code: def _process_args_as_rows_or_columns(self, arg, unpack=False):
          
  
          flags = set()
          #
          if isinstance(arg, (tuple, list, numpy.ndarray)):
              # a sequence was entered
              if isstring(arg[0]):
                  result = arg
              else:
                  result = arg
                  flags.add('isrows')
          elif isstring(arg):
              # a single string was entered
              result = arg
          elif isinstance(arg, slice):
              if unpack:
                  flags.add('isrows')
                  result = self._slice2rows(arg.start, arg.stop, arg.step)
              else:
                  flags.add('isrows')
                  flags.add('isslice')
                  result = self._process_slice(arg)
          else:
              # a single object was entered.
              # Probably should apply some more checking on this
              result = arg
              flags.add('isrows')
              if numpy.ndim(arg) == 0:
                  flags.add('isscalar')
  
          return result, flags
docs: We must be able to interpret the args as as either a column name or
          row number, or sequences thereof.  Numpy arrays and slices are also
          fine.
  
          Examples:
              'field'
              35
              [35,55,86]
              ['f1',f2',...]
          Can also be tuples or arrays.