BUG: Allow using numpy in DataFrame.eval and DataFrame.query via @-notation (pandas-dev#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: 2 people

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):