pandas.api.indexers.check_bool_array_indexer¶

pandas.api.indexers.check_bool_array_indexer(array: ~AnyArrayLike, mask: ~AnyArrayLike) → numpy.ndarray[source]¶

Check if mask is a valid boolean indexer for array.

array and mask are checked to have the same length, and the dtype is validated.

New in version 1.0.0.

Parameters

arrayarray: The array that’s being masked.
maskarray: The boolean array that’s masking.

Returns

numpy.ndarray: The validated boolean mask.

Raises

IndexError: When the lengths don’t match.
ValueError: When mask cannot be converted to a bool-dtype ndarray.

See also

api.types.is_bool_dtype: Check if key is of boolean dtype.

Examples

A boolean ndarray is returned when the arguments are all valid.

>>> mask = pd.array([True, False])
>>> arr = pd.array([1, 2])
>>> pd.api.extensions.check_bool_array_indexer(arr, mask)
array([ True, False])

An IndexError is raised when the lengths don’t match.

>>> mask = pd.array([True, False, True])
>>> pd.api.extensions.check_bool_array_indexer(arr, mask)
Traceback (most recent call last):
...
IndexError: Item wrong length 3 instead of 2.

A ValueError is raised when the mask cannot be converted to a bool-dtype ndarray.

>>> mask = pd.array([True, pd.NA])
>>> pd.api.extensions.check_bool_array_indexer(arr, mask)
Traceback (most recent call last):
...
ValueError: cannot convert to bool numpy array in presence of missing values