Python 熊猫分组索引在2行和3行中表现不同

我有两个数据帧df1和df2。它们的格式相同，唯一的区别是第一行有3行，第二行有2行

df1 = pd.DataFrame({
    'Company': ['Foo Inc.', 'Foo Inc.', 'Foo Inc.'],
    'ID': ['123456', '123456', '123456'],
    'Employee': ['John Doe', 'Richard Roe', 'Jane Doe'],
    'Position': ['Executive Director', 'Director', 'Company Secretary']
})

df2 = pd.DataFrame({
    'Company': ['Bar Inc.', 'Bar Inc.'],
    'ID': ['56789', '56789'],
    'Employee': ['Mark Moe', 'Larry Loe'],
    'Position': ['Tax Consultant', 'Company Secretary']
})

print(df1)
    Company     Employee      ID            Position
0  Foo Inc.     John Doe  123456  Executive Director
1  Foo Inc.  Richard Roe  123456            Director
2  Foo Inc.     Jane Doe  123456   Company Secretary

print(df2)
    Company   Employee     ID           Position
0  Bar Inc.   Mark Moe  56789     Tax Consultant
1  Bar Inc.  Larry Loe  56789  Company Secretary

当我试着做下面的事情时，它对第一个有效，但对第二个无效

gb1 = df1.set_index(['Company', 'ID', 'Employee']).groupby(['Company', 'ID'])
gb2 = df2.set_index(['Company', 'ID', 'Employee']).groupby(['Company', 'ID'])

for (name, id), new_df in gb1:
    print(name)
    print(id)

for (name, id), new_df in gb2:
    print(name)
    print(id)

Foo Inc.
123456

      3     print(id)
      4
----> 5 for (name, id), new_df in gb2:
      6     print(name)
      7     print(id)

ValueError: too many values to unpack (expected 2)

这是因为它们的指数不同

gb1.indices
>>> {('Foo Inc.', '123456'): array([0, 1, 2], dtype=int64)}

gb2.indices
>>> {'Company': array([0], dtype=int64), 'ID': array([1], dtype=int64)}

---

我错过什么了吗？这是一个错误吗？

当你

设置索引时，你是
groupby
索引
不再是列，因此你可以添加
level=
，
groupby
索引
而不使用
level
会发生什么事情

gb2 = df2.set_index(['Company', 'ID', 'Employee']).groupby(level=['Company', 'ID'])
for (name, id), new_df in gb2:
    print(name)
    print(id)

Bar Inc.
56789