Don't raise with nullable boolean

Author: Daniel Saxton

pandas/core/common.py

@@ -114,7 +114,6 @@ def is_bool_indexer(key: Any) -> bool:
     check_array_indexer : Check that `key` is a valid array to index,
         and convert to an ndarray.
     """
-    na_msg = "cannot mask with array containing NA / NaN values"
     if isinstance(key, (ABCSeries, np.ndarray, ABCIndex)) or (
         is_array_like(key) and is_extension_array_dtype(key.dtype)
     ):
@@ -127,11 +126,6 @@ def is_bool_indexer(key: Any) -> bool:
                 return False
             return True
         elif is_bool_dtype(key.dtype):
-            # an ndarray with bool-dtype by definition has no missing values.
-            # So we only need to check for NAs in ExtensionArrays
-            if is_extension_array_dtype(key.dtype):
-                if np.any(key.isna()):
-                    raise ValueError(na_msg)
             return True
     elif isinstance(key, list):
         try:

pandas/core/indexing.py

@@ -8,6 +8,8 @@
 from pandas.util._decorators import Appender
 
 from pandas.core.dtypes.common import (
+    is_bool_dtype,
+    is_extension_array_dtype,
     is_float,
     is_integer,
     is_iterator,
@@ -2229,6 +2231,11 @@ def check_bool_indexer(index: Index, key) -> np.ndarray:
                 "the indexed object do not match)."
             )
         result = result.astype(bool)._values
+    elif is_extension_array_dtype(key) and is_bool_dtype(key):
+        mask = isna(key)
+        if mask.any():
+            result[mask] = False
+        result = np.asarray(result, dtype=bool)
     else:
         # key might be sparse / object-dtype bool, check_array_indexer needs bool array
         result = np.asarray(result, dtype=bool)