[Python] Python pandas: Compare rows of dataframe based on some columns and drop row with...

I have a data frame df:

first_seen last_seen uri
0 2015-05-11 23:08:46 2015-05-11 23:08:50 http://11i-ssaintandder.com/
1 2015-05-11 23:08:46 2015-05-11 23:08:46 http://11i-ssaintandder.com/
2 2015-05-02 18:27:10 2015-06-06 03:52:03 http://example.com/NMqjd1
3 2015-05-02 18:27:10 2015-06-08 08:44:53 http://example.com/NMqjd1


I would like to remove the rows that has the same "first_seen","uri" and keep only the row that has the latest last_seen.

Here is the an example of expected dataset:

first_seen last_seen uri
0 2015-05-11 23:08:46 2015-05-11 23:08:50 http://11i-ssaintandder.com/
3 2015-05-02 18:27:10 2015-06-08 08:44:53 http://example.com/NMqjd1


Does anybody know who to do it without writing a for loop?

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