Backport PR #35794: BUG: issubclass check with dtype instead of type, closes GH#24883 (#35919)

Co-authored-by: jbrockmendel <[email protected]>

Author: simonjayhawkins

doc/source/whatsnew/v1.1.2.rst

@@ -24,7 +24,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
-
+- Bug in :meth:`DataFrame.eval` with ``object`` dtype column binary operations (:issue:`35794`)
 - Bug in :class:`Series` constructor raising a ``TypeError`` when constructing sparse datetime64 dtypes (:issue:`35762`)
 - Bug in :meth:`DataFrame.apply` with ``result_type="reduce"`` returning with incorrect index (:issue:`35683`)
 - Bug in :meth:`DateTimeIndex.format` and :meth:`PeriodIndex.format` with ``name=True`` setting the first item to ``"None"`` where it should bw ``""`` (:issue:`35712`)

pandas/core/computation/ops.py

@@ -481,13 +481,21 @@ def stringify(value):
             self.lhs.update(v)
 
     def _disallow_scalar_only_bool_ops(self):
+        rhs = self.rhs
+        lhs = self.lhs
+
+        # GH#24883 unwrap dtype if necessary to ensure we have a type object
+        rhs_rt = rhs.return_type
+        rhs_rt = getattr(rhs_rt, "type", rhs_rt)
+        lhs_rt = lhs.return_type
+        lhs_rt = getattr(lhs_rt, "type", lhs_rt)
         if (
-            (self.lhs.is_scalar or self.rhs.is_scalar)
+            (lhs.is_scalar or rhs.is_scalar)
             and self.op in _bool_ops_dict
             and (
                 not (
-                    issubclass(self.rhs.return_type, (bool, np.bool_))
-                    and issubclass(self.lhs.return_type, (bool, np.bool_))
+                    issubclass(rhs_rt, (bool, np.bool_))
+                    and issubclass(lhs_rt, (bool, np.bool_))
                 )
             )
         ):

pandas/tests/frame/test_query_eval.py

@@ -160,6 +160,13 @@ def test_eval_resolvers_as_list(self):
         assert df.eval("a + b", resolvers=[dict1, dict2]) == dict1["a"] + dict2["b"]
         assert pd.eval("a + b", resolvers=[dict1, dict2]) == dict1["a"] + dict2["b"]
 
+    def test_eval_object_dtype_binop(self):
+        # GH#24883
+        df = pd.DataFrame({"a1": ["Y", "N"]})
+        res = df.eval("c = ((a1 == 'Y') & True)")
+        expected = pd.DataFrame({"a1": ["Y", "N"], "c": [True, False]})
+        tm.assert_frame_equal(res, expected)
+
 
 class TestDataFrameQueryWithMultiIndex:
     def test_query_with_named_multiindex(self, parser, engine):