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Exercise

Broadcasting across rows

In the last set of exercises, you used monthly_industry_multipliers, to create sales predictions. Recall that monthly_industry_multipliers looks like this:

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]])

Assume you're not comfortable being so specific with your estimates. Rather, you'd like to use monthly_industry_multipliers to find a single average multiplier for each industry. Then you'll use that multiplier to project next year's sales.

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.

Instructions 1/3

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  • Find the mean sales projection multiplier for each industry; save in an array called mean_multipliers.