code: def interpolate(self, year):
          
          df = self.pivot_table(index=IAMC_IDX, columns=['year'],
                                values='value', aggfunc=np.sum)
          # drop year-rows where values are already defined
          if year in df.columns:
              df = df[np.isnan(df[year])]
          fill_values = df.apply(fill_series,
                                 raw=False, axis=1, year=year)
          fill_values = fill_values.dropna().reset_index()
          fill_values = fill_values.rename(columns={0: "value"})
          fill_values['year'] = year
          self.data = self.data.append(fill_values, ignore_index=True)
docs: Interpolate missing values in timeseries (linear interpolation)
  
          Parameters
          ----------
          year: int
               year to be interpolated