<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def assign(self, variables=None, **variables_kwargs):
 """Assign new data variables to a Dataset, returning a new object with all the original variables in addition to the new ones. Parameters variables : mapping, value pairs Mapping from variables names to the new values. If the new values are callable, they are computed on the Dataset and assigned to new data variables. If the values are not callable, (e.g. a DataArray, scalar, or array), they are simply assigned. **variables_kwargs: The keyword arguments form of ``variables``. One of variables or variables_kwarg must be provided. Returns ------- ds : Dataset A new Dataset with the new variables in addition to all the existing variables. Notes ----- Since ``kwargs`` is a dictionary, the order of your arguments may not be preserved, and so the order of the new variables is not well defined. Assigning multiple variables within the same ``assign`` is possible, but you cannot reference other variables created within the same ``assign`` call. See Also -------- pandas.DataFrame.assign """

        variables = either_dict_or_kwargs(
            variables, variables_kwargs, 'assign')
        data = self.copy()
        # do all calculations first...
        results = data._calc_assign_results(variables)
        # ... and then assign
        data.update(results)
        return data