Practice / aggregations
The Daily Grind wants revenue broken out by store and day, not just per store.
You have the orders DataFrame:
Your task: return store, day, and revenue (the sum of amount) for every store-and-day combination.
Assign your answer DataFrame to result. Row order doesn't matter.
ordersinput DataFrame| column | type |
|---|---|
| store | string |
| day | string |
| amount | double |
| store | day | amount |
|---|---|---|
| Downtown | Mon | 5 |
| Downtown | Mon | 3 |
| Downtown | Tue | 4 |
| Pier | Mon | 6 |
storedayrevenue· 3 rowsGroup by both keys at once: groupBy("store", "day"). You get one row per
unique store-and-day combination; sum amount into revenue.
This problem builds on Aggregations & groupBy (~7 min). Pop it open in a new tab if you want a quick recap.