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Assume you're given a table containing data on Amazon customers and their spending on products in different category. Write a query using to identify the number of unique products within each product category.
| Column Name | Type |
|---|---|
| category | string |
| product | string |
| user_id | integer |
| spend | decimal |
| transaction_date | timestamp |
| category | product | user_id | spend | transaction_date |
|---|---|---|---|---|
| appliance | refrigerator | 165 | 246.00 | 12/26/2021 12:00:00 |
| appliance | refrigerator | 123 | 299.99 | 03/02/2022 12:00:00 |
| appliance | washing machine | 123 | 219.80 | 03/02/2022 12:00:00 |
| electronics | vacuum | 178 | 152.00 | 04/05/2022 12:00:00 |
| electronics | wireless headset | 156 | 249.90 | 07/08/2022 12:00:00 |
| electronics | vacuum | 145 | 189.00 | 07/15/2022 12:00:00 |
| category | count |
|---|---|
| appliance | 2 |
| electronics | 2 |
Within the "appliance" category, the two unique products are refrigerator & washing machine. Within the electronics category, the two unique products are vacuum and wireless headset.
The dataset you are querying against may have different input & output - this is just an example!
If this was a bit confusing, maybe that's a sign for you to try refresh yourself on SQL GROUP BY.