The Purchase Pulse
Kindled's revenue dashboard shows a pulse: purchases per calendar day. It is watched for gaps, because a day with no sales usually means the checkout is broken rather than that nobody wanted anything. The growth lead wants the underlying numbers in date order — only the days that actually recorded a sale, since a day with none produces nothing to count.
events — one row per tracked action. user_id points at a row in users. event_type is one of signup, view_product, add_to_cart and purchase. event_date is the day the action happened. Nothing guarantees a person produces all four kinds, or any particular number of rows.
| id | user_id | event_type | event_date |
|---|---|---|---|
| 1 | 1 | signup | 2023-05-01 |
| 2 | 1 | view_product | 2023-05-01 |
| 3 | 1 | add_to_cart | 2023-05-02 |
| 4 | 1 | purchase | 2023-05-03 |
| 5 | 2 | signup | 2023-05-02 |
| 6 | 2 | view_product | 2023-05-02 |
| 7 | 3 | signup | 2023-05-03 |
| 8 | 3 | view_product | 2023-05-03 |
| 9 | 3 | add_to_cart | 2023-05-04 |
| 10 | 4 | signup | 2023-05-04 |
| 11 | 4 | view_product | 2023-05-05 |
| 12 | 4 | add_to_cart | 2023-05-05 |
| 13 | 4 | purchase | 2023-05-06 |
| 14 | 5 | signup | 2023-05-05 |
| 15 | 6 | signup | 2023-05-06 |
| 16 | 6 | view_product | 2023-05-06 |
| 17 | 7 | signup | 2023-05-07 |
| 18 | 7 | view_product | 2023-05-07 |
| 19 | 7 | add_to_cart | 2023-05-08 |
| 20 | 7 | purchase | 2023-05-09 |
| 21 | 8 | signup | 2023-05-08 |
The table already exists in the database — there is nothing to create or load.
Task: Write a query that returns one row per day on which at least one purchase happened, with columns event_date and purchases — how many purchases that day recorded. Oldest day first.
Example output — shape only, on invented days. A day with no purchase is absent rather than zero, which is why the dates can skip:
| event_date | purchases |
|---|---|
| 2022-11-04 | 14 |
| 2022-11-08 | 8 |
| 2022-11-15 | 4 |
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