MediumSQL challenge #106JOINGROUP BYSUMAVG

Calculate Revenue and Units Sold per Product Category

Report orders, units sold, revenue and average price for each product category.

The challenge runs on the SQLabHub practice database (SQLite) and uses the products and order_items tables. You can solve it in the browser, with nothing to install.

Solve This SQL Challenge

The task

Calculate total revenue, units sold and number of orders per product category.

A correct answer returns 10 rows with 5 columns: category, total_orders, units_sold, total_revenue, avg_price.

Tables used in this challenge

`products` 120 rows

id INTEGER (PK) · name TEXT · category TEXT · price REAL · cost REAL · stock INTEGER · sku TEXT · status TEXT · rating REAL · review_count INTEGER

First 3 rows of the products table
id	name	category	price	cost	stock	sku	status	rating	review_count
1	Play Kitchen Deluxe	Toys	1786.38	589.51	257	SKU-000001	active	4	57
2	Micro-Cut Paper Shredder 8-Sheet	Office Supplies	907.93	281.46	131	SKU-000002	active	2.5	447
3	4K Dual Dash Camera	Automotive	568.89	204.8	176	SKU-000003	active	4.1	29

`order_items` 496 rows

id INTEGER (PK) · order_id INTEGER · product_id INTEGER · quantity INTEGER · unit_price REAL · subtotal REAL

First 3 rows of the order_items table
id	order_id	product_id	quantity	unit_price	subtotal
1	1	76	5	192.21	961.05
2	1	82	3	107.1	321.3
3	1	65	1	5.39	5.39

The first rows of each table are shown. See how all the tables relate on the database schema page.

Expected output

Expected output of the challenge
category	total_orders	units_sold	total_revenue	avg_price
Office Supplies	56	191	47482.77	1045.38
Toys	50	181	44782.9	953.26
Automotive	44	161	43055.93	1171.73
Food & Beverage	54	179	42452.58	1299.58
Books	54	190	40552.7	974.42
Health & Beauty	43	139	33218.16	767.65
Home & Garden	35	124	31079.84	1228.11
Sports & Outdoors	46	141	30319.13	1056.02
Clothing	34	119	28015.78	1429.37
Electronics	32	102	25811.19	792.15

The complete result: 10 rows. This is the output of the model solution on the practice database.

What you practise

Summarising many rows into one value with COUNT, SUM, AVG, MIN or MAX
Counting different values with COUNT(DISTINCT …)
Grouping rows with GROUP BY to get one result row per group
Combining rows from two tables on a matching key with an inner join
Sorting the result with ORDER BY

Hint and approach

Try the challenge first. Open these only when you need them.

Show the hint

JOIN order_items with products, then GROUP BY category

Show the step-by-step approach

How the model solution is built, in the order the database evaluates it:

Read from the order_items table.
Join products on products.id = order_items.product_id.
Group the rows by products.category, so the result has one row for each value.
For each group, compute COUNT(DISTINCT order_items.order_id), which counts each different value once, SUM(order_items.quantity), SUM(order_items.subtotal) and AVG(products.price).
ROUND() trims the calculated figures to a fixed number of decimals.
Sort the result by total_revenue descending.

Model solution

Checking your session…

What to watch for

One order can contain several lines in the same category, so orders are counted with COUNT(DISTINCT order_id). The average price here is weighted by how often a product was sold, because it is averaged over order lines rather than over products.

INNER JOIN. An inner join drops rows that have no partner on the other side, and it repeats a row once for every match, which inflates SUM and COUNT.
COUNT(DISTINCT). After a join, COUNT(*) counts joined rows. Counting the parent entity needs COUNT(DISTINCT its id).
GROUP BY. Every selected column must either be in GROUP BY or sit inside an aggregate. SQLite accepts other columns and returns an arbitrary value for them; most databases raise an error.