BUG: NumericArray.__pos__ should make a copy (#44492)

Author: jbrockmendel

pandas/core/arrays/numeric.py

@@ -168,7 +168,7 @@ def __neg__(self):
         return type(self)(-self._data, self._mask.copy())
 
     def __pos__(self):
-        return self
+        return self.copy()
 
     def __abs__(self):
         return type(self)(abs(self._data), self._mask.copy())

pandas/core/arrays/timedeltas.py

@@ -800,7 +800,7 @@ def __neg__(self) -> TimedeltaArray:
         return type(self)(-self._ndarray)
 
     def __pos__(self) -> TimedeltaArray:
-        return type(self)(self._ndarray, freq=self.freq)
+        return type(self)(self._ndarray.copy(), freq=self.freq)
 
     def __abs__(self) -> TimedeltaArray:
         # Note: freq is not preserved

pandas/tests/arrays/floating/test_arithmetic.py

@@ -200,4 +200,6 @@ def test_unary_float_operators(float_ea_dtype, source, neg_target, abs_target):
 
     tm.assert_extension_array_equal(neg_result, neg_target)
     tm.assert_extension_array_equal(pos_result, arr)
+    assert not np.shares_memory(pos_result._data, arr._data)
+    assert not np.shares_memory(pos_result._mask, arr._mask)
     tm.assert_extension_array_equal(abs_result, abs_target)

pandas/tests/arrays/integer/test_arithmetic.py

@@ -300,4 +300,6 @@ def test_unary_int_operators(any_signed_int_ea_dtype, source, neg_target, abs_ta
 
     tm.assert_extension_array_equal(neg_result, neg_target)
     tm.assert_extension_array_equal(pos_result, arr)
+    assert not np.shares_memory(pos_result._data, arr._data)
+    assert not np.shares_memory(pos_result._mask, arr._mask)
     tm.assert_extension_array_equal(abs_result, abs_target)

pandas/tests/arrays/test_timedeltas.py

@@ -99,9 +99,11 @@ def test_pos(self):
 
         result = +arr
         tm.assert_timedelta_array_equal(result, arr)
+        assert not np.shares_memory(result._ndarray, arr._ndarray)
 
         result2 = np.positive(arr)
         tm.assert_timedelta_array_equal(result2, arr)
+        assert not np.shares_memory(result2._ndarray, arr._ndarray)
 
     def test_neg(self):
         vals = np.array([-3600 * 10 ** 9, "NaT", 7200 * 10 ** 9], dtype="m8[ns]")