The most well-known (and literal) use for a heat map chart is weather tracking. By using shades of red for high temperatures and blues for lows, analysts can place data over a geographical map or on a table to paint a picture of the climate.

With that said, because heat maps track concentrations of activity (or any other variable), they have countless use cases. To give you an idea of their versatility, you could create a heat map sample to display:

- Clicks and mouse movements on a website to improve UX

- Patterns on the sports field

- Large DNA or RNA datasets

- Groups congregating in different areas of a building

In short: heat maps are used for data visualization.

When using a heat map, you first need a color palette. One of the best practices for creating a legible heat map design is to use varying degrees of a single color.

For example, you might choose green to indicate how many trees you’ve planted in various areas. Darker shades of green would correspond with a higher value, while lighter shades would indicate lower concentrations.

From there, all you have to do is fill in each area with the corresponding color—dark green for the spots with 1000+ trees, medium green for the 500-999 areas, and so on.

How you visualize a heat map depends on the purpose of your data analysis. If you’re looking at user behavior on your website, you might visualize the data overtop of your home page. If you’re visualizing weather patterns, you might overlay your data on a map of the continent.

Ultimately, you have to choose a format and a color palette that makes sense with the data you’re presenting. To do that, think hard about the heat map’s purpose, its intended audience, and the insights you’re trying to uncover.