如何将列添加到多索引DataFrame？

Question

我有一个像这样的DataFrame:

upper    level1    level2 
lower    name      name
1        Mary      Tom
2        ...       ...

如果我想添加另一列,我该怎么办level1？例如

upper    level1       level2 
lower    name    age  name
1        Mary    13   Tom
2        ...    ...    ...

我可以访问数据df['level1'].loc[:,'name'],但我不知道如何添加/删除列.

如果我只是使用df.level1['age']=1,Python会返回一个复制警告,并且DataFrame中没有任何更改:

SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
if __name__ == '__main__':

Answer 1

试试这个:

df.insert(1, ('level1', 'age'), pd.Series([13]))

Answer 2

您可以在作业中使用元组：

In [11]: df[('level1', 'age')] = 13  # or a Series here, rather than a number

In [12]: df
Out[12]:
  upper level1 level2 level1
  lower   name   name    age
0     1   Mary    Tom     13
1     2    ...    ...     13