Pivot table aggregation
You are given `rows`, a list of dicts each with keys 'region', 'product', and 'amount' (an integer). Build a pivot table: return a list of [region, product, total] triples giving the summed 'amount' for every (region, product) pair that appears. Sort the output ascending by region, then by product. Regions/products are non-empty strings; amounts may be negative.
Implement
pivot_totals(rows: list[dict]) → list[list]Examples
in
[[{"amount":10,"region":"us","product":"a"},{"amount":5,"region":"us","product":"a"},{"amount":3,"region":"eu","product":"b"}]]out[["eu","b",3],["us","a",15]]What a strong answer looks like
State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
0:00 of about 25 min
solution.py
InputExpectedGot
[[{"amount":10,"region":"us","product":"a"},{"amount":5,"region":"us","product":"a"},{"amount":3,"region":"eu","product":"b"}]][["eu","b",3],["us","a",15]]not run yetsample