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Create Pandas DataFrame from 2 tuple lists with common first elements

I currently have 2 lists of tuples, both of which have the same information on the first element of the tuple. I’m trying to see if there is a way to “Join” these two tuple lists in a dataframe based on their common elements. Something like an SQL JOIN on a common column.

Lists are something like this:

listA = [(0, A), (1, B), (2, C)]
listB = [(0, G), (1, H), (2, I)]

and what I’m trying to achieve is a dataframe that looks something like this:

Col1  Col2  Col3
 0      A     G
 1      B     H
 2      C     I

Ideally, I dont want to “extract” the first element of a single list into a separete one and use that as the first column. I really want this “Join on the common column” functionality. The reason being that Im not sure that the tuples match on every single place and so I would like that be cared for automatically (like in SQL).


Try this,


import pandas as pd

l1 = [(0, 'A'), (1, 'B'), (2, 'C')]
l2 = [(0, 'G'), (1, 'H'), (2, 'I')]
ur_lists = [l1, l2]

list_of_dfs = [pd.DataFrame(data, columns=['key', f'col{idx}']) 
               for idx, data in enumerate(ur_lists)]
dfs = [df.set_index('key') for df in list_of_dfs]
pd.concat(dfs, axis=1).reset_index()


   key col0 col1    
    0   A   G
    1   B   H
    2   C   I