python - Pandas 多索引 DataFrame 为每个索引添加子索引

Question

我有一个带有“bar”和“baz”行的多索引数据框，每一行都有一行“一”和“二”。我现在想在每一行“bar”和“foo”中添加一行“三”。
有没有一种优雅的方式来做到这一点？
例如:

import pandas as pd
import numpy as np

arrays = [["bar", "bar", "baz", "baz"],
          ["one", "two", "one", "two"]]

tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=["first", "second"])
df = pd.DataFrame(np.random.randn(3, 4), index=["A", "B", "C"], columns=index)

In [38]: df
Out[38]: 
first        bar                 baz          
second       one       two       one       two
A       0.357392 -1.880279  0.099014  1.354570
B       0.474572  0.442074 -1.173530 -1.362059
C      -0.980140 -0.173440 -1.490654 -0.539123

我想要这样的东西:

first        bar                           baz                    
second       one       two     three       one       two     three
A      -0.096890  0.012150       nan -0.749569 -0.965033       nan
B      -0.854206  0.118473       nan  0.263058 -0.025849       nan
C      -0.688007 -0.258569       nan  0.127305 -0.955044       nan

Answer 1

我不知道它有多像 Python，但有两种方法可以做到这一点:简单替换和使用插入。

换人

df[('bar','three')] = np.NaN
df[('baz','three')] = np.NaN 

插入

df.insert(2,('bar','three'),np.NaN)
df.insert(5,('baz','three'),np.NaN)
first                   bar                     baz
second  one     two     three   one     two     three
A   -0.973338   -0.233507   NaN     0.777288    -2.282688   NaN
B   -0.377486   0.080627    NaN     0.401302    0.355696    NaN
C   0.481056    0.651335    NaN     0.161145    1.001937    NaN