updating tests

Author: Laurent Mutricy

pandas/conftest.py

@@ -1448,6 +1448,21 @@ def complex_dtype(request):
     return request.param
 
 
+@pytest.fixture(params=tm.COMPLEX_DTYPES + tm.FLOAT_NUMPY_DTYPES)
+def complex_or_float_dtype(request):
+    """
+    Parameterized fixture for complex and numpy float dtypes.
+
+    * complex
+    * 'complex64'
+    * 'complex128'
+    * float
+    * 'float32'
+    * 'float64'
+    """
+    return request.param
+
+
 @pytest.fixture(params=tm.SIGNED_INT_NUMPY_DTYPES)
 def any_signed_int_numpy_dtype(request):
     """

pandas/core/computation/ops.py

@@ -18,7 +18,6 @@
 
 from pandas.core.dtypes.common import (
     is_list_like,
-    is_numeric_dtype,
     is_scalar,
 )
 

pandas/tests/computation/test_eval.py

@@ -758,16 +758,25 @@ class TestTypeCasting:
     # maybe someday... numexpr has too many upcasting rules now
     # chain(*(np.core.sctypes[x] for x in ['uint', 'int', 'float']))
     @pytest.mark.parametrize("left_right", [("df", "3"), ("3", "df")])
-    def test_binop_typecasting(self, engine, parser, op, float_numpy_dtype, left_right):
-        df = DataFrame(
-            np.random.default_rng(2).standard_normal((5, 3)), dtype=float_numpy_dtype
-        )
+    def test_binop_typecasting(
+        self, engine, parser, op, complex_or_float_dtype, left_right, request
+    ):
+        # GH#21374
+        dtype = complex_or_float_dtype
+        df = DataFrame(np.random.default_rng(2).standard_normal((5, 3)), dtype=dtype)
         left, right = left_right
         s = f"{left} {op} {right}"
         res = pd.eval(s, engine=engine, parser=parser)
-        assert df.values.dtype == float_numpy_dtype
-        assert res.values.dtype == float_numpy_dtype
-        tm.assert_frame_equal(res, eval(s))
+        if dtype == "complex64" and engine == "numexpr":
+            mark = pytest.mark.xfail(
+                reason="numexpr issue with complex that are upcast "
+                "to complex 128 "
+                "https://github.com/pydata/numexpr/issues/492"
+            )
+            request.node.add_marker(mark)
+        assert df.values.dtype == dtype
+        assert res.values.dtype == dtype
+        tm.assert_frame_equal(res, eval(s), check_exact=False)
 
 
 # -------------------------------------

pandas/tests/frame/test_query_eval.py

@@ -206,7 +206,7 @@ def test_extension_array_eval(self, engine, parser):
         # GH#58748
         df = DataFrame({"a": pd.array([1, 2, 3]), "b": pd.array([4, 5, 6])})
         result = df.eval("a / b", engine=engine, parser=parser)
-        expected = Series([0.25, 0.40, 0.50])
+        expected = Series(pd.array([0.25, 0.40, 0.50]))
         tm.assert_series_equal(result, expected)