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How's Order Volume Trending Month to Month?

hardSQLDatesGroupBy

Ops at Whetcode Supply is putting a month-over-month order-volume chart on the warehouse wall, and someone has to hand the charting tool a tidy series: one figure per calendar month.

Nothing in the database is stored per month. Every order carries a full calendar date, and the ten of them scatter across five different months of 2023, so the month is a thing you have to make out of the date before you can total anything by it. Bear in mind too that a month in which nobody ordered leaves no trace at all in a table of orders — there is no blank row waiting to be found.

orders — one row per order placed. order_date is the calendar date the order was placed, stored as text in YYYY-MM-DD form.

id customer_id product_id quantity order_date
1 1 1 2 2023-02-01
2 1 4 1 2023-02-01
3 2 2 1 2023-02-10
4 3 3 3 2023-03-05
5 4 5 5 2023-03-11
6 1 3 1 2023-04-02
7 5 1 4 2023-05-20
8 2 5 2 2023-05-22
9 3 4 1 2023-06-01
10 5 2 1 2023-06-15

The table already exists in the database — there is nothing to create or load.

Task: Write a query returning two columns, order_month and num_orders. order_month is the calendar month the order was placed in, as text in YYYY-MM form — 2023-04, not April and not 4. num_orders is how many orders fell in that month. There is one row for every month that saw at least one order; a month with no orders produces no row rather than a row reading 0. Rows come back sorted by order_month, earliest first.

Example output — shape only, on an invented year. Note the month format: 2021-08, not August and not 8.

order_month num_orders
2021-08 4
2021-09 1
2021-11 7

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