Prepend a level to a pandas MultiIndex

I have a DataFrame with a MultiIndex created after some grouping:

import numpy as np
import pandas as pd
from numpy.random import randn

df = pd.DataFrame({'A' : ['a1', 'a1', 'a2', 'a3'], 
                   'B' : ['b1', 'b2', 'b3', 'b4'], 
                   'Vals' : randn(4)}
                 ).groupby(['A', 'B']).sum()

#            Vals
# A  B           
# a1 b1 -1.632460
#    b2  0.596027
# a2 b3 -0.619130
# a3 b4 -0.002009

How do I prepend a level to the MultiIndex so that I turn it into something like:

#                       Vals
# FirstLevel A  B           
# Foo        a1 b1 -1.632460
#               b2  0.596027
#            a2 b3 -0.619130
#            a3 b4 -0.002009

Solution 1:

A nice way to do this in one line using pandas.concat():

import pandas as pd

pd.concat([df], keys=['Foo'], names=['Firstlevel'])

An even shorter way:

pd.concat({'Foo': df}, names=['Firstlevel'])

This can be generalized to many data frames, see the docs.

Solution 2:

You can first add it as a normal column and then append it to the current index, so:

df['Firstlevel'] = 'Foo'
df.set_index('Firstlevel', append=True, inplace=True)

And change the order if needed with:

df.reorder_levels(['Firstlevel', 'A', 'B'])

Which results in:

                      Vals
Firstlevel A  B           
Foo        a1 b1  0.871563
              b2  0.494001
           a2 b3 -0.167811
           a3 b4 -1.353409