def quantile(psser: 'Series') -> Column:
    spark_type = psser.spark.data_type
    spark_column = psser.spark.column
    if isinstance(spark_type, (BooleanType, NumericType)):
        return F.percentile_approx(spark_column.cast(DoubleType()), qq, accuracy)
    else:
        raise TypeError('Could not convert {} ({}) to numeric'.format(spark_type_to_pandas_dtype(spark_type), spark_type.simpleString()))
def quantile(psser: 'Series') -> Column:
    spark_type = psser.spark.data_type
    spark_column = psser.spark.column
    if isinstance(spark_type, (BooleanType, NumericType)):
        return F.percentile_approx(spark_column.cast(DoubleType()), qq, accuracy)
    else:
        raise TypeError('Could not convert {} ({}) to numeric'.format(spark_type_to_pandas_dtype(spark_type), spark_type.simpleString()))