pandas join DataFrame force suffix?

pandas, python

Solution

You could force a suffix on the actual DataFrame:

In [11]: df_a = pd.DataFrame([[1], [2]], columns=['A'])

In [12]: df_b = pd.DataFrame([[3], [4]], columns=['B'])

In [13]: df_a.join(df_b)
Out[13]: 
   A  B
0  1  3
1  2  4

By appending to its column's names:

In [14]: df_a.columns = df_a.columns.map(lambda x: str(x) + '_a')

In [15]: df_a
Out[15]: 
   A_a
0    1
1    2

Now joins won't need the suffix correction, whether they collide or not:

In [16]: df_b.columns = df_b.columns.map(lambda x: str(x) + '_b')

In [17]: df_a.join(df_b)
Out[17]: 
   A_a  B_b
0    1    3
1    2    4

Problem

How can I force a suffix on a merge or join. I understand it's possible to provide one if there is a collision but in my case I'm merging df1 with df2 which doesn't cause any collision but then merging again on df2 which uses the suffixes but I would prefer for each merge to have a suffix because it gets confusing if I do different combinations as you could imagine.

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