If you’ve ever looked at a report — like “Total sales per customer” or “Number of logins per day” — then you’ve already seen what GROUP BY does.
GROUP BY turns messy, unorganized rows into clean summaries.

And the best part?
It’s easier than most beginners think.

Let’s walk through this together.

⭐ Why Do We Use GROUP BY?

Imagine a table named orders:

If you want to answer:

• How many products did each customer buy?

• How much total money did each customer spend?

You need GROUP BY.

It groups rows based on a column, then applies functions like:

• COUNT()

• SUM()

• AVG()

• MAX()

• MIN()

⭐ 1. Count How Many Orders Each Customer Has

SELECT customer, COUNT(*) AS total_orders
FROM orders
GROUP BY customer;

Result:

Simple, right?

⭐ 2. Sum Total Spending Per Customer

SELECT customer, SUM(amount) AS total_spent
FROM orders
GROUP BY customer;

Result:

GROUP BY + SUM is one of the most common combinations in real-world apps.

⭐ 3. Average Amount Spent Per Order (Per Customer)

SELECT customer, AVG(amount) AS average_spent
FROM orders
GROUP BY customer;

This is useful for analytics dashboards or business intelligence reports.

⭐ 4. Count Orders per Product

You can group by ANY column — not just customer.

SELECT product, COUNT(*) AS total_sold
FROM orders
GROUP BY product;

⭐ Common GROUP BY Mistake (Every Beginner Does This)

❌ You must include every non-aggregated column in GROUP BY.

This will fail:

SELECT customer, product, COUNT(*)
FROM orders
GROUP BY customer;

Because product is not grouped or aggregated.