也许第 1 行有错别字：df["Usage_Per_Year "]？列名末尾有一个空格。

pd.cut 将值分成相等的大小。这就是为什么您的所有垃圾箱都具有相同大小的原因。看来您应该在分箱后计算每个组的最小值和最大值。

此外，要将值归入相等的频率，您应该使用 pd.qcut。

示例输入：

import numpy as np
import pandas as pd

rng = np.random.default_rng(20210514)
df = pd.DataFrame({
    'Miles_Driven_Per_Year': rng.gamma(1.05,10000,(1000,)).astype(int)
})

# 1
group_label = ['Low','Medium','High']
df['Usage_Per_Year'] = pd.cut(df['Miles_Driven_Per_Year'],bins=3,labels=group_label)

# 2
print(df.groupby('Usage_Per_Year').agg(['count','min','max']))

# 3
df['Usage_Per_Year'] = pd.qcut(df['Miles_Driven_Per_Year'],q=3,labels=group_label)

# 4
print(df.groupby('Usage_Per_Year').agg(['count','max']))

示例输出：

               Miles_Driven_Per_Year              
                               count    min    max
Usage_Per_Year                                    
Low                              878     31  20905
Medium                           107  20955  41196
High                              15  41991  62668
               Miles_Driven_Per_Year              
                               count    min    max
Usage_Per_Year                                    
Low                              334     31   4378
Medium                           333   4449  11424
High                             333  11442  62668