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 as pd
 
ratings = pd.read_csv('ratings.csv')
print(ratings.head())
 
# Create a function which return the average lifetime of users
def lifetime(group):
  return group.max() - group.min()
 
lifetime_users = ratings.groupby('userId').agg(lifetime)
print(lifetime_users)
 
average_lifetime = lifetime_users['timestamp'].mean()
print(average_lifetime)
 
# output:
#        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
#        timestamp
# userId    
# 1           203560
# 2           866607
# 3           8