There is a Pandas dataframe: userId movieId rating timestamp 0 1 31 2.5 1260759144 1 1 1029 3.0 1260759179 2 1 1061 3.0 1260759182 3 1 1129 2.0 1260759185 4 1 1172 4.0 1260759205 Calculate the average lifetime of users. The lifetime is the difference between the maximum and minimum values of the "timestamp" column for a given "userId".

import pandas

users = pandas.read_csv('ml-100k/u.user', sep='|', names=['user_id', 'age', 'gender', 'occupation', 'zip_code'])
ratings = pandas.read_csv('ml-100k/u.data', sep='\t', names=['user_id', 'movie_id', 'rating', 'timestamp'])


avg_lifetime = ratings.groupby('user_id')['timestamp'].agg(['max','min']).mean(axis=1).mean()
print(avg_lifetime)