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]),
         ],