Fix query on coordinate-only datasets

doc/whats-new.rst

@@ -170,6 +170,9 @@ Deprecations
 
 Bug Fixes
 ~~~~~~~~~
+- :py:meth:`Dataset.query` now resolves coordinates in datasets with no data
+  variables (:issue:`6449`).
+  By `Liang, Jingyi <https://github.com/LJimmy007>`_.
 - Results of the string accessor methods ``strip``, ``pad``, ``center``,
   ``ljust``, ``rjust``, ``zfill`` and ``replace`` on dask arrays are no longer
   truncated to a single character, and ``repeat`` no longer fails on dask arrays

xarray/core/dataset.py

@@ -10025,9 +10025,12 @@ def query(
                 msg = f"expr for dim {dim} must be a string to be evaluated, {type(expr)} given"
                 raise ValueError(msg)
 
-        # evaluate the queries to create the indexers
+        # Include coords so pandas considers the resolvers nonempty even when
+        # there are no data variables.
         indexers = {
-            dim: pd.eval(expr, resolvers=[self], parser=parser, engine=engine)
+            dim: pd.eval(
+                expr, resolvers=[self, self.coords], parser=parser, engine=engine
+            )
             for dim, expr in queries.items()
         }
 

xarray/tests/test_dataset.py

@@ -37,7 +37,7 @@
 from xarray.core.common import duck_array_ops, full_like
 from xarray.core.coordinates import Coordinates, DatasetCoordinates
 from xarray.core.indexes import Index, PandasIndex
-from xarray.core.types import ArrayLike
+from xarray.core.types import ArrayLike, QueryEngineOptions, QueryParserOptions
 from xarray.core.utils import is_scalar
 from xarray.groupers import SeasonResampler, TimeResampler
 from xarray.namedarray.pycompat import array_type, integer_types
@@ -7933,11 +7933,18 @@ def test_astype_attrs(self) -> None:
         assert not data.astype(float, keep_attrs=False).attrs
         assert not data.astype(float, keep_attrs=False).var1.attrs
 
+    @pytest.mark.parametrize("coords_only", [False, True])
     @pytest.mark.parametrize("parser", ["pandas", "python"])
     @pytest.mark.parametrize(
         "engine", ["python", None, pytest.param("numexpr", marks=[requires_numexpr])]
     )
-    def test_query(self, use_dask: bool, engine, parser) -> None:
+    def test_query(
+        self,
+        use_dask: bool,
+        engine: QueryEngineOptions,
+        parser: QueryParserOptions,
+        coords_only: bool,
+    ) -> None:
         """Test querying a dataset."""
         # setup test data
         np.random.seed(42)
@@ -7992,6 +7999,9 @@ def test_query(self, use_dask: bool, engine, parser) -> None:
                 },
             )
 
+        if coords_only:
+            ds = ds.set_coords(list(ds.data_vars))
+
         # query single dim, single variable
         with raise_if_dask_computes():
             actual = ds.query(x="a2 > 5", engine=engine, parser=parser)
@@ -8084,6 +8094,17 @@ def test_query(self, use_dask: bool, engine, parser) -> None:
             expect = ds.isel(dict(x=(a > 5), y=(c < 0.5), z=(d == "bar")))
             assert_identical(expect, actual)
 
+        # query a dimension without a coordinate
+        with raise_if_dask_computes():
+            actual = ds.query(x="x > 5", engine=engine, parser=parser)
+        assert_identical(ds.isel(x=slice(6, None)), actual)
+
+        # query a dimension coordinate
+        ds = ds.assign_coords(x=a + 10)
+        with raise_if_dask_computes():
+            actual = ds.query(x="x > 15", engine=engine, parser=parser)
+        assert_identical(ds.isel(x=slice(6, None)), actual)
+
         # test error handling
         with pytest.raises(ValueError):
             ds.query("a > 5")  # type: ignore[arg-type] # must be dict or kwargs