Courses/SQL/SELECT Statement

Lesson 3 • Beginner Track

SELECT Statement

By the end of this lesson you'll be able to pull exactly the data you want out of any table — choosing columns, renaming them, removing duplicates, paginating, and calculating new values on the fly. SELECT is the command you'll use more than any other in SQL.

What You'll Learn

✓Select all columns vs. just the ones you need
✓Rename columns in the output with AS
✓Remove duplicate rows with DISTINCT
✓Page through results with LIMIT and OFFSET
✓Build calculated columns with maths
✓Read a query result like a database does

Before you start: finish Database Basics & Tables so you're comfortable with rows, columns, and data types. The in-browser editor lets you write and edit SQL; to run it, copy your query into a free playground like sqliteonline.com or db-fiddle.com. Every example below shows the expected result so you can check yourself.

Our Sample Table: `products`

Every query in this lesson runs against this little products table. Keep it in mind as you read — knowing the data is half of writing good SQL.

Result:

id	product_name	category	price	stock
1	Wireless Mouse	Electronics	24.99	120
2	Coffee Mug	Kitchen	9.5	300
3	Mechanical Keyboard	Electronics	79	45
4	Notebook	Stationery	3.25	500
5	Desk Lamp	Home	32	80
6	USB-C Cable	Electronics	12.99	200

1. The Basic SELECT

A SELECT statement answers the question "show me some data". The simplest version asks for everything:

🛒 Real-world analogy

SELECT is like ordering from a menu. SELECT * means "bring me one of everything"; SELECT product_name, price means "just the dish name and the price, please".

SELECT * — every column

Return all columns and all rows.

Try it Yourself »

SQL

-- Return EVERY column for EVERY row in the table
SELECT * FROM products;

-- The * is a wildcard meaning "all columns".
-- Great for exploring, but name your columns in real apps (see below).

Result — 6 rows:

id	product_name	category	price	stock
1	Wireless Mouse	Electronics	24.99	120
2	Coffee Mug	Kitchen	9.5	300
…	…	…	…	…

In real applications, name the columns you want instead of using * — it's faster, clearer, and won't silently change when the table gains new columns.

Specific columns

Ask only for product_name and price.

Try it Yourself »

SQL

-- Ask for only the columns you actually need
SELECT product_name, price
FROM products;

-- Cleaner output, faster query, and it won't break
-- if someone adds new columns to the table later.

Result:

product_name	price
Wireless Mouse	24.99
Coffee Mug	9.5
Mechanical Keyboard	79
…	…

Your Turn: pick the columns

Fill in the blanks to list the category and stock of every product. The expected result is in the comments so you can check yourself.

🎯 Your Turn: category & stock

Replace the ___ blanks with the column names.

Try it Yourself »

SQL

-- 🎯 YOUR TURN — fill in the two blanks, then press "Try it Yourself"
-- Goal: list the category and stock level of every product.

SELECT ___, ___      -- 👉 put the column names here: category, stock
FROM products;

-- ✅ Expected result: 6 rows, two columns (category, stock),
--    e.g. Electronics | 120 ,  Kitchen | 300 , ...

2. Renaming Columns with AS

The AS keyword gives a column a friendly name in the result. The underlying table is never changed — the alias only exists for this one query. It becomes essential the moment you start calculating columns.

Column aliases

Rename columns for readable output.

Try it Yourself »

SQL

-- AS renames a column just for this result (the table is unchanged)
SELECT
    product_name AS "Product",
    price        AS "Price (USD)"
FROM products;

-- Aliases make headings readable and are essential
-- once you start using calculated columns.

Result:

Product	Price (USD)
Wireless Mouse	24.99
Coffee Mug	9.5
…	…

3. DISTINCT — Remove Duplicates

DISTINCT collapses duplicate rows into one. Our table has three Electronics products, but asking for distinct categories returns each category only once.

Pro tip: DISTINCT compares every selected column, so it can be slow on big tables. Only reach for it when you genuinely need unique values.

DISTINCT categories

Collapse duplicates to unique values.

Try it Yourself »

SQL

-- DISTINCT removes duplicate rows from the result
SELECT DISTINCT category
FROM products;

-- A row counts as a duplicate only if EVERY selected
-- column matches, so DISTINCT works on the whole row.

Result — 4 unique rows:

category
Electronics
Kitchen
Stationery
Home

Your Turn: unique categories

One blank this time — add the keyword that removes duplicates.

🎯 Your Turn: DISTINCT

Return each category exactly once.

Try it Yourself »

SQL

-- 🎯 YOUR TURN — fill in the blank to list each category only once.

SELECT ___ category   -- 👉 the keyword that removes duplicates
FROM products;

-- ✅ Expected result (4 rows): Electronics, Kitchen, Stationery, Home

4. LIMIT & OFFSET — Control How Many Rows

LIMIT caps the number of rows returned; OFFSET skips rows first. Together they power "page 1, page 2, page 3" pagination you see on every website.

LIMIT 3 OFFSET 3 is "skip the first 3 results, then give me the next 3" — exactly page 2 of a 3-per-page list.

LIMIT & pagination

Cap and page through rows.

Try it Yourself »

SQL

-- LIMIT caps how many rows come back
SELECT product_name, price
FROM products
LIMIT 3;

-- OFFSET skips rows first — this is how pagination works:
SELECT product_name, price
FROM products
LIMIT 3 OFFSET 3;   -- skip the first 3, return the next 3

5. Calculated Columns

A SELECT can compute brand-new columns from existing ones using maths or functions. The original data stays untouched — the new column lives only in the result.

Calculated columns

Add a price_with_tax column on the fly.

Try it Yourself »

SQL

-- You can compute new columns on the fly
SELECT
    product_name,
    price,
    price * 1.20 AS price_with_tax   -- add 20% tax
FROM products;

-- The products table is never changed — the calculation
-- only exists in this query's result.

Result:

product_name	price	price_with_tax
Wireless Mouse	24.99	29.988
Coffee Mug	9.5	11.4
…	…	…

Common Errors (and the fix)

"no such column: productname" — column names must match exactly (and SQL has no spaces in names). It's product_name, not productname or "product name".
Forgetting FROM: SELECT product_name; errors — every column query needs a table: SELECT product_name FROM products;
SELECT * in real apps: it works, but fetches columns you don't need and breaks code when the table changes. Name your columns.
Quotes mix-up: use single quotes for text values ('Electronics'); double quotes are for identifiers/aliases in most databases. ' ≠ ".
Missing semicolon: most tools need ; to end a statement, especially when running several at once.

📘 Quick Reference

Syntax	Purpose
SELECT *	Every column
SELECT col1, col2	Only these columns
AS alias	Rename a column in the output
DISTINCT	Remove duplicate rows
LIMIT n	Return at most n rows
OFFSET n	Skip the first n rows
price * 1.2 AS x	A calculated column

Frequently Asked Questions

Q: Does the order of columns in SELECT matter?

Yes — the result shows columns in the exact order you list them. SELECT price, product_name puts price first.

Q: Is SQL case-sensitive?

Keywords (SELECT, FROM) are not — but it's convention to UPPERCASE them. Table and column names can be case-sensitive depending on the database, so match them exactly.

Q: Why use AS if the table doesn't change?

Readability and necessity: calculated columns have no name until you give them one, and clear headings make results far easier to read.

Q: Will DISTINCT change my data?

No. SELECT only reads — it never modifies the table. DISTINCT just de-duplicates the result.

Mini-Challenge: Half-Price Preview

Put it all together — a brief, a blank canvas, and the expected result in the comments. Write it, then copy it into a playground to confirm.

🎯 Mini-Challenge

product_name + a half_price calculated column, first 4 rows.

Try it Yourself »

SQL

-- 🎯 MINI-CHALLENGE
-- Using ONLY what this lesson covered (SELECT, AS, calculated columns, LIMIT):
--   1. Show product_name and a column called half_price (price * 0.5)
--   2. Return just the first 4 products
--
-- ✅ Expected: 4 rows, columns product_name and half_price
--    e.g. Wireless Mouse | 12.495 , Coffee Mug | 4.75 , ...

-- your query here

🎉 Lesson Complete

✅ SELECT * grabs everything; naming columns is better in real apps
✅ AS renames columns in the output only
✅ DISTINCT removes duplicate rows from the result
✅ LIMIT + OFFSET cap and paginate results
✅ You can compute calculated columns without changing the table
✅ Next: the WHERE clause — return only the rows that match a condition

SELECT Statement

What You'll Learn

Our Sample Table: products

1. The Basic SELECT

SELECT * — every column

Specific columns

Your Turn: pick the columns

🎯 Your Turn: category & stock

2. Renaming Columns with AS

Column aliases

3. DISTINCT — Remove Duplicates

DISTINCT categories

Your Turn: unique categories

🎯 Your Turn: DISTINCT

4. LIMIT & OFFSET — Control How Many Rows

LIMIT & pagination

5. Calculated Columns

Calculated columns

Common Errors (and the fix)

📘 Quick Reference

Frequently Asked Questions

Mini-Challenge: Half-Price Preview

🎯 Mini-Challenge

🎉 Lesson Complete

Cookie & Privacy Settings

Our Sample Table: `products`