code: def list_lv_grid_districts(self, session, lv_stations):
          
          gw2kw = 10 ** 6  # load in database is in GW -> scale to kW
  
          # 1. filter grid districts of relevant load area
          lv_grid_districs_sqla = session.query(
              self.orm['orm_lv_grid_district'].mvlv_subst_id,
              (self.orm[
                   'orm_lv_grid_district'].sector_peakload_residential * gw2kw).
                  label('peak_load_residential'),
              (self.orm['orm_lv_grid_district'].sector_peakload_retail * gw2kw).
                  label('peak_load_retail'),
              (self.orm[
                   'orm_lv_grid_district'].sector_peakload_industrial * gw2kw).
                  label('peak_load_industrial'),
              (self.orm[
                   'orm_lv_grid_district'].sector_peakload_agricultural * gw2kw).
                  label('peak_load_agricultural'),
              ). \
              filter(self.orm['orm_lv_grid_district'].mvlv_subst_id.in_(
              lv_stations)). \
              filter(self.orm['version_condition_lvgd'])
  
          # read data from db
          lv_grid_districts = pd.read_sql_query(lv_grid_districs_sqla.statement,
                                                session.bind,
                                                index_col='mvlv_subst_id')
  
          return lv_grid_districts
docs: Imports all lv grid districts within given load area
  
          Parameters
          ----------
          session : sqlalchemy.orm.session.Session
              Database session
          lv_stations:
              List required LV_stations==LV districts.
  
          Returns
          -------
          pandas Dataframe
              Table of lv_grid_districts