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Learn how to group and count values by a new characteristic in PostgreSQL, using a practical example of counting pets by species.
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Counting Values Grouped by Species in PostgreSQL

In the world of data analysis, often you need to group and summarize data in meaningful ways. One common scenario is counting items across different categories. In this guide, we will address a specific question: How can we count values in a PostgreSQL database, grouped by a new characteristic related to a specific column?

Imagine you have a dataset with information about pets, specifically their names and breeds. The challenge is to categorize these breeds into broader groups, like "Cats" and "Dogs," and then count how many fall into each category.

Understanding the Problem

Consider the following data table:

[[See Video to Reveal this Text or Code Snippet]]

From the data, we want to derive a new classification for the breeds:

Cats: Persian, Asian

Dogs: Labrador, Huskey, Golden Retriever

Our desired output after this grouping would be:

[[See Video to Reveal this Text or Code Snippet]]

Solution Explained

To solve this problem, we can use SQL’s CASE statement to categorize the breeds into our new species classifications. We then group the results by this newly defined species and count the occurrences.

Step 1: Creating a New Column with CASE

To create a new column that assigns each breed to either "Cats" or "Dogs," we will write a SQL query that uses a CASE statement.

Here’s how it would look, utilizing Common Table Expressions (CTEs) for better readability:

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Counting by Species

In the SQL query above:

We first create a CTE named animal_species.

Inside this CTE, we select all data from the animals table.

We use the CASE statement to classify each breed into species of either "Cats" or "Dogs."

Finally, we count the number of entries for each species and group the results accordingly.

Alternative Method: Without CTEs

If your version of MySQL does not support CTEs, you can achieve the same result using a derived table. Here’s how:

[[See Video to Reveal this Text or Code Snippet]]

Summary

By using a CASE statement and grouping the results appropriately, we can easily modify and analyze our datasets based on new characteristics.

Create a classification using CASE

Count occurrences by grouping

With the structured queries provided above, counting by new variables in PostgreSQL becomes straightforward, empowering you to easily derive insights from your data.

Now you can not only execute your queries with clarity but also ensure that your analysis aligns with the specific characteristics that are important for your data interpretation.