Saturday Sales by Loyalty Tier

PandasMediumMid level~10 min

Problem

You are given two DataFrames. `orders` (CSV `orders.csv`, one row per order) has columns shopper_id, order_day, and cents_paid; `shoppers` (CSV `shoppers.csv`) has columns shopper_id and tier. A farmers' market opens every Saturday; in September 2024 those Saturdays were the 7th, 14th, 21st, and 28th (week 1 is the first Saturday and so on). Report the total spend by `Gold` and `Silver` shoppers on each of those four Saturdays. Every combination of week and the two tiers must appear, with a total of 0 when there were no qualifying orders that day. Output columns: `week_no`, `tier`, and `total_cents`, ordered by `week_no` then `tier`.

Input data

Example rows — the live problem includes the full dataset.

orders

shopper_id	order_day	cents_paid
11	2024-09-07	1126
15	2024-09-14	7473
17	2024-09-21	2414
12	2024-09-28	9692
8	2024-09-28	5117

shoppers

shopper_id	tier
11	Gold
15	Silver
17	Bronze
12	Silver
8	Gold

Expected output

Your answer should return 8 rows with the columns week_no, tier, total_cents.

Starter code (Pandas (Python))

import pandas as pd

def saturday_sales_by_loyalty_tier(orders, shoppers) -> pd.DataFrame:
    # Your code here
    return orders

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