Grouper tweaks. (#10362)

dcherian · kmuehlbauer · web-flow · commit 42836f391d82 · 2025-05-30T09:02:28.000-06:00
Co-authored-by: Kai Mühlbauer &lt;kai.muehlbauer@uni-bonn.de&gt;
diff --git a/xarray/core/groupby.py b/xarray/core/groupby.py
@@ -387,7 +387,7 @@ def _parse_group_and_groupers(
 ) -> tuple[ResolvedGrouper, ...]:
     from xarray.core.dataarray import DataArray
     from xarray.core.variable import Variable
-    from xarray.groupers import UniqueGrouper
+    from xarray.groupers import Grouper, UniqueGrouper
 
     if group is not None and groupers:
         raise ValueError(
@@ -402,6 +402,13 @@ def _parse_group_and_groupers(
             f"`group` must be a DataArray. Received {type(group).__name__!r} instead"
         )
 
+    if isinstance(group, Grouper):
+        raise TypeError(
+            "Cannot group by a Grouper object. "
+            f"Instead use `.groupby(var_name={type(group).__name__}(...))`. "
+            "You may need to assign the variable you're grouping by as a coordinate using `assign_coords`."
+        )
+
     if isinstance(group, Mapping):
         grouper_mapping = either_dict_or_kwargs(group, groupers, "groupby")
         group = None
diff --git a/xarray/groupers.py b/xarray/groupers.py
@@ -186,7 +186,7 @@ class UniqueGrouper(Grouper):
         present in ``labels`` will be ignored.
     """
 
-    _group_as_index: pd.Index | None = field(default=None, repr=False)
+    _group_as_index: pd.Index | None = field(default=None, repr=False, init=False)
     labels: ArrayLike | None = field(default=None)
 
     @property
diff --git a/xarray/tests/test_groupby.py b/xarray/tests/test_groupby.py
@@ -757,6 +757,12 @@ def test_groupby_grouping_errors() -> None:
     with pytest.raises(ValueError, match=r"Failed to group data."):
         dataset.to_dataarray().groupby(dataset.foo * np.nan)
 
+    with pytest.raises(TypeError, match=r"Cannot group by a Grouper object"):
+        dataset.groupby(UniqueGrouper(labels=[1, 2, 3]))  # type: ignore[arg-type]
+
+    with pytest.raises(TypeError, match=r"got multiple values for argument"):
+        UniqueGrouper(dataset.x, labels=[1, 2, 3])  # type: ignore[misc]
+
 
 def test_groupby_reduce_dimension_error(array) -> None:
     grouped = array.groupby("y")
