code: def load(fnames, tag='', sat_id=None):
      
  
      # Ensure that there are files to load
      if len(fnames) <= 0 :
          return pysat.DataFrame(None), pysat.Meta(None)
  
      # Ensure that the files are in a list
      if isinstance(fnames, str):
          fnames = [fnames]
  
      # Initialise the output data
      data = pds.DataFrame()
      baseline = list()
  
      # Cycle through the files
      for fname in fnames:
          fname = fname[:-11] # Remove date index from end of filename
          file_type = path.splitext(fname)[1].lower()
  
          # Open and load the files for each file type
          if file_type == ".csv":
              if tag != "indices":
                  temp = load_csv_data(fname, tag)
          else:
              temp, bline = load_ascii_data(fname, tag)
  
              if bline is not None:
                  baseline.append(bline)
  
          # Save the loaded data in the output data structure
          if len(temp.columns) > 0:
              data = pds.concat([data, temp], axis=0)
          del temp
  
      # If data was loaded, update the meta data
      if len(data.columns) > 0:
          meta = pysat.Meta()
          for cc in data.columns:
              meta[cc] = update_smag_metadata(cc)
  
          meta.info = {'baseline':format_baseline_list(baseline)}
      else:
          meta = pysat.Meta(None)
  
      return data, meta
docs: Load the SuperMAG files
  
      Parameters
      -----------
      fnames : (list)
          List of filenames
      tag : (str or NoneType)
          Denotes type of file to load.  Accepted types are 'indices', 'all',
          'stations', and '' (for just magnetometer measurements). (default='')
      sat_id : (str or NoneType)
          Satellite ID for constellations, not used. (default=None)
  
      Returns
      --------
      data : (pandas.DataFrame)
          Object containing satellite data
      meta : (pysat.Meta)
          Object containing metadata such as column names and units