PostgreSQL is one of the most robust Relational Database Management Systems. You can use SQL to query your data stored in the database. There might be instances where there would be a need to count the number of records in a table or sometimes a specific number of rows according to a condition.
This is where you can use the COUNT() function in PostgreSQL. In this article, you will come to know about the PostgreSQL COUNT function along with a wide range of use cases and examples. Let’s get started!
PostgreSQL COUNT() Function: Overview
The different ways of using the PostgreSQL COUNT() function are as follows:
1) COUNT(*)
You can use the PostgreSQL COUNT(*) function along with a SELECT statement to return the total number of rows in a table including the NULL values as well as the duplicates.
It can be implemented in the following format.
SELECT
COUNT(*)
FROM
table_name
WHERE
condition;
In this case, the COUNT(*) function is applied to the entire table i.e, table_name table. And this function will count the number of rows according to the condition applied along with the WHERE clause.
2) COUNT(Column_name)
You can use the COUNT(Column_name) function along with a SELECT statement to return the total number of non-NULL values in the Column_name column.
It can be implemented in the following format.
SELECT
COUNT(column_name)
FROM
table_name
WHERE
condition;
In this case, the COUNT(column_name) function is applied to the column_name column. And this function will count the number of rows according to the condition applied along with the WHERE clause.
3) COUNT(DISTINCT Column_name)
You can use the COUNT(DISTINCT Column_name) function along with a SELECT statement to return the total number of unique, non-NULL values in the Column_name column.
It can be implemented in the following format.
SELECT
COUNT(DISTINCT column_name)
FROM
table_name
WHERE
condition;
In this case, the COUNT(DISTINCT column_name) function is applied to the column_name column. And this function will count the number of rows according to the condition applied along with the WHERE clause.
As you master the functions for using PostgreSQL data for applications, understanding methods to replicate the data is also important. Hevo’s Data Pipeline Platform can integrate data from over 150+ sources in a matter of minutes. The platform gives complete control in the hands of data teams with intuitive dashboards for pipeline monitoring, auto-schema management, and custom ingestion/loading schedules.
All of this combined with transparent pricing and 24×7 support makes us the most loved data pipeline software on review sites. Take our 14-day free trial to experience a better way to manage data pipelines.
Get started for Free with Hevo!
PostgreSQL COUNT() Function: Example Queries
For showcasing different example queries using the PostgreSQL COUNT() function, we are considering this table with the following fields.
The different use cases of the PostgreSQL COUNT() function can be illustrated as follows:
1) COUNT(*)
SELECT COUNT(*)
FROM Employees;
This function will return the total number of records in the Employees table.
2) COUNT() on Specific Column
SELECT COUNT(commission)
FROM Employees;
The PostgreSQL COUNT() function is applied to the commission column. It will return the total count of the non-null values in the commission column i.e., it will give the count of the employees who only earn a commission.
3) COUNT() DISTINCT
SELECT COUNT(DISTINCT designation)
FROM Employees;
The PostgreSQL COUNT() function is applied to the commission column along with the DISTINCT clause. It will return the total count of the unique values of designation.
4) COUNT() with GROUP BY clause
SELECT
dept_no,
COUNT (*) AS "Number of Employees"
FROM
Employees
GROUP BY
dept_no;
The PostgreSQL COUNT() function is used here to count the total number of employees in each department. Hence, GROUP By clause is applied to the dept_no column.
5) COUNT() with WHERE clause
SELECT
dept_no,
COUNT (*) AS "Number of Employees"
FROM
Employees
WHERE
Salary > 50000
GROUP BY
dept_no;
The PostgreSQL COUNT() function is used here to count the total number of employees in each department. Hence, GROUP By clause is applied to the dept_no column. Along with that, the WHERE clause is used to set a condition, it will only count the number of employees in each department whose salary is greater than $50,000.
6) COUNT() with HAVING clause
SELECT
dept_no,
COUNT (*) AS "Number of Employees"
FROM
Employees
GROUP BY
dept_no;
ORDER BY
COUNT(*) DESC;
The PostgreSQL COUNT() function is used here to count the total number of employees in each department. Hence, GROUP By clause is applied to the dept_no column. And it will only display the total count of employees in those departments where the employee count is greater than 40.
The PostgreSQL COUNT() function is used here to count the total number of employees in each department. Hence, GROUP By clause is applied to the dept_no column. And it will only display the output in the descending order of the number of employees in each department.
7) COUNT() with ORDER BY & GROUP BY clauses
SELECT
dept_no,
COUNT (*) AS "Number of Employees"
FROM
Employees
GROUP BY
dept_no
HAVING
COUNT(*)> 40;
For further information on the COUNT() function in PostgreSQL, you can visit here.
Before wrapping up, let’s cover some basics as well.
What is PostgreSQL COUNT() Function?
The COUNT() function in PostgreSQL is an aggregate function that counts the number of rows or non-NULL values against a specified column or an entire table. It can also be used to return the number of rows that match a given query criterion.
1) Syntax
COUNT (* | [DISTINCT] ALL | column_name)
2) Parameters
- column_name: This represents the name of the column for which you want to count non-NULL values of the records.
- *: This represents the total number of rows for all the fields.
- DISTINCT: It indicates the number of unique values for any particular column or all the values. It is an optional clause.
- ALL: It is a default clause. And it’s optional.
Conclusion
This article illustrated the usage of the COUNT() function in PostgreSQL. You had an in-depth understanding of the different syntax and use cases of the COUNT() function. Now, you can move forward and use the COUNT() function to count the number of rows in a table according to your requirements.
Want to explore more about different clauses and statements while writing queries and creating tables in PostgreSQL? You can go through these articles.
It will take a lot of time to import and move data into your selected warehouse by using ETL for Data Analysis with PostgreSQL as your data source. However, with Hevo at your fingertips, you won’t have to worry about your PostgreSQL Data Replication demands. It will just take a few minutes to load your data into your chosen data warehouse.
Hevo is the only real-time ELT No-code Data Pipeline platform that cost-effectively automates data pipelines that are flexible to your needs. With integration with 150+ Data Sources, the platform also helps you to transform & enrich your data, & make it analysis-ready.
Visit our Website to Explore Hevo
Why don’t you give Hevo a try? Sign Up here for a 14-day full feature access trial and experience the feature-rich Hevo suite first hand. You can also check our unbeatable pricing and make a decision on your best-suited plan.
Share your thoughts on learning about the PostgreSQL COUNT() function in the comments section below. If you have any questions, do let us know. We’d be happy to help.
Frequently Asked Questions
1. How to get count in Postgres?
Use COUNT(*) to count all rows in a table.
2. How do you count tables in Postgres?
To count the number of tables, query the pg_tables system catalog.
3. How do you count specific values in PostgreSQL?
Use COUNT(*) with a WHERE clause to count specific values in a column
Manisha Jena is a data analyst with over three years of experience in the data industry and is well-versed with advanced data tools such as Snowflake, Looker Studio, and Google BigQuery. She is an alumna of NIT Rourkela and excels in extracting critical insights from complex databases and enhancing data visualization through comprehensive dashboards. Manisha has authored over a hundred articles on diverse topics related to data engineering, and loves breaking down complex topics to help data practitioners solve their doubts related to data engineering.