code: def curtailment(self):
          
          if self._curtailment is not None:
              if isinstance(self._curtailment, pd.DataFrame):
                  try:
                      return self._curtailment.loc[[self.timeindex], :]
                  except:
                      return self._curtailment.loc[self.timeindex, :]
              elif isinstance(self._curtailment, list):
                  try:
                      curtailment = pd.DataFrame()
                      for gen in self._curtailment:
                          curtailment[gen] = gen.curtailment
                      return curtailment
                  except:
                      raise
          else:
              return None
docs: Get curtailment time series of dispatchable generators (only active
          power)
  
          Parameters
          ----------
          curtailment : list or :pandas:`pandas.DataFrame<dataframe>`
              See class definition for details.
  
          Returns
          -------
          :pandas:`pandas.DataFrame<dataframe>`
              In the case curtailment is applied to all solar and wind generators
              curtailment time series either aggregated by technology type or by
              type and weather cell ID are returnded. In the first case columns
              of the DataFrame are 'solar' and 'wind'; in the second case columns
              need to be a :pandas:`pandas.MultiIndex<multiindex>` with the
              first level containing the type and the second level the weather
              cell ID.
              In the case curtailment is only applied to specific generators,
              curtailment time series of all curtailed generators, specified in
              by the column name are returned.