Tutorials

Mapping geographic data in R can be tricky, because there are so many…

A detailed guide for R users who want to polish their charts in the popular graphic design app for readability and aesthetics.

In the the last part of the four-part series, you make a longer animation with more data and annotate.

How to make a bunch of maps and string them together to show change.

How to make a more readable and more visually accurate map, before you dive into the big transitions.

Rarely do you have evenly-spaced data across an entire geographic space. Here is a way to fill in the gaps.

There are many ways to show parts of a whole. Here are quick one-liners for the more common ones.

Try the more element-based approach instead of your traditional histogram or boxplot.

Use a force-directed graph to form a collection of bubbles and move them around based on data.

Instead of traditional pie charts that rely on angles and arc lengths to show parts of a whole, try this easier-to-read version.

Let the data speak for itself they say. That doesn't work a lot of the time, and when that happens, you need to explain.

Learn to visualize temporal patterns in a couple of days.

Show connections and changes over time with start and end points.

Whether you use circles as visual encodings or as a way to highlight areas of a plot, there are functions at your disposal.

R makes it easy to add squares and rectangles to your plots, but it gets a little tricky when you have a bunch to draw at once. The key is to break it down to the elements.

The deldir package by Rolf Turner makes the calculations and plotting straightforward, with a few lines of code.

Make sure you explain your visual encodings so that others can interpret them.

Stacked area charts let you see categorical data over time. Interaction allows you to focus on specific categories without losing sight of the big picture.