Where Do Customers Live?
Whetcode Supply is choosing somewhere to put a second warehouse, and the shortlist starts from the simplest signal available: how many registered customers live in each city. Shipping costs fall fastest beside the biggest cluster, so the busiest city needs to be at the top of the list.
Three of the four cities have the same number of customers, so the list also needs a rule for what happens when two cities tie — otherwise the same query produces a different shortlist on different runs and nobody can tell which one they read last week.
customers — one row per registered customer. city is the city given at signup and signup_date is the day they registered, written year-month-day.
| id | name | city | signup_date |
|---|---|---|---|
| 1 | Priya Nair | Austin | 2022-01-15 |
| 2 | Tom Becker | Berlin | 2022-03-02 |
| 3 | Sofia Rossi | Milan | 2022-05-19 |
| 4 | Liam OConnor | Dublin | 2023-01-08 |
| 5 | Wei Zhang | Austin | 2023-04-27 |
The table already exists in the database — there is nothing to create or load.
Task: Write a query returning two columns, city and n (how many registered customers give that city), one row per city that appears in the table, most customers first. When two cities have the same number, list them alphabetically by city. A city with no registered customers does not appear at all.
Example output — shape only, on invented cities. The second and third share a headcount, so they fall alphabetically:
| city | n |
|---|---|
| Lisbon | 6 |
| Osaka | 3 |
| Utrecht | 3 |
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