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 who gave more than 100 ratings. The lifetime is the difference between the maximum and minimum values of the timestamp column for a given userId.

df = pd.read_csv('ratings.csv')
df.head()
df.columns
df.groupby('userId').size()
df.groupby('userId').size().index
df.groupby('userId').size().values

#df.groupby('userId').size().values > 100
df.groupby('userId').size().values[df.groupby('userId').size().values > 100]
df.groupby('userId').size().index[df.groupby('userId').size().values > 100]

df[df['userId'] == 1]
df[df['userId'] == 1].timestamp
df[df['userId'] == 1].timestamp.diff()

df[df['userId'] == 1].timestamp.diff().min()
df[df['userId'] == 1].timestamp.diff().max()
df[df['userId'] == 1].timestamp.diff().max() - df[df['userId'] == 1].timestamp.diff().min()

def get_lif