How to split aggregated list into multiple columns in pandas

Question

I want to create separate columns for each item in the 'name' lists for each row in this pandas dataframe. The 'name' lists have between 1-10 items, and I just want the column heads to be "1", "2", "3", etc.

out = dataframe.groupby(by=['location'], as_index=False).agg({'people':'sum', 'name':list})

Is there a way to split the aggregated list like this?

This is my original dataframe:

This is the dataframe I want to have:

Answer 1

This can be done by two steps, cumcount with pivot

out1 = dataframe.groupby('location').agg({'people':'sum'})
out2 = dataframe.assign(key = dataframe.groupby('location').cumcount()).pivot('location', 'key', 'name')
out = out1.join(out2).reset_index()