MediumSQL challenge #134JOINGROUP BY

Calculate the Average Review Rating per Product Category

Return each product category with the average rating of its reviews.

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

Solve This SQL Challenge

The task

Find average product rating by category.

A correct answer returns 10 rows with 2 columns: category, AVG(r.rating).

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

`reviews` 180 rows

id INTEGER (PK) · product_id INTEGER · user_id INTEGER · rating INTEGER · comment TEXT · reviewed_at TEXT · helpful_votes INTEGER

First 3 rows of the reviews table
id	product_id	user_id	rating	comment	reviewed_at	helpful_votes
1	23	45	5	Works perfectly. Very happy with this purchase.	2022-09-02	40
2	101	68	5	Excellent build quality. Will buy again!	2023-01-05	96
3	40	39	1	Would give 6 stars if I could!	2023-05-15	17

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	AVG(r.rating)
Automotive	2.8
Books	2.962962962962963
Clothing	2.3636363636363638
Electronics	2.5
Food & Beverage	3.1153846153846154
Health & Beauty	2.7222222222222223
Home & Garden	2.8333333333333335
Office Supplies	2.92
Sports & Outdoors	2.75
Toys	2.8461538461538463

The complete result: 10 rows. This is the output of the model solution on the practice database. The task does not fix a sort order, so your rows may come back in a different order.

What you practise

Summarising many rows into one value with COUNT, SUM, AVG, MIN or MAX
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

Hint and approach

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

Show the hint

JOIN products and reviews

Show the step-by-step approach

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

Read from the products table.
Join reviews on products.id = reviews.product_id.
Group the rows by products.category, so the result has one row for each value.
For each group, compute AVG(reviews.rating).

Model solution

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What to watch for

The category is on products and the rating on reviews, so the join comes first and the grouping second. Each review counts once, so heavily reviewed products pull their category's average more than rarely reviewed ones.

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.
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.
Aggregate functions. Aggregates skip NULLs. AVG divides by the number of non-NULL values and COUNT(column) can be smaller than COUNT(*).