REGR: inplace Series op not actually operating inplace (pandas-dev#37508

)

doc/source/whatsnew/v1.1.4.rst

@@ -30,6 +30,7 @@ Fixed regressions
 - Fixed regression in setitem with :meth:`DataFrame.iloc` which raised error when trying to set a value while filtering with a boolean list (:issue:`36741`)
 - Fixed regression in setitem with a Series getting aligned before setting the values (:issue:`37427`)
 - Fixed regression in :attr:`MultiIndex.is_monotonic_increasing` returning wrong results with ``NaN`` in at least one of the levels (:issue:`37220`)
+- Fixed regression in inplace arithmetic operation on a Series not updating the parent DataFrame (:issue:`36373`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/generic.py

@@ -11115,6 +11115,11 @@ def _inplace_method(self, other, op):
         """
         result = op(self, other)
 
+        if self.ndim == 1 and result._indexed_same(self) and result.dtype == self.dtype:
+            # GH#36498 this inplace op can _actually_ be inplace.
+            self._values[:] = result._values
+            return self
+
         # Delete cacher
         self._reset_cacher()
 

pandas/tests/frame/test_arithmetic.py

@@ -1698,3 +1698,16 @@ def test_arith_list_of_arraylike_raise(to_add):
         df + to_add
     with pytest.raises(ValueError, match=msg):
         to_add + df
+
+
+def test_inplace_arithmetic_series_update():
+    # https://github.com/pandas-dev/pandas/issues/36373
+    df = DataFrame({"A": [1, 2, 3]})
+    series = df["A"]
+    vals = series._values
+
+    series += 1
+    assert series._values is vals
+
+    expected = DataFrame({"A": [2, 3, 4]})
+    tm.assert_frame_equal(df, expected)

pandas/tests/indexing/test_loc.py

@@ -888,6 +888,7 @@ def test_identity_slice_returns_new_object(self):
         original_series[:3] = [7, 8, 9]
         assert all(sliced_series[:3] == [7, 8, 9])
 
+    @pytest.mark.xfail(reason="accidental fix reverted - GH37497")
     def test_loc_copy_vs_view(self):
         # GH 15631
         x = DataFrame(zip(range(3), range(3)), columns=["a", "b"])