How to create a multilevel dataframe in pandas?

问题

Given two different df's:

'A'

            a  b         
2016-11-21  2  1
2016-11-22  3  4
2016-11-23  5  2 
2016-11-24  6  3 
2016-11-25  6  3

'B'

            a  b         
2016-11-21  3  0
2016-11-22  1  0
2016-11-23  1  6 
2016-11-24  1  5 
2016-11-25  0  2

How can I create a 'multilevel' dataframe of this shape:

'C'

            A     B
            a  b  a  b           
2016-11-21  2  1  3  0
2016-11-22  3  4  1  0
2016-11-23  5  2  1  6
2016-11-24  6  3  1  5
2016-11-25  6  3  0  2

*index is a 'datatime' object

Thanks

回答1:

One option is to use MultiIndex() to construct the columns level for A and B and then concatenate them:

import pandas as pd
A.columns = pd.MultiIndex.from_product([['A'], A.columns])
B.columns = pd.MultiIndex.from_product([['B'], B.columns])
pd.concat([A, B], axis = 1)

#           A       B
#           a   b   a   b
#2016-11-21 2   1   3   0
#2016-11-22 3   4   1   0
#2016-11-23 5   2   1   6
#2016-11-24 6   3   1   5
#2016-11-25 6   3   0   2

回答2:

You can use concat with parameter keys:

df = pd.concat([A, B], axis = 1, keys=(list('AB')))
print (df)
            A     B   
            a  b  a  b
2016-11-21  2  1  3  0
2016-11-22  3  4  1  0
2016-11-23  5  2  1  6
2016-11-24  6  3  1  5
2016-11-25  6  3  0  2

来源：https://stackoverflow.com/questions/40820017/how-to-create-a-multilevel-dataframe-in-pandas