pandas - get most recent value of a particular column indexed by another column (get maximum value of a particular column indexed by another column)

Question

I have the following dataframe:

   obj_id   data_date   value
0  4        2011-11-01  59500    
1  2        2011-10-01  35200 
2  4        2010-07-31  24860          


        

Answer 1

The aggregate() method on groupby objects can be used to create a new DataFrame from a groupby object in a single step. (I'm not aware of a cleaner way to extract the first/last row of a DataFrame though.)

In [12]: df.groupby('obj_id').agg(lambda df: df.sort('data_date')[-1:].values[0])
Out[12]: 
         data_date  value
obj_id                   
1       2009-07-28  15860
2       2011-10-01  35200
4       2011-11-01  59500

You can also perform aggregation on individual columns, in which case the aggregate function works on a Series object.

In [25]: df.groupby('obj_id')['value'].agg({'diff': lambda s: s.max() - s.min()})
Out[25]: 
          diff
obj_id        
1            0
2       165000
4        34640