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I using pandas for deep learning. I have a data like this.

a   b   c  
0   [1] [1,2]  
1   [2] [3,4]  
0   [3] [5,6]   
1   [1] [1,2]  
1   [2] [3,4]

I want to remove just thing that not duplicate a columns & duplciate b,c columns.
Like this.

a   b   c  
1   [2] [3,4]  
0   [3] [5,6]     
1   [2] [3,4]

I used drop_duplicate(subset['b','c'], keep=False]
But result isn't that I want.

a   b   c  
0   [3] [5,6]

How can I remove this?
It's different remove all duplicate.
I want to remove just "same 2 columns but different 1 columns".

azzyjk
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  • Does this answer your question? [Drop all duplicate rows across multiple columns in Python Pandas](https://stackoverflow.com/questions/23667369/drop-all-duplicate-rows-across-multiple-columns-in-python-pandas) – Let's try Aug 12 '20 at 09:38
  • Try `keep = True` – Let's try Aug 12 '20 at 09:38
  • No I want to remove all "not duplicate `a` columns & duplciate `b`,`c` columns." If I use `keep = True` data remove one raw & remain one raw. I want to remove all. – azzyjk Aug 12 '20 at 09:43
  • You should include `a` in your `drop_duplicate` – Let's try Aug 12 '20 at 09:45
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    You mean `drop_duplicate(subset['a', 'b', 'c'], keep=False)` or I just must to remove all duplciates? – azzyjk Aug 12 '20 at 09:49

0 Answers0