>> pd.array([1, 1, pd.NA]).all()
        True
        >>> pd.array([True, False, pd.NA]).all()
        False
        >>> pd.array([], dtype="boolean").all()
        True
        >>> pd.array([pd.NA], dtype="boolean").all()
        True
        >>> pd.array([pd.NA], dtype="Float64").all()
        True

        With ``skipna=False``, the result can be NA if this is logically
        required (whether ``pd.NA`` is True or False influences the result):

        >>> pd.array([True, True, pd.NA]).all(skipna=False)
        <NA>
        >>> pd.array([1, 1, pd.NA]).all(skipna=False)
        <NA>
        >>> pd.array([True, False, pd.NA]).all(skipna=False)
        False
        >>> pd.array([1, 0, pd.NA]).all(skipna=False)
        False
        rQ