code: def to_dataframe(self):
          
          if pd is None:
              raise DatasetsError(
                  "pandas is required to load DataFrame, it can be installed with pip"
              )
  
          path = find_dataset_path(self.name, ext=".csv.gz", data_home=self.data_home)
          return pd.read_csv(path, compression="gzip")
docs: Returns the entire dataset as a single pandas DataFrame.
  
          Returns
          -------
          df : DataFrame with shape (n_instances, n_columns)
              A pandas DataFrame containing the complete original data table
              including all targets (specified by the meta data) and all
              features (including those that might have been filtered out).