code: def timeseries(self, iamc_index=False):
          
          index = IAMC_IDX if iamc_index else IAMC_IDX + self.extra_cols
          df = (
              self.data
              .pivot_table(index=index, columns=self.time_col)
              .value  # column name
              .rename_axis(None, axis=1)
          )
          if df.index.has_duplicates:
              raise ValueError('timeseries object has duplicates in index ',
                               'use `iamc_index=False`')
          return df
docs: Returns a pd.DataFrame in wide format (years or timedate as columns)
  
          Parameters
          ----------
          iamc_index: bool, default False
              if True, use `['model', 'scenario', 'region', 'variable', 'unit']`;
              else, use all `data` columns