REGR: Fix IntegerArray unary ops regression

doc/source/whatsnew/v1.1.3.rst

@@ -14,7 +14,7 @@ including other versions of pandas.
 
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
--
+- Fixed regression in :class:`IntegerArray` unary plus and minus operations raising a ``TypeError`` (:issue:`36063`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/arrays/integer.py

@@ -364,6 +364,9 @@ def __init__(self, values: np.ndarray, mask: np.ndarray, copy: bool = False):
             )
         super().__init__(values, mask, copy=copy)
 
+    def __neg__(self):
+        return type(self)(0 - self._data, self._mask)
+
     @classmethod
     def _from_sequence(cls, scalars, dtype=None, copy: bool = False) -> "IntegerArray":
         return integer_array(scalars, dtype=dtype, copy=copy)

pandas/core/generic.py

@@ -1408,13 +1408,9 @@ def __neg__(self):
 
     def __pos__(self):
         values = self._values
-        if is_bool_dtype(values):
+        if is_bool_dtype(values) or is_numeric_dtype(values):
             arr = values
-        elif (
-            is_numeric_dtype(values)
-            or is_timedelta64_dtype(values)
-            or is_object_dtype(values)
-        ):
+        elif is_timedelta64_dtype(values) or is_object_dtype(values):
             arr = operator.pos(values)
         else:
             raise TypeError(f"Unary plus expects numeric dtype, not {values.dtype}")

pandas/tests/series/test_arithmetic.py

@@ -687,3 +687,27 @@ def test_datetime_understood(self):
         result = series - offset
         expected = pd.Series(pd.to_datetime(["2011-12-26", "2011-12-27", "2011-12-28"]))
         tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize("dtype", ["Int64", "Int32", "Int16", "Int8"])
+    @pytest.mark.parametrize(
+        "source, target",
+        [
+            ([1, 2, 3], [-1, -2, -3]),
+            ([1, 2, None], [-1, -2, None]),
+            ([-1, 0, 1], [1, 0, -1]),
+        ],
+    )
+    def test_unary_minus_nullable_int(self, dtype, source, target):
+        s = pd.Series(source, dtype=dtype)
+        result = -s
+        expected = pd.Series(target, dtype=dtype)
+        tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize("dtype", ["Int64", "Int32", "Int16", "Int8"])
+    @pytest.mark.parametrize(
+        "source", [[1, 2, 3], [1, 2, None], [-1, 0, 1]],
+    )
+    def test_unary_plus_nullable_int(self, dtype, source):
+        expected = pd.Series(source, dtype=dtype)
+        result = +expected
+        tm.assert_series_equal(result, expected)