def reduce(self, func, dim=None, keep_attrs=None, **kwargs):
        """Reduce the items in this group by applying `func` along some
        dimension(s).

        Parameters
        ----------
        func : function
            Function which can be called in the form
            `func(x, axis=axis, **kwargs)` to return the result of collapsing
            an np.ndarray over an integer valued axis.
        dim : str or sequence of str, optional
            Dimension(s) over which to apply `func`.
        axis : int or sequence of int, optional
            Axis(es) over which to apply `func`. Only one of the 'dimension'
            and 'axis' arguments can be supplied. If neither are supplied, then
            `func` is calculated over all dimension for each group item.
        keep_attrs : bool, optional
            If True, the datasets's attributes (`attrs`) will be copied from
            the original object to the new one.  If False (default), the new
            object will be returned without attributes.
        **kwargs : dict
            Additional keyword arguments passed on to `func`.

        Returns
        -------
        reduced : Array
            Array with summarized data and the indicated dimension(s)
            removed.
        """
        if dim == DEFAULT_DIMS:
            dim = ALL_DIMS
            # TODO change this to dim = self._group_dim after
            # the deprecation process. Do not forget to remove _reduce_method
            warnings.warn(
                "Default reduction dimension will be changed to the "
                "grouped dimension in a future version of xarray. To "
                "silence this warning, pass dim=xarray.ALL_DIMS "
                "explicitly.",
                FutureWarning, stacklevel=2)
        elif dim is None:
            dim = self._group_dim

        if keep_attrs is None:
            keep_attrs = _get_keep_attrs(default=False)

        def reduce_dataset(ds):
            return ds.reduce(func, dim, keep_attrs, **kwargs)
        return self.apply(reduce_dataset)