Using clustering to make a color scale

Posted to Statistics  |  Tags: ,  |  Nathan Yau

Choice of color scale can make a big difference in how the data reads. A careless choice might make the data appear skewed too far low or too far high, so you need to look at the data and decide what’s right for the context. But, sometimes you just gotta make a lot of charts or maps. Or, you just don’t feel like manually picking the colors.

David Schnurr describes a way to use clustering to pick the natural breaks in a more automatic fashion. The best part:

In an effort to make it easier for anyone to use this technique in data visualizations, I’ve ported this new algorithm to JavaScript and created a custom d3 scale called d3-scale-cluster. You can find d3-scale-cluster on Github and npm–give it a try and shoot me a tweet @dschnr with your thoughts!

More on GitHub.

And I await for someone to make an R package.

Favorites

The Changing American Diet

See what we ate on an average day, for the past several decades.

How You Will Die

So far we’ve seen when you will die and how other people tend to die. Now let’s put the two together to see how and when you will die, given your sex, race, and age.

How to Spot Visualization Lies

Many charts don’t tell the truth. This is a simple guide to spotting them.

Best Data Visualization Projects of 2016

Here are my favorites for the year.