让我们使用Pandascut来基于bin对cumsum列进行分类

s  = df['sum'].iat[0] 

df['class'] = pd.cut(
    df['cumsum'], bins=[0, s * .95, s * .975, s],
    labels=[1, 2, 3], include_lowest=True
)

如果需要按代码分组，则按唯一代码组应用分类功能

def categorize(g):
   s  = g['sum'].iat[0] 
   return pd.cut(
        g['cumsum'], 
        bins=[0, s * .95, s * .975, s],
        labels=[1, 2, 3], include_lowest=True
    ) 

df['class'] =  df.groupby('Code', group_keys=False).apply(categorize)

结果

Code  Notes    Qty    sum  cumsum class
4302      AGA   2A2K  14323  30613   14323     1
4301      AGA   2A1K   4810  30613   19133     1
4303      AGA   2A4K   4180  30613   23313     1
4306      AGA   2A5K   3759  30613   27072     1
4307      AGA   2A7K   1472  30613   28544     1
4304      AGA   2A8K    783  30613   29327     2
4311      AGA   2A9K    571  30613   29898     3
4310      AGA  2A10K    243  30613   30141     3
4312      AGA  2A11K    139  30613   30280     3

你可以通过这个尝试代码实现你的目标解决方案：

import pandas as pd

data = {'Code': ['AGA', 'AGA', 'AGA', 'AGA', 'AGA', 'AGA', 'AGA', 'AGA', 'AGA'],
        'Notes': ['2A2K', '2A1K', '2A4K', '2A5K', '2A7K', '2A8K', '2A9K', '2A10K', '2A11K'],
        'Qty': [14323, 4810, 4180, 3759, 1472, 783, 571, 243, 139],
        'sum': [30613, 30613, 30613, 30613, 30613, 30613, 30613, 30613, 30613],
        'cumsum': [14323, 19133, 23313, 27072, 28544, 29327, 29898, 30141, 30280]}

df = pd.DataFrame(data)

df['class'] = 0

cumsum_95 = df['sum'][0] * 0.95
cumsum_97_5 = df['sum'][0] * 0.975

class_1 = df[df['cumsum'] <= cumsum_95].index
class_2 = df[(df['cumsum'] > cumsum_95) & (df['cumsum'] <= cumsum_97_5)].index

df.loc[class_1, 'class'] = 1
df.loc[class_2, 'class'] = 2
df.loc[df['cumsum'] > cumsum_97_5, 'class'] = 3

print(df)

• • 结果：**

Code  Notes    Qty    sum  cumsum  class
0      AGA   2A2K  14323  30613   14323      1
1      AGA   2A1K   4810  30613   19133      1
2      AGA   2A4K   4180  30613   23313      1
3      AGA   2A5K   3759  30613   27072      1
4      AGA   2A7K   1472  30613   28544      1
5      AGA   2A8K    783  30613   29327      2
6      AGA   2A9K    571  30613   29898      3
7      AGA  2A10K    243  30613   30141      3
8      AGA  2A11K    139  30613   30280      3