Fix reduction by subset of grouper dimensions (pydata#10258)

Author: dcherian

xarray/core/groupby.py

@@ -78,7 +78,8 @@ def check_reduce_dims(reduce_dims, dimensions):
         if any(dim not in dimensions for dim in reduce_dims):
             raise ValueError(
                 f"cannot reduce over dimensions {reduce_dims!r}. expected either '...' "
-                f"to reduce over all dimensions or one or more of {dimensions!r}."
+                f"to reduce over all dimensions or one or more of {dimensions!r}. "
+                f"Alternatively, install the `flox` package. "
             )
 
 
@@ -1135,7 +1136,7 @@ def _flox_reduce(
         group_dims = set(grouper.group.dims)
         new_coords = []
         to_drop = []
-        if group_dims.issubset(set(parsed_dim)):
+        if group_dims & set(parsed_dim):
             for grouper in self.groupers:
                 output_index = grouper.full_index
                 if isinstance(output_index, pd.RangeIndex):

xarray/tests/test_groupby.py

@@ -1646,6 +1646,19 @@ def test_groupby_multidim(self) -> None:
             actual_sum = array.groupby(dim).sum(...)
             assert_identical(expected_sum, actual_sum)
 
+        if has_flox:
+            # GH9803
+            # reduce over one dim of a nD grouper
+            array.coords["labels"] = (("ny", "nx"), np.array([["a", "b"], ["b", "a"]]))
+            actual = array.groupby("labels").sum("nx")
+            expected_np = np.array([[[0, 1], [3, 2]], [[5, 10], [20, 15]]])
+            expected = xr.DataArray(
+                expected_np,
+                dims=("time", "ny", "labels"),
+                coords={"labels": ["a", "b"]},
+            )
+            assert_identical(expected, actual)
+
     def test_groupby_multidim_map(self) -> None:
         array = self.make_groupby_multidim_example_array()
         actual = array.groupby("lon").map(lambda x: x - x.mean())