# Groupby the loan id and calculate the max of the months balance
max_months_balance = bureau_balance.groupby('SK_ID_BUREAU',
                                            as_index = False)['MONTHS_BALANCE'].agg(['max'])

# Rename the column
max_months_balance = max_months_balance.rename(columns = {'max': 'max_months_balance'})

# Need the client id in the dataframe
max_months_balance = max_months_balance.merge(bureau_balance[['SK_ID_CURR', 'SK_ID_BUREAU']],
                                              on = 'SK_ID_BUREAU', how = 'left')

# Groupby the client id and calculate the mean of the max
average_loan_max_months_balance = max_months_balance.groupby('SK_ID_CURR'
                                  )['max_months_balance'].agg(['mean']).reset_index()

# Rename the column
average_loan_max_months_balance = average_loan_max_months_balance.rename(
  columns = {'mean': 'average_of_max_months_balance'})

# Merge with the parent dataframe
app = app.merge(average_loan_max_months_balance[['SK_ID_CURR', 'average_of_max_months_balance']],
                 on = 'SK_ID_CURR', how = 'left')