In this lesson, we'll cover how to write SQL queries to retrieve and add specific data to SQL database tables.
- Define a query as an SQL statement that retrieves data from a database
- Use the
ORDER BY
modifier to order tables by specificSELECT
statements - Use the
ASC
andDESC
modifiers to sort queries in ascending or descending order - Use the
LIMIT
modifier to determine the number of records to retrieve from a dataset - Use the
BETWEEN
modifier to retrieve records that contain a value that is within a given range - Use the
NULL
data type keyword to insert new records into a table - Use the
COUNT
function to count the number of records that meet a certain condition - Use the
GROUP BY
function to group your results according to the values in a given column
The term "query" refers to any SQL statement that retrieves data from your
database. In fact, we've already written a number of SQL queries using basic
SELECT
statements. We've already seen how to retrieve single units of data, or
rows, with queries like these:
To select all of the rows from a cats
table:
SELECT * FROM cats;
To select only rows representing data meeting certain conditions:
SELECT * FROM cats WHERE name = "Maru";
What if, however, we wanted to select the oldest cat? Or all of the cats that don't currently belong to an owner? Or all of the cats with short names?
Data storage isn't very useful if we can't manipulate, view, and analyze that data. Luckily for us, SQL is actually a powerful tool for doing just that.
In this exercise, we'll walk through executing a handful of common and handy SQL queries.
In this code along, we'll be creating a cats
table in a pets_database.db
.
So, let's navigate to our terminal and get started.
First let's create our pets_database
by running the following command.
sqlite3 pets_database.db
Now that we have a database, let's create our cats
table along with id
,
name
, age
, breed
, and owner_id
columns.
CREATE TABLE cats (
id INTEGER PRIMARY KEY,
name TEXT,
age INTEGER,
breed TEXT,
owner_id INTEGER
);
Good work. Let's quit the SQL interface by typing: .quit
. You'll be returned
to the shell prompt. Now, output the list of files (ls
on Linux-based machines
and dir
on Windows-based machines) in the terminal and see what just happened.
A new file should appear called pets_database.db
! This is the binary
representation of the database. You can think of this like a .jpg file. It won't
open up in a text editor, but it does open up in the image viewer app. It is the
same way for .db files. They won't open in your editor, but they can be read by
the appropriate database engine.
Let's add some cats to our cats
table to make this more interesting. Get back
to the sqlite
prompt by running sqlite3 pets_database.db
again. Then execute
each of the following INSERT commands:
INSERT INTO cats (name, age, breed, owner_id) VALUES ("Maru", 3 , "Scottish Fold", 1);
INSERT INTO cats (name, age, breed, owner_id) VALUES ("Hana", 1 , "Tabby", 1);
INSERT INTO cats (name, age, breed) VALUES ("Lil\' Bub", 5, "American Shorthair");
INSERT INTO cats (name, age, breed) VALUES ("Moe", 10, "Tabby");
INSERT INTO cats (name, age, breed) VALUES ("Patches", 2, "Calico");
Let's check out our cats
table now:
SELECT * FROM cats;
This should return:
1|Maru|3|Scottish Fold|1
2|Hana|1|Tabby|1
3|Lil\' Bub|5|American Shorthair|
4|Moe|10|Tabby|
5|Patches|2|Calico|
Top-Tip: You can format the output of your select statements with a few helpful options:
.headers on # output the name of each column
.mode column # now we are in column mode, enabling us to run the next two .width commands
.width auto # adjusts and normalizes column width
# or
.width NUM1, NUM2 # customize column width
Run the first two commands and then execute the above SELECT
statement again
and you should see something like this:
id name age breed owner_id
---------- ---------- ---------- ------------- ----------
1 Maru 3 Scottish Fold 1
2 Hana 1 Tabby 1
3 Lil\' Bub 5 American Shor
4 Moe 10 Tabby
5 Patches 2 Calico
Much better.
The first query modifier we'll explore is ORDER BY
. This modifier allows us to
order the table rows returned by a certain SELECT
statement. Here's a
boilerplate SELECT
statement that uses ORDER BY
:
SELECT column_name FROM table_name ORDER BY column_name ASC|DESC;
Let's select our cats and order them by age:
SELECT * FROM cats ORDER BY age;
This should return the following:
id name age breed owner_id
---------- ---------- ---------- ---------- ----------
2 Hana 1 Tabby 1
5 Patches 2 Calico
1 Maru 3 Scottish F 1
3 Lil\' Bub 5 American S
4 Moe 10 Tabby
When using ORDER BY
, the default is to order in ascending order. If we want to
specify though, we can use ASC
for "ascending" or DESC
for "descending."
Let's try to select all of our cats and sort them by age in descending order.
SELECT * FROM cats ORDER BY age DESC;
This should return
id name age breed owner_id
---------- ---------- ---------- ---------- ----------
4 Moe 10 Tabby
3 Lil\' Bub 5 American S
1 Maru 3 Scottish F 1
5 Patches 2 Calico
2 Hana 1 Tabby 1
What if we want the oldest cat? If we want to select extremes from a database
table — for example, the employee with the highest paycheck or the patient
with the most recent appointment — we can use ORDER BY
in conjunction
with LIMIT
.
LIMIT
is used to determine the number of records you want to return from a dataset. For example:
SELECT * FROM cats ORDER BY age DESC LIMIT 1;
This part of the statement: SELECT * FROM cats ORDER BY age DESC
returns all
of the cats in order from oldest to youngest. Setting a LIMIT
of 1
returns
just the first, i.e. oldest, cat on the list.
Execute the above statement in your terminal and you should see:
id name age breed owner_id
---------- ---------- ---------- ---------- ----------
4 Moe 10 Tabby
Let's get the two oldest cats:
SELECT * FROM cats ORDER BY age DESC LIMIT 2;
Execute that statement and you should see:
id name age breed owner_id
---------- ---------- ---------- ---------- ----------
4 Moe 10 Tabby
3 Lil\' Bub 5 American S
As we've already established, being able to sort and select specific data sets
is important. Continuing on with our example, let's say we urgently need to
select all of the cats whose age is between 1 and 3. To create such a query, we
can use BETWEEN
. Here's a boilerplate SELECT
statement using BETWEEN
:
SELECT column_name(s) FROM table_name WHERE column_name BETWEEN value1 AND value2;
Let's try it out on our cats
table:
SELECT name FROM cats WHERE age BETWEEN 1 AND 3;
This should return:
Maru
Hana
Patches
Let's say the administrator of our Pets Database has found a new cat. This kitty
doesn't have a name yet, but should be added to our database right away. We can
add data with missing values using the NULL
keyword.
Let's insert our new cat into the database. Our abandoned kitty has a breed, but no name or age as of yet:
INSERT INTO cats (name, age, breed) VALUES (NULL, NULL, "Tabby");
Now, if we look at our cats
data with SELECT * FROM cats;
, we should see:
id name age breed owner_id
---------- ---------- ---------- ------------- ----------
1 Maru 3 Scottish Fold 1
2 Hana 1 Tabby 1
3 Lil\' Bub 5 American Shor
4 Moe 10 Tabby
5 Patches 2 Calico
6 Tabby
We can even select the mysterious, nameless kitty with the following query:
SELECT * FROM cats WHERE name IS NULL;
This should return the following:
id name age breed owner_id
---------- ---------- ---------- ---------- ----------
6 Tabby
Now, we'll talk about a SQL aggregate function, COUNT
.
SQL aggregate functions are SQL statements that operate on groups of records in our database rather than individual records. For example, we can retrieve minimum and maximum values from a column, sum values in a column, get the average of a column's values, or count a number of records that meet certain conditions. You can learn more about these SQL aggregators here and here.
For now, we'll just focus on COUNT
. COUNT
will count the number of records
that meet a certain condition. Here's a boilerplate SQL query using COUNT
:
SELECT COUNT([column name]) FROM [table name] WHERE [column name] = [value]
Let's try it out and count the number of cats who have an owner_id
of 1
:
SELECT COUNT(owner_id) FROM cats WHERE owner_id = 1;
This should return:
COUNT(owner_id)
---------------
2
Lastly, we'll talk about the handy aggregate function GROUP BY
. Like its name
suggests, it groups your results by a given column.
Let's take our table of cats
id name age breed owner_id
---------- ---------- ---------- ------------- ----------
1 Maru 3 Scottish Fold 1
2 Hana 1 Tabby 1
3 Lil\' Bub 5 American Shor
4 Moe 10 Tabby
5 Patches 2 Calico
6 Tabby
Here, we can see at a glance that there are three tabby cats and one of every
other breed — but what if we had a larger database where we couldn't
easily see the number of cats grouped by breed? That's where — you
guessed it! — GROUP BY
comes in handy.
SELECT breed, COUNT(breed) FROM cats GROUP BY breed;
This should return
breed COUNT(breed)
------------------ ------------
American Shorthair 1
Calico 1
Scottish Fold 1
Tabby 3
GROUP BY is a great function for aggregating results into different segments — you can even use it on multiple columns!
SELECT breed, owner_id, COUNT(breed) FROM cats GROUP BY breed, owner_id;
Below you can see that the cats are still grouped by breed but are also now further broken down by owner_id, so the two tabby cats without an owner_id are listed separately from the tabby who belongs to owner 1.
breed owner_id COUNT(breed)
------------------ ---------- ------------
American Shorthair 1
Calico 1
Scottish Fold 1 1
Tabby 2
Tabby 1 1
We are now familiar with this syntax:
SELECT name FROM cats;
However, you may not know that this can be written like this as well:
SELECT cats.name FROM cats;
Both return:
name
----------
Maru
Hana
Lil\' Bub
Moe
Patches
SQLite allows us to explicitly state the tableName.columnName we want to select. This is particularly useful when we want data from two different tables.
Imagine we have another table called dogs
with a column for the dog names:
CREATE TABLE dogs (
id INTEGER PRIMARY KEY,
name TEXT
);
INSERT INTO dogs (name) VALUES ("Clifford");
If we want to get the names of all the dogs and cats, we can no longer run a
query with just the column name. SELECT name FROM cats,dogs;
will return
Error: ambiguous column name: name
.
Instead, we must explicitly follow the tableName.columnName syntax.
SELECT cats.name, dogs.name FROM cats, dogs;
You may see this in the future. Don't let it trip you up.