Concatenate specific pairs of columns in a dataframe based on a reference dataframe with a different index

Question

My goal is to concatenate columns in a dataframe(Source), based on pairs that are described in a separate dataframe(Reference). The resulting dataframe should replace the c

Answer 1

There will likely be better solutions, but at least this one is working:

import pandas as pd

df1 = pd.DataFrame({'FIRST': pd.Series(['Alpha', 'Alpha', 'Charlie'],
                                       index=['H1', 'H2',  'H3']),
                    'SECOND': pd.Series(['Bravo', 'Delta', 'Delta'],
                                        index=['H1', 'H2', 'H3'])})

df2 = pd.DataFrame({'Alpha' : pd.Series(['A', 'C'], index = ['item-000', 'item-111']),
                    'Bravo' : pd.Series(['A', 'C'], index = ['item-000', 'item-111']),
                    'Delta' : pd.Series(['T', 'C'], index = ['item-000', 'item-111']),
                    'Charlie' : pd.Series(['T', 'G'], index = ['item-000', 'item-111'])})

pd.concat((df1.T.apply(lambda x: x.map(df2.loc[idx]).str.cat())
           for idx in df2.index),
          axis=1).rename_axis(pd.Series(df2.index), axis=1).T

Out[]:
          H1  H2  H3
item-000  AA  AT  TT
item-111  CC  CC  GC

Of course this relies on both a for loop in the iterator and an apply, so it will not be very efficient.