熊猫自我加入非独特的价值观

Question

I have the following table:

       ind_ID  pair_ID orig_data
0           A        1         W 
1           B        1         X
2           C        2         Y
3           D        2         Z
4           A        3         W          
5           C        3         X          
6           B        4         Y          
7           D        4         Z          

Each row has an individual_ID , and a pair_ID that it shares with exactly one other row. I want to do a self join, so that every row has its original data, and the data of the row it shares a pair_ID with:

       ind_ID  pair_ID orig_data partner_data
0           A        1         W            X
1           B        1         X            W
2           C        2         Y            Z
3           D        2         Z            Y
4           A        3         W            X
5           C        3         X            W
6           B        4         Y            Z
7           D        4         Z            Y

I have tried:

df.join(df, on='pair_ID')

But obviously since pair_ID values are not unique I get:

       ind_ID  pair_ID orig_data partner_data
0           A        1         W          NaN
1           B        1         X          NaN
2           C        2         Y          NaN
3           D        2         Z          NaN
4           A        3         W          NaN
5           C        3         X          NaN
6           B        4         Y          NaN
7           D        4         Z          NaN 

I've also thought about creating a new column that concatenates ind_ID+pair_ID which would be unique, but then the join would not know what to match on.

Is it possible to do a self-join on pair_ID where each row is joined with the matching row that is not itself?

Answer 1

In your case (with only two pairs) - you can probably just groupby and transform based on the ID, and just reverse the order of the values in the group, eg:

df.loc[:, 'partner_data'] = df.groupby('pair_ID').orig_data.transform(lambda L: L[::-1])

Which gives you:

  ind_ID  pair_ID orig_data partner_ID
0      A        1         W          X
1      B        1         X          W
2      C        2         Y          Z
3      D        2         Z          Y
4      A        3         W          X
5      C        3         X          W
6      B        4         Y          Z
7      D        4         Z          Y