code: def nd_load_and_stats(filenames, base_path=BASEPATH):
      
  
      # load Ding0 data
      nds = []
      for filename in filenames:
          try:
              nd_load = results.load_nd_from_pickle(filename=
                                                    os.path.join(base_path,
                                                                 'grids',
                                                                 filename))
  
              nds.append(nd_load)
          except:
              print("File {mvgd} not found. It was maybe excluded by Ding0 or "
                    "just forgotten to generate by you...".format(mvgd=filename))
  
      nd = nds[0]
  
      for n in nds[1:]:
          nd.add_mv_grid_district(n._mv_grid_districts[0])
  
      # get statistical numbers about grid
      stats = results.calculate_mvgd_stats(nd)
  
      return stats
docs: Load multiple files from disk and generate stats
  
      Passes the list of files assuming the ding0 data structure as default in
      :code:`~/.ding0`.
      Data will be concatenated and key indicators for each grid district are
      returned in table and graphic format.
  
      Parameters
      ----------
      filenames : list of str
          Provide list of files you want to analyze
      base_path : str
          Root directory of Ding0 data structure, i.e. '~/.ding0' (which is
          default).
  
      Returns
      -------
      stats : pandas.DataFrame
          Statistics of each MV grid districts