def sortby(self, variables, ascending=True):
        """
        Sort object by labels or values (along an axis).

        Sorts the dataset, either along specified dimensions,
        or according to values of 1-D dataarrays that share dimension
        with calling object.

        If the input variables are dataarrays, then the dataarrays are aligned
        (via left-join) to the calling object prior to sorting by cell values.
        NaNs are sorted to the end, following Numpy convention.

        If multiple sorts along the same dimension is
        given, numpy's lexsort is performed along that dimension:
        https://docs.scipy.org/doc/numpy/reference/generated/numpy.lexsort.html
        and the FIRST key in the sequence is used as the primary sort key,
        followed by the 2nd key, etc.

        Parameters
        ----------
        variables: str, DataArray, or list of either
            1D DataArray objects or name(s) of 1D variable(s) in
            coords/data_vars whose values are used to sort the dataset.
        ascending: boolean, optional
            Whether to sort by ascending or descending order.

        Returns
        -------
        sorted: Dataset
            A new dataset where all the specified dims are sorted by dim
            labels.
        """
        from .dataarray import DataArray

        if not isinstance(variables, list):
            variables = [variables]
        else:
            variables = variables
        variables = [v if isinstance(v, DataArray) else self[v]
                     for v in variables]
        aligned_vars = align(self, *variables, join='left')
        aligned_self = aligned_vars[0]
        aligned_other_vars = aligned_vars[1:]
        vars_by_dim = defaultdict(list)
        for data_array in aligned_other_vars:
            if data_array.ndim != 1:
                raise ValueError("Input DataArray is not 1-D.")
            if (data_array.dtype == object and
                    LooseVersion(np.__version__) < LooseVersion('1.11.0')):
                raise NotImplementedError(
                    'sortby uses np.lexsort under the hood, which requires '
                    'numpy 1.11.0 or later to support object data-type.')
            (key,) = data_array.dims
            vars_by_dim[key].append(data_array)

        indices = {}
        for key, arrays in vars_by_dim.items():
            order = np.lexsort(tuple(reversed(arrays)))
            indices[key] = order if ascending else order[::-1]
        return aligned_self.isel(**indices)
Sort object by labels or values (along an axis).

        Sorts the dataset, either along specified dimensions,
        or according to values of 1-D dataarrays that share dimension
        with calling object.

        If the input variables are dataarrays, then the dataarrays are aligned
        (via left-join) to the calling object prior to sorting by cell values.
        NaNs are sorted to the end, following Numpy convention.

        If multiple sorts along the same dimension is
        given, numpy's lexsort is performed along that dimension:
        https://docs.scipy.org/doc/numpy/reference/generated/numpy.lexsort.html
        and the FIRST key in the sequence is used as the primary sort key,
        followed by the 2nd key, etc.

        Parameters
        ----------
        variables: str, DataArray, or list of either
            1D DataArray objects or name(s) of 1D variable(s) in
            coords/data_vars whose values are used to sort the dataset.
        ascending: boolean, optional
            Whether to sort by ascending or descending order.

        Returns
        -------
        sorted: Dataset
            A new dataset where all the specified dims are sorted by dim
            labels.