Introduction to SQL CASE expressions
When it comes to working with databases, SQL is the go-to language for developers and analysts alike. SQL provides various features that allow for efficient data manipulation and retrieval, one of which is the SQL CASE expression.
SQL CASE is a powerful tool that can be used to apply if-else logic to query results, making it easier to handle complex data. In this article, we will explore the purpose and usage of SQL CASE, as well as the results and data types it produces.
We will also provide a simple example to demonstrate how SQL CASE works in practice.
Usage and syntax
Before diving in
to SQL CASE expressions, it is essential to understand the necessary syntax to use it correctly. The primary keywords required for SQL CASE are
SELECT, WHERE, and
GROUP BY, which all help to retrieve specific data from the database. The syntax for SQL CASE is as follows:
SELECT
column_1,
CASE
WHEN condition_1 THEN result_1
WHEN condition_2 THEN result_2
ELSE result_3
END
FROM
table_1
WHERE
condition_3
GROUP BY
column_1;
Here, “column_1” is the column that is being selected, and “table_1” is the table from which the data is being retrieved. “condition_3” is a condition that is being used to filter the results, and “CASE” provides the if-else functionality.
Results and Data Types
The SQL CASE expression produces a result that depends on the conditions specified in the query. The result can be any value or data type, depending on the context of the query.
For example, if the column being selected is a text type, then the result of the CASE expression will also be text.
Simple SQL CASE example
The following simple example demonstrates how SQL CASE can be used to calculate a bonus amount based on employee salaries:
SELECT
employee_name,
CASE
WHEN salary > 50000 THEN salary * 0.1
WHEN salary BETWEEN 30000 AND 50000 THEN salary * 0.05
ELSE salary * 0.02
END AS bonus_amount
FROM
employee_data
WHERE
department = 'Sales';
Here, we are selecting the employee name and the bonus amount calculated based on their salary. If the salary is above 50,000, the bonus is calculated as 10% of the salary.
If the salary is between 30,000 and 50,000, the bonus is calculated as 5% of the salary, and for salaries below 30,000, the bonus is calculated as 2% of the salary.
Matching conditions and results
The SQL CASE expression evaluates the specified conditions in the order they are written. Once a matching condition is found, it stops evaluating and returns the corresponding result.
If none of the conditions match, then the ELSE clause provides a fallback result.
Data type of result
As mentioned earlier, the data type of the result depends on the context of the query. SQL CASE produces results that match the data type of the column being selected.
If the column is a numeric type, the result of the CASE expression will also be numeric. Similarly, if the column is a text type, the result will also be text.
3) SQL CASE WHEN with ELSE
SQL CASE expressions allow for massive flexibility in analyzing data, but not all scenarios can be predicted before running the query. The use of an ELSE statement in the SQL CASE expression can provide a fallback when none of the specified conditions match.
Adding ELSE statement
The ELSE statement in the SQL CASE expression is optional but recommended, especially for queries where all possible conditions are not known beforehand. It provides a catch-all clause that ensures that there is a result even if none of the specified conditions match.
SELECT
product_name,
CASE
WHEN product_price > 100 THEN 'Expensive'
WHEN product_price >= 50 AND product_price <= 100 THEN 'Moderate'
ELSE 'Inexpensive' -- adding ELSE statement
END AS 'Price Category'
FROM
products;
In the above query, we categorize the products based on their price, but not all products may fit into the specified categories. The inclusion of an ELSE statement ensures that all products are accurately categorized.
Categorizing data into multiple groups
Multiple conditions can be specified in a single SQL CASE expression, categorizing data into more than two categories. This method is useful in situations where data needs to be classified into multiple groups.
SELECT
product_name,
CASE
WHEN product_weight < 100 THEN 'Light'
WHEN product_weight >= 100 AND product_weight < 500 THEN 'Medium'
WHEN product_weight >= 500 THEN 'Heavy'
END AS 'Weight Category'
FROM
products;
In this query, product data is classified based on its weight, forming three categories: Light, Medium, and Heavy.
4) Using multiple CASEs
Multiple SQL CASE expressions can be used in a single query to evaluate multiple conditions. This method is useful when working with complex logic that requires multiple conditions to be applied before generating the query result.
Evaluating multiple conditions
In the following query, we use multiple SQL CASE expressions to evaluate multiple conditions. “`
SELECT
customer_name,
CASE
WHEN order_total > 1000 THEN 'Platinum'
WHEN order_total >= 500 AND order_total < 1000 THEN 'Gold'
ELSE 'Bronze'
END AS 'Category',
CASE
WHEN order_date > '2021-01-01' THEN 'New'
ELSE 'Returning'
END AS 'Customer Type'
FROM
orders;
The query generates a report that classifies customers into different categories based on their order total and customer type. The use of two SQL CASE expressions enables us to apply the complex logic required to generate the desired report.
Generating a report for stock table
The following query demonstrates how multiple SQL CASE expressions can generate a report for a stock table:
SELECT
product_name,
SUM(CASE WHEN warehouse_location = 'A' THEN quantity ELSE 0 END) AS 'A',
SUM(CASE WHEN warehouse_location = 'B' THEN quantity ELSE 0 END) AS 'B',
SUM(CASE WHEN warehouse_location = 'C' THEN quantity ELSE 0 END) AS 'C',
SUM(quantity) AS 'Total'
FROM
stock
GROUP BY
product_name;
In this query, we use multiple SQL CASE expressions to generate a report of the total quantity of stock in each warehouse location for each product. The use of the SUM() function and
GROUP BY clause enable us to perform the necessary calculations and group the results by the product name.
Conclusion
SQL CASE expressions enable complex logic to be applied to query results, allowing for efficient data analysis. Whether it is to categorize data or generate complex reports, SQL CASE expressions are a powerful tool in the data analyst’s toolkit.
Understanding the syntax and how to use SQL CASE is crucial for queries that require more complex data analysis. With the knowledge gained from this article, you should be able to incorporate SQL CASE into your queries and work with your data more efficiently.
5) CASE with NULL values
In some queries, NULL values may be present in the data, and SQL CASE expressions must handle these unwanted values properly. SQL CASE can be used to evaluate conditions, but these conditions may not cover all possible scenarios.
Thus, the use of an ELSE statement is vital in preventing unwanted results.
Handling unwanted NULL values
When evaluating conditions, if a value is NULL, it does not match any condition. The result of this scenario depends on the context in which the query is being run.
For example, in a query that is summing values, the result of the query may be NULL if one of the values is NULL. To handle such situations, we can use an ELSE statement to specify what should happen if a NULL value is encountered.
SELECT
product_name,
CASE
WHEN product_weight < 100 THEN 'Light'
WHEN product_weight >= 100 AND product_weight < 500 THEN 'Medium'
ELSE 'Heavy'
END AS 'Weight Category'
FROM
products;
Here, if the product weight is NULL, then the result of the query would be ‘Heavy’, as specified in the ELSE statement.
Scenario not covered by conditions
Suppose there is a situation where the conditions specified in the SQL CASE expression do not match a particular scenario. In that case, the result would be NULL unless an ELSE statement was included.
For example:
SELECT
customer_id,
CASE
WHEN country='USA' THEN 'American'
WHEN country='FR' THEN 'French'
END AS 'Country of Origin'
FROM
customers;
If the customers’ country of origin is not the USA or France, the result of the SQL CASE expression will be NULL. To avoid this issue, it’s essential to include an ELSE statement that covers any uncovered scenarios.
6)
GROUP BY with CASE
SQL CASE statements can also be used with the
GROUP BY clause to group data based on categories and aggregate functions. This method is helpful in situations where data needs to be classified into groups before calculating any aggregate functions.
Using with
GROUP BY
In the following query, we use SQL CASE with the
GROUP BY clause to categorize data based on the total sold quantity within a particular price range. “`
SELECT
CASE
WHEN product_price BETWEEN 10 AND 20 THEN 'Low'
WHEN product_price BETWEEN 21 AND 50 THEN 'Medium'
ELSE 'High'
END AS 'Product Category',
SUM(sold_quantity) AS 'Total Sold'
FROM
products
GROUP BY
CASE
WHEN product_price BETWEEN 10 AND 20 THEN 'Low'
WHEN product_price BETWEEN 21 AND 50 THEN 'Medium'
ELSE 'High'
END;
The query generates a report categorized by the total sold quantity in each price range, forming three categories: Low, Medium, and High.
Grouping items based on price
In the following query, we use SQL CASE with the MIN() and MAX() aggregate functions to group items based on their price range. “`
SELECT
product_category,
MIN(product_price) AS 'Minimum Price',
MAX(product_price) AS 'Maximum Price'
FROM
products
GROUP BY
CASE
WHEN product_price BETWEEN 1 AND 10 THEN 'Cheap'
WHEN product_price BETWEEN 11 AND 50 THEN 'Affordable'
ELSE 'Expensive'
END AS 'Product Category';
The query generates a report that categorizes items into three price ranges: Cheap, Affordable, and Expensive, and calculates the minimum and maximum price within each price range.
Conclusion
SQL CASE expressions are a powerful tool that enables complex logic to be applied to query results, making it an essential tool for data analysts. By understanding how to handle NULL values and include necessary ELSE statements, analysts can retrieve accurate results avoiding any unintentional flawed data.
Using SQL CASE with the
GROUP BY clause enables data categorization into groups, giving meaningful insights, making it easier for analysts in data analysis and decision-making.
7) Reusable complex queries
SQL CASE expressions are not only useful for evaluating simple conditions, but they are also powerful tools for building complex queries. The flexibility of SQL CASE expressions allows for reusable queries that can be used to generate customized reports, regardless of the dataset.
Using SQL CASE for complex queries
In complex queries, it is common to use SQL CASE expressions to evaluate multiple conditions and generate desired results. “`
SELECT
customer_name,
SUM(CASE
WHEN order_date BETWEEN '2021-01-01' AND '2021-06-30' THEN order_total
ELSE 0
END) AS 'Total Sales H1',
SUM(CASE
WHEN order_date BETWEEN '2021-07-01' AND '2021-12-31' THEN order_total
ELSE 0
END) AS 'Total Sales H2'
FROM orders
GROUP BY customer_name;
In this query, we have used a SQL CASE expression to generate the total sales information for each customer name. We specify multiple conditions to retrieve data between January 1st to June 30th, as well as between July 1st to December 31st, using the
GROUP BY clause to divide them per customer name.
The CASE statement sums the relevant order total for each product.
Building customized reports
SQL CASE expressions are essential for building customized reports that need to address complex queries, and sites such as LearnSQL offer useful resources on how to design those types of queries. “`
SELECT
product_name,
CASE
WHEN order_date BETWEEN '2021-01-01' AND '2021-06-30' THEN COUNT(order_id)
END AS 'H1 Sales',
CASE
WHEN order_date BETWEEN '2021-07-01' AND '2021-12-31' THEN COUNT(order_id)
END AS 'H2 Sales'
FROM
orders
JOIN order_items ON order_items.order_id = orders.order_id
JOIN products ON products.product_id = order_items.product_id
GROUP BY
product_name;
This query demonstrates the usefulness of the SQL CASE expression in generating customized reports for specific metrics such as sales for a particular product. We use SQL CASE expressions together with the COUNT aggregate function to retrieve the “H1” and “H2” sales details efficiently.
Conclusion
SQL CASE expressions provide a powerful approach for building complex queries, generating customized reports, and addressing uncommon data requests. Their flexibility and usefulness make it a useful tool for data analysts in their everyday tasks, from gathering data to providing insights to support decision-making.
Through continuous practice and expertise, analysts can improve their SQL mastery and develop the skills to extract meaningful insights from large datasets, making them essential to any business’s success. Sites such as LearnSQL offer useful resources in learning how to use SQL in complex queries.
In conclusion, SQL CASE expressions are a vital tool for data analysts, enabling them to work with complex queries and generate customized reports. By applying if-else logic to query results, analysts can filter and manipulate data with ease, providing valuable insights to decision-makers.
SQL CASE expressions are flexible and powerful, allowing analysts to handle complex scenarios such as NULL values and uncovered scenarios effectively. SQL is a critical skill for data analysts, and mastering SQL CASE expressions is essential for data manipulation and analysis.
Sites such as LearnSQL can help analysts improve their SQL knowledge and expertise, becoming more efficient and effective in handling complex data.