如果有多索引，Pandas 将不允许选择列？

Question

我正在调试一些意外创建 MultiIndex 而不是常规索引的 pandas 代码。由于多索引，Pandas 不允许选择列。在这种情况下，我可以摆脱 MultiIndex，但如果我确实需要 MultiIndex，你如何选择一列？ 附加信息——我在使用 pandas 0.25.1 时遇到了这个错误，但这段代码是在几年前有人写的笔记本中，所以显然它曾经适用于旧版本？

import numpy as np
import pandas as pd

names = ['FirstColumn', 'SecondColumn']
data = np.array([[5,6],[7,8]])
df = pd.DataFrame(data, columns = [names]) #Bug: this "works" but isn't what you want.
#The brackets around "[names]" creates a multi-index but that was unintentional.
#But "df.head()" and "df.describe()" both look normal so you can't see anything is wrong. 

df['FirstColumn'] #ERROR! works fine with a single index, but fails with multiindex
df.FirstColumn #ERROR! works fine with a single index, but fails with multiindex
df.loc[:,'FirstColumn'] #ERROR! works fine with a single index, but fails with multiindex

这两个陈述都给出了关于 only integer scalar arrays can be converted to a scalar index 的误导性错误 那么当存在多索引时如何选择列呢？我知道一些技巧，例如unstack 或更改索引等；但似乎应该有一个简单的方法？

更新：原来这在 pandas 0.22.0 中运行良好，但在 0.25.1 中失败。看起来引入了回归错误。我已经在pandas github上报告了。

Answer 1

使用DataFrame.xs函数：

print (df.xs('FirstColumn', axis=1, level=0))
  FirstColumn
0           5
1           7