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# Basic DB Using SQL Server (Part 6)

Hey there! We have come to the 6th post of the series! This post will be about Aggregations. The topics we're covering today are...

Before we explore each topic, let's take a look at what Aggregation function means. Aggregation function basically means a function where values of multiple rows are grouped together to form a single summary value. For example, you have a salary column and you have 100 rows with each person's salary. You want to know the average salary of this table. That is when we use the aggregation function.

# 1) Basic Aggregation functions

Some of the aggregation functions that are widely used include `COUNT()`, `SUM()`, `AVG()`, `MIN()`, and `MAX()`.

We are going to use the table `Part` from the database called `PremierProducts` to demonstrate each of the function. The table looks like this. ## `COUNT()`

`COUNT()` returns the number of rows that match the criteria.

``````-- How to use COUNT --
SELECT COUNT(*) FROM Table_name
-- or --
SELECT COUNT(Column_name) FROM Table_name
-- or --
SELECT COUNT(DISTINCT Column_name) FROM Table_name
``````

If you want to count every row in the table, you can write something like

``````SELECT COUNT(*) FROM Part;
-- or --
SELECT COUNT(Class) FROM Part;
-- It doesn't matter which column we choose
-- because every row in the column will be counted
``````

The result is `10` because we have a total of 10 rows.

However, if you want to count only the unique value among duplicates, you add the keyword `DISTINCT`.

``````SELECT COUNT(DISTINCT Class) FROM Part;
-- using different column may yield a different reult!
``````

The result is now `3` because there are only 3 unique `Class` in the table.

## `SUM()`

`SUM()` returns total number (sum) of a numeric column.

For example, we want to find the total price of every part in the table

``````SELECT SUM(Price) FROM Part;
``````

We will get `4504.74` as a result.

## `AVG()`

`AVG()` returns the average value of a numeric column.

For example, we want to find the average price of every part in the table

``````SELECT AVG(Price) FROM Part;
``````

We will get `450.474` as a result.

## `MIN()`

`MIN()` returns the smallest value of a column.

We can use `MIN()` to find the minimum price of every part in the table

``````SELECT MIN(Price) FROM Part;
``````

We will get `24.95` as a result.

However, we can use `MIN()` in a non-numeric column as well. For example,

``````SELECT MIN(Class) FROM Part;
``````

This will return `AP` as the resul because the letter A comes before other letters.

## `MAX()`

`MAX()` returns the largest value of a column.

This works similarly to `MIN()` but instead of returning the minimum value, it returns the maximum value.

``````SELECT MAX(Price) FROM Part; -- the result is 1390.00
SELECT MAX(Class) FROM Part; -- the result is SG
``````

## Tips~

When we run the aggregation function (like above), the result will displayed as a new, untitled column. Like this.. However, we can rename that column with alias `AS`! Like so

``````SELECT AVG(Price) AS average_price FROM Part        -- without space
SELECT AVG(Price) AS 'average price' FROM Part      -- with space
``````

# 2) Aggregation with `WHERE` clause

Like any other SQL queries, you can use `WHERE` clause with aggregation functions to specify a condition.

``````SELECT COUNT(*) AS Count, SUM(Price) AS Total_Price, AVG(Price) AS Avg_price
FROM Part;
-- versus --
SELECT COUNT(*) AS Count, SUM(Price) AS Total_Price, AVG(Price) AS Avg_price
FROM Part
WHERE Class='AP';
``````

See the difference? The second query only includes the row that meets the criteria (class='AP').

# 3) Aggregation with `GROUP BY` clause

`GROUP BY` is useful when we want to learn about each group's characteristics. Remember the last query where we ask for the number of element, the total price, and the average price from `Part`? What if we use `GROUP BY` with it?

``````SELECT COUNT(*) AS Count, SUM(Price) AS Total_Price, AVG(Price) AS Avg_price, Class
FROM Part
GROUP BY Class
``````

As you can see below, instead of getting the information on the whole table, we get information of each `Class`. ## `HAVING` clause

Sometimes we want to use filter the results of aggregate functions with `GROUP BY` clause, this is when `HAVING` comes into play.

Now, let's use the previous query

``````SELECT COUNT(*) AS Count, SUM(Price) AS Total_Price, AVG(Price) AS Avg_price, Class
FROM Part
GROUP BY Class
HAVING Class <> 'SG'    -- <> is the same as !=
``````

The result of this query is the table below. The row which has `Class = 'SG'` isn't included in the table. We can also use aggregate functions with `HAVING` clause as well.

``````SELECT COUNT(*) AS Count, SUM(Price) AS Total_Price, AVG(Price) AS Avg_price, Class
FROM Part
GROUP BY Class
HAVING AVG(Price) > 200     -- like so
``````

The result will return a table that includes row that has an average price (of each class) larger than 200. # 4) `HAVING` VS `WHERE`

The main difference between `WHERE` and `HAVING` clause is that `WHERE` clause is used to filter the row BEFORE grouping while `HAVING` is used to filter the row AFTER grouping.

This means we cannot use `HAVING` without `GROUP BY` clause. At the same time, we cannot use aggregate function with `WHERE` clause.

# 5) `ORDER BY` clause

This is an optional clause to display the results of your query in a sorted mamner. We will use types of arguments which are `ASC` and `DESC`.

For example,

``````SELECT * FROM Part
ORDER BY Class      -- you can add ASC or leave it blank like this
``````

The result will return a table that is sorted by `Class` in an ascending order. If we want to display the same result but in descending order, we can add `DESC` like so...

``````SELECT * FROM Part
ORDER BY Class DESC
``````

The result will be like so... Moreover, we can even sort using more than one column! Let's sort the table above using `Class` and then `Price` in an ascending order.

``````SELECT * FROM Part
ORDER BY Class, Price ASC   -- you can leave out the ASC argument
``````

The result of the above query is the table below. # EOF !!

We have come to the end of this post! The script to create `PremierProducts` database can be found here. There's an exercise if you want to test your knowledge here and as usual the SQL queries to the exercise can be found here.

I'll see you in the next post!