Pandas compute mean over top n records of a group

Question

Suppose I have pandas DataFrame like this:

   id  value
0   1      1
1   1      2
2   1      3
3   2      4
4   2      3
5   2      2
6   2      1
7   3      1

I'd like to compute the mean per id over the first 2 records and and append the resulte as new column like:

   id  value  top_2_mean
0   1      1         1.5
1   1      2         1.5
2   1      3         1.5
3   2      4         3.5
4   2      3         3.5
5   2      2         3.5
6   2      1         3.5
7   3      1           1

Answer 1

Use GroupBy.transform with lambda function for first 2 values and mean:

df['top_2_mean'] = df.groupby('id')['value'].transform(lambda x: x.head(2).mean())
#alternative    
#df['top_2_mean'] = df.groupby('id')['value'].transform(lambda x: x.iloc[:2].mean())
print (df)
   id  value  top_2_mean
0   1      1         1.5
1   1      2         1.5
2   1      3         1.5
3   2      4         3.5
4   2      3         3.5
5   2      2         3.5
6   2      1         3.5
7   3      1         1.0