# Compute the burn rate of each customer, compare average burn rate
# with the burn rate of customer who leave the bank.
import numpy as np
from cust_journey_data import cust_journeys
from dateutil.parser import parse
from datetime import date
from calendar import monthrange
burn_rates = [
# Return the mean of customer's burn rates
select (cj, np.mean(burn_rates) if burn_rates else 0 as burn_rate)
# Iterate over customer journeys
for cj in cust_journeys
# Get the dates of the first and last customer journey events
let first_date = parse(cj[0].date),
last_date = parse(cj[-1].date),
withdrawals = [select (e.amount as amount, parse(e.date) as date)
for e in cj where e.event_name=='withdraw']
# Compute the burn rates by iterating over all months in the
# perioud from the first to last events in the customer journey
let burn_rates = [
select sum(ws)
for yr in range(first_date.year, last_date.year+1),
month in range(1,12+1)
let last_day_month = date(yr, month, monthrange(yr,month)[1]),
first_day_month = date(yr,month,1)
where last_day_month > first_date.date() and first_day_month < last_date.date()
let ws = [select e.amount
for e in withdrawals
where e.date.year == yr and e.date.month == month] ]
]
average_rate = np.mean([select x.burn_rate for x in burn_rates])
# Compute the burn rate of customer who left the bank
churn_burn_rate = np.mean([select x.burn_rate
for x in burn_rates
where [ select e
for e in x.cj
where e.event_name=='close']])
print("Average burn rate:",average_rate)
print("Churn burn rate:",churn_burn_rate)
