Python: combining values by specific conditions and creating new dataframe

Question

I have a dataframe that looks something like this:

df_old=pd.Dataframe([
['2019-10-07', 2, 'coworker_a', 'project_a'], # row 1.1
['2019-10-07', 1, 'coworker_b', 'project_a'], # row 2.1
['2019-10-07', 8, 'coworker_b', 'project_b'], # row 3
['2019-10-07', 1, 'coworker_a', 'project_a'], # row 1.2
['2019-10-07', 5, 'coworker_b', 'project_a'], # row 2.2
['2019-10-08', 1, 'coworker_b', 'project_a'], # row 4.1
['2019-10-08', 4, 'coworker_a', 'project_b'], # row 5.1
['2019-10-08', 7, 'coworker_a', 'project_b'], # row 5.2
['2019-10-08', 4, 'coworker_b', 'project_a']  # row 4.2
], columns=['date', 'value', 'coworker', 'project']
)

Now I'm trying to get a new dataframe, that combines all the integers in 'value', so that there's only one row for each combination of 'date', 'coworker' and 'project'. Something like this:

df_new=pd.Dataframe([
['2019-10-07', 3, 'coworker_a', 'project_a'], # row 1.1 & row 1.2
['2019-10-07', 6, 'coworker_b', 'project_a'], # row 2.1 & row 2.2
['2019-10-07', 8, 'coworker_b', 'project_b'], # row 3
['2019-10-08', 5, 'coworker_b', 'project_a'], # row 4.1 & row 4.2
['2019-10-08', 11, 'coworker_a', 'project_b'] # row 5.1 & row 5.2
], columns=['date', 'value', 'coworker', 'project']
)

Is there - and in case there is - and what's the best solution for my problem? Thanks.