Some of my Favorite Data Visualization Resources

Data Visualization is one pillar of the solution to the problem of overwhelming data. What may appear to be completely noisy, incoherent data points can appear as immediately recognizable patterns when projected onto the right data visualization.

Visualization is more art than science at this point, although some have used it enough to be able to identify successful techniques for various purposes. Most successful visualizations are perhaps more dependent upon the decision or task at hand than the actual original structure of the data. For example, geographical information might actually not be best visualized on a map, if the task at hand doesn't depend on comparing geographical distances or directionality.

Sometimes the distribution of values in the data call for one specific visualization rather than another. A good example is illustrated in a recent post on Business Insider showing how a pie chart, while it could be good for showing a distinction between 2 or 3 data points with different values, is terrible for comparing 10 values with subtly differing values; a task much better served by a bar chart.

Here are a few great resources on data visualization. There are too many out there for me to do them all justice. These are just a few that I've found useful and use on a regular basis.

Books on Visualization

Visualize This
By Nathan Yau

This book is great because it discusses everything from how visualization can solve an information problem to creating the visualization using open tools to adding the final touches.

Visualizing Data
By Ben Fry

This is another great book for a comprehensive look at creating visualizations. Using a seven step pipeline this book covers the conception of a good visualization all the way to completion. Ben Fry is also the author of an interactive visualization framework called Processing that is used throughout the book.

R Graphics Cookbook
By Winston Chang

I recently picked this up because R is such a useful tool for doing so many things with data, and the visualizations R produces are fairly good out of the box. This cookbook helps you get to a good visualization quickly with examples for almost any visualization you might want.

Information is Beautiful
By David McCandless

This fascinating book is a collection of interesting visualizations of a wide variety of things that author David McCandless has created. David describes himself as a data journalist and information designer. These are some very creative visualizations that go far beyond the classic charts and graphs.

The Visual Display of Quantitative Information
By Edward Tufte

This is a much older book than most of the others yet it describes principles that apply to all good visualizations. In particular I like Tufte's emphasis on parsimonious designs that get out of the way and let the information tell the story.

Universal Principles of Design
By William Lidwell, Kritina Holden, and Jeff Butler

This book contains an alphabetical list of good design principles that apply to all aspects of design, including visualizations and information design.

Sites for Visualizations and Design

Flowing Data -
Nathan Yau's (author of Visualize This) site

Visual Complexity -
A site containing many different ways to tackle visualizing graphs, one of the most difficult types of visualization. - is like a hub for infographics. One could argue that too many things are being made into infographics, but there have been some amazing things posted at that push the envelope in terms of making unfathomable things understandable, like this Perspective on Time.

The New York Times -
The Times has done some fantastic visualizations around individual stories in the past.

Wanken -
The blog of designer Shelby White, who just manages to find consistently amazing design. Also author if the site designspiration.


R -
The reason I like R is that it produces pretty good visualizations out of the box which can then be exported as SVG to another application for fine-tuning, styling, and labeling.

Python's Matplot lib -
In conjunction with things like scikit-learn and NLTK, Python's matplotlib makes for a very well-rounded data processing and visualization toolkit.

D3 -
D3 is great for creating custom visualizations for the web that may need to be interactive. The only drawback is that it can be more difficult to use than a focused graphic library. Classic customization vs convenience trade-off here.

Highcharts -
Highcharts are ready-to-use javascript charts that look great and are fantastic for showing live updates to data. Highcharts must be licensed for commercial use.

Chart.js -
Chart.js are really good looking animated HTML5 charts. These are so great I recently built them into our product at Koverse for visualizing various aspects of data collections. Below is one example.

Processing -
Processing is a project to make building interactive visualizations easy using a scripting language built on Java and integrated development environment. Processing has a lot of great libraries for doing things like simulating physics and even face detection in webcam video. Many a sophisticated experiential design and art project have been built using Processing.

Hopefully the above list proves useful in your own endeavors. Happy visualization!