- MySQL Basics
- MySQL - Home
- MySQL - Introduction
- MySQL - Features
- MySQL - Versions
- MySQL - Variables
- MySQL - Installation
- MySQL - Administration
- MySQL - PHP Syntax
- MySQL - Node.js Syntax
- MySQL - Java Syntax
- MySQL - Python Syntax
- MySQL - Connection
- MySQL - Workbench
- MySQL Databases
- MySQL - Create Database
- MySQL - Drop Database
- MySQL - Select Database
- MySQL - Show Database
- MySQL - Copy Database
- MySQL - Database Export
- MySQL - Database Import
- MySQL - Database Info
- MySQL Users
- MySQL - Create Users
- MySQL - Drop Users
- MySQL - Show Users
- MySQL - Change Password
- MySQL - Grant Privileges
- MySQL - Show Privileges
- MySQL - Revoke Privileges
- MySQL - Lock User Account
- MySQL - Unlock User Account
- MySQL Tables
- MySQL - Create Tables
- MySQL - Show Tables
- MySQL - Alter Tables
- MySQL - Rename Tables
- MySQL - Clone Tables
- MySQL - Truncate Tables
- MySQL - Temporary Tables
- MySQL - Repair Tables
- MySQL - Describe Tables
- MySQL - Add/Delete Columns
- MySQL - Show Columns
- MySQL - Rename Columns
- MySQL - Table Locking
- MySQL - Drop Tables
- MySQL - Derived Tables
- MySQL Queries
- MySQL - Queries
- MySQL - Constraints
- MySQL - Insert Query
- MySQL - Select Query
- MySQL - Update Query
- MySQL - Delete Query
- MySQL - Replace Query
- MySQL - Insert Ignore
- MySQL - Insert on Duplicate Key Update
- MySQL - Insert Into Select
- MySQL Indexes
- MySQL - Indexes
- MySQL - Create Index
- MySQL - Drop Index
- MySQL - Show Indexes
- MySQL - Unique Index
- MySQL - Clustered Index
- MySQL - Non-Clustered Index
- MySQL Operators and Clauses
- MySQL - Where Clause
- MySQL - Limit Clause
- MySQL - Distinct Clause
- MySQL - Order By Clause
- MySQL - Group By Clause
- MySQL - Having Clause
- MySQL - AND Operator
- MySQL - OR Operator
- MySQL - Like Operator
- MySQL - IN Operator
- MySQL - ANY Operator
- MySQL - EXISTS Operator
- MySQL - NOT Operator
- MySQL - NOT EQUAL Operator
- MySQL - IS NULL Operator
- MySQL - IS NOT NULL Operator
- MySQL - Between Operator
- MySQL - UNION Operator
- MySQL - UNION vs UNION ALL
- MySQL - MINUS Operator
- MySQL - INTERSECT Operator
- MySQL - INTERVAL Operator
- MySQL Joins
- MySQL - Using Joins
- MySQL - Inner Join
- MySQL - Left Join
- MySQL - Right Join
- MySQL - Cross Join
- MySQL - Full Join
- MySQL - Self Join
- MySQL - Delete Join
- MySQL - Update Join
- MySQL - Union vs Join
- MySQL Keys
- MySQL - Unique Key
- MySQL - Primary Key
- MySQL - Foreign Key
- MySQL - Composite Key
- MySQL - Alternate Key
- MySQL Triggers
- MySQL - Triggers
- MySQL - Create Trigger
- MySQL - Show Trigger
- MySQL - Drop Trigger
- MySQL - Before Insert Trigger
- MySQL - After Insert Trigger
- MySQL - Before Update Trigger
- MySQL - After Update Trigger
- MySQL - Before Delete Trigger
- MySQL - After Delete Trigger
- MySQL Data Types
- MySQL - Data Types
- MySQL - VARCHAR
- MySQL - BOOLEAN
- MySQL - ENUM
- MySQL - DECIMAL
- MySQL - INT
- MySQL - FLOAT
- MySQL - BIT
- MySQL - TINYINT
- MySQL - BLOB
- MySQL - SET
- MySQL Regular Expressions
- MySQL - Regular Expressions
- MySQL - RLIKE Operator
- MySQL - NOT LIKE Operator
- MySQL - NOT REGEXP Operator
- MySQL - regexp_instr() Function
- MySQL - regexp_like() Function
- MySQL - regexp_replace() Function
- MySQL - regexp_substr() Function
- MySQL Fulltext Search
- MySQL - Fulltext Search
- MySQL - Natural Language Fulltext Search
- MySQL - Boolean Fulltext Search
- MySQL - Query Expansion Fulltext Search
- MySQL - ngram Fulltext Parser
- MySQL Functions & Operators
- MySQL - Date and Time Functions
- MySQL - Arithmetic Operators
- MySQL - Numeric Functions
- MySQL - String Functions
- MySQL - Aggregate Functions
- MySQL Misc Concepts
- MySQL - NULL Values
- MySQL - Transactions
- MySQL - Using Sequences
- MySQL - Handling Duplicates
- MySQL - SQL Injection
- MySQL - SubQuery
- MySQL - Comments
- MySQL - Check Constraints
- MySQL - Storage Engines
- MySQL - Export Table into CSV File
- MySQL - Import CSV File into Database
- MySQL - UUID
- MySQL - Common Table Expressions
- MySQL - On Delete Cascade
- MySQL - Upsert
- MySQL - Horizontal Partitioning
- MySQL - Vertical Partitioning
- MySQL - Cursor
- MySQL - Stored Functions
- MySQL - Signal
- MySQL - Resignal
- MySQL - Character Set
- MySQL - Collation
- MySQL - Wildcards
- MySQL - Alias
- MySQL - ROLLUP
- MySQL - Today Date
- MySQL - Literals
- MySQL - Stored Procedure
- MySQL - Explain
- MySQL - JSON
- MySQL - Standard Deviation
- MySQL - Find Duplicate Records
- MySQL - Delete Duplicate Records
- MySQL - Select Random Records
- MySQL - Show Processlist
- MySQL - Change Column Type
- MySQL - Reset Auto-Increment
- MySQL - Coalesce() Function
MySQL - VAR_POP() Function
The MySQL VAR_POP() function calculates and returns population standard variance of a particular column. It measures how much each number in the set differs from the average (mean) of the entire set. If the specified row(s) doesn't exist this function returns NULL.
This function is only applied on columns/fields with numeric datatype as mathematical operations are applied on them.
Syntax
Following is the syntax of MySQL VAR_POP() function −
VAR_POP(expr);
Parameters
This method accepts a parameter. The same is described below −
expr: An expression or column for which we want to calculate the population standard variance.
Return value
This function calculates and returns population standard variance of a particular column.
Example
First of all, let us create a table named CUSTOMERS using the CREATE TABLE statement as follows −
CREATE TABLE CUSTOMERS ( ID INT AUTO_INCREMENT, NAME VARCHAR(20) NOT NULL, AGE INT NOT NULL, ADDRESS CHAR (25), SALARY DECIMAL (18, 2), PRIMARY KEY (ID) );
The below query inserts 7 records into the above created table −
INSERT INTO CUSTOMERS (ID,NAME,AGE,ADDRESS,SALARY) VALUES (1, 'Ramesh', 32, 'Ahmedabad', 2000.00 ), (2, 'Khilan', 25, 'Delhi', 1500.00 ), (3, 'Kaushik', 23, 'Kota', 2000.00 ), (4, 'Chaitali', 25, 'Mumbai', 6500.00 ), (5, 'Hardik', 27, 'Bhopal', 8500.00 ), (6, 'Komal', 22, 'Hyderabad', 4500.00 ), (7, 'Muffy', 24, 'Indore', 10000.00 );
Execute the following query to fetch all the records that are inserted in the CUSTOMERS table −
Select * From CUSTOMERS;
Following is the CUSTOMERS table −
ID | NAME | AGE | ADDRESS | SALARY |
---|---|---|---|---|
1 | Ramesh | 32 | Ahmedabad | 2000.00 |
2 | Khilan | 25 | Delhi | 1500.00 |
3 | Kaushik | 23 | Kota | 2000.00 |
4 | Chaitali | 25 | Mumbai | 6500.00 |
5 | Hardik | 27 | Bhopal | 8500.00 |
6 | Komal | 22 | Hyderabad | 4500.00 |
7 | Muffy | 24 | Indore | 10000.00 |
Here, we are using the MySQL VAR_POP() function to calculate the population standard variance of salaries of all the customers −
SELECT VAR_POP(SALARY) FROM CUSTOMERS;
Output
This will produce the following result −
VAR_POP(SALARY) |
---|
10000000 |
Example
Let us consider a scenario where there is same value in the data set −
In the CUSTOMERS table, the customer with ID 2 and 5 has same age. If we calculate the variance of their age, the VAR_POP() function will return 0 as output because both has same age values.
SELECT VAR_POP(AGE) FROM CUSTOMERS WHERE ID = 2;
The output for the query above is produced as given below −
VAR_POP(AGE) |
---|
0 |
Now, let us consider a scenario where there is only one value in the data set −
SELECT VAR_POP(AGE) FROM CUSTOMERS WHERE ID = 3;
The result for the above query will also be 0 because there's only customer with age 23 −
VAR_POP(AGE) |
---|
0 |
Now, let us consider a scenario where there is no data in the data set −
SELECT VAR_POP(AGE) FROM CUSTOMERS WHERE ID = 10;
The result of this query will be NULL because there are no values present for ID = 10 in the table −
VAR_POP(AGE) |
---|
NULL |