Drop duplicates of one column based on value in another column, Python, Pandas

Viewed 10905

I have a dataframe like this:

Date                PlumeO      Distance
2014-08-13 13:48:00  754.447905 5.844577 
2014-08-13 13:48:00  754.447905 6.888653
2014-08-13 13:48:00  754.447905 6.938860
2014-08-13 13:48:00  754.447905 6.977284
2014-08-13 13:48:00  754.447905 6.946430 
2014-08-13 13:48:00  754.447905 6.345506
2014-08-13 13:48:00  754.447905 6.133567
2014-08-13 13:48:00  754.447905 5.846046 
2014-08-13 16:59:00  754.447905 6.345506 
2014-08-13 16:59:00  754.447905 6.694847 
2014-08-13 16:59:00  754.447905 5.846046 
2014-08-13 16:59:00  754.447905 6.977284 
2014-08-13 16:59:00  754.447905 6.938860 
2014-08-13 16:59:00  754.447905 5.844577 
2014-08-13 16:59:00  754.447905 6.888653 
2014-08-13 16:59:00  754.447905 6.133567 
2014-08-13 16:59:00  754.447905 6.946430

I'm trying to keep the date with the smallest distance, so drop the duplicates dates and keep the with the smallest distance.

Is there a way to achieve this in pandas' df.drop_duplicates or am I stuck using if statements to find the smallest distance?

3 Answers
Related