Calculating Percentages with SQL

An effective tool for managing and analysing data kept in relational databases is SQL, or Structured Query Language. Calculating percentages is a frequent operation in data analysis and can offer important insights into the data distribution. This post will explain how to use SQL to calculate percentages and provide useful code samples.

Understanding Percentages

Before we get into SQL code samples, let's take a moment to review percentage concepts. A ratio represented as a fraction of 100 is called a percentage. It is frequently employed to depict distributions, comparisons, and proportions in data.

Example Table SQL

Let's assume we have a table named sales with columns product_name and sales_amount.

CREATE TABLE sales (

    product_name VARCHAR(255),

    sales_amount DECIMAL(10, 2)

);

INSERT INTO sales (product_name, sales_amount)

VALUES 

    ('Product A', 1500.00),

    ('Product B', 2000.00),

    ('Product C', 1200.00),

    ('Product D', 1800.00);

 Calculating Percentage of Total Sales:

SELECT 

    product_name,

    sales_amount,

    (sales_amount / SUM(sales_amount) OVER ()) * 100 AS percentage_of_total

FROM 

    sales;

Calculating Percentage Growth:

SELECT 

    product_name,

    sales_amount,

    (sales_amount - LAG(sales_amount, 1, 0) OVER (ORDER BY product_name)) / 

    LAG(sales_amount, 1, 1) OVER (ORDER BY product_name) * 100 AS percentage_growth

FROM 

    sales;

 Calculating Percentage within Groups

SELECT 

    product_name,

    sales_amount,

    sales_amount / SUM(sales_amount) OVER (PARTITION BY product_name) * 100 AS percentage_of_group

FROM 

    sales;

Calculating Percentage Change from a Specific Value:

DECLARE @reference_value DECIMAL(10, 2);

SET @reference_value = 1500.00;

SELECT 

    product_name,

    sales_amount,

    (sales_amount - @reference_value) / @reference_value * 100 AS percentage_change_from_reference

FROM 

    sales;

These examples should give you a good starting point for calculating percentages in SQL based on different scenarios. Adjust the queries according to your specific use case and table structure.