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SQL: NOT Condition

This SQL tutorial explains how to use the SQL NOT condition with syntax and examples.

Description

The SQL NOT condition (sometimes called the NOT Operator) is used to negate a condition in the WHERE clause of a SELECT, INSERT, UPDATE, or DELETE statement.

Syntax

The syntax for the NOT condition in SQL is:

NOT condition

Parameters or Arguments

condition
This is the condition to negate. The opposite of the condition must be met for the record to be included in the result set.

DDL/DML for Examples

If you want to follow along with this tutorial, get the DDL to create the tables and the DML to populate the data. Then try the examples in your own database!

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Example - Using NOT with the IN Condition

Let's start by looking at how to use NOT with the IN condition. When we use the NOT operator with the IN condition, we create a NOT IN condition. This will test to see if an expression is not in a list.

In this example, we have a table called products with the following data:

product_id product_name category_id
1 Pear 50
2 Banana 50
3 Orange 50
4 Apple 50
5 Bread 75
6 Sliced Ham 25
7 Kleenex NULL

Enter the following SQL statement:

Try It
SELECT *
FROM products
WHERE product_name NOT IN ('Pear', 'Banana', 'Bread');

There will be 4 records selected. These are the results that you should see:

product_id product_name category_id
3 Orange 50
4 Apple 50
6 Sliced Ham 25
7 Kleenex NULL

This example would return all rows from the products table where the product_name is not Pear, Banana or Bread. Sometimes, it is more efficient to list the values that you do not want, as opposed to the values that you do want.

It is equivalent to the following SQL statement:

Try It
SELECT *
FROM products
WHERE product_name <> 'Pear'
AND product_name <> 'Banana'
AND product_name <> 'Bread';

Example - Using NOT with the IS NULL Condition

When you combine the NOT operator with the IS NULL condition, you create an IS NOT NULL condition that allows you to test for a non-NULL value. This is the recommended comparison operator to use in SQL when testing for non-NULL values. Let's look at an example that shows how to use the IS NOT NULL condition in a query.

Using the same products as the previous example:

product_id product_name category_id
1 Pear 50
2 Banana 50
3 Orange 50
4 Apple 50
5 Bread 75
6 Sliced Ham 25
7 Kleenex NULL

Enter the following SQL statement:

Try It
SELECT *
FROM products
WHERE category_id IS NOT NULL;

There will be 6 records selected. These are the results that you should see:

product_id product_name category_id
1 Pear 50
2 Banana 50
3 Orange 50
4 Apple 50
5 Bread 75
6 Sliced Ham 25

This example will return all records from the products table where the customer_id does not contain a NULL value.

Example - Using NOT with the LIKE Condition

Next, let's look at an example of how to use the NOT operator with the LIKE condition.

In this example, we have a table called suppliers with the following data:

supplier_id supplier_name city state
100 Microsoft Redmond Washington
200 Google Mountain View California
300 Oracle Redwood City California
400 Kimberly-Clark Irving Texas
500 Tyson Foods Springdale Arkansas
600 SC Johnson Racine Wisconsin
700 Dole Food Company Westlake Village California
800 Flowers Foods Thomasville Georgia
900 Electronic Arts Redwood City California

Let's look for all records in the suppliers table where the supplier_name does not contain the letter 'o'. Enter the following SQL statement:

Try It
SELECT *
FROM suppliers
WHERE supplier_name NOT LIKE '%o%';

There will be 1 record selected. These are the results that you should see:

supplier_id supplier_name city state
400 Kimberly-Clark Irving Texas

In this example, there is only one record in the suppliers table where the supplier_name does not contain the letter 'o'.

Example - Using NOT with the BETWEEN Condition

The NOT operator can also be combined with the BETWEEN condition to create a NOT BETWEEN condition. Let's explore an example that shows how to use the NOT BETWEEN condition in a query.

In this example, we have a table called customers with the following data:

customer_id last_name first_name favorite_website
4000 Jackson Joe techonthenet.com
5000 Smith Jane digminecraft.com
6000 Ferguson Samantha bigactivities.com
7000 Reynolds Allen checkyourmath.com
8000 Anderson Paige NULL
9000 Johnson Derek techonthenet.com

Enter the following SQL statement:

Try It
SELECT *
FROM customers
WHERE customer_id NOT BETWEEN 5000 AND 8000;

There will be 2 records selected. These are the results that you should see:

customer_id last_name first_name favorite_website
4000 Jackson Joe techonthenet.com
9000 Johnson Derek techonthenet.com

This would return all rows where the customer_id was NOT between 5000 and 8000, inclusive. It would be equivalent to the following SELECT statement:

Try It
SELECT *
FROM customers
WHERE customer_id < 5000
OR customer_id > 8000;

Example - Using NOT with the EXISTS Condition

Finally, the NOT condition can be combined with the EXISTS condition to create a NOT EXISTS condition. Let's look at an example that shows how to use the NOT EXISTS condition in SQL.

In this example, we have a table called customers with the following data:

customer_id last_name first_name favorite_website
4000 Jackson Joe techonthenet.com
5000 Smith Jane digminecraft.com
6000 Ferguson Samantha bigactivities.com
7000 Reynolds Allen checkyourmath.com
8000 Anderson Paige NULL
9000 Johnson Derek techonthenet.com

And a table called orders with the following data:

order_id customer_id order_date
1 7000 2016/04/18
2 5000 2016/04/18
3 8000 2016/04/19
4 4000 2016/04/20
5 NULL 2016/05/01

Enter the following SQL statement:

Try It
SELECT *
FROM customers
WHERE NOT EXISTS
  (SELECT * 
   FROM orders
   WHERE customers.customer_id = orders.customer_id);

There will be 2 records selected. These are the results that you should see:

customer_id last_name first_name favorite_website
6000 Ferguson Samantha bigactivities.com
9000 Johnson Derek techonthenet.com

This example would return all records from the customers table where there are no records in the orders table for the given customer_id.