When working with large datasets in SQL, it is common to encounter rows with null or empty data. These empty values can occur for a variety of reasons, such as missing information or data entry errors. While it may seem like a minor issue, these empty values can cause problems when running queries or performing data analysis. In this article, we will explore how to filter out rows with null or empty data in SQL.
Null values, also known as missing values, represent the absence of data. They can occur in any data type, including strings, numbers, and dates. In SQL, null values are represented by the keyword NULL. On the other hand, empty values refer to data that is present but has no value. For example, an empty string '' or a zero value for a numeric column. Both null and empty values can cause issues when working with data, as they can skew results and calculations.
To filter out rows with null or empty data, we can use the WHERE clause in our SQL query. The WHERE clause allows us to specify conditions for the data we want to retrieve from a table. Let's say we have a table called "employees" with the following columns: id, name, department, and salary. We want to retrieve all the employees from the sales department with a salary greater than 50000. However, some employees' salary values are missing, and we don't want them to be included in our results.
We can use the IS NOT NULL operator in our WHERE clause to filter out null values for the salary column. This operator checks if a value is not null and returns true if it is not, and false if it is. Our query would look like this:
SELECT id, name, department, salary
FROM employees
WHERE department = 'sales' AND salary > 50000
AND salary IS NOT NULL;
This query will only retrieve employees from the sales department with a salary greater than 50000 and exclude those with null values for the salary column.
Similarly, we can use the IS NOT NULL operator to filter out empty values. Let's say we have a table called "products" with the following columns: id, name, category, and price. We want to retrieve all the products from the electronics category with a price greater than zero. However, some products' prices are missing, and we don't want them to be included in our results.
Our query would look like this:
SELECT id, name, category, price
FROM products
WHERE category = 'electronics' AND price > 0
AND price IS NOT NULL;
This query will only retrieve products from the electronics category with a price greater than zero and exclude those with empty values for the price column.
In some cases, we may want to retrieve rows with null or empty data instead of filtering them out. For example, if we want to update or replace the null or empty values with a default value. In such cases, we can use the IS NULL operator in our WHERE clause. This operator checks if a value is null and returns true if it is, and false if it is not.
Let's say we want to update the products table and replace all empty values in the price column with a default value of 100. Our query would look like this:
UPDATE products
SET price = 100
WHERE price IS NULL;
This query will update all the rows with empty values in the price column and replace them with 100.
