Skip to main content
St Louis

Back to all posts

How to Group Separately By Multiple Columns In Postgresql?

Published on
4 min read
How to Group Separately By Multiple Columns In Postgresql? image

Best SQL Query Books to Buy in October 2025

1 SQL QuickStart Guide: The Simplified Beginner's Guide to Managing, Analyzing, and Manipulating Data With SQL (Coding & Programming - QuickStart Guides)

SQL QuickStart Guide: The Simplified Beginner's Guide to Managing, Analyzing, and Manipulating Data With SQL (Coding & Programming - QuickStart Guides)

BUY & SAVE
$21.26 $27.99
Save 24%
SQL QuickStart Guide: The Simplified Beginner's Guide to Managing, Analyzing, and Manipulating Data With SQL (Coding & Programming - QuickStart Guides)
2 Practical SQL, 2nd Edition: A Beginner's Guide to Storytelling with Data

Practical SQL, 2nd Edition: A Beginner's Guide to Storytelling with Data

BUY & SAVE
$25.48 $39.99
Save 36%
Practical SQL, 2nd Edition: A Beginner's Guide to Storytelling with Data
3 SQL Pocket Guide: A Guide to SQL Usage

SQL Pocket Guide: A Guide to SQL Usage

BUY & SAVE
$23.73 $35.99
Save 34%
SQL Pocket Guide: A Guide to SQL Usage
4 SQL Programming QuickStudy Laminated Reference Guide

SQL Programming QuickStudy Laminated Reference Guide

BUY & SAVE
$7.39 $7.95
Save 7%
SQL Programming QuickStudy Laminated Reference Guide
5 SQL Queries for Mere Mortals: A Hands-On Guide to Data Manipulation in SQL

SQL Queries for Mere Mortals: A Hands-On Guide to Data Manipulation in SQL

BUY & SAVE
$31.36 $59.99
Save 48%
SQL Queries for Mere Mortals: A Hands-On Guide to Data Manipulation in SQL
6 SQL All-in-One For Dummies (For Dummies (Computer/Tech))

SQL All-in-One For Dummies (For Dummies (Computer/Tech))

BUY & SAVE
$24.92 $39.99
Save 38%
SQL All-in-One For Dummies (For Dummies (Computer/Tech))
7 SQL: The Practical Guide to Master Relational Databases, SQL Syntax, and Sublanguages for Effective Database Management (Rheinwerk Computing)

SQL: The Practical Guide to Master Relational Databases, SQL Syntax, and Sublanguages for Effective Database Management (Rheinwerk Computing)

BUY & SAVE
$35.91 $49.95
Save 28%
SQL: The Practical Guide to Master Relational Databases, SQL Syntax, and Sublanguages for Effective Database Management (Rheinwerk Computing)
+
ONE MORE?

To group separately by multiple columns in PostgreSQL, you can use the GROUP BY clause along with the columns you want to group by. This allows you to combine rows that have the same values in those columns and perform aggregate functions on the grouped data. By specifying multiple columns in the GROUP BY clause, you can group the data separately based on the unique combinations of values in those columns. This allows for more granular analysis of the data and can provide valuable insights into trends and patterns within the dataset.

How to group separately by multiple columns in PostgreSQL?

To group by multiple columns separately in PostgreSQL, you can use the following query:

SELECT column1, column2, SUM(column3) FROM table_name GROUP BY column1, column2;

In this query, replace column1, column2, column3, and table_name with the actual column names and table name from your database. This query will group the results by column1 and column2 separately, and then calculate the sum of column3 for each group.

How to handle NULL values when grouping by multiple columns in PostgreSQL?

When grouping by multiple columns in PostgreSQL, NULL values can often cause issues and need to be handled appropriately. Here are some ways to handle NULL values when grouping by multiple columns:

  1. Use the COALESCE function: The COALESCE function can be used to replace any NULL values in the columns being grouped by with a default value. For example:

SELECT COALESCE(column1, 'default1'), COALESCE(column2, 'default2'), COUNT(*) FROM table_name GROUP BY COALESCE(column1, 'default1'), COALESCE(column2, 'default2');

  1. Use the GROUP BY clause with IS NOT NULL: You can also use the IS NOT NULL condition in the GROUP BY clause to exclude NULL values from the grouping. For example:

SELECT column1, column2, COUNT(*) FROM table_name WHERE column1 IS NOT NULL AND column2 IS NOT NULL GROUP BY column1, column2;

  1. Use the FILTER clause: Another option is to use the FILTER clause to filter out NULL values when grouping. For example:

SELECT column1, column2, COUNT(*) FROM table_name GROUP BY column1, column2 FILTER (WHERE column1 IS NOT NULL AND column2 IS NOT NULL);

By using these methods, you can handle NULL values effectively when grouping by multiple columns in PostgreSQL.

How to count and group by multiple columns in PostgreSQL?

To count and group by multiple columns in PostgreSQL, you can use the GROUP BY clause along with the COUNT() function. Here's an example query that counts and groups by multiple columns:

SELECT column1, column2, COUNT(*) FROM your_table GROUP BY column1, column2;

In this query:

  • your_table is the name of the table you are querying.
  • column1 and column2 are the columns you want to group by and count.
  • COUNT(*) is the function that will count the number of rows in each group.

You can add more columns to the GROUP BY clause if you want to group by more than two columns. Just make sure to include those columns in the SELECT clause as well.

Keep in mind that when using the GROUP BY clause, all non-aggregated columns in your SELECT statement must be included in the GROUP BY clause.

What is the order of operations when grouping by multiple columns in PostgreSQL?

When grouping by multiple columns in PostgreSQL, the order of operations is as follows:

  1. GROUP BY clause: The data is grouped based on the specified columns in the GROUP BY clause.
  2. HAVING clause: Filters the grouped data based on the specified conditions in the HAVING clause.
  3. SELECT clause: Selects the columns to be displayed in the final result set.
  4. ORDER BY clause: Sorts the result set based on the specified columns in the ORDER BY clause.

What is the best practice for grouping by multiple columns in PostgreSQL?

The best practice for grouping by multiple columns in PostgreSQL is to use the GROUP BY clause followed by the columns you want to group by. You can list multiple columns separated by commas within the GROUP BY clause.

For example, if you want to group by the columns "column1" and "column2" in a table called "table_name", you would write the following query:

SELECT column1, column2, COUNT(*) FROM table_name GROUP BY column1, column2;

This will group the data in the table by the values of "column1" and "column2", and then return the count of rows for each unique combination of values in those columns.