REGR: Fix assignment bug for unary operators (#39971)

Author: dsaxton

doc/source/whatsnew/v1.2.3.rst

@@ -16,6 +16,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 
 - Fixed regression in :meth:`~DataFrame.to_excel` raising ``KeyError`` when giving duplicate columns with ``columns`` attribute (:issue:`39695`)
+- Fixed regression in :class:`IntegerArray` unary ops propagating mask on assignment (:issue:`39943`)
 - Fixed regression in :meth:`DataFrame.__setitem__` not aligning :class:`DataFrame` on right-hand side for boolean indexer (:issue:`39931`)
 
 .. ---------------------------------------------------------------------------

pandas/core/arrays/integer.py

@@ -316,13 +316,13 @@ def __init__(self, values: np.ndarray, mask: np.ndarray, copy: bool = False):
         super().__init__(values, mask, copy=copy)
 
     def __neg__(self):
-        return type(self)(-self._data, self._mask)
+        return type(self)(-self._data, self._mask.copy())
 
     def __pos__(self):
         return self
 
     def __abs__(self):
-        return type(self)(np.abs(self._data), self._mask)
+        return type(self)(np.abs(self._data), self._mask.copy())
 
     @classmethod
     def _from_sequence(

pandas/core/arrays/masked.py

@@ -172,7 +172,7 @@ def __len__(self) -> int:
         return len(self._data)
 
     def __invert__(self: BaseMaskedArrayT) -> BaseMaskedArrayT:
-        return type(self)(~self._data, self._mask)
+        return type(self)(~self._data, self._mask.copy())
 
     def to_numpy(
         self,

pandas/tests/arrays/masked/test_arithmetic.py

@@ -162,3 +162,16 @@ def test_error_len_mismatch(data, all_arithmetic_operators):
         s = pd.Series(data)
         with pytest.raises(ValueError, match="Lengths must match"):
             op(s, other)
+
+
+@pytest.mark.parametrize("op", ["__neg__", "__abs__", "__invert__"])
+@pytest.mark.parametrize(
+    "values, dtype", [([1, 2, 3], "Int64"), ([True, False, True], "boolean")]
+)
+def test_unary_op_does_not_propagate_mask(op, values, dtype):
+    # https://github.com/pandas-dev/pandas/issues/39943
+    s = pd.Series(values, dtype=dtype)
+    result = getattr(s, op)()
+    expected = result.copy(deep=True)
+    s[0] = None
+    tm.assert_series_equal(result, expected)