Dropping rows from Pandas DataFrame using specific criteria?

Asked Jun 24 '19 at 18:40

Active Jun 24 '19 at 18:43

Viewed 22 times

I currently have a DataFrame with 3 columns: SLR, NAME and OID, which looks something like this:

SLR  NAME  OID 
5    A     1   
5    B     2   
6    A     1   
6    B     2   
7    A     1   
7    B     2   
7    C     3

What I am trying to do is delete/drop any rows where NAME and OID match, and where the one that is kept has the lowest SLR value. Using the above table, the result should look something like:

  SLR  NAME  OID 
    5    A     1   
    5    B     2        
    7    C     3

I've searched all over and messed around with the df.drop_duplicates() commands, but haven't gotten anywhere. Any ideas?

asked Jun 24 '19 at 18:40

Jared

2

`df.sort_values('SLR').drop_duplicates(['NAME', 'OID'])` – cs95 Jun 24 '19 at 18:42
https://stackoverflow.com/questions/12497402/python-pandas-remove-duplicates-by-columns-a-keeping-the-row-with-the-highest – harvpan Jun 24 '19 at 18:44
In particular, see https://stackoverflow.com/a/53880282/2336654 – piRSquared Jun 24 '19 at 18:45

Dropping rows from Pandas DataFrame using specific criteria?

0 Answers0