Convert this rolling object to xr.Dataset,
        where the window dimension is stacked as a new dimension

        Parameters
        ----------
        window_dim: str
            New name of the window dimension.
        stride: integer, optional
            size of stride for the rolling window.
        fill_value: optional. Default dtypes.NA
            Filling value to match the dimension size.

        Returns
        -------
        Dataset with variables converted from rolling object.

def construct(self, window_dim, stride=1, fill_value=dtypes.NA):
        """
        Convert this rolling object to xr.Dataset,
        where the window dimension is stacked as a new dimension

        Parameters
        ----------
        window_dim: str
            New name of the window dimension.
        stride: integer, optional
            size of stride for the rolling window.
        fill_value: optional. Default dtypes.NA
            Filling value to match the dimension size.

        Returns
        -------
        Dataset with variables converted from rolling object.
        """

        from .dataset import Dataset

        dataset = OrderedDict()
        for key, da in self.obj.data_vars.items():
            if self.dim in da.dims:
                dataset[key] = self.rollings[key].construct(
                    window_dim, fill_value=fill_value)
            else:
                dataset[key] = da
        return Dataset(dataset, coords=self.obj.coords).isel(
            **{self.dim: slice(None, None, stride)})