Fix Dataset.map to handle non-DataArray outputs

After PR pydata#10602, Dataset.map started failing when functions returned
non-DataArray values (e.g., scalars), raising AttributeError when
trying to access .coords on the returned values.

This restores backward compatibility by converting non-DataArray
outputs to DataArrays, which was the behavior before the regression.

Fixes pydata#10835

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: max-sixty

xarray/core/dataset.py

@@ -6923,12 +6923,19 @@ def map(
             foo      (dim_0, dim_1) float64 48B 1.764 0.4002 0.9787 2.241 1.868 0.9773
             bar      (x) float64 16B 1.0 2.0
         """
+        from xarray.core.dataarray import DataArray
+
         if keep_attrs is None:
             keep_attrs = _get_keep_attrs(default=False)
         variables = {
             k: maybe_wrap_array(v, func(v, *args, **kwargs))
             for k, v in self.data_vars.items()
         }
+        # Convert non-DataArray values to DataArrays
+        variables = {
+            k: v if isinstance(v, DataArray) else DataArray(v)
+            for k, v in variables.items()
+        }
         coord_vars, indexes = merge_coordinates_without_align(
             [v.coords for v in variables.values()]
         )

xarray/tests/test_dataset.py

@@ -6268,6 +6268,31 @@ def func(arr):
         ds["x"].attrs["y"] = "x"
         assert ds["x"].attrs != actual["x"].attrs
 
+    def test_map_non_dataarray_outputs(self) -> None:
+        # Test that map handles non-DataArray outputs by converting them
+        # Regression test for GH10835
+        ds = xr.Dataset({"foo": ("x", [1, 2, 3]), "bar": ("y", [4, 5])})
+
+        # Scalar output
+        result = ds.map(lambda x: 1)
+        expected = xr.Dataset({"foo": 1, "bar": 1})
+        assert_identical(result, expected)
+
+        # Numpy array output with same shape
+        result = ds.map(lambda x: x.values)
+        expected = ds.copy()
+        assert_identical(result, expected)
+
+        # Mixed: some return scalars, some return arrays
+        def mixed_func(x):
+            if "x" in x.dims:
+                return 42
+            return x
+
+        result = ds.map(mixed_func)
+        expected = xr.Dataset({"foo": 42, "bar": ("y", [4, 5])})
+        assert_identical(result, expected)
+
     def test_apply_pending_deprecated_map(self) -> None:
         data = create_test_data()
         data.attrs["foo"] = "bar"