code: def normalize(self, inplace=False, **kwargs):
          
          if len(kwargs) > 1 or self.time_col not in kwargs:
              raise ValueError('Only time(year)-based normalization supported')
          ret = copy.deepcopy(self) if not inplace else self
          df = ret.data
          # change all below if supporting more in the future
          cols = self.time_col
          value = kwargs[self.time_col]
          x = df.set_index(IAMC_IDX)
          x['value'] /= x[x[cols] == value]['value']
          ret.data = x.reset_index()
          if not inplace:
              return ret
docs: Normalize data to a given value. Currently only supports normalizing
          to a specific time.
  
          Parameters
          ----------
          inplace: bool, default False
              if True, do operation inplace and return None
          kwargs: the values on which to normalize (e.g., `year=2005`)