Code RoomJoin on differently named keys
HardPrep Room Coding #5032

Join on differently named keys

CodingAlgorithms & data structuresSenior–Staff~12 min

Given `orders` with columns `order_id`, `customer`, `amount`, `status` and `placed`, and `people` with columns `handle` and `city`, join `customer` to `handle` and return `order_id` and `city` for the orders whose customer is known, sorted by `order_id` ascending.

Implement
orders_with_city(orders: dataframe, people: dataframe) → dataframe
Examples
in[{"__df__":[{"amount":120.5,"placed":"2024-01-05","status":"paid","customer":"ada","order_id":1},{"amount":80,"placed":"2024-01-07","status":"refunded","customer":"bo","order_id":2},{"amount":45.25,"placed":"2024-02-11","status":"paid","customer":"ada","order_id":3},{"amount":200,"placed":"2024-02-14","status":"paid","customer":"cy","order_id":4},{"amount":15.75,"placed":"2024-03-02","status":"pending","customer":"bo","order_id":5},{"amount":60,"placed":"2024-03-19","status":"paid","customer":"ada","order_id":6}]},{"__df__":[{"city":"Oslo","handle":"ada"},{"city":"Lima","handle":"cy"}]}]out[{"city":"Oslo","order_id":1},{"city":"Oslo","order_id":3},{"city":"Lima","order_id":4},{"city":"Oslo","order_id":6}]
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 12 min
InputExpectedGot
[{"__df__":[{"amount":120.5,"placed":"2024-01-05","status":"paid","customer":"ada","order_id":1},{"amount":80,"placed":"2024-01-07","status":"refunded","customer":"bo","order_id":2},{"amount":45.25,"placed":"2024-02-11","status":"paid","customer":"ada","order_id":3},{"amount":200,"placed":"2024-02-14","status":"paid","customer":"cy","order_id":4},{"amount":15.75,"placed":"2024-03-02","status":"pending","customer":"bo","order_id":5},{"amount":60,"placed":"2024-03-19","status":"paid","customer":"ada","order_id":6}]},{"__df__":[{"city":"Oslo","handle":"ada"},{"city":"Lima","handle":"cy"}]}][{"city":"Oslo","order_id":1},{"city":"Oslo","order_id":3},{"city":"Lima","order_id":4},{"city":"Oslo","order_id":6}]not run yetsample