Aggregate Functions

Tihomir Babic

How to Use Aggregate Functions in WHERE Clause

Filtering data according to the result of an aggregate function is a common data analysis task. So how do you use aggregates in the  WHERE clause? We’ll dedicate this whole article to answering that question.   Combining aggregate functions and filtering based on their results is often used in data analysis – e.g. showing branches with total sales above X,  countries where the number of posts is lower than Y, students with an average score below Z, and so on.

Tihomir Babic

How to Combine Two Aggregate Functions in SQL

Having trouble using two aggregate functions in one query? This article will show you how to do it the right way – actually, the two right ways. In data analysis and reporting, we often need to count the number of records or sum them up and then calculate the average of this count or sum. Translated to SQL logic, this is the aggregation of aggregated data, or multi-level aggregation. For aggregation purposes, there are the SQL aggregate functions.

Martyna Sławińska

What Are Aggregate Functions in SQL, and How Do I Use Them?

Data is your source of knowledge. And thanks to SQL aggregate functions, you can extract the precise knowledge you need from your data efficiently. Read along to find out more. The core SQL aggregate functions are the following: COUNT(column_name | *) returns the number of rows in a table. SUM(column_name) returns the sum of the values of a numeric column. AVG(column_name) returns the average value of a numeric column.

Tihomir Babic

An Overview of Aggregate Functions in SQL

Aggregate functions are commonly used in SQL. This article will lead you through their use and show examples of how they work. SQL aggregate functions are a useful tool, especially for creating reports. They’re not difficult to understand, especially if you have some experience with Excel or similar programs. You’ve probably used aggregate functions like SUM or AVERAGE in a spreadsheet. Even if you only occasionally use them, knowing aggregate functions can help you better understand your data and work more efficiently.

Kateryna Koidan

SQL Window Functions vs. SQL Aggregate Functions: Similarities and Differences

If you aren’t familiar with SQL’s window functions, you may wonder how they differ from aggregate functions. When should you use window functions? In this article, we’ll review window functions and aggregate functions, examine their similarities and differences, and see which one to choose depending on what you need to do. After you’ve tackled basic SQL, you’ll probably want to get into some of its more advanced functions. That’s great; these functions make reporting and analysis easier.

Aldo Zelen

Common SQL Window Functions: Positional Functions

Positional SQL window functions deal with data's location in the set. In this post, we explain LEAD, LAG, and other positional functions. SQL window functions allow us to aggregate data while still using individual row values. We've already dealt with ranking functions and the use of partitions. In this post, we'll examine positional window functions, which are extremely helpful in reporting and summarizing data. Specifically, we'll look at LAG, LEAD, FIRST_VALUE and LAST_VALUE.

Dejan Sarka

SQL Statistical Analysis Part 3: Measuring Spread of Distribution

Besides knowing the centers of a distribution in your data, you need to know how varied the observations are. In this article, we’ll explain how to find the spread of a distribution in SQL. Are you dealing with a very uniform or a very spread population? To really understand what the numbers are saying, you must know the answer to this question. In the second part of this series, we discussed how to calculate centers of distribution.

Francisco Claria

An Introduction to Using SQL Aggregate Functions with JOINs

Previously, we've discussed the use of SQL aggregate functions with the GROUP BY statement. Regular readers of the our blog will also remember our recent tutorial about JOINs. If you're a bit rusty on either subject, I encourage you to review them before continuing this article. That's because we will dig further into aggregate functions by pairing them with JOINs. This duo unleashes the full possibilities of SQL aggregate functions and allows us to perform computations on multiple tables in a single query.

Francisco Claria

A Beginner’s Guide to SQL Aggregate Functions

Aggregate functions are powerful SQL tools that compute numerical calculations on data, allowing the query to return summarized information about a given column or result set. These functions can be used in conjunction with the GROUP BY statement. Let’s see how they work using some easy examples. SQL Aggregate Functions Suppose we have users residing in a city, and we store their information in two tables. These tables and their relationship are shown below:

Aldo Zelen

Useful SQL Patterns: Conditional Summarization with CASE

As you start coding in SQL, you will use some statements and techniques over and over again. We call these "SQL patterns". This series will look at the most common SQL patterns and consider how to use them. Previously, we looked at the SQL pattern of matching NULLs. This is important when you are comparing columns containing NULL values. Today, we're going to consider another SQL practice: conditional summarization with CASE operator.

Maria Alcaraz

NULL Values and the GROUP BY Clause

We've already covered how to use the GROUP BY clause and some aggregation functions like SUM(), AVG(), MAX(), MIN(), COUNT(). In this article, we will explain how the GROUP BY clause works when NULL values are involved. We will also explain about using NULLs with the ORDER BY clause. The best way to master GROUP BY and NULL in SQL is through practice. I recommend the SQL Practice track at LearnSQL.