Advanced Filtering and Conditional Logic

Use SQL's AND, OR, and CASE statements for more control over queries

In this lesson, we’ll explore advanced filtering techniques and conditional logic with SQL. You’ll learn how to refine your queries using multiple conditions and implement conditional expressions with the CASE statement.

1. Combining Conditions with AND and OR

In SQL, you can combine multiple conditions in a WHERE clause to narrow down results. The AND and OR operators are used to create more complex filters.

• AND: All conditions must be true for the row to be included in the results.
• OR: At least one condition must be true for the row to be included in the results.

Example: Using AND to Refine Results

• Example: Retrieve users over the age of 25 who have an email ending with “example.com”.

    SELECT * FROM users
    WHERE age > 25 AND email LIKE '%example.com';
  

Example: Using OR to Broaden Results

• Example: Retrieve users who are either named “Alice” or have an age of 30.

    SELECT * FROM users
    WHERE name = 'Alice' OR age = 30;
  

Combining AND and OR

You can combine AND and OR in the same query, but use parentheses to control the logic and ensure accurate results.

• Example: Retrieve users named “Alice” who are older than 25, or users whose age is exactly 30.

    SELECT * FROM users
    WHERE (name = 'Alice' AND age > 25) OR age = 30;
  

2. Using IN for List Filtering

The IN operator allows you to specify a list of values for SQL to search for in a column, simplifying queries with multiple OR conditions.

Example: Using IN

• Example: Retrieve users aged 25, 30, or 35.

    SELECT * FROM users
    WHERE age IN (25, 30, 35);
  

This query is equivalent to using OR conditions but is more concise.

3. Filtering with BETWEEN

The BETWEEN operator is used to filter data within a specific range. It’s often used with numeric or date values.

Example: Using BETWEEN

• Example: Retrieve users aged between 20 and 30 (inclusive).

    SELECT * FROM users
    WHERE age BETWEEN 20 AND 30;
  

Tip: BETWEEN includes the boundary values, so this query retrieves users who are exactly 20 or 30 years old as well as those in between.

4. Pattern Matching with LIKE

The LIKE operator enables pattern matching with the % and _ wildcards:

• %: Matches any sequence of characters.
• _: Matches a single character.

Example: Using LIKE with Wildcards

• Example: Retrieve users whose names start with “A”.

    SELECT * FROM users
    WHERE name LIKE 'A%';
  

• Example: Retrieve users with a 3-letter name where the second letter is “o”.

    SELECT * FROM users
    WHERE name LIKE '_o_';
  

5. Conditional Logic with CASE

The CASE statement in SQL allows you to add conditional logic to your queries. It’s often used to create calculated fields based on certain conditions, similar to IF statements in other languages.

Basic CASE Syntax

SELECT column1,
    CASE
        WHEN condition1 THEN result1
        WHEN condition2 THEN result2
        ELSE result
    END AS new_column
FROM table_name;

Example: Categorizing Data with CASE

Let’s say you want to categorize users based on their age group.

• Example: Create an age category for each user.

    SELECT name, age,
        CASE
            WHEN age < 18 THEN 'Minor'
            WHEN age BETWEEN 18 AND 65 THEN 'Adult'
            ELSE 'Senior'
        END AS age_category
    FROM users;
  

In this example:

• Users under 18 are labeled “Minor”.
• Users between 18 and 65 are labeled “Adult”.
• Users over 65 are labeled “Senior”.

Example: Using CASE with Conditions in WHERE

The CASE statement can also be used to dynamically choose values based on conditions.

• Example: Mark users who don’t have an email with “No Email”.

    SELECT name,
        CASE
            WHEN email IS NULL THEN 'No Email'
            ELSE email
        END AS contact_info
    FROM users;
  

In this example, users without an email will display “No Email” in the contact_info column.

6. Practice Exercise: Advanced Filtering and Conditional Logic

1. Retrieve all users whose age is either 20, 25, or 30 using the IN operator.

    SELECT * FROM users
    WHERE age IN (20, 25, 30);
   

2. Retrieve users with an age between 18 and 30 who also have a name starting with “B”.

    SELECT * FROM users
    WHERE age BETWEEN 18 AND 30 AND name LIKE 'B%';
   

3. Categorize users into “Young Adult” if they are under 25, “Adult” if between 25 and 40, and “Middle-aged” if over 40 using CASE.

    SELECT name, age,
        CASE
            WHEN age < 25 THEN 'Young Adult'
            WHEN age BETWEEN 25 AND 40 THEN 'Adult'
            ELSE 'Middle-aged'
        END AS age_group
    FROM users;
   

4. Display all users, but show “Unknown Email” for any user who does not have an email address.

    SELECT name,
        CASE
            WHEN email IS NULL THEN 'Unknown Email'
            ELSE email
        END AS contact_info
    FROM users;
   

Summary of Advanced Filtering and Conditional Logic

Here’s a recap of the advanced filtering techniques and conditional logic covered in this lesson:

By mastering these advanced filtering techniques and conditional logic, you can create more precise and flexible SQL queries. In the next lesson, we’ll move on to working with joins to retrieve data from multiple tables.

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