使用分层列创建DataFrame [英] Creating DataFrame with Hierarchical Columns

问题描述

使用分层列创建DataFrame的最简单方法是什么?

What is the easiest way to create a DataFrame with hierarchical columns?

我当前正在使用以下命令从名称字典-> Series创建一个DataFrame:

I am currently creating a DataFrame from a dict of names -> Series using:

df = pd.DataFrame(data=serieses)

我想使用相同的列名，但在列上添加一个更高级别的层次结构.我暂时希望其他级别的列具有相同的值，例如估算".

I would like to use the same columns names but add an additional level of hierarchy on the columns. For the time being I want the additional level to have the same value for columns, let's say "Estimates".

我正在尝试以下操作，但这似乎不起作用:

I am trying the following but that does not seem to work:

pd.DataFrame(data=serieses,columns=pd.MultiIndex.from_tuples([(x, "Estimates") for x in serieses.keys()]))

我得到的是一个带有所有NaN的DataFrame.

All I get is a DataFrame with all NaNs.

例如，我要寻找的大致是:

For example, what I am looking for is roughly:

l1               Estimates    
l2  one  two  one  two  one  two  one  two
r1   1    2    3    4    5    6    7    8
r2   1.1  2    3    4    5    6    71   8.2

其中l1和l2是MultiIndex的标签

where l1 and l2 are the labels for the MultiIndex

推荐答案

这似乎有效:

import pandas as pd

data = {'a': [1,2,3,4], 'b': [10,20,30,40],'c': [100,200,300,400]}

df = pd.concat({"Estimates": pd.DataFrame(data)}, axis=1, names=["l1", "l2"])

l1  Estimates         
l2          a   b    c
0           1  10  100
1           2  20  200
2           3  30  300
3           4  40  400

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