How to create a multilevel dataframe in pandas?

Question

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

Solution 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

Solution 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

Comments

[Alex]

Why not just use MultiIndex.from_product() once on the resultant df? result = pd.concat([A, B], axis=1) result.columns = pd.MultiIndex.from_product([('A', 'B'), A.columns])

[Alex]

Also why isn't the first level of your columnar multi-index aligned the way it is in jezrael's answer?

[Psidom]

If the two data frames have different dimensions or different column names, use MultiIndex on the result won't work. The first level is aligned the same way as jezrael's answer, if you check the answer. I probably have indented differently here.

[alphazwest]

This works great for my, admittedly simple, use-case.