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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _values_for_factorize(self) -> Tuple[np.ndarray, Any]: """ Return an array and missing value suitable for factorization. Returns ------- values : ndarray An array suitable for factorization. This should maintain order and be a supported dtype (Float64, Int64, UInt64, String, Object). By default, the extension array is cast to object dtype. na_value : object The value in `values` to consider missing. This will be treated as NA in the factorization routines, so it will be coded as `na_sentinal` and not included in `uniques`. By default, ``np.nan`` is used. Notes ----- The values returned by this method are also used in :func:`pandas.util.hash_pandas_object`. """

        return self.astype(object), np.nan