docs: 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