How to Build a Data Visualization Style Guide
How to Build a Data Visualization Style Guide
Blog Article
Creating a data visualization style guide might sound a bit formal, but it’s really just a helpful document that keeps the look and feel of your charts consistent. Whether you’re working solo or as part of a team, having one saves time and makes your visuals easier to read and understand. We’ve seen many great examples at routecanal.com, and the best ones always keep it simple and clear.
Start by choosing your colors. You don’t need a huge palette—three to five key colors will usually do the trick. Pick shades that show up well on both light and dark backgrounds. Try to include one accent color for highlighting important data and a few quieter shades for everything else. If you have a brand color, this is a good place to bring it in.
Next, think about fonts. Stick to one or two that are easy to read. It helps if they work well in both titles and chart labels. Keep font size readable, especially in legends and axis labels, where it’s easy for text to get too small.
Decide on chart types for specific jobs. For example, use a bar chart to compare things, a line chart to show trends over time, or a scatter plot to explore relationships. Write down which chart types to avoid too—like those colorful but often confusing 3D pie charts.
It’s also a good idea to agree on how to label charts. Should all charts have titles? Should numbers be rounded? What kind of date format will you use (MM/DD/YYYY or DD/MM/YYYY)? These small things really help keep your visuals clean and avoid confusion.
Include examples in your guide. Show a version of a “good” chart and a “not-so-good” one. You can even do a before-and-after to show how simple changes make a big difference.
Lastly, remember your guide is a living document. As your team grows or your data changes, you might want to tweak and update it. Keep it digital so everyone can access and edit the latest version easily.
A good style guide is like a friendly map. It helps you and others create clear, honest, and useful visuals every time. And once you have it, making charts becomes a lot more fun—and a lot less frustrating.