grouping dataframe by column with condition

there is my dataframe :

df = pd.DataFrame({
'name':["aa","aa","aa","bb","cc","cc"],
'value':[1,2,3,4,5,6]})

I would like grouping by ‘name’ and values sum . Only ‘name’ column items having more than one occurence are selected . the new dataframe will contain 2 columns ‘name’ and ‘total’

Desired output :

I tried this :
(df[df.groupby([‘name’]).count() > 1].groupby([‘name’])[‘value’].sum())
but didn’t work . I got an error

Would be great to get a hint – Thanks

>Solution :

Code

make condition using transform & aggregate

cond = df.groupby('name')['value'].transform('count') > 1
out = df[cond].groupby('name')['value'].sum().reset_index(name='total')

out

    name    total
0   aa      6
1   cc      11