这基本上打印出整个表，但我不确定您希望如何构造子组的打印。
但无论如何它可能会帮助你

for name, group in df.groupby("id"):
    print("id", name)
    for idx, row in group.iterrows():
        print("\trow index", idx, "color", row.color, "value", row.value)

打印

id 1
    row index 0 color Red value 20
    row index 1 color Red value 25
    row index 2 color Blue value 20
    row index 3 color Blue value 15
    row index 4 color Green value 5
id 2
    row index 5 color Red value 100
    row index 6 color Blue value 20
    row index 7 color Blue value 220
    row index 8 color Blue value 120
    row index 9 color Blue value 20
    row index 10 color Green value 220
    row index 11 color Green value 120
    row index 12 color Green value 45
    row index 13 color Green value 2
    row index 14 color Green value 5

编辑：

for name, group in df.groupby("id"):
    print("id", name)
    for color, subgroup in group.groupby("color"):
        print("\t", color, list(subgroup["value"]))

给予

id 1
     Blue [20, 15]
     Green [5]
     Red [20, 25]
id 2
     Blue [20, 220, 120, 20]
     Green [220, 120, 45, 2, 5]
     Red [100]

你在找那个吗？

import pandas as pd
import numpy as np

data = pd.read_excel('test.csv.xlsx')

id_list = list(data['id'].unique())
color_list = list(data['color'].unique())

for i in id_list :
    for j in color_list :
    count = (data['color'][(data['color'] == j) & (data['id'] == i )]).count()
    print (f"The count of {j} in ID {i} is equal to {count}")

输出：

The count of Red in ID 1 is equal to 2 
The count of Blue in ID 1 is equal to 2
The count of Green in ID 1 is equal to 1
The count of Red in ID 2 is equal to 1
The count of Blue in ID 2 is equal to 4
The count of Green in ID 2 is equal to 5