GROUP BY single and multiple columns in PostgreSQL

Introduction

GROUP BY helps you organize data into groups so you can summarize or count things easily.

When you want to count how many sales each product has.

When you want to find the average score for each student.

When you want to see total expenses by category and month.

When you want to group customers by city and state to see how many are in each area.

Syntax

PostgreSQL

SELECT column1, column2, aggregate_function(column3)
FROM table_name
GROUP BY column1, column2;

You list the columns you want to group by after GROUP BY.

Aggregate functions like COUNT(), SUM(), AVG() work on each group.

Examples

Groups products by category and counts how many products are in each category.

PostgreSQL

SELECT category, COUNT(*)
FROM products
GROUP BY category;

Groups sales data by city and state, then finds the average sales for each group.

PostgreSQL

SELECT city, state, AVG(sales)
FROM sales_data
GROUP BY city, state;

Counts employees in each department.

PostgreSQL

SELECT department, COUNT(employee_id)
FROM employees
GROUP BY department;

Sample Program

This creates a sales table, adds some products with categories and amounts, then groups by category to find total sales amount per category.

PostgreSQL

CREATE TABLE sales (
  id SERIAL PRIMARY KEY,
  product VARCHAR(50),
  category VARCHAR(50),
  amount INT
);

INSERT INTO sales (product, category, amount) VALUES
('Pen', 'Stationery', 10),
('Pencil', 'Stationery', 5),
('Notebook', 'Stationery', 15),
('Apple', 'Fruit', 7),
('Banana', 'Fruit', 3);

SELECT category, SUM(amount) AS total_amount
FROM sales
GROUP BY category;

Important Notes

Every column in SELECT that is not inside an aggregate function must be listed in GROUP BY.

You can group by one or many columns to get more detailed groups.

Summary

GROUP BY groups rows that have the same values in specified columns.

Use aggregate functions to summarize data in each group.

You can group by one or multiple columns depending on how you want to organize data.

Practice

1. What does the GROUP BY clause do in a PostgreSQL query?

easy

A. It updates values in the specified columns.

B. It sorts the rows in ascending order.

C. It deletes duplicate rows from the table.

D. It groups rows that have the same values in specified columns.

Solution

1. Step 1: Understand the purpose of GROUP BY

   The GROUP BY clause collects rows that share the same value in one or more columns into groups.

2. Step 2: Differentiate from other clauses

   Unlike ORDER BY which sorts rows, GROUP BY organizes rows into groups for aggregation.

3. Final Answer:

   It groups rows that have the same values in specified columns. -> Option D

4. Quick Check:

   GROUP BY = groups rows by column values [OK]

Hint: GROUP BY collects rows sharing column values into groups [OK]

Common Mistakes:

• Confusing GROUP BY with ORDER BY
• Thinking GROUP BY deletes duplicates
• Assuming GROUP BY updates data

2. Which of the following is the correct syntax to group data by two columns, category and region?

easy

A. SELECT category, region, COUNT(*) FROM sales GROUP BY category, region;

B. SELECT category, region, COUNT(*) FROM sales GROUP BY category region;

C. SELECT category, region, COUNT(*) FROM sales GROUP BY (category, region);

D. SELECT category, region, COUNT(*) FROM sales GROUP category, region;

Solution

1. Step 1: Check correct GROUP BY syntax

   In PostgreSQL, multiple columns are separated by commas in GROUP BY without parentheses.

2. Step 2: Validate each option

   SELECT category, region, COUNT(*) FROM sales GROUP BY category, region; uses commas correctly; SELECT category, region, COUNT(*) FROM sales GROUP BY category region; misses comma; SELECT category, region, COUNT(*) FROM sales GROUP BY (category, region); uses parentheses incorrectly; SELECT category, region, COUNT(*) FROM sales GROUP category, region; misses BY keyword.

3. Final Answer:

   SELECT category, region, COUNT(*) FROM sales GROUP BY category, region; -> Option A

4. Quick Check:

   GROUP BY columns separated by commas [OK]

Hint: Separate multiple columns with commas in GROUP BY [OK]

Common Mistakes:

• Omitting commas between columns
• Using parentheses around columns
• Forgetting the BY keyword

3. Given the table orders with columns customer_id, product_id, and quantity, what will this query return?

SELECT customer_id, SUM(quantity) FROM orders GROUP BY customer_id;

medium

A. Total quantity ordered by each customer.

B. Total quantity ordered by each product.

C. Total quantity ordered by each customer and product.

D. Syntax error due to missing GROUP BY columns.

Solution

1. Step 1: Analyze the SELECT and GROUP BY columns

   The query groups rows by customer_id and sums quantity for each group.

2. Step 2: Understand the aggregation result

   SUM(quantity) calculates total quantity per customer_id, ignoring product_id.

3. Final Answer:

   Total quantity ordered by each customer. -> Option A

4. Quick Check:

   GROUP BY customer_id sums quantity per customer [OK]

Hint: GROUP BY column matches SELECT non-aggregates [OK]

Common Mistakes:

• Assuming product_id affects grouping
• Thinking query returns per product totals
• Confusing aggregation with filtering

4. Identify the error in this query:

SELECT product_id, region, COUNT(*) FROM sales GROUP BY product_id;

medium

A. COUNT(*) cannot be used with GROUP BY.

B. Missing region in GROUP BY causes error.

C. product_id cannot be grouped alone.

D. Syntax error due to missing FROM clause.

Solution

1. Step 1: Check SELECT columns vs GROUP BY columns

   SELECT includes product_id and region, but GROUP BY only has product_id.

2. Step 2: Understand PostgreSQL grouping rules

   All non-aggregated columns in SELECT must appear in GROUP BY; region is missing.

3. Final Answer:

   Missing region in GROUP BY causes error. -> Option B

4. Quick Check:

   All SELECT non-aggregates must be in GROUP BY [OK]

Hint: Include all non-aggregated SELECT columns in GROUP BY [OK]

Common Mistakes:

• Forgetting to add all columns to GROUP BY
• Thinking COUNT(*) disallows grouping
• Ignoring SELECT and GROUP BY mismatch

5. You want to find the total sales quantity for each product in each region from the sales table with columns product_id, region, and quantity. Which query correctly groups and sums the data?

hard

A. SELECT product_id, SUM(quantity) FROM sales GROUP BY product_id;

B. SELECT product_id, region, SUM(quantity) FROM sales GROUP BY product_id;

C. SELECT product_id, region, SUM(quantity) FROM sales GROUP BY product_id, region;

D. SELECT product_id, region, SUM(quantity) FROM sales;

Solution

1. Step 1: Identify grouping needs

   We want totals per product and per region, so both columns must be grouped.

2. Step 2: Check each option's GROUP BY clause

   SELECT product_id, region, SUM(quantity) FROM sales GROUP BY product_id, region; groups by product_id and region, matching SELECT columns; others miss region or GROUP BY entirely.

3. Final Answer:

   SELECT product_id, region, SUM(quantity) FROM sales GROUP BY product_id, region; -> Option C

4. Quick Check:

   Group by all non-aggregated columns for correct totals [OK]

Hint: Group by all selected non-aggregated columns [OK]

Common Mistakes:

• Grouping by only one column when selecting multiple
• Omitting GROUP BY causing aggregation errors
• Selecting columns without aggregation or grouping