handle numpy bool

doc/source/user_guide/boolean.rst

@@ -76,19 +76,4 @@ In ``and``
  pd.Series([True, False, np.nan], dtype="object") & True
  pd.Series([True, False, np.nan], dtype="boolean") & True
 
-
-.. warning::
-
- At the moment, NumPy's boolean scalars ``np.bool_(False)``
- and ``np.bool_(True)`` do not defer to :class:`arrays.BooleanArray`
- for binary operations. If the first argument of a logical operation
- is a ``np.bool_``, you'll get the wrong result.
-
- .. ipython:: python
-
- a = pd.array([True, False, pd.NA], dtype="boolean")
- a | np.bool_(True) # correct
- np.bool_(True) | a # incorrect!
-
-
 .. _Kleene Logic: https://en.wikipedia.org/wiki/Three-valued_logic#Kleene_and_Priest_logics

pandas/core/ops/dispatch.py

@@ -189,6 +189,9 @@ def maybe_dispatch_ufunc_to_dunder_op(
  "ge",
  "remainder",
  "matmul",
+ "or",
+ "xor",
+ "and",
  }
  aliases = {
  "subtract": "sub",
@@ -204,6 +207,9 @@ def maybe_dispatch_ufunc_to_dunder_op(
  "less_equal": "le",
  "greater": "gt",
  "greater_equal": "ge",
+ "bitwise_or": "or",
+ "bitwise_and": "and",
+ "bitwise_xor": "xor",
  }
 
  # For op(., Array) -> Array.__r{op}__

pandas/tests/arrays/test_boolean.py

@@ -454,16 +454,13 @@ def test_kleene_or_scalar(self, other, expected):
  expected = pd.array(expected, dtype="boolean")
  tm.assert_extension_array_equal(result, expected)
 
- if not isinstance(other, np.bool_):
- # NumPy scalars don't dispatch, so they give the wrong answer.
-
- result = other | a
- tm.assert_extension_array_equal(result, expected)
+ result = other | a
+ tm.assert_extension_array_equal(result, expected)
 
-  # ensure we haven't mutated anything inplace
-  tm.assert_extension_array_equal(
-  a, pd.array([True, False, None], dtype="boolean")
-  )
+ # ensure we haven't mutated anything inplace
+ tm.assert_extension_array_equal(
+ a, pd.array([True, False, None], dtype="boolean")
+ )
 
  def test_kleene_and(self):
  # A clear test of behavior.
@@ -502,15 +499,13 @@ def test_kleene_and_scalar(self, other, expected):
  expected = pd.array(expected, dtype="boolean")
  tm.assert_extension_array_equal(result, expected)
 
- if not isinstance(other, np.bool_):
- # NumPy scalars don't dispatch, so they give the wrong answer.
- result = other & a
- tm.assert_extension_array_equal(result, expected)
+ result = other & a
+ tm.assert_extension_array_equal(result, expected)
 
-  # ensure we haven't mutated anything inplace
-  tm.assert_extension_array_equal(
-  a, pd.array([True, False, None], dtype="boolean")
-  )
+ # ensure we haven't mutated anything inplace
+ tm.assert_extension_array_equal(
+ a, pd.array([True, False, None], dtype="boolean")
+ )
 
  def test_kleene_xor(self):
  a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")
@@ -547,15 +542,13 @@ def test_kleene_xor_scalar(self, other, expected):
  expected = pd.array(expected, dtype="boolean")
  tm.assert_extension_array_equal(result, expected)
 
- if not isinstance(other, np.bool_):
- # NumPy scalars don't dispatch, so they give the wrong answer.
- result = other ^ a
- tm.assert_extension_array_equal(result, expected)
+ result = other ^ a
+ tm.assert_extension_array_equal(result, expected)
 
-  # ensure we haven't mutated anything inplace
-  tm.assert_extension_array_equal(
-  a, pd.array([True, False, None], dtype="boolean")
-  )
+ # ensure we haven't mutated anything inplace
+ tm.assert_extension_array_equal(
+ a, pd.array([True, False, None], dtype="boolean")
+ )
 
  @pytest.mark.parametrize(
  "other",