Aggregating and calculating values

Aggregation

SQL contains functions which allow you to make calculations on data in your database for reports. Some of the most common functions are MAX, MIN, AVG, COUNT, SUM, and they will: MAX (find the maximum value in a field), MIN (find the minimum value in a field), AVG (find the average value of a field), COUNT (count the number of values in a field and present the total), and SUM (add up the values in a field and present the sum).

Let’s say we wanted to get the average Citation_Count for each of the ISSNs. We can use AVG and the GROUP BY clause in a query:

SELECT ISSNs, AVG(Citation_Count)
FROM articles
GROUP BY ISSNs;

GROUP BY is used by SQL to arrange identical data into groups. In this case, we are arranging all the citation counts by ISSNs. AVG acts on the Citation_Count in parentheses. This process is also called aggregation which allows us to combine results by grouping records based on value and calculating combined values in groups.

As you can see, it is difficult to tell though what ISSN has the highest average citation count and the least. We can improve upon the query above by using ORDER BY and DESC.

SELECT ISSNs, AVG(Citation_Count)
FROM articles
GROUP BY ISSNs 
ORDER BY AVG(Citation_Count) DESC;

SELECT ISSNs, COUNT(Title)
FROM articles
GROUP BY ISSNs
ORDER BY COUNT(Title) DESC;

The HAVING keyword

SQL offers a mechanism to filter the results based on aggregate functions, through the HAVING keyword.

For example, we can adapt the last request we wrote to only return information about journal ISSNs with 10 or more published articles:

SELECT ISSNs, COUNT(*)
FROM articles
GROUP BY ISSNs
HAVING COUNT(Title) >= 10;

The HAVING keyword works exactly like the WHERE keyword, but uses aggregate functions instead of database fields. When you want to filter based on an aggregation like MAX, MIN, AVG, COUNT, SUM, use HAVING; to filter based on the individual values in a database field, use WHERE.

Note that HAVING comes after GROUP BY. One way to think about this is: the data are retrieved (SELECT), can be filtered (WHERE), then joined in groups (GROUP BY); finally, we only select some of these groups (HAVING).

SELECT ISSNs, AVG(Citation_Count)
FROM articles
GROUP BY ISSNs
HAVING AVG(Citation_Count) >= 5;

Calculations

In SQL, we can also perform calculations as we query the database. Also known as computed columns, we can use expressions on a column or multiple columns to get new values during our query. For example, what if we wanted to calculate a new column called CoAuthor_Count:

SELECT Title, ISSNs, Author_Count - 1 as CoAuthor_Count
FROM articles
ORDER BY CoAuthor_Count DESC;

In section 6. Joins and aliases we are going to learn more about the SQL keyword AS and how to make use of aliases - in this example we simply used the calculation and AS to represent that the new column is different from the original SQL table data.

We can use any arithmetic operators (like +, -, *, /, square root SQRT or the modulo operator %) if we would like.

If you would like to learn more about calculated values, the Software Carpentry Databases and SQL lesson includes a useful episode on Calculating New Values.