我有一个价格值的数字数组。我想对这个参数进行分类，所以我想创建一定数量的具有相同粒度的类。我想创建一个通用函数，给定数组和类数，我希望它自动返回这些类的价格区间。目前这是我的价格属性：

df_cleaned.price.describe()
>>>
count    122668.000000
mean      11253.349594
std        7856.513917
min        1010.000000
25%        4995.000000
50%        8995.000000
75%       15965.000000
max       34991.000000
Name: price, dtype: float64

我手动创建了一个函数来创建 6 个类，它看起来像这样：

def normalize_price(df): 
    cond = [
        (df['price'] >= 1000) & (df['price'] <= 4999),
        (df['price'] >= 5000) & (df['price'] <= 8999),
        (df['price'] >= 9000) & (df['price'] <= 15999),
        (df['price'] >= 16000) & (df['price'] <= 24999), 
        (df['price'] >= 25000) & (df['price'] <= 34000),
        (df['price'] >= 34001) & (df['price'] <= 40000) 
    ]

    choice = [
        1000,
        5000,
        9000,
        16000,
        25000,
        35000,
    ]

    df['price'] = np.select(cond, choice, df['price'])
    return df

谁能帮我即兴发挥这个功能？请谢谢