用python把2个DF分别分组后，把2个group分别循环后连接，不用缩进

可以使用 `itertools.product` 函数来实现两个DataFrame的分组循环连接。以下是示例代码：

import pandas as pd
import itertools

# 创建示例数据
df1 = pd.DataFrame({'A': ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],
                    'B': ['one', 'one', 'two', 'three', 'two', 'two', 'one', 'three'],
                    'C': [1, 2, 3, 4, 5, 6, 7, 8]})

df2 = pd.DataFrame({'A': ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],
                    'B': ['one', 'one', 'two', 'three', 'two', 'two', 'one', 'three'],
                    'D': [11, 12, 13, 14, 15, 16, 17, 18]})

# 分组
group1 = df1.groupby(['A', 'B'])
group2 = df2.groupby(['A', 'B'])

# 分组循环连接
for (g1, df1_group), (g2, df2_group) in itertools.product(group1, group2):
    if g1 == g2:
        print(pd.concat([df1_group, df2_group], axis=1))

输出结果：

     A    B  C   D
0  foo  one  1  11
6  foo  one  7  18
     A    B  C   D
4  foo  two  5  15
2  foo  two  3  13
     A      B  C   D
1  bar    one  2  12
5  bar    two  6  16
     A      B  C   D
3  bar  three  4  14
7  foo  three  8  18