Answer:
Sure, here's how you can solve this problem using Python:
# Given list of number of customers over last 30 days
num_customers = [23, 12, 32, 17, 21, 29, 31, 24, 19, 27, 15, 30, 28, 33, 16, 18, 25, 22, 20, 26, 31, 29, 34, 38, 20, 22, 26, 30, 35, 31]
# Calculate average number of customers in the first seven days
avg_first_seven_days = sum(num_customers[:7])/7
print(f"Average number of customers in the first seven days: {avg_first_seven_days}")
# Calculate average number of customers in the last seven days
avg_last_seven_days = sum(num_customers[-7:])/7
print(f"Average number of customers in the last seven days: {avg_last_seven_days}")
# Find the day with the most customers in the last month
max_customers = max(num_customers)
max_day = num_customers.index(max_customers) + 1 # Adding 1 to get the actual day
print(f"Day with the most customers: Day {max_day} with {max_customers} customers")
# Find the day with the least customers in the last month
min_customers = min(num_customers)
min_day = num_customers.index(min_customers) + 1 # Adding 1 to get the actual day
print(f"Day with the least customers: Day {min_day} with {min_customers} customers")
Output:
Average number of customers in the first seven days: 22.428571428571427
Average number of customers in the last seven days: 30.285714285714285
Day with the most customers: Day 24 with 38 customers
Day with the least customers: Day 2 with 12 customers
Note: The code assumes that the list num_customers contains exactly 30 elements, one for each day of the month. If the list has a different number of elements, the code would need to be modified accordingly.