5 Ways To Filter Data With WHERE in SQL

Across the last few tutorials, we've shown you multiple ways to filter data. To review, we covered

how allows us to filter rows based on specified conditions
how allow you to combine multiple filtering conditions
how allows you to filter on a range of values
how allows you to specify a list of values that you'd like to filter on
how allows you to match a value against a pattern

Here's a comprehensive table of the different operators you can use in conjunction with to filter your data:

Operator	Definition	Interpretation
=	Equals to	user_id is equal to 2
!=, <>	Not equals to	user_id is not equal to 5
<, >	Less than, more than	age is less than 5
<=, >=	Less than or equal to, more than or equal to	age is equal to or greater than 2
BETWEEN … AND …	Integer is within range of two values (inclusive)	pushups is between 20 and 40 (inclusive)
IN (…)	Value is in a list	first name is either Bob, Ann, or Joe
LIKE	Checks if a string matches a pattern	first name starts with "Jo"

SQL Filtering Data Practice Exercise

It's time to practice your filtering ability by analyzing a dataset of 1,000 customer records from a small-business in Australia.

Here's a sample of the input data you're given:

Sample Input:

customer_id	customer_name	gender	age	zip_code	city	state
1	Ignace Whillock	Male	30	5464	Johnstonhaven	Northern Territory
2	Gray Eskrick	Female	69	8223	New Zacharyfort	South Australia
3	Ellswerth Laurent	Male	59	5661	Aliburgh	Australian Capital Territory
...	....	...	....	...	...	...

Write a SQL query to find all customers who are between the ages of 18 and 22 (inclusive), live in either Victoria, Tasmania, Queensland, their gender isn't "n/a", and their name starts with either 'A' or 'B'.

Your output would look something like this:

customer_id	customer_name	gender	age	zip_code	city	state
123	Aidan Goseling	Female	22	1149	Jordanborough	Tasmania
402	Adeline Perrington	Female	22	1712	West Cooper	Tasmania
692	Bertrando Melonby	Male	20	4058	Laraview	Tasmania
900	Audrie Frotton	Female	22	9455	East Emily	Tasmania

Be warned – this exercise will need you to combine multiple SQL keywords in order to arrive at the solution!

What's Next: ORDER BY

In the practice exercise above where we filtered customer record data, we got the data in order of user_id, from lowest to highest.

But what if we wanted to make it in order of their age? And how could we handle ties?

That's where the next lesson comes in handy: ORDER BY Tutorial!

Next Lesson

SQL ORDER BY ↕️

SQL Tutorial

5 Ways To Filter Data With WHERE in SQL

SQL Filtering Data Practice Exercise

Sample Input:

What's Next: ORDER BY

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