Iterate through the rows of a dataframe and reassign minimum values by group

Question

I am working with a dataframe that looks like this.

  id time diff
0 0   34   nan
1 0   36   2
2 1   43   7
3 1   55   12
4 1   59   4
5 2   2    -57
6 2   10   8

What is an efficient way find the minimum values for 'time' by id, then set 'diff' to nan at those minimum values. I am looking for a solution that results in:

   id time diff
0 0   34   nan
1 0   36   2
2 1   43   nan
3 1   55   12
4 1   59   4
5 2   2    nan
6 2   10   8

Answer 1

groupby('id') and use idxmin to find the location of minimum values of 'time'. Finally, use loc to assign np.nan

df.loc[df.groupby('id').time.idxmin(), 'diff'] = np.nan
df