- Explain the importance of grouping and sorting data stored in a database
- Group and sort data with the
GROUP BY()
andORDER 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
andWHERE
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 it.
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:
Create the database in your terminal with the following:
sqlite3 pets_database.db
Creating the tables:
In the sqlite3>
prompt in your terminal:
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:
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);
SELECT column_name, column_name
FROM table_name
ORDER BY column_name DESC, column_name ASC|DESC;
ORDER BY()
will automatically sort the returned values in ascending order. Use
the DESC
keyword, as above, to sort in descending order.
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 with a basic SELECT
statement:
SELECT * FROM cats WHERE net_worth > 0;
This will return:
name age breed net_worth
--------------- ---------- ------------- ----------
Maru 3 Scottish Fold 1000000
Hana 1 Tabby 21800
Grumpy Cat 4 Persian 181600
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 lines:
SELECT * FROM cats ORDER BY(net_worth) DESC;
This will return:
name age breed net_worth
--------------- ---------- ------------- ----------
Lil\' Bub 2 Tortoiseshell 2000000
Maru 3 Scottish Fold 1000000
Grumpy Cat 4 Persian 181600
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.
The GROUP BY()
keyword is very similar to ORDER BY()
. The only difference is that ORDER BY()
sorts the resulting data set of basic queries while GROUP BY()
sorts the result sets of 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.networth)
--------------- ----------
Penny 181600
Sophie 1021800
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 3 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, when we use the SUM(cats.net_worth)
aggregator in
conjunction with GROUP BY
, the combination changes the way that our query
behaves. Without GROUP BY
, we would get a sum of the net worth of all the
cats:
owners.name SUM(cats.networth)
--------------- ----------
Sophie 1203400
By adding GROUP BY
, we now get the net_worth of all cats by owner. In our
original data, Sophie is the owner of Maru and Hana (100000 + 21800), while
Penny is the owner of Lil' Bub (181600).
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 the
those values, but only after those cats have been grouped.
Note: If you forget to add
SUM
here and just try to getcats.net_worth
, you'll still group by owner, but it will only display the first cat's net worth, not the aggregate.
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
:
Employee | Bonus |
---|---|
Matthew | 1000 |
Abigail | 2000 |
Matthew | 500 |
Tom | 700 |
Abigail | 1250 |
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 | Bonus |
---|---|
Abigail | 3250 |
Matthew | 1500 |
Tom | 700 |
Now, suppose we wanted to find the employees who received more than $1,000 in bonuses for the year of 2007. 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 doesn’t work
with aggregates – like 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 to other values – just how the WHERE
clause can be used with
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
clause in SQL is that the
WHERE
clause can not be used with aggregates but the HAVING
clause can.
HAVING filters out groups of rows, created by 'GROUP BY' and WHERE filters out
rows. Another way to think of it is that the HAVING
clause is an additional
filter to the WHERE
clause.
-
HAVING supports aggregate functions as it has to work with groups of rows. So for example, if there are multiple integers in a group it can filter out the groups with a low average, a high total (sum) or count how many rows are in the group.
-
WHERE on the other hand deals with each row individually, so aggregate functions wouldn't work for what would you be aggregating.
Also, note syntax differences:
HAVING is after GROUP BY and WHERE is before GROUP BY changing the order will produce a syntax error.
SELECT
FROM
JOIN
ON
WHERE
GROUP BY
HAVING
ORDER BY
LIMIT
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