BUG: Allow using numpy in DataFrame.eval and DataFrame.query via @-notation (#58057)

* Allow @np to be used within df.eval and df.query

Add additional check to make sure that ndim of the provided
variable is an int. This makes sure that the ndim guard doesn't
trigger if it is something else (e.g., a function in case of a
numpy). This allow for using @np in df.eval and df.query methods.

* Add whatsnew

* Fix typo

Co-authored-by: Abdulaziz Aloqeely <[email protected]>

* Test: skip checking names due to inconsistencies between OSes

* Elaborate futher on whatsnew message

* Fix the test by explicitly specifing engine.

Also move the test to more appropriate file.

---------

Co-authored-by: Abdulaziz Aloqeely <[email protected]>

Author: domsmrz

doc/source/whatsnew/v3.0.0.rst

@@ -338,6 +338,7 @@ Bug fixes
 - Fixed bug in :class:`SparseDtype` for equal comparison with na fill value. (:issue:`54770`)
 - Fixed bug in :meth:`.DataFrameGroupBy.median` where nat values gave an incorrect result. (:issue:`57926`)
 - Fixed bug in :meth:`DataFrame.cumsum` which was raising ``IndexError`` if dtype is ``timedelta64[ns]`` (:issue:`57956`)
+- Fixed bug in :meth:`DataFrame.eval` and :meth:`DataFrame.query` which caused an exception when using NumPy attributes via ``@`` notation, e.g., ``df.eval("@np.floor(a)")``. (:issue:`58041`)
 - Fixed bug in :meth:`DataFrame.join` inconsistently setting result index name (:issue:`55815`)
 - Fixed bug in :meth:`DataFrame.to_string` that raised ``StopIteration`` with nested DataFrames. (:issue:`16098`)
 - Fixed bug in :meth:`DataFrame.transform` that was returning the wrong order unless the index was monotonically increasing. (:issue:`57069`)

pandas/core/computation/ops.py

@@ -115,7 +115,7 @@ def _resolve_name(self):
         res = self.env.resolve(local_name, is_local=is_local)
         self.update(res)
 
-        if hasattr(res, "ndim") and res.ndim > 2:
+        if hasattr(res, "ndim") and isinstance(res.ndim, int) and res.ndim > 2:
             raise NotImplementedError(
                 "N-dimensional objects, where N > 2, are not supported with eval"
             )

pandas/tests/frame/test_query_eval.py

@@ -188,6 +188,16 @@ def test_eval_object_dtype_binop(self):
         expected = DataFrame({"a1": ["Y", "N"], "c": [True, False]})
         tm.assert_frame_equal(res, expected)
 
+    def test_using_numpy(self, engine, parser):
+        # GH 58041
+        skip_if_no_pandas_parser(parser)
+        df = Series([0.2, 1.5, 2.8], name="a").to_frame()
+        res = df.eval("@np.floor(a)", engine=engine, parser=parser)
+        expected = np.floor(df["a"])
+        if engine == "numexpr":
+            expected.name = None  # See GH 58069
+        tm.assert_series_equal(expected, res)
+
 
 class TestDataFrameQueryWithMultiIndex:
     def test_query_with_named_multiindex(self, parser, engine):