Groupby() and mean() in pandas dataframe with returning more than two columns

A super simple question, which I cannot find so far.

This is my dataframe

    id  Name    Lastname    Journal     Article   Score
0   1   John    Doo         Journal2    Article1    23
1   2   John    Doo         Journal1    Article2    12
2   3   Bill    Foo         Journal17   Article3    8

When I use

df.groupby('id', as_index=False)['Score'].mean()

it gives me

    id  Score
0   1   17.5
1   2   8.0

Expected output

   id   Name Lastname Score
0   1   Joe  Doe      17.5
1   2   Bill Foo      8.0

>Solution :

If same values per id in Name and Lastname columns add it to groupby:

df.groupby(['id','Name','Lastname'], as_index=False)['Score'].mean()

If possible different values per id is possible extract first/last values per groups:

df.groupby('id', as_index=False).agg({'Score':'mean', 'Name':'first', 'Lastname':'first'})

df.groupby('id', as_index=False).agg({'Score':'mean', 'Name':'last', 'Lastname':'last'})