// Given the data structure below, write a solution that will aggregate the values both by // which quarter of the year they occurred in and their forward sortation area (FSA), which is the first half of the canadian postal code. const data = [ ["M5V 3L9", 120.50, "2025-02-10", "Canada"], ["V6B 2W1", 250.00, "2025-01-12", "Canada"], ["M4C 1A1", 75.25, "2025-03-11", "Canada"], ["V6B 3H6", 400.00, "2025-04-10", "Canada"], ["K1A 0B1", 60.00, "2025-05-09", "Canada"], ["K1A 0B3", 34.00, "2025-06-08", "Canada"], ["V6B 0D2", 80.00, "2025-01-08", "Canada"], ] // example output: // { // 'Q1': { // 'M5V': 120.5, // 'V6B': 330.0, // 'M4C': 75.25 // }, // 'Q2': { // 'V6B': 400.0, // 'K1A': 94.0 // }, // } The second revision, add this to the array: [“V6B 0D2", 80.00, "2025-10-08", "Canada"] Their revision, add this to the array: ["V6B10D2", 80.00, "2025-01-08", "Pytown"],
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