我需要将DataFrame
列分成两部分,并在新列中添加一个附加值。我需要将原始列名提升一级并添加两个新列名。
给出一个DataFrame
h
:
>>> import pandas as pd
>>> h = pd.DataFrame({'a': [0.6, 0.4, 0.1], 'b': [0.2, 0.4, 0.7]})
>>> h
a b
0 0.6 0.2
1 0.4 0.4
2 0.1 0.7
我需要将原始列名提升一级并添加两个新列名。结果应如下所示:
>>> # some stuff...
a b
expected received expected received
0 0.6 1 0.2 1
1 0.4 1 0.4 1
2 0.1 1 0.7 1
我已经尝试过了:
>>> h['a1'] = [1, 1, 1]
>>> h['b1'] = [1, 1, 1]
>>> t = [('f', 'expected'),('f', 'received'), ('g', 'expected'), ('g', 'received')]
>>> h.columns = pd.MultiIndex.from_tuples(t)
>>> h
f g
expected received expected received
0 0.6 0.2 1 1
1 0.4 0.4 1 1
2 0.1 0.7 1 1
这只会重命名列,但无法正确对齐它们。我认为问题在于a1
和b1
与expected
和received
列之间没有链接。
如何将原始列名提升一级并添加两个新列名?
答案 0 :(得分:1)
我将concat
和keys
一起使用swaplevel
h1=h.copy()
h1[:]=1
pd.concat([h,h1],keys=['expected', 'received'],axis=1).\
swaplevel(0,1,axis=1).\
sort_index(level=0,axis=1)
Out[233]:
a b
expected received expected received
0 0.6 1.0 0.2 1.0
1 0.4 1.0 0.4 1.0
2 0.1 1.0 0.7 1.0