code: def transform_dataframe(
      self, dataframe: pd.DataFrame
  ) -> pd.DataFrame:
      processed_df = super().transform_dataframe(dataframe)
      # Ensure feature column names are strings (some are numeric); keep special names as is
      processed_df.columns = [
          "C" + str(col) for col in processed_df.columns
      ]
      processed_df.rename(
          columns={"CID": "ID", "Ctarget": "target", "Csplit": "split"},
          inplace=True,
      )
      return processed_df
  
imports: import pandas
  from ludwig.datasets.loaders.dataset_loader import DatasetLoader
label_desc: Use image node_id 1 for calling the SantanderValuePredictionLoader obj's underlying member method code with example usage: obj.transform_dataframe(dataframe) and returns: processed_df