developer-roadmap/src/data/courses/sql-mastery/chapters/window-functions/lessons/price-tier-rankings.md

title	description	order	type	setup
Price Tier Rankings	Practice using RANK to analyze book sales across different price tiers	160	challenge	```sql CREATE TABLE book ( id INT PRIMARY KEY, title VARCHAR(100), category VARCHAR(50), price DECIMAL(10,2), copies_sold INT ); INSERT INTO book (id, title, category, price, copies_sold) VALUES (1, 'SQL Basics', 'Programming', 29.99, 1500), (2, 'Advanced SQL', 'Programming', 49.99, 2500), (3, 'Data Science', 'Data Analysis', 39.99, 2000), (4, 'Web Development', 'Programming', 34.99, 1800), (5, 'Statistics 101', 'Data Analysis', 24.99, 1200), (6, 'Python Basics', 'Programming', 29.99, 3000), (7, 'Machine Learning', 'Data Analysis', 44.99, 2200), (8, 'Database Design', 'Programming', 49.99, 1700), (9, 'R Programming', 'Data Analysis', 34.99, 1600); ```

The bookstore wants to analyze how books perform within different price ranges. They want to identify the bestsellers in each price tier:

• Budget: Less than $30
• Standard: $30 to $40
• Premium: Over $40

Given the following data in table book:

id	title	category	price	copies_sold
1	SQL Basics	Programming	29.99	1500
2	Advanced SQL	Programming	49.99	2500
3	Data Science	Data Analysis	39.99	2000
4	Web Development	Programming	34.99	1800
5	Statistics 101	Data Analysis	24.99	1200
6	Python Basics	Programming	29.99	3000
7	Machine Learning	Data Analysis	44.99	2200
8	Database Design	Programming	49.99	1700
9	R Programming	Data Analysis	34.99	1600

Write a query that shows:

• Book title
• Price tier (Budget/Standard/Premium)
• Price
• Copies sold
• Rank within price tier (based on copies sold)

Order the results by price tier (ascending) and rank within tier (ascending).

Expected Output

title	price_tier	price	copies_sold	tier_rank
Python Basics	Budget	29.99	3000	1
SQL Basics	Budget	29.99	1500	2
Statistics 101	Budget	24.99	1200	3
Advanced SQL	Premium	49.99	2500	1
Machine Learning	Premium	44.99	2200	2
Database Design	Premium	49.99	1700	3
Data Science	Standard	39.99	2000	1
Web Development	Standard	34.99	1800	2
R Programming	Standard	34.99	1600	3

Hint: You can use a CASE statement inside the PARTITION BY clause for partitioning the data into different price tiers i.e.

PARTITION BY CASE
    WHEN price < 30 THEN 'Budget'
    WHEN price <= 40 THEN 'Standard'
    ELSE 'Premium'
END

Solution

SELECT
    title,
    CASE
        WHEN price < 30 THEN 'Budget'
        WHEN price <= 40 THEN 'Standard'
        ELSE 'Premium'
    END as price_tier,
    price,
    copies_sold,
    RANK() OVER (
        PARTITION BY
            CASE
                WHEN price < 30 THEN 'Budget'
                WHEN price <= 40 THEN 'Standard'
                ELSE 'Premium'
            END
        ORDER BY copies_sold DESC
    ) as tier_rank
FROM book
ORDER BY price_tier, tier_rank;