# Aggregating and calculating values

Last updated on 2024-03-26 | Edit this page

## Overview

### Questions

- How can we aggregate values in SQL for reports?
- Can SQL be used to make calculations?

### Objectives

- Use SQL functions like
`AVG`

in combination with clauses like`Group By`

to aggregate values and return results for reports. - Make calculations on fields using SQL.

## 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).

Letâ€™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:

`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`

.

### SQL

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

### Challenge

Write a query using an aggregate function that returns the number of
article titles per ISSNs, sorted by title count in descending order.
Which ISSN has the most titles? (Hint to choosing which aggregate
function to use - it is one of the common aggregate functions
`MAX, MIN, AVG, COUNT, SUM`

.)

## 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:

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`

).

## 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`

:

### SQL

```
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.