**Course Title:** SQLite Mastery: Lightweight Database Management **Section Title:** Aggregate Functions and Grouping Data **Topic:** Grouping data with GROUP BY **Introduction** In the previous topic, we explored the use of aggregate functions in SQLite, including COUNT, SUM, AVG, MIN, and MAX. However, in many cases, we may want to apply these aggregate functions to groups of data rather than the entire dataset. This is where the GROUP BY clause comes in. In this topic, we will delve into the world of grouping data with GROUP BY and explore how to use this powerful clause to gain insights into our data. **What is GROUP BY?** The GROUP BY clause is used to group rows of a result set based on one or more columns. This allows us to apply aggregate functions to each group of rows, which is useful for tasks such as calculating summaries or detecting patterns in the data. **Syntax** The basic syntax of the GROUP BY clause is as follows: ```sql SELECT column1, column2, ... FROM tablename GROUP BY column1, column2, ...; ``` In this syntax, we specify the columns we want to select, the table we want to query, and the columns we want to group by. **Example 1: Grouping by a Single Column** Suppose we have a table called "employees" with the following structure: | id | name | department | salary | | --- | --- | --- | --- | | 1 | John | Sales | 50000 | | 2 | Jane | Marketing | 60000 | | 3 | Bob | Sales | 55000 | | 4 | Alice | Marketing | 70000 | We want to calculate the average salary for each department. We can use the GROUP BY clause as follows: ```sql SELECT department, AVG(salary) AS avg_salary FROM employees GROUP BY department; ``` This will give us a result set with two rows, one for each department, and the average salary for each department. **Example 2: Grouping by Multiple Columns** Suppose we have a table called "orders" with the following structure: | id | customer_id | order_date | total | | --- | --- | --- | --- | | 1 | 1 | 2022-01-01 | 100 | | 2 | 1 | 2022-01-15 | 200 | | 3 | 2 | 2022-02-01 | 300 | | 4 | 2 | 2022-03-01 | 400 | We want to calculate the total orders for each customer in each quarter. We can use the GROUP BY clause as follows: ```sql SELECT customer_id, STRFTIME('%Y', order_date) AS year, STRFTIME('%q', order_date) AS quarter, SUM(total) AS total_orders FROM orders GROUP BY customer_id, STRFTIME('%Y', order_date), STRFTIME('%q', order_date); ``` This will give us a result set with two rows for each customer, one for each quarter, and the total orders for each quarter. **Key Concepts** * The GROUP BY clause groups rows of a result set based on one or more columns. * Aggregate functions can be applied to each group of rows. * The GROUP BY clause must be used in conjunction with an aggregate function or a grouping function. **Best Practices** * Use the GROUP BY clause when you want to apply aggregate functions to groups of rows rather than the entire dataset. * Make sure to specify all non-aggregated columns in the GROUP BY clause. * Use indexes on the columns used in the GROUP BY clause to improve performance. **Conclusion** In this topic, we explored the use of the GROUP BY clause in SQLite to group data based on one or more columns. We saw examples of how to use the GROUP BY clause to calculate summaries and detect patterns in the data. We also discussed key concepts and best practices for using the GROUP BY clause effectively. **Additional Resources** * SQLite documentation on GROUP BY clause: [https://sqlite.org/lang_select.html](https://sqlite.org/lang_select.html) * W3Schools tutorial on GROUP BY clause: [https://www.w3schools.com/sql/sql_groupby.asp](https://www.w3schools.com/sql/sql_groupby.asp) **Comment Below** If you have any questions or need further clarification on the GROUP BY clause, please leave a comment below. What are some scenarios where you have used the GROUP BY clause in your own projects? **Next Topic:** In the next topic, we will explore how to filter grouped data using the HAVING clause.