# AVG

Calculate the average value from a set of numbers.

NULL values are ignored. If no values can be averaged, this function returns NULL.

May be used as a window function and with the frame clause.

## Syntax

## Aggregate Function

```sql
AVG ( [DISTINCT] expression )
```

## Window Function & Window Frame Clause

```sql
AVG( [ DISTINCT ] ( ) OVER (
     [ PARTITION BY (col | expr), ...] 
     [ORDER BY (col | expr), ...] [ <window_frame> ]
)
```

## Arguments

* DISTINCT: optional keyword. If present, will average the unique values.
* expression: any numerical expression. This may be a column name, the result of another function, or a math operation

## Return Type

A double if the input type is double, otherwise decimal.

## Examples

```sql
CREATE TABLE player_scores(player_name VARCHAR(50), player_id VARCHAR(10), 
    1st_qtr_score DECIMAL(5,2), 2nd_qtr_score DECIMAL(5,2), 
    3rd_qtr_score DECIMAL(5,2), 4th_qtr_score DECIMAL(5,2), 
    yearly_total AS 1st_qtr_score + 2nd_qtr_score + 3rd_qtr_score + 4th_qtr_score PERSISTED DECIMAL(5,2));

INSERT INTO player_scores VALUES
    ('Steve', '119','22.50','72.00', '63.00', '45.00'),
    ('Jack', '432', '90.10', '78.00','88.20', '92.20'),
    ('Jim', '779','75.00', '68.90','55.70', '72.00'), 
    ('Eve', '189','91.50', '88.10', '95.00', '94.50'),
    ('Shelia','338', '75.60', '72.00', '81.10', '78.40'),
    ('June', '521', '81.00', '87.30','76.80','82.20'),
    ('Martin', '674','98.80', '95.10', '88.00', '96.40');

```

## Aggregate Function

```sql
SELECT AVG(yearly_total) FROM player_scores;

```

```output

+-------------------+
| AVG(yearly_total) |
+-------------------+
|        314.914286 |
+-------------------+

```

```sql
SELECT AVG(yearly_total), (player_name) FROM player_scores GROUP BY player_name;

```

```output

+-------------------+-------------+
| AVG(yearly_total) | player_name |
+-------------------+-------------+
|        327.300000 | June        |
|        348.500000 | Jack        |
|        369.100000 | Eve         |
|        202.500000 | Steve       |
|        378.300000 | Martin      |
|        271.600000 | Jim         |
|        307.100000 | Shelia      |
+-------------------+-------------+
```

## Window Function

```sql
SELECT player_id, avg(1st_qtr_score), avg(2nd_qtr_score), avg(3rd_qtr_score), avg(4th_qtr_score) 
OVER (PARTITION BY player_id) 
FROM player_scores 
GROUP BY player_id 
ORDER BY player_id;

```

```output

+-----------+--------------------+--------------------+--------------------+--------------------------+
| player_id | avg(1st_qtr_score) | avg(2nd_qtr_score) | avg(3rd_qtr_score) | avg(4th_qtr_score) OVER  |
|           |                    |                    |                    | (partition by player_id) |
+-----------+--------------------+--------------------+--------------------+--------------------------+
| 119       |          22.500000 |          72.000000 |          63.000000 |                45.000000 |
| 189       |          91.500000 |          88.100000 |          95.000000 |                94.500000 |
| 338       |          75.600000 |          72.000000 |          81.100000 |                78.400000 |
| 432       |          90.100000 |          78.000000 |          88.200000 |                92.200000 |
| 521       |          81.000000 |          87.300000 |          76.800000 |                82.200000 |
| 674       |          98.800000 |          95.100000 |          88.000000 |                96.400000 |
| 779       |          75.000000 |          68.900000 |          55.700000 |                72.000000 |
+-----------+--------------------+--------------------+--------------------+--------------------------+

```

```sql
CREATE TABLE avg_tick_table(TIMESTAMP DATETIME(6), symbol VARCHAR(5), comp_name VARCHAR (30), price NUMERIC(18,4));

INSERT INTO avg_tick_table VALUES('2022-11-18 10:55:36.000000', 'STC', 'SomeTechCo', 100.00),  
('2022-11-18 10:55:37.000000', 'STC', 'SomeTechCo', 102.00),
('2022-11-18 10:55:42.000000', 'STC', 'SomeTechCo', 105.00),
('2022-11-18 10:55:48.000000', 'STC', 'SomeTechCo', 101.00),
('2022-11-18 10:56:03.000000', 'STC', 'SomeTechCo', 99.00),
('2022-11-18 10:55:42.000000', 'AME', 'ACME', 198.00),
('2022-11-18 10:55:50.000000', 'AME', 'ACME', 208.00),
('2022-11-18 10:55:52.000000', 'AME', 'ACME', 210.00),
('2022-11-18 10:55:55.000000', 'AME', 'ACME', 211.00),
('2022-11-18 10:55:52.000000', 'OCO', 'OnCallCo', 21.00),
('2022-11-18 10:55:55.000000', 'OCO', 'OnCallCo', 22.00),
('2022-11-18 10:55:57.000000', 'OCO', 'OnCallCo', 21.00),
('2022-11-18 10:56:00.000000', 'OCO', 'OnCallCo', 23.00),
('2022-11-18 10:56:03.000000', 'OCO', 'OnCallCo', 24.00);
```

```sql
SELECT TIMESTAMP, symbol, price, AVG(price) OVER (PARTITION BY symbol) FROM avg_tick_table GROUP BY TIMESTAMP;


```

```output

+----------------------------+--------+----------+---------------------------------------+
| TIMESTAMP                  | symbol | price    | AVG(price) OVER (PARTITION BY symbol) |
+----------------------------+--------+----------+---------------------------------------+
| 2022-11-18 10:55:50.000000 | AME    | 208.0000 |                          209.00000000 |
| 2022-11-18 10:55:52.000000 | AME    | 210.0000 |                          209.00000000 |
| 2022-11-18 10:55:57.000000 | OCO    |  21.0000 |                           22.50000000 |
| 2022-11-18 10:56:00.000000 | OCO    |  23.0000 |                           22.50000000 |
| 2022-11-18 10:56:03.000000 | OCO    |  24.0000 |                           22.50000000 |
| 2022-11-18 10:55:55.000000 | OCO    |  22.0000 |                           22.50000000 |
| 2022-11-18 10:55:36.000000 | STC    | 100.0000 |                          102.00000000 |
| 2022-11-18 10:55:48.000000 | STC    | 101.0000 |                          102.00000000 |
| 2022-11-18 10:55:42.000000 | STC    | 105.0000 |                          102.00000000 |
| 2022-11-18 10:55:37.000000 | STC    | 102.0000 |                          102.00000000 |
+----------------------------+--------+----------+---------------------------------------+
```

## Window Frame Clause

```sql
CREATE TABLE avg_table(col_a INT, col_b DECIMAL(4,2), 
   col_c DECIMAL(4,2), col_d VARCHAR(15), col_e INT);

INSERT INTO avg_table VALUES(1, 1.1, 11.17, 'one', 47),
(2, 2.2, 22.21, 'two', NULL),
(NULL, 3.3, 33.32, 'three', 892),
(4, 4.4, 44.43, 'four', NULL),
(5, 5.5, 55.54, 'five', 1102),
(6, NULL, 66.65, 'six', NULL);

```

```sql
SELECT col_a, col_b, col_c, col_d, col_e,
AVG(col_e) OVER 
(PARTITION BY col_a ORDER BY col_b rows between UNBOUNDED PRECEDING
and CURRENT ROW) avg_col_e_rows_pre
FROM avg_table
ORDER BY col_a;


```

```output

+-------+-------+-------+-------+-------+--------------------+
| col_a | col_b | col_c | col_d | col_e | avg_col_e_rows_pre |
+-------+-------+-------+-------+-------+--------------------+
|  NULL |  3.30 | 33.32 | three |   892 |           892.0000 |
|     1 |  1.10 | 11.17 | one   |    47 |            47.0000 |
|     2 |  2.20 | 22.21 | two   |  NULL |               NULL |
|     4 |  4.40 | 44.43 | four  |  NULL |               NULL |
|     5 |  5.50 | 55.54 | five  |  1102 |          1102.0000 |
|     6 |  NULL | 66.65 | six   |  NULL |               NULL |
+-------+-------+-------+-------+-------+--------------------+

```

```sql
SELECT TIMESTAMP, symbol, price,
AVG(price) OVER (PARTITION BY symbol
ROWS between 1 PRECEDING
and CURRENT ROW) AS AVG_2,
AVG(price) OVER (ORDER BY TIMESTAMP
ROWS between 2 PRECEDING
and CURRENT ROW) AS AVG_3
FROM avg_tick_table;


```

```output

+----------------------------+--------+----------+--------------+--------------+
| TIMESTAMP                  | symbol | price    | AVG_2        | AVG_3        |
+----------------------------+--------+----------+--------------+--------------+
| 2022-11-18 10:55:36.000000 | STC    | 100.0000 | 100.50000000 | 100.00000000 |
| 2022-11-18 10:55:37.000000 | STC    | 102.0000 | 103.50000000 | 101.00000000 |
| 2022-11-18 10:55:42.000000 | STC    | 105.0000 | 105.00000000 | 102.33333333 |
| 2022-11-18 10:55:42.000000 | AME    | 198.0000 | 204.50000000 | 135.00000000 |
| 2022-11-18 10:55:48.000000 | STC    | 101.0000 | 101.50000000 | 134.66666667 |
| 2022-11-18 10:55:50.000000 | AME    | 208.0000 | 203.00000000 | 169.00000000 |
| 2022-11-18 10:55:52.000000 | OCO    |  21.0000 |  22.00000000 | 110.00000000 |
| 2022-11-18 10:55:52.000000 | AME    | 210.0000 | 210.00000000 | 146.33333333 |
| 2022-11-18 10:55:55.000000 | OCO    |  22.0000 |  23.00000000 |  84.33333333 |
| 2022-11-18 10:55:55.000000 | AME    | 211.0000 | 210.50000000 | 147.66666667 |
| 2022-11-18 10:55:57.000000 | OCO    |  21.0000 |  21.00000000 |  84.66666667 |
| 2022-11-18 10:56:00.000000 | OCO    |  23.0000 |  22.50000000 |  85.00000000 |
| 2022-11-18 10:56:03.000000 | STC    |  99.0000 |  99.50000000 |  47.66666667 |
| 2022-11-18 10:56:03.000000 | OCO    |  24.0000 |  24.00000000 |  48.66666667 |
+----------------------------+--------+----------+--------------+--------------+

```

***

Modified at: May 31, 2023

Source: [/db/v9.1/reference/sql-reference/aggregate-functions/avg/](https://docs.singlestore.com/db/v9.1/reference/sql-reference/aggregate-functions/avg/)

(An index of the documentation is available at /llms.txt)