code: def __prepare_dataset_parameter(self, dataset):
          
  
          # Translate the dataset argument into the proper type
          if not isinstance(dataset, _SFrame):
              def raise_dataset_type_exception():
                  raise TypeError("The dataset parameter must be either an SFrame, "
                                  "or a dictionary of (str : list) or (str : value).")
  
              if type(dataset) is dict:
                  if not all(type(k) is str for k in _six.iterkeys(dataset)):
                      raise_dataset_type_exception()
  
                  if all(type(v) in (list, tuple, _array.array) for v in _six.itervalues(dataset)):
                      dataset = _SFrame(dataset)
                  else:
                      dataset = _SFrame({k : [v] for k, v in _six.iteritems(dataset)})
              else:
                  raise_dataset_type_exception()
  
          return dataset
docs: Processes the dataset parameter for type correctness.
          Returns it as an SFrame.