docs: def series_fetch_by_relname(self, name, column):
          """ Construct DataFrame with component timeseries data from filtered
          table data.
  
          Parameters
          ----------
          name : str
              Component name.
          column : str
              Component field with timevarying data.
  
          Returns
          -------
          pd.DataFrame
              Component data.
          """
  
          ormclass = self._mapped[name]
  
          # TODO: This is implemented in a not very robust way.
          id_column = re.findall(r'[A-Z][^A-Z]*', name)[0] + '_' + 'id'
          id_column = id_column.lower()
  
          query = self.session.query(
              getattr(ormclass, id_column),
              getattr(ormclass, column)[self.start_snapshot: self.end_snapshot].
              label(column)).filter(and_(
                  ormclass.scn_name == self.scn_name,
                  ormclass.temp_id == self.temp_id))
  
          if self.version:
              query = query.filter(ormclass.version == self.version)
  
          df = pd.io.sql.read_sql(query.statement,
                                  self.session.bind,
                                  columns=[column],
                                  index_col=id_column)
  
          df.index = df.index.astype(str)
  
          # change of format to fit pypsa
          df = df[column].apply(pd.Series).transpose()
  
          try:
              assert not df.empty
              df.index = self.timeindex
          except AssertionError:
              print("No data for %s in column %s." % (name, column))
  
          return df