SQL | GROUP BY
The GROUP BY statement in SQL is used for organizing and summarizing data based on identical values in specified columns. By leveraging the GROUP BY clause, users can apply aggregate functions like SUM, COUNT, AVG, MIN, and MAX to each group, making it easier to perform detailed data analysis.
In this article, we will learn the SQL GROUP BY syntax, explore practical examples with single and multiple columns, and demonstrate advanced use cases with the HAVING clause for conditional grouping. Whether you’re new to SQL or an experienced professional, this article will help you master the GROUP BY clause for efficient data querying.
GROUP BY Clause in SQL
The GROUP BY Statement in SQL is used to arrange identical data into groups with the help of some functions. i.e. if a particular column has the same values in different rows then it will arrange these rows in a group.
- GROUP BY clause is used with the SELECT statement.
- In the query, the GROUP BY clause is placed after the WHERE clause.
- In the query, the GROUP BY clause is placed before the ORDER BY clause if used.
- In the query, the Group BY clause is placed before the Having clause.
- Place condition in the having clause.
Syntax:
SELECT column1, function_name(column2)
FROM table_name
GROUP BY column1, column2
Explanation:
- function_name: Name of the function used for example, SUM() , AVG().
- table_name: Name of the table.
- condition: Condition used.
Examples of GROUP BY in SQL
Let’s assume that we have two tables Employee and Student Sample Table is as follows after adding two tables we will do some specific operations to learn about GROUP BY.
Employee Table:
CREATE TABLE emp (
emp_no INT PRIMARY KEY,
name VARCHAR(50),
sal DECIMAL(10,2),
age INT
);
Insert some random data into a table and then we will perform some operations in GROUP BY.
INSERT INTO emp (emp_no, name, sal, age) VALUES
(1, 'Aarav', 50000.00, 25),
(2, 'Aditi', 60000.50, 30),
(3, 'Aarav', 75000.75, 35),
(4, 'Anjali', 45000.25, 28),
(5, 'Chetan', 80000.00, 32),
(6, 'Divya', 65000.00, 27),
(7, 'Gaurav', 55000.50, 29),
(8, 'Divya', 72000.75, 31),
(9, 'Gaurav', 48000.25, 26),
(10, 'Divya', 83000.00, 33);
SELECT * from emp;
Output:
Emp TABLE
Student Table:
CREATE TABLE student (
name VARCHAR(50),
year INT,
subject VARCHAR(50)
);
INSERT INTO student (name, year, subject) VALUES
('Alice', 1, 'Mathematics'),
('Bob', 2, 'English'),
('Charlie', 3, 'Science'),
('David', 1, 'Mathematics'),
('Emily', 2, 'English'),
('Frank', 3, 'Science');
Output:
Student TABLE
Example 1 : Group By Single Column
Group By single column means, placing all the rows with the same value of only that particular column in one group. Consider the query as shown below:
Query:
SELECT name, SUM(sal) FROM emp
GROUP BY name;
The above query will produce the below output:
Output
Explanations:
As you can see in the above output, the rows with duplicate NAMEs are grouped under the same NAME and their corresponding SALARY is the sum of the SALARY of duplicate rows. The SUM() function of SQL is used here to calculate the sum. The NAMES that are added are Aarav, Divya and Gaurav.
Example 2 : Group By Multiple Columns
Group by multiple columns is say, for example, GROUP BY column1, column2. This means placing all the rows with the same values of columns column 1 and column 2 in one group. Consider the below query:
Query:
SELECT SUBJECT, YEAR, Count(*)
FROM Student
GROUP BY SUBJECT, YEAR;
Output:
Output
Explantions:
As you can see in the above output the students with both the same SUBJECT and YEAR are placed in the same group. And those whose only SUBJECT is the same but not YEAR belong to different groups. So here we have grouped the table according to two columns or more than one column. The Grouped subject and years are (English,2) , (Mathematics,1) and (Science,3). The above mentioned all groups and years are repeated twice.
HAVING Clause in GROUP BY Clause
We know that the WHERE clause is used to place conditions on columns but what if we want to place conditions on groups? This is where the HAVING clause comes into use. We can use the HAVING clause to place conditions to decide which group will be part of the final result set. Also, we can not use aggregate functions like SUM(), COUNT(), etc. with the WHERE clause. So we have to use the HAVING clause if we want to use any of these functions in the conditions.
Syntax:
SELECT column1, function_name(column2)
FROM table_name
WHERE condition
GROUP BY column1, column2
HAVING condition
ORDER BY column1, column2;
Explanation:
- function_name: Name of the function used for example, SUM() , AVG().
- table_name: Name of the table.
- condition: Condition used.
Example: HAVING Clause in GROUP BY Clause
SELECT NAME, SUM(sal) FROM Emp
GROUP BY name
HAVING SUM(sal)>50000;
Output:
Output
As you can see in the above output only Anjali name not appears in the output because it has SALARY is less than 50000. So it removed from the output. So like this we can use the HAVING clause here to place this condition as the condition is required to be placed on groups not columns.
Conclusion
SQL’s group by function is used to arrange identical data into groups so that group-by-group aggregate analysis is possible. SQL’s group by clause effectively summarizes data by utilizing aggregate functions. The HAVING clause filters aggregated results and can be used to apply conditions on groups. The group by sql statement is flexible for a range of data retrieval requirements because it may be used on one or more columns.
