    try:
+        seniority_df = follower_stats_df[
+            (follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] == 'follower_seniority') &
+            (follower_stats_df[FOLLOWER_STATS_CATEGORY_COLUMN].notna()) &
+            (follower_stats_df[FOLLOWER_STATS_ORGANIC_COLUMN].notna())
+        ].copy()
+        if not seniority_df.empty:
             seniority_df_sorted = seniority_df.sort_values(by=FOLLOWER_STATS_ORGANIC_COLUMN, ascending=False)
             html_parts.append("<h4>Followers by Seniority (Top 10 Organic):</h4>")
             html_parts.append(seniority_df_sorted[[FOLLOWER_STATS_CATEGORY_COLUMN, FOLLOWER_STATS_ORGANIC_COLUMN, FOLLOWER_STATS_PAID_COLUMN]].head(10).to_html(escape=True, index=False, classes="table table-sm"))
 
-            fig_seniority, ax_seniority = plt.subplots(figsize=(8,5))
+            fig_seniority_local, ax_seniority = plt.subplots(figsize=(8,5))
             top_n_seniority = seniority_df_sorted.nlargest(10, FOLLOWER_STATS_ORGANIC_COLUMN)
             ax_seniority.bar(top_n_seniority[FOLLOWER_STATS_CATEGORY_COLUMN], top_n_seniority[FOLLOWER_STATS_ORGANIC_COLUMN], color='skyblue')
-            ax_seniority.set_title("Follower Distribution by Seniority (Top 10 Organic)")
+            ax_seniority.set_title("Follower Distribution by Seniority (Top 10 Organic)", y=1.03) # MODIFIED
             ax_seniority.set_ylabel("Organic Follower Count")
             plt.xticks(rotation=45, ha='right')
             plt.grid(axis='y', linestyle='--', alpha=0.7)
             plt.tight_layout()
-            plot_seniority_dist = fig_seniority
+            plot_seniority_dist = fig_seniority_local
             logging.info("Follower stats tab: Seniority distribution plot generated.")
-        except Exception as e:
-            logging.error(f"Error processing or plotting seniority data: {e}", exc_info=True)
-            html_parts.append("<p>Error displaying follower seniority data.</p>")
-        finally:
-            if plot_seniority_dist is not None and plot_seniority_dist is not plt:
-                 plt.close(plot_seniority_dist)
-            elif plot_seniority_dist is None and plt.get_fignums():
-                 plt.close('all')
-    else:
-        html_parts.append("<p>No follower seniority data available or required columns missing.</p>")
+        else:
+            html_parts.append("<p>No follower seniority data available or required columns missing.</p>")
+    except Exception as e:
+        logging.error(f"Error processing or plotting seniority data: {e}", exc_info=True)
+        html_parts.append("<p>Error displaying follower seniority data.</p>")
+        plot_seniority_dist = None
+    finally:
+        if fig_seniority_local and fig_seniority_local is not plt:
+             plt.close(fig_seniority_local)
     html_parts.append("<hr/>")
 
-    industry_df = follower_stats_df[
-        (follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] == 'follower_industry') &
-        (follower_stats_df[FOLLOWER_STATS_CATEGORY_COLUMN].notna()) &
-        (follower_stats_df[FOLLOWER_STATS_ORGANIC_COLUMN].notna())
-    ].copy()
-    if not industry_df.empty:
-        try:
+    # Industry Plot
+    fig_industry_local = None
+    try:
+        industry_df = follower_stats_df[
+            (follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] == 'follower_industry') &
+            (follower_stats_df[FOLLOWER_STATS_CATEGORY_COLUMN].notna()) &
+            (follower_stats_df[FOLLOWER_STATS_ORGANIC_COLUMN].notna())
+        ].copy()
+        if not industry_df.empty:
             industry_df_sorted = industry_df.sort_values(by=FOLLOWER_STATS_ORGANIC_COLUMN, ascending=False)
             html_parts.append("<h4>Followers by Industry (Top 10 Organic):</h4>")
             html_parts.append(industry_df_sorted[[FOLLOWER_STATS_CATEGORY_COLUMN, FOLLOWER_STATS_ORGANIC_COLUMN, FOLLOWER_STATS_PAID_COLUMN]].head(10).to_html(escape=True, index=False, classes="table table-sm"))
 
-            fig_industry, ax_industry = plt.subplots(figsize=(8,5))
+            fig_industry_local, ax_industry = plt.subplots(figsize=(8,5))
             top_n_industry = industry_df_sorted.nlargest(10, FOLLOWER_STATS_ORGANIC_COLUMN)
             ax_industry.bar(top_n_industry[FOLLOWER_STATS_CATEGORY_COLUMN], top_n_industry[FOLLOWER_STATS_ORGANIC_COLUMN], color='lightcoral')
-            ax_industry.set_title("Follower Distribution by Industry (Top 10 Organic)")
+            ax_industry.set_title("Follower Distribution by Industry (Top 10 Organic)", y=1.03) # MODIFIED
             ax_industry.set_ylabel("Organic Follower Count")
             plt.xticks(rotation=45, ha='right')
             plt.grid(axis='y', linestyle='--', alpha=0.7)
             plt.tight_layout()
-            plot_industry_dist = fig_industry
+            plot_industry_dist = fig_industry_local
             logging.info("Follower stats tab: Industry distribution plot generated.")
-        except Exception as e:
-            logging.error(f"Error processing or plotting industry data: {e}", exc_info=True)
-            html_parts.append("<p>Error displaying follower industry data.</p>")
-        finally:
-            if plot_industry_dist is not None and plot_industry_dist is not plt:
-                 plt.close(plot_industry_dist)
-            elif plot_industry_dist is None and plt.get_fignums():
-                 plt.close('all')
-    else:
-        html_parts.append("<p>No follower industry data available or required columns missing.</p>")
+        else:
+            html_parts.append("<p>No follower industry data available or required columns missing.</p>")
+    except Exception as e:
+        logging.error(f"Error processing or plotting industry data: {e}", exc_info=True)
+        html_parts.append("<p>Error displaying follower industry data.</p>")
+        plot_industry_dist = None
+    finally:
+        if fig_industry_local and fig_industry_local is not plt:
+            plt.close(fig_industry_local)
+
 
     html_parts.append("</div>")
     follower_html_output = "\n".join(html_parts)
@@ -318,10 +330,10 @@ def create_analytics_plot_panel(label, plot_id_str):
         explore_button (gr.Button): Explore/Zoom button.
         formula_button (gr.Button): Formula button.
     """
-    with gr.Column() as panel_col: 
-        with gr.Row(equal_height=False, variant="panel"): 
-            plot_component = gr.Plot(label=label, scale=8) 
-            with gr.Column(scale=2, min_width=100): 
+    with gr.Column() as panel_col: # This will be the component that gets hidden/shown by explore
+        with gr.Row(equal_height=False, variant="panel"): # Removed variant="compact" as it might affect spacing
+            plot_component = gr.Plot(label=label, scale=8) # The label here is for Gradio, not the Matplotlib title
+            with gr.Column(scale=2, min_width=100): # min_width for button column
                 bomb_button = gr.Button(BOMB_ICON, variant="secondary", size="sm", elem_id=f"bomb_{plot_id_str}")
                 explore_button = gr.Button(EXPLORE_ICON, variant="secondary", size="sm", elem_id=f"explore_{plot_id_str}")
                 formula_button = gr.Button(FORMULA_ICON, variant="secondary", size="sm", elem_id=f"formula_{plot_id_str}")
@@ -333,8 +345,8 @@ def build_analytics_tab_plot_area(plot_configs):
     Returns a dictionary of plot UI objects.
     """
     logging.info(f"Building plot area for {len(plot_configs)} analytics plots.")
-    plot_ui_objects = {} 
-    
+    plot_ui_objects = {}
+
     current_section_title = ""
     i = 0
     while i < len(plot_configs):
@@ -343,26 +355,24 @@ def build_analytics_tab_plot_area(plot_configs):
         # Start a new section if necessary
         if config1["section"] != current_section_title:
             current_section_title = config1["section"]
-            gr.Markdown(f"### {current_section_title}")
+            gr.Markdown(f"### {current_section_title}") # Section title
 
-        # Create a new row for each pair of plots or a single plot if it's the last one
-        # or if the next plot is in a different section.
-        with gr.Row(equal_height=False):
+        # Create a new row for each pair of plots or a single plot
+        with gr.Row(equal_height=False): # A new row for one or two plots
             # Process the first plot of the potential pair
             panel_col1, plot_comp1, bomb_btn1, explore_btn1, formula_btn1 = \
                 create_analytics_plot_panel(config1["label"], config1["id"])
             plot_ui_objects[config1["id"]] = {
                 "plot_component": plot_comp1, "bomb_button": bomb_btn1,
                 "explore_button": explore_btn1, "formula_button": formula_btn1,
-                "label": config1["label"], "panel_component": panel_col1
+                "label": config1["label"], "panel_component": panel_col1 # panel_col1 is the gr.Column from create_analytics_plot_panel
             }
             logging.debug(f"Created UI panel for plot_id: {config1['id']}")
-            i += 1 # Move to the next plot configuration
+            i += 1
 
-            # Check if there's a second plot for this row
+            # Check if there's a second plot for this row and if it's in the same section
             if i < len(plot_configs):
                 config2 = plot_configs[i]
-                # Add to the same row ONLY if it's in the same section
                 if config2["section"] == current_section_title:
                     panel_col2, plot_comp2, bomb_btn2, explore_btn2, formula_btn2 = \
                         create_analytics_plot_panel(config2["label"], config2["id"])
@@ -372,11 +382,11 @@ def build_analytics_tab_plot_area(plot_configs):
                         "label": config2["label"], "panel_component": panel_col2
                     }
                     logging.debug(f"Created UI panel for plot_id: {config2['id']} in same row")
-                    i += 1 # Move to the next plot configuration
+                    i += 1
                 # If config2 is in a new section, the row ends with config1.
                 # config2 will be processed as the first plot in a new row in the next iteration.
-            # If no more plots or next is in new section, row is complete.
-        
+            # Row ends here. Next iteration will start a new gr.Row if needed.
+
     logging.info(f"Finished building plot area. Total plot objects: {len(plot_ui_objects)}")
     if len(plot_ui_objects) != len(plot_configs):
         logging.error(f"MISMATCH: Expected {len(plot_configs)} plot objects, but created {len(plot_ui_objects)}.")