Raise for NaN

Author: TomAugspurger

pandas/core/arrays/boolean.py

@@ -286,7 +286,7 @@ def __getitem__(self, item):
 
  def _coerce_to_ndarray(self, force_bool: bool = False):
  """
- Coerce to an ndarary of object dtype or bool dtype (if force_bool=True).
+ Coerce to an ndarray of object dtype or bool dtype (if force_bool=True).
 
  Parameters
  ----------
@@ -743,9 +743,9 @@ def boolean_arithmetic_method(self, other):
 
 
 def kleene_or(
- left: Union[bool, np.nan, np.ndarray],
- right: Union[bool, np.nan, np.ndarary],
- left_mask: Optional[np.ndarary],
+ left: Union[bool, np.ndarray],
+ right: Union[bool, np.ndarray],
+ left_mask: Optional[np.ndarray],
  right_mask: Optional[np.ndarray],
 ):
  """
@@ -772,8 +772,7 @@ def kleene_or(
  if left_mask is None:
  return kleene_or(right, left, right_mask, left_mask)
 
- assert left_mask is not None
- right_is_scalar = right_mask is None
+ raise_for_nan(right, method="or")
 
  mask = left_mask
 
@@ -783,11 +782,11 @@ def kleene_or(
  mask = mask.copy()
 
  # handle scalars:
- if right_is_scalar and np.isnan(right): # TODO(pd.NA): change to NA
- result = left.copy()
- mask = left_mask.copy()
- mask[~result] = True
- return result, mask
+ # if right_is_scalar and right is libmissing.NA:
+ #  result = left.copy()
+ #  mask = left_mask.copy()
+ #  mask[~result] = True
+ #  return result, mask
 
  # XXX: verify that this doesn't assume masked values are False!
  result = left | right
@@ -798,9 +797,9 @@ def kleene_or(
 
 
 def kleene_xor(
- left: Union[bool, np.nan, np.ndarray],
- right: Union[bool, np.nan, np.ndarary],
- left_mask: Optional[np.ndarary],
+ left: Union[bool, np.ndarray],
+ right: Union[bool, np.ndarray],
+ left_mask: Optional[np.ndarray],
  right_mask: Optional[np.ndarray],
 ):
  """
@@ -826,29 +825,30 @@ def kleene_xor(
  if left_mask is None:
  return kleene_xor(right, left, right_mask, left_mask)
 
- # Re-use or, and update with adustments.
+ raise_for_nan(right, method="xor")
+ # Re-use or, and update with adjustments.
  result, mask = kleene_or(left, right, left_mask, right_mask)
 
- # TODO(pd.NA): change to pd.NA
- if lib.is_scalar(right) and right is np.nan:
- # True | NA == True
- # True ^ NA == NA
- mask[result] = True
- else:
-  # XXX: verify that this doesn't assume masked values are False!
-  result[left & right] = False
-  mask[right & left_mask] = True
-  if right_mask is not None:
-  mask[left & right_mask] = True
+ # # TODO(pd.NA): change to pd.NA
+ # if lib.is_scalar(right) and right is libmissing.NA:
+ #  # True | NA == True
+ #  # True ^ NA == NA
+ #  mask[result] = True
+
+ # XXX: verify that this doesn't assume masked values are False!
+ result[left & right] = False
+ mask[right & left_mask] = True
+ if right_mask is not None:
+ mask[left & right_mask] = True
 
  result[mask] = False
  return result, mask
 
 
 def kleene_and(
- left: Union[bool, np.nan, np.ndarray],
- right: Union[bool, np.nan, np.ndarary],
- left_mask: Optional[np.ndarary],
+ left: Union[bool, np.ndarray],
+ right: Union[bool, np.ndarray],
+ left_mask: Optional[np.ndarray],
  right_mask: Optional[np.ndarray],
 ):
  """
@@ -871,6 +871,7 @@ def kleene_and(
  if left_mask is None:
  return kleene_and(right, left, right_mask, left_mask)
 
+ raise_for_nan(right, method="and")
  mask = left_mask
 
  if right_mask is not None:
@@ -882,6 +883,7 @@ def kleene_and(
  result = left.copy()
  mask = left_mask.copy()
  if np.isnan(right):
+ # TODO(pd.NA): change to NA
  mask[result] = True
  else:
  result = result & right # already copied.
@@ -898,6 +900,11 @@ def kleene_and(
  return result, mask
 
 
+def raise_for_nan(value, method):
+ if lib.is_scalar(value) and isinstance(value, float) and np.isnan(value):
+ raise ValueError(f"Cannot perform logical '{method}' with NaN")
+
+
 BooleanArray._add_logical_ops()
 BooleanArray._add_comparison_ops()
 BooleanArray._add_arithmetic_ops()

pandas/tests/arrays/test_boolean.py

@@ -374,6 +374,14 @@ def test_logical_length_mismatch_raises(self, all_logical_operators):
  with pytest.raises(ValueError, match=msg):
  getattr(a, op_name)(pd.array([True, False], dtype="boolean"))
 
+ def test_logical_nan_raises(self, all_logical_operators):
+ op_name = all_logical_operators
+ a = pd.array([True, False, None], dtype="boolean")
+ msg = ""
+
+ with pytest.raises(ValueError, match=msg):
+ getattr(a, op_name)(np.nan)
+
  def test_kleene_or(self):
  # A clear test of behavior.
  a = pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")
@@ -390,7 +398,7 @@ def test_kleene_or(self):
  @pytest.mark.parametrize(
  "other, expected",
  [
- (np.nan, [True, None, None]),
+ # (pd.NA, [True, None, None]),
  (True, [True, True, True]),
  (False, [True, False, None]),
  ],
@@ -421,7 +429,7 @@ def test_kleene_and(self):
  @pytest.mark.parametrize(
  "other, expected",
  [
- (np.nan, [None, False, None]),
+ # (pd.NA, [None, False, None]),
  (True, [True, False, None]),
  (False, [False, False, False]),
  ],
@@ -450,7 +458,7 @@ def test_kleene_xor(self):
  @pytest.mark.parametrize(
  "other, expected",
  [
- (np.nan, [None, None, None]),
+ # (pd.NA, [None, None, None]),
  (True, [False, True, None]),
  (False, [True, False, None]),
  ],