REGR: fix inplace operations for EAs with non-EA arg

doc/source/whatsnew/v1.1.5.rst

@@ -17,7 +17,7 @@ Fixed regressions
 - Regression in addition of a timedelta-like scalar to a :class:`DatetimeIndex` raising incorrectly (:issue:`37295`)
 - Fixed regression in :meth:`Series.groupby` raising when the :class:`Index` of the :class:`Series` had a tuple as its name (:issue:`37755`)
 - Fixed regression in :meth:`DataFrame.loc` and :meth:`Series.loc` for ``__setitem__`` when one-dimensional tuple was given to select from :class:`MultiIndex` (:issue:`37711`)
--
+- Fixed regression in inplace operations on :class:``ExtensionArray`` with NumPy array argument (:issue:`37910`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/generic.py

@@ -70,6 +70,7 @@
     is_datetime64_any_dtype,
     is_datetime64tz_dtype,
     is_dict_like,
+    is_dtype_equal,
     is_extension_array_dtype,
     is_float,
     is_list_like,
@@ -11266,7 +11267,11 @@ def _inplace_method(self, other, op):
         """
         result = op(self, other)
 
-        if self.ndim == 1 and result._indexed_same(self) and result.dtype == self.dtype:
+        if (
+            self.ndim == 1
+            and result._indexed_same(self)
+            and is_dtype_equal(result.dtype, self.dtype)
+        ):
             # GH#36498 this inplace op can _actually_ be inplace.
             self._values[:] = result._values
             return self

pandas/tests/series/methods/test_inplace_ops.py

@@ -0,0 +1,36 @@
+import pytest
+
+from pandas import Series
+import pandas._testing as tm
+
+
+@pytest.mark.parametrize(
+    "dtype1, dtype2, dtype_expected, dtype_mul",
+    (
+        ["Int64"] * 4,
+        ["float"] * 4,
+        ["Int64"] + ["float"] * 3,
+        pytest.param(
+            "Int64",
+            "Float64",
+            "Float64",
+            "Float64",
+            marks=pytest.mark.xfail(reason="Not implemented yet"),
+        ),
+    ),
+)
+def test_series_inplace_ops(dtype1, dtype2, dtype_expected, dtype_mul):
+
+    ser1 = Series([1], dtype=dtype1)
+    ser2 = Series([2], dtype=dtype2)
+    ser1 += ser2
+    expected = Series([3], dtype=dtype_expected)
+    tm.assert_series_equal(ser1, expected)
+
+    ser1 -= ser2
+    expected = Series([1], dtype=dtype_expected)
+    tm.assert_series_equal(ser1, expected)
+
+    ser1 *= ser2
+    expected = Series([2], dtype=dtype_mul)
+    tm.assert_series_equal(ser1, expected)