当两列重复时删除，但根据第三列的值保留（熊猫）

Question

I'm looking at a way in which to remove all rows which are duplicated on Barcode and Product No., but to keep those duplicated rows when it was their latest Input. Example below:

What I have:

Input ID	Barcode	Product No.
001	225	111
001	225	111
001	225	111
002	225	111
002	225	111
002	225	111
002	225	111
003	226	222
003	226	222
004	226	222
004	226	222
005	227	222
005	227	222
006	227	222
006	227	222

Output:

Input ID	Barcode	Product No.
002	225	111
002	225	111
002	225	111
002	225	111
004	226	222
004	226	222
006	227	222
006	227	222

You can see where the Barcode and Product no. are the same all but the highest Input ID rows have now been removed leaving only duplicates which have the latest input.

Thanks Oli

Answer 1

You could run duplicated to identify the last duplicate and extend the selection per group using groupby + transform('any') :

df[((~df[['Product No.', 'Barcode']].duplicated(keep='last'))
   .groupby(df['Input ID']).transform('any'))]

output:

    Input ID  Barcode  Product No.
3          2      225          111
4          2      225          111
5          2      225          111
6          2      225          111
9          4      226          222
10         4      226          222
13         6      227          222
14         6      227          222