We spend a lot of time in Lede discussing the storytelling aspects of charts and graphs. What colors do you choose? What data do you highlight? How can you most effectively tell the story?
In times like those, it’s good to have a handful of ways to pump out charts and graphs. If you’re looking to kick it up a notch, you might be interested in more fully-featured interactive options.
Think programming is the end-all be-all of data visualization? Think again! Adobe Illustrator is a great tool to both design custom graphs from the ground up as well as customize the output of Python tools and QGIS mapping software.
DataWrapper is an open-source tool that guides you through the creation of interactive charts and maps. Since its creation it has grown from a low-tech, easy-to-use tool into a powerhouse used by newsrooms around the world.
matplotlib is a library for Python that allows you to create all sorts of charts and graphs from your data sets. Most any visual you see in an academic paper was probably created using matplotlib.
When a simple chart or graph just isn’t enough, it’s time to call in the big guns.
The JavaScript library d3.js – Data Driven Documents – powers most all of the custom visualizations you see on the internet today. Was there a fun interactive in New York Times today? Definitely d3.
Vega and Altair are visualization grammars that build on the same theory-driven foundations as D3. While not nearly as popular as they should be, they’re a handy tool to have in your arsenal.