python - 在多索引数据框中插入列

Question

我有一个多索引数据框，我想在级别 1 中添加一列并将其分组到适当的级别 0 列中。当我分配新列时，它会将其附加到 df 的末尾。

In [28]: df
Out[28]: 
first        qux                 bar                 foo          
second       one       two       one       two       one       two
A      -0.563477 -0.032948 -0.131031  1.110537 -0.541374  0.760088
B      -1.767642 -1.305016 -0.786291 -0.396981  1.983372 -0.106018
C      -0.471136  0.616730  0.019877  0.910230  0.352304 -0.361370

In [29]: df['qux','three'] = [1,2,3]

In [30]: df
Out[30]: 
first        qux                 bar                 foo             qux
second       one       two       one       two       one       two three
A      -0.563477 -0.032948 -0.131031  1.110537 -0.541374  0.760088     1
B      -1.767642 -1.305016 -0.786291 -0.396981  1.983372 -0.106018     2
C      -0.471136  0.616730  0.019877  0.910230  0.352304 -0.361370     3

我希望它看起来像

first        qux                 bar                 foo           
second       one       two three      one       two       one       two
A      -0.563477 -0.032948     1 -0.131031  1.110537 -0.541374  0.760088
B      -1.767642 -1.305016     2 -0.786291 -0.396981  1.983372 -0.106018 
C      -0.471136  0.616730     3  0.019877  0.910230  0.352304 -0.361370

我尝试了 df.sort_index(axis=1,level=0)，它至少将 qux 分组在一起，但它按字母顺序排列了我的 0 级标题。我如何才能在不按字母顺序排列的情况下对常用列名称进行分组？

Answer 1

只需使用:

df = df[['qux', 'bar', 'foo']]

示例(不同的 DataFrame)

使用 documentation for MultiIndex 的修改版，这是与您的问题类似的问题:

import pandas as pd
import numpy as np

arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
   ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
df = pd.DataFrame(np.random.randn(8, 4), index=arrays)
df = df.T

# Here is your insertion
df['foo', 'three'] = range(4)

>>> df[['bar', 'qux', 'foo']]
    bar     qux     foo
    one     two     one     two     one     two     three
0   0.450777    -1.386835   0.423801    -0.386144   0.362138    2.566733    0
1   0.844537    2.466605    -0.093472   0.226886    0.633393    2.167570    1
2   1.655898    0.995926    0.097128    -0.351759   0.138233    1.099168    2
3   0.409964    -1.232129   1.112228    0.700660    -0.860548   0.219503    3