How to Efficiently Get the Top N Records within Each Pandas Group?

Getting Topmost Records within a Pandas Group

In the following dataset:

df = pd.DataFrame({'id':[1,1,1,2,2,2,2,3,4], 'value':[1,2,3,1,2,3,4,1,1]})

we wish to obtain the top two records for each id. A straightforward approach involves assigning row numbers within each group using the groupby method:

dfN = df.groupby('id').apply(lambda x:x['value'].reset_index()).reset_index()

However, a more efficient solution is provided by the head function:

df.groupby('id').head(2)

This operation produces:

       id  value
id             
1  0   1      1
   1   1      2 
2  3   2      1
   4   2      2
3  7   3      1
4  8   4      1

To remove the MultiIndex and flatten the results, use:

df.groupby('id').head(2).reset_index(drop=True)

This yields the desired output:

    id  value
0   1      1
1   1      2
2   2      1
3   2      2
4   3      1
5   4      1

Thus, the head function provides a concise and optimized approach for retrieving the topmost records within each Pandas group.

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