Practice / reshaping
The Daily Grind wants a revenue cross-tab: stores down the side, months across the top.
sales
Your task: produce one row per store with a Jun and a Jul column holding the total amount for that store in that month.
Assign your answer DataFrame to result. Row order doesn't matter.
salesinput DataFrame| column | type |
|---|---|
| store | string |
| month | string |
| amount | double |
| store | month | amount |
|---|---|---|
| Downtown | Jun | 10 |
| Downtown | Jun | 5 |
| Downtown | Jul | 8 |
| Pier | Jun | 4 |
| Pier | Jul | 6 |
| Pier | Jul | 6 |
storeJunJul· 2 rowsgroupBy("store").pivot("month", ["Jun", "Jul"]).agg(F.sum("amount")). Passing
the value list to pivot fixes the column order and skips a scan.
This problem builds on Reshaping Data (~7 min). Pop it open in a new tab if you want a quick recap.