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AVG

Compute the average.

AVG

AVG returns the average of a column. It ignores NULL values.

SELECT AVG(price) FROM products;

This query gives the average price.

AVG(price) is selected from products.

AVG — details

AVG divides the sum by the row count. NULLs are excluded from both sum and count.

For example, the average of 10, 20 and NULL is 15 (30 / 2); to count NULL as 0 you write AVG(COALESCE(price, 0)).

Practice AVG

Compute the average price in products with AVG(price).

Starter code

query.sql
-- average price
SELECT

Sample solution

query.sql
SELECT AVG(price) FROM products;

Expected output

avg
233.33

Questions and answers

Review the lesson questions together with their answers. To test yourself, solve the lesson interactively.

1 AVG: match the terms

Term Meaning
AVG average
SUM sum
NULL skip
numeric numeric

2 Add AVG

Question 
SELECT ____(price) FROM products;
Answer 
SELECT AVG(price) FROM products;

Explanation: AVG(price) returns the average price; NULL values are ignored.

3 How does AVG handle NULLs?

  • Skips Correct answer
  • Raises an error
  • Counts them as zero
  • Includes them in the count

Explanation: AVG skips NULL values.

All lessons in Intermediate

1 INNER JOIN in depth

  1. INNER JOIN logic
  2. Choosing the join column
  3. Three-table INNER JOIN
  4. Self JOIN
  5. Filtering joins
  6. Summary - INNER JOIN

2 LEFT and RIGHT JOIN

  1. LEFT JOIN
  2. RIGHT JOIN
  3. Unmatched rows
  4. JOINs with NULL
  5. LEFT vs RIGHT
  6. Summary - LEFT and RIGHT JOIN

3 FULL and CROSS JOIN

  1. FULL OUTER JOIN
  2. CROSS JOIN
  3. When to CROSS JOIN
  4. Comma JOIN
  5. Choosing a JOIN type
  6. Summary - FULL and CROSS JOIN

4 Project: Library database

  1. Library design
  2. Books and authors
  3. List loans with LEFT JOIN
  4. Find overdue loans
  5. Member summary

5 GROUP BY

  1. What is GROUP BY?
  2. Single-column grouping
  3. Multi-column grouping
  4. GROUP BY with aggregates
  5. Ordering grouped results
  6. Summary - GROUP BY

6 HAVING

  1. What is HAVING?
  2. HAVING vs WHERE
  3. HAVING with aggregates
  4. Multiple conditions
  5. HAVING with aliases
  6. Summary - HAVING

7 Aggregate functions

  1. COUNT
  2. SUM
  3. AVG
  4. MIN and MAX
  5. NULL and aggregates
  6. Summary - Aggregates

8 Project: Sales report

  1. Sales design
  2. Daily revenue
  3. Best sellers
  4. Customer segments
  5. Low performers

9 Subquery

  1. What is a subquery?
  2. Scalar subquery
  3. Subquery with IN
  4. ANY and ALL
  5. Correlated subquery
  6. Summary - Subquery

10 EXISTS

  1. What is EXISTS?
  2. NOT EXISTS
  3. EXISTS vs IN
  4. EXISTS performance
  5. Multiple EXISTS
  6. Summary - EXISTS

11 UNION and INTERSECT

  1. UNION
  2. UNION ALL
  3. INTERSECT
  4. EXCEPT
  5. Set rules
  6. Summary - UNION and INTERSECT

12 CASE

  1. What is CASE?
  2. Searched CASE
  3. Simple CASE
  4. The ELSE branch
  5. CASE with aggregates
  6. Summary - CASE

13 VIEW

  1. What is a VIEW?
  2. CREATE VIEW
  3. Querying a VIEW
  4. DROP VIEW
  5. Updatable VIEWs
  6. Summary - VIEW

14 INDEX basics

  1. What is an INDEX?
  2. CREATE INDEX
  3. Composite INDEX
  4. DROP INDEX
  5. When to index
  6. Summary - INDEX

15 Project: Blog database

  1. Blog design
  2. Post list
  3. Tag search
  4. Author stats
  5. Search index

16 Normalization

  1. What is normalization?
  2. First normal form
  3. Second normal form
  4. Third normal form
  5. BCNF
  6. Summary - Normalization

17 Data integrity

  1. What is integrity?
  2. Entity integrity
  3. Referential integrity
  4. Domain integrity
  5. Integrity with triggers
  6. Summary - Data integrity

18 Transaction basics

  1. What is a transaction?
  2. BEGIN and COMMIT
  3. ROLLBACK
  4. SAVEPOINT
  5. ACID
  6. Summary - Transaction

19 ALTER and DROP

  1. ALTER TABLE
  2. Adding a column
  3. Dropping a column
  4. Changing a column type
  5. DROP TABLE
  6. Summary - ALTER and DROP

20 Intermediate final

  1. Multi-JOIN report
  2. Aggregate analysis
  3. Subquery challenge
  4. Transaction scenario