Update app.py

app.py

@@ -70,16 +70,16 @@ def upload_csv(file):
                 date_ranges = ['All']
                 debug_msg += "Warning: Could not determine date range due to invalid timestamps.\n"
             else:
-                min_date = min_date.strftime('%Y-%m-%d')
-                max_date = max_date.strftime('%Y-%m-%d')
+                min_date_str = min_date.strftime('%Y-%m-%d')
+                max_date_str = max_date.strftime('%Y-%m-%d')
                 date_ranges = ['All', f"{min_date_str} to {max_date_str}"]
-                debug_msg += f"Date Range: {min_date} to {max_date}\n"
+                debug_msg += f"Date Range: {min_date_str} to {max_date_str}\n"
         
-        # Automatically trigger filter_and_display after CSV upload with default filters
+        # Automatically trigger filter_and_visualize after upload with default filters
         debug_msg += "Triggering initial visualization with default filters...\n"
         try:
-            result = filter_and_display("All", "All", "All")
-            device_cards, plot_daily, plot_uptime_buf, anomaly_text, filter_msg = result
+            result = filter_and_visualize("All", "All", "All")
+            device_cards, plot_daily, plot_uptime, anomaly_text, filter_msg = result
             debug_msg += f"Initial Filter Result: {filter_msg}\n"
         except Exception as e:
             debug_msg += f"Initial Filter Error: {str(e)}\n"
@@ -87,9 +87,9 @@ def upload_csv(file):
         
         return labs, types, date_ranges, debug_msg, "All", "All", "All", device_cards, plot_daily, plot_uptime, anomaly_text
     except Exception as e:
-        return ["All"], ["All"], ["All"], f"{debug_msg}Failed to process CSV: {str(e)}", "All", "All", "All", None, None, None, None"
+        return ["All"], ["All"], ["All"], f"{debug_msg}Failed to process CSV: {str(e)}", "All", "All", "All", None, None, None, None
 
-def filter_and_display(selected_lab, selected_type, selected_date_range):
+def filter_and_visualize(selected_lab, selected_type, selected_date_range):
     global df
     if df.empty:
         return None, None, None, None, "No data available."
@@ -102,7 +102,7 @@ def filter_and_display(selected_lab, selected_type, selected_date_range):
     error_msg += f"Initial DataFrame: {len(filtered_df)} rows\n"
     
     if selected_lab != "All":
-        filtered_df = filtered_df[filtered_df["Lab'] == "selected_lab"]
+        filtered_df = filtered_df[filtered_df["Lab"] == selected_lab]
         error_msg += f"After Lab filter ({selected_lab}): {len(filtered_df)} rows\n"
     if selected_type != "All":
         filtered_df = filtered_df[filtered_df["Type"] == selected_type]
@@ -112,21 +112,21 @@ def filter_and_display(selected_lab, selected_type, selected_date_range):
             start_date, end_date = selected_date_range.split(" to ")
             start_date = pd.to_datetime(start_date)
             end_date = pd.to_datetime(end_date) + timedelta(days=1)  # Include end date
-            filtered_df = filtered_df[(filtered_df["Timestamp"] >= start_date) & (filtered_df['Timestamp'] < end_date)]
+            filtered_df = filtered_df[(filtered_df["Timestamp"] >= start_date) & (filtered_df["Timestamp"] < end_date)]
             error_msg += f"After Date Range filter ({start_date} to {end_date}): {len(filtered_df)} rows\n"
         except Exception as e:
             error_msg += f"Error parsing date range: {str(e)}\n"
     
     if filtered_df.empty:
-        return None, None, None, None, f"{error_msg}No data matches the selected filters.\n"
+        return None, None, None, None, f"{error_msg}No data matches the selected filters."
     
     # Debug: Log the filtered DataFrame
-    error_msg += f"Filtered DataFrame:\n{filtered_df.to_string()}\n\n"
+    error_msg += f"Filtered DataFrame:\n{filtered_df.to_string()}\n"
     
     # Device Cards (as a table)
-    device_cards = filtered_df[['DeviceID', 'Lab', 'Type', 'UsageCount', 'Timestamp']].sort_values(by='Timestamp')
+    device_cards = filtered_df[['DeviceID', 'Lab', 'Type', 'UsageCount', 'Timestamp']].sort_values(by='Timestamp', ascending=False)
     
-    # Daily Log Trends
+    # Daily Log Trends (Line Chart)
     try:
         if df['Timestamp'].isna().all():
             error_msg += "Warning: All timestamps are invalid. Skipping Daily Log Trends.\n"
@@ -232,7 +232,7 @@ def filter_and_display(selected_lab, selected_type, selected_date_range):
         error_msg += f"Error generating Anomaly Alerts: {str(e)}\n"
         anomaly_text = "Error generating anomaly alerts."
     
-    return device_cards, buf1, buf2, anomaly_text, f"{error_msg}\nFilters applied successfully."
+    return device_cards, buf1, buf2, anomaly_text, f"{error_msg}Filters applied successfully."
 
 def download_pdf(selected_lab, selected_type, selected_date_range):
     global df
@@ -299,13 +299,13 @@ with gr.Blocks() as demo:
     csv_input.change(
         fn=upload_csv,
         inputs=csv_input,
-        outputs=[lab_dropdown, type_dropdown, date_dropdown, error_box, lab_dropdown, type_dropdown, date_dropdown, device_cards, plot_daily, plot_uptime, anomaly_output],
+        outputs=[lab_dropdown, type_dropdown, date_dropdown, error_box, lab_dropdown, type_dropdown, date_dropdown, device_cards, plot_daily, plot_uptime, anomaly_output]
     )
     
     submit_btn.click(
         fn=filter_and_visualize,
         inputs=[lab_dropdown, type_dropdown, date_dropdown],
-        outputs=[device_cards, plot_daily, plot_uptime, anomaly_output, error_box],
+        outputs=[device_cards, plot_daily, plot_uptime, anomaly_output, error_box]
     )
     
     download_btn.click(