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# Find rows with differences diff_df = source_df.compare(target_df, keep_shape=True) if not diff_df.empty: # Generate an update query dynamically update_query = f"UPDATE {table_name} SET " column_updates = [] for column_name in diff_df.columns: source_col = diff_df[column_name]['self'] target_col = diff_df[column_name]['other'] # Identify rows where values are different diff_rows = np.where(source_col != target_col)[0] for row_number in diff_rows: source_val = source_col.iloc[row_number] target_val = target_col.iloc[row_number] # Include the column update in the query column_updates.append(f"{column_name} = '{source_val}'") update_query += ", ".join(column_updates) print(update_query) # Execute the update query cursor_ext.execute(update_query) instead of using rownnum in where condition can you use the values of this primary_df['eprm_table_col_pk'] =source_row[primary_df['eprm_table_col_pk']] just predefine thos values and in the update statement where clause use them