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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