Returned accidentally removed update note, modified test_add_frame to remove double negative

Author: eicchen

doc/source/whatsnew/v3.0.0.rst

@@ -1082,6 +1082,7 @@ MultiIndex
 - :meth:`MultiIndex.insert` would not insert NA value correctly at unified location of index -1 (:issue:`59003`)
 - :func:`MultiIndex.get_level_values` accessing a :class:`DatetimeIndex` does not carry the frequency attribute along (:issue:`58327`, :issue:`57949`)
 - Bug in :class:`DataFrame` arithmetic operations in case of unaligned MultiIndex columns (:issue:`60498`)
+- Bug in :class:`DataFrame` arithmetic operations with :class:`Series` in case of unaligned MultiIndex (:issue:`61009`)
 - Bug in :class:`DataFrame` arithmetic operations with :class:`Series` now works with ``fill_value`` parameter (:issue:`61581`)
 - Bug in :meth:`MultiIndex.union` raising when indexes have duplicates with differing names (:issue:`62059`)
 - Bug in :meth:`MultiIndex.from_tuples` causing wrong output with input of type tuples having NaN values (:issue:`60695`, :issue:`60988`)

pandas/tests/arithmetic/test_string.py

@@ -257,14 +257,15 @@ def test_add_strings(any_string_dtype, request):
     tm.assert_frame_equal(result, expected)
 
 
-@pytest.mark.xfail(reason="GH-28527")
-def test_add_frame(request, dtype):
-    if dtype.storage == "python":
-        # Inconsistent behavior between different versions of the python engine.
-        # Some return correctly, some return but with the wrong dtype
-        # Others just fail, we are blanket failing all
-        mark = pytest.mark.xfail(reason="[XPASS(strict)] GH-28527")
-        request.node.applymarker(mark)
+def test_add_frame(any_string_dtype, request):
+    # Inconsistent behavior between different versions of the python engine.
+    # Environments without PyArrow correctly return the value for python storage
+    # The same does not hold for
+    dtype = any_string_dtype
+    if HAS_PYARROW or getattr(dtype, "storage", None) != "python":
+        marks = pytest.mark.xfail(reason="GH-28527")
+        request.applymarker(marks)
+
     arr = pd.array(["a", "b", np.nan, np.nan], dtype=dtype)
     df = pd.DataFrame([["x", np.nan, "y", np.nan]])
     assert arr.__add__(df) is NotImplemented