Grouping Data Using GROUP BY

The GROUP BY clause in SQL is used to group rows that have the same values in specified columns into summary rows, such as the total, average, or count of each group. It is commonly used in conjunction with aggregate functions like COUNT(), SUM(), AVG(), MAX(), and MIN() to calculate summary statistics for each group.

1. Syntax of GROUP BY

The basic syntax for using GROUP BY is:

SELECT column1, column2, ..., aggregate_function(column_name) FROM table_name WHERE condition GROUP BY column1, column2, ...;
aggregate_function(): A function that performs an operation on a column, such as COUNT(), SUM(), AVG(), MAX(), or MIN().
GROUP BY column1, column2: Specifies the columns by which to group the data.

2. Examples of GROUP BY Usage

Example 1: Counting Records by Group

SELECT department, COUNT(*) AS employee_count FROM employees GROUP BY department;

This query counts the number of employees in each department. The result will display the department and the corresponding count of employees in that department.

Example 2: Summing Values in Groups

SELECT department, SUM(salary) AS total_salary FROM employees GROUP BY department;

This query sums the salaries of employees in each department. It groups the employees by their department and calculates the total salary for each department.

Example 3: Finding Average Salary by Department

SELECT department, AVG(salary) AS average_salary FROM employees GROUP BY department;

This query calculates the average salary for employees in each department. The result will show the department and the corresponding average salary.

Example 4: Using Multiple Columns for Grouping

SELECT department, gender, COUNT(*) AS employee_count FROM employees GROUP BY department, gender;

This query groups employees by both department and gender. It counts how many employees are in each combination of department and gender.

3. Using HAVING with GROUP BY

The HAVING clause is used to filter the results of a GROUP BY query based on aggregate values. While WHERE filters rows before grouping, HAVING filters after the grouping operation.

Example: Filtering Groups with HAVING

SELECT department, COUNT(*) AS employee_count FROM employees GROUP BY department HAVING COUNT(*) > 5;

This query groups employees by department and counts how many employees are in each department. The HAVING clause filters out departments that have fewer than 6 employees.

4. Sorting Data with GROUP BY

You can use the ORDER BY clause to sort the grouped data after applying GROUP BY.

Example: Sorting Grouped Data

SELECT department, SUM(salary) AS total_salary FROM employees GROUP BY department ORDER BY total_salary DESC;

This query calculates the total salary by department and sorts the departments by the total salary in descending order.

5. GROUP BY with Multiple Aggregate Functions

You can use multiple aggregate functions in the same query to perform several calculations on the grouped data.

Example: Using Multiple Aggregate Functions

SELECT department, COUNT(*) AS employee_count, AVG(salary) AS average_salary, MAX(salary) AS highest_salary FROM employees GROUP BY department;

This query groups the data by department and calculates three aggregate values: the number of employees, the average salary, and the highest salary in each department.

Conclusion

The GROUP BY clause is a powerful feature in SQL that allows you to group rows based on one or more columns and perform aggregate calculations on each group. By using GROUP BY with aggregate functions like COUNT(), SUM(), AVG(), MAX(), and MIN(), you can gain valuable insights into your data. Combined with the HAVING clause, GROUP BY offers a flexible and effective way to summarize and analyze your data.

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