How to keep top [2-31] rows of each group in a pandas data frame?

Question

This anwser said that I can use df.groupby('id')['value'].nlargest(30)to get top30 rows for each group. But how to get the rows form top2 to top31 for each group? Is there a function that can do the similar thing like pandas.Series.nlargest

BENY · Accepted Answer · 2017-11-21T15:32:05.393

3

Try apply and .iloc to get , for example you want 1:30

df.sort_values('value').groupby('id').value.apply(lambda x : x.iloc[1:30])

edited Nov 21 '17 at 15:32

answered Nov 21 '17 at 15:23

BENY

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But the question was from nlargest right? `top 2 - 31`. Maybe you need to `sort_values`? – Bharath Nov 21 '17 at 15:30
@Dawei Yw~ have a nice day :-) – BENY Nov 21 '17 at 15:38

How to keep top [2-31] rows of each group in a pandas data frame?

1 Answers1