R

The code to create these bar chart variations is almost the same as if you were to make a standard bar chart. But make sure you get the math right.

Where to start? What to learn next? Here’s a course to help take you from beginner to advanced.

It’s easy to draw dots. The challenge is to make them meaningful and readable.

Learn to draw lines wherever and however you want, and you’ve got yourself some flexibility.

You can customize graphics in R with par(), but the docs are mostly text and just organized alphabetically. Here is a more visual reference, categorized by what you can change. Plus, a one-page printout.

The chart type seems simple enough, but there sure are a lot of bad ones out there. Get yourself out of default mode.

It might not be sexy, but you have to load your data and get it in the right format before you can visualize it. Here are the basics, which might be all you need.

Fill those empty polygons with color, based on shapefile or external data.

No need to settle for the mapping defaults in R. Apply map projections to show geographic data in a way most suitable for your work.

Geographic data is often available as a shapefile, and there’s plenty of heavy software to get that data in a map. R is an open source option, and as a bonus, much of the work can be done in a few lines of code.