Practice / selecting and filtering
The Daily Grind coffee chain is having a moment: a customer ordered a large drink so expensive the register printed a receipt in italics. The shift manager wants a list of every big spender order to study.
You have the orders DataFrame:
Your task: return every order that is size "large" and has a price greater than 6.00. Keep only the columns order_id, drink, and price.
Assign your answer DataFrame to result. Row order doesn't matter.
ordersinput DataFrame| column | type |
|---|---|
| order_id | long |
| drink | string |
| size | string |
| price | double |
| tip | double |
| order_id | drink | size | price | tip |
|---|---|---|---|---|
| 1001 | oat latte | large | 6.5 | 1 |
| 1002 | drip coffee | small | 3 | 0 |
| 1003 | caramel macchiato | large | 7.25 | 2 |
| 1004 | flat white | medium | 5 | 1.5 |
| 1005 | cold brew | large | 5.5 | 0.5 |
| 1006 | espresso | small | 2.5 | 0.75 |
| 1007 | mocha | large | 6.75 | 0.25 |
| 1008 | latte | medium | 5.25 | 2 |
| 1009 | gold-dust affogato | small | 6.5 | 0.75 |
| 1010 | barrel-aged cold brew | large | 6 | 0.5 |
order_iddrinkprice· 3 rowsTwo steps: filter with both conditions combined by & (wrap each condition
in parentheses!), then select the three columns the shift manager asked for.
This problem builds on Selecting & Filtering (~6 min). Pop it open in a new tab if you want a quick recap.