copy df error in logs fix

weekly.py

@@ -9,6 +9,9 @@ def generate_weekly_report(uploaded_files):
         st.error("No files uploaded. Please upload CSV files for analysis.")
         return
 
+    # Set pandas option to use Copy-on-Write
+    pd.options.mode.copy_on_write = True
+
     combined_data = pd.DataFrame()
     for uploaded_file in uploaded_files:
         data = preprocess_uploaded_file(uploaded_file)
@@ -33,15 +36,19 @@ def generate_weekly_report(uploaded_files):
         st.error("No data found in the uploaded files. Please check the file contents.")
         return
 
-    failed_data = combined_data[combined_data['Status'] == 'FAILED']
+    # Create a boolean mask for failed data
+    failed_mask = combined_data['Status'] == 'FAILED'
+
+    # Use .loc to set the 'Date' column for failed data
+    combined_data.loc[failed_mask, 'Date'] = combined_data.loc[failed_mask, 'File Date']
+
+    # Filter failed data
+    failed_data = combined_data[failed_mask]
 
     if failed_data.empty:
         st.warning("No failed scenarios found in the uploaded data.")
         return
 
-    # Use 'File Date' for grouping
-    failed_data['Date'] = failed_data['File Date']
-
     # UI for selecting environments and functional areas
     environments = combined_data['Environment'].unique()
     selected_environments = st.multiselect("Select Environments", options=environments, default=environments)
@@ -82,6 +89,9 @@ def generate_weekly_report(uploaded_files):
     date_range = pd.date_range(start=start_date, end=end_date)
     daily_failures = daily_failures.reindex(date_range, fill_value=0)
 
+    # Convert all columns to int64 to avoid Arrow serialization issues
+    daily_failures = daily_failures.astype('int64')
+
     # Y-axis scaling option
     y_axis_scale = st.radio("Y-axis Scaling", ["Fixed", "Dynamic"])