How to do join of multiindex dataframe with a single index dataframe?

Question

The single index of df1 matches with a sublevel of multiindex of df2. Both have the same columns. I want to copy all rows and columns of df1 to df2.

It is similar to thi

Answer 1

This feels a little too manual, but in practice I might do something like this:

In [46]: mult[:] = sngl.loc[mult.index.get_level_values(2)].values

In [47]: mult
Out[47]: 
             one       two     three      four
10 1 a  1.175042  0.044014  1.341404 -0.223872
     b  0.216168 -0.748194 -0.546003 -0.501149
   2 a  1.175042  0.044014  1.341404 -0.223872
     b  0.216168 -0.748194 -0.546003 -0.501149
20 1 a  1.175042  0.044014  1.341404 -0.223872
     b  0.216168 -0.748194 -0.546003 -0.501149
   2 a  1.175042  0.044014  1.341404 -0.223872
     b  0.216168 -0.748194 -0.546003 -0.501149

That is, first select the elements we want to use to index:

In [64]: mult.index.get_level_values(2)
Out[64]: Index(['a', 'b', 'a', 'b', 'a', 'b', 'a', 'b'], dtype='object')

Then use these to index into sngl:

In [65]: sngl.loc[mult.index.get_level_values(2)]
Out[65]: 
        one       two     three      four
a  1.175042  0.044014  1.341404 -0.223872
b  0.216168 -0.748194 -0.546003 -0.501149
a  1.175042  0.044014  1.341404 -0.223872
b  0.216168 -0.748194 -0.546003 -0.501149
a  1.175042  0.044014  1.341404 -0.223872
b  0.216168 -0.748194 -0.546003 -0.501149
a  1.175042  0.044014  1.341404 -0.223872
b  0.216168 -0.748194 -0.546003 -0.501149

and then we can use .values to throw away the indexing information and just get the raw array to fill with.

It's not very elegant, but it's straightforward.