• Explain the importance of grouping and sorting data stored in a database
• Group and sort data with the GROUP BY() and ORDER BY() keywords
• Craft advanced queries using aggregator functions along with sorting keywords and other conditional clauses

SQL isn't picky about how it returns data to you, based on your queries. It will simply return the relevant table rows in the order in which they exist in the table. This is often insufficient for the purposes of data analysis and organization.

How common is it to order a list of items alphabetically? Or numerically from least to greatest?

We can tell our SQL queries and aggregate functions to group and sort our data using several clauses:

• ORDER BY()
• LIMIT
• GROUP BY()
• HAVING and WHERE
• ASC/DESC

Let's take a closer look at how we use these keywords to narrow our search criteria as well as to order and group the results.

Some cats are very famous, and accordingly very wealthy. Our Pets Database will have a cats table in which each cat has a name, age, breed, and net worth. Our database will also have an owners table and cats_owners join table so that a cat can have many owners and an owner can have many cats.

Creating the Database:

In your terminal, create the database and start sqlite3 with the following:

sqlite3 pets_database.db

Creating the tables:

Create the tables by entering the commands below at the sqlite> prompt:

cats table:

CREATE TABLE cats (
id INTEGER PRIMARY KEY,
name TEXT,
age INTEGER,
breed TEXT,
net_worth INTEGER
);

owners Table:

CREATE TABLE owners (id INTEGER PRIMARY KEY, name TEXT);

cats_owners Table:

CREATE TABLE cats_owners (
cat_id INTEGER,
owner_id INTEGER
);

Inserting the values:

Finally, to insert the values, enter the following:

cats:

INSERT INTO cats (id, name, age, breed, net_worth) VALUES (1, "Maru", 3, "Scottish Fold", 1000000);
INSERT INTO cats (id, name, age, breed, net_worth) VALUES (2, "Hana", 1, "Tabby", 21800);
INSERT INTO cats (id, name, age, breed, net_worth) VALUES (3, "Grumpy Cat", 4, "Persian", 181600);
INSERT INTO cats (id, name, age, breed, net_worth) VALUES (4, "Lil\' Bub", 2, "Tortoiseshell", 2000000);

owners:

INSERT INTO owners (name) VALUES ("mugumogu");
INSERT INTO owners (name) VALUES ("Sophie");
INSERT INTO owners (name) VALUES ("Penny");

cats_owners:

INSERT INTO cats_owners (cat_id, owner_id) VALUES (2, 2);
INSERT INTO cats_owners (cat_id, owner_id) VALUES (4, 3);
INSERT INTO cats_owners (cat_id, owner_id) VALUES (1, 2);

The general syntax for selecting values and sorting them is:

SELECT column_name, column_name
FROM table_name
ORDER BY column_name ASC, column_name DESC;

Note that ORDER BY() will automatically sort the returned values in ascending order so the use of the ASC keyword is optional. If we want to sort in descending order instead, we need to use the DESC keyword.

Imagine you're working for an important investment firm in Manhattan. The investors are interested in investing in a lucrative and popular cat. They need your help to decide which cat that will be. They want a list of famous and wealthy cats. We can do that by running a basic SELECT statement at the sqlite> prompt:

SELECT * FROM cats WHERE net_worth > 0;

This will return:

id           name             age         breed          net_worth
-----------  ---------------  ----------  -------------  ----------
1            Maru             3           Scottish Fold  1000000
2            Hana             1           Tabby          21800
3            Grumpy Cat       4           Persian        181600
4            Lil\' Bub        2           Tortoiseshell  2000000

Our investors are busy people though. They don't have time to manually sort through this list of cats for the best candidate. They want you to return the list to them with the cats sorted by net worth, from greatest to least.

We can do so with the following line:

SELECT * FROM cats ORDER BY(net_worth) DESC;

This will return:

id           name             age         breed          net_worth
-----------  ---------------  ----------  -------------  ----------
4            Lil\' Bub        2           Tortoiseshell  2000000
1            Maru             3           Scottish Fold  1000000
3            Grumpy Cat       4           Persian        181600
2            Hana             1           Tabby          21800

Turns out our investors are very impatient. They don't want to review the list themselves, they just want you to return to them the wealthiest cat. We can accomplish this by using the LIMIT keyword with the above query:

SELECT * FROM cats ORDER BY(net_worth) DESC LIMIT 1;

Which will return:

name             age         breed          net_worth
---------------  ----------  -------------  ----------
Lil\' Bub        2           Tortoiseshell  2000000

The LIMIT keyword specifies how many of the records resulting from the query you'd like to actually return. In this case, because we've sorted the records in descending order by net worth and set the LIMIT to 1, the wealthiest cat is returned.

The GROUP BY() keyword is very similar to ORDER BY(). The main difference is that ORDER BY() sorts sets of data returned by basic queries while GROUP BY() sorts sets of data returned by aggregate functions.

SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name;

Let's calculate the sum of the net worth of all of the cats, grouped by owner name:

SELECT owners.name, SUM(cats.net_worth)
FROM owners
INNER JOIN cats_owners
ON owners.id = cats_owners.owner_id
JOIN cats ON cats_owners.cat_id = cats.id
GROUP BY owners.name;

This should return:

owners.name      SUM(cats.net_worth)
---------------  -------------------
Penny            2000000
Sophie           1021800

Note: If you have headers turned on, the headers you see in your terminal may differ from the ones displayed here and below.

In the above query, we've implemented two joins. First, we're joining owners and cat_owners on owners.id = cats_owners.owner_id. This first joined table would look like the following if we were to query it:

owners.id  owners.name      cat_owners.cat_id  cat_owners.owner_id
---------  -----------      -----------------  -------------------
2          Sophie           2                  2
3          Penny            4                  3
2          Sophie           1                  2

With this table, we then implement a second join with cats on cats_owners.cat_id = cats.id. To better understand this, try running the provided query, but select everything rather than just the owner's name and the sum of their cats' net worth, and remove the GROUP BY line. You'll be able to see all three tables have been joined.

In our example query above, we need to use the SUM(cats.net_worth) aggregator in conjunction with GROUP BY to get the information we want. Without GROUP BY, only the first owner in the table would be returned, along with the sum of the net worth of all the cats:

owners.name      SUM(cats.net_worth)
---------------  -------------------
Sophie           3021800

If, on the other hand, we forget to use SUM and just get cats.net_worth, the results will be grouped by owner, but only the net worth of the first cat belonging to each owner will be returned, not the aggregate:

owners.name      cats.net_worth
---------------  ---------------
Penny            2000000
Sophie           21800

When we use SUM and GROUP BY together, SUM looks at all of the values in the net_worth column of the cats table (or whichever column you specify in parentheses) and takes the sum of those values, but only after those cats have been grouped by owner:

owners.name      SUM(cats.net_worth)
---------------  -------------------
Penny            2000000
Sophie           1021800

In our original data, Penny is the owner of Lil' Bub (2000000) while Sophie is the owner of Maru and Hana (1000000 + 21800).

Suppose we have a table called employee_bonus as shown below. Note that the table has multiple entries for employees Abigail and Matthew.

employee_bonus:

To calculate the total bonus that each employee received, we would write a SQL statement like this:

SELECT employee, SUM(bonus) FROM employee_bonus GROUP BY employee;

This should return:

employee         SUM(bonus)
---------------  -------------------
Abigail          3250
Matthew          1500
Tom              700

Now, suppose we wanted to find the employees who received more than $1,000 in bonuses. You might think that we could write a query like this:

BAD SQL:
SELECT employee, SUM(bonus) FROM employee_bonus
GROUP BY employee WHERE SUM(bonus) > 1000;

Unfortunately, the above will not work because the WHERE clause can't be used with aggregates (SUM, AVG, MAX, etc). What we need to use is the HAVING clause. The HAVING clause was added to SQL so that we could compare aggregates in the same way that the WHERE clause can be used for comparing non-aggregates. Now, the correct SQL will look like this:

GOOD SQL:
SELECT employee, SUM(bonus) FROM employee_bonus
GROUP BY employee HAVING SUM(bonus) > 1000;

The difference between the HAVING and WHERE clauses in SQL is that the WHERE clause cannot be used with aggregates while the HAVING clause can. HAVING filters out groups of rows created by GROUP BY, and WHERE filters out individual rows. Note that there is nothing to stop you from using both of them in the same query.

Finally, it is important to remember that order matters here: WHERE must come before GROUP BY and HAVING must come after it, as shown below; changing the order will produce a syntax error.

SELECT
FROM
JOIN
  ON
WHERE
GROUP BY
HAVING
ORDER BY
LIMIT

• ORDER BY vs GROUP BY clauses

• HAVING vs WHERE clauses

• Video Review- SQL Joins Overview