Projecting sales
You'd like to be able to plan for next year's operations by projecting what sales will be, and you've gathered multipliers specific to each month and industry. These multipliers are saved in an array called monthly_industry_multipliers
. For example, the multiplier at monthly_industry_multipliers[0, 0]
of 0.98
means that the liquor store industry is projected to have 98% of this January's sales in January of next year.
array([[0.98, 1.02, 1. ],
[1.00, 1.01, 0.97],
[1.06, 1.03, 0.98],
[1.08, 1.01, 0.98],
[1.08, 0.98, 0.98],
[1.1 , 0.99, 0.99],
[1.12, 1.01, 1. ],
[1.1 , 1.02, 1. ],
[1.11, 1.01, 1.01],
[1.08, 0.99, 0.97],
[1.09, 1. , 1.02],
[1.13, 1.03, 1.02]])
numpy
is loaded for you as np
, and the monthly_sales
and monthly_industry_multipliers
arrays are available. The monthly_sales
columns in order refer to liquor store, restaurant, and department store sales.
This exercise is part of the course
Introduction to NumPy
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create an array of monthly projected sales for all industries
projected_monthly_sales = ____
print(projected_monthly_sales)