AVG
Syntax
AVG([DISTINCT] expr)
Contents
Description
Returns the average value of expr. The DISTINCT option can be used to return the average of the distinct values of expr. NULL values are ignored. It is an aggregate function, and so can be used with the GROUP BY clause.
AVG() returns NULL if there were no matching rows.
AVG() can be used as a window function.
Examples
CREATE TABLE sales (sales_value INT); INSERT INTO sales VALUES(10),(20),(20),(40); SELECT AVG(sales_value) FROM sales; +------------------+ | AVG(sales_value) | +------------------+ | 22.5000 | +------------------+ SELECT AVG(DISTINCT(sales_value)) FROM sales; +----------------------------+ | AVG(DISTINCT(sales_value)) | +----------------------------+ | 23.3333 | +----------------------------+
Commonly, AVG() is used with a GROUP BY clause:
CREATE TABLE student (name CHAR(10), test CHAR(10), score TINYINT); INSERT INTO student VALUES ('Chun', 'SQL', 75), ('Chun', 'Tuning', 73), ('Esben', 'SQL', 43), ('Esben', 'Tuning', 31), ('Kaolin', 'SQL', 56), ('Kaolin', 'Tuning', 88), ('Tatiana', 'SQL', 87), ('Tatiana', 'Tuning', 83); SELECT name, AVG(score) FROM student GROUP BY name; +---------+------------+ | name | AVG(score) | +---------+------------+ | Chun | 74.0000 | | Esben | 37.0000 | | Kaolin | 72.0000 | | Tatiana | 85.0000 | +---------+------------+
Be careful to avoid this common mistake, not grouping correctly and returning mismatched data:
SELECT name,test,AVG(score) FROM student; +------+------+------------+ | name | test | MIN(score) | +------+------+------------+ | Chun | SQL | 31 | +------+------+------------+
As a window function:
CREATE TABLE student_test (name CHAR(10), test CHAR(10), score TINYINT); INSERT INTO student_test VALUES ('Chun', 'SQL', 75), ('Chun', 'Tuning', 73), ('Esben', 'SQL', 43), ('Esben', 'Tuning', 31), ('Kaolin', 'SQL', 56), ('Kaolin', 'Tuning', 88), ('Tatiana', 'SQL', 87), ('Tatiana', 'Tuning', 83); SELECT name, test, score, AVG(score) OVER (PARTITION BY test) AS average_by_test FROM student_test; +---------+--------+-------+-----------------+ | name | test | score | average_by_test | +---------+--------+-------+-----------------+ | Chun | SQL | 75 | 65.2500 | | Chun | Tuning | 73 | 68.7500 | | Esben | SQL | 43 | 65.2500 | | Esben | Tuning | 31 | 68.7500 | | Kaolin | SQL | 56 | 65.2500 | | Kaolin | Tuning | 88 | 68.7500 | | Tatiana | SQL | 87 | 65.2500 | | Tatiana | Tuning | 83 | 68.7500 | +---------+--------+-------+-----------------+
See Also
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