R

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.

Here are some tips to get you started, based on my own experiences with R, and more recently, the JavaScript library d3.js.

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.

Figure out which is best with a side-by-side comparison.

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

For presentation purposes, it can be useful to adjust the style of your axes and reference lines for readability. It’s all about the details.

Make a bunch of charts, string them together like a flip book, and there’s your animation. Sometimes good for showing changes over time. Always fun to play with.

Quickly compare two time series variables with this line-area chart hybrid that originated in the 1700s. Also known as: difference chart.

The conterminous United States always gets the attention, while Alaska and Hawaii are often left out. It is time to bring them back into view.

It’s like working with a bunch of tiny dots, and oh look, all of sudden patterns emerge.

The relatively new and lesser known time series visualization can be useful if you know what you’re looking at, and they take up a lot less space.