Book Image

Visualize This

By : Nathan Yau‚ÄØ
Book Image

Visualize This

By: Nathan Yau‚ÄØ

Overview of this book

Visualize This is a guide on how to visualize and tell stories with data, providing practical design tips complemented with step-by-step tutorials. It begins with a description of the huge growth of data and visualization in industry, news, and gov't and opportunities for those who tell stories with data. Logically it moves on to actual stories in data-statistical ones with trends and human stories. the technical part comes up quickly with how to gather, parse and format data with Python, R, Excel, Google docs, and so on, and details tools to visualize data-native graphics for the Web like ActionScript, Flash libraries, PHP, JavaScript, CSS, HTML. Every chapter provides an example as well. Patterns over time and kinds of data charts are followed by proportions, chart types and examples. Next, examples and descriptions of outliers and how to show them, different kinds of maps, how to guide your readers and explain the data "in the visualization". The book ends with a value-add appendix on graphical perception.
Table of Contents (12 chapters)

Reducing Dimensions

When you use Chernoff Faces or parallel coordinates, your main goal is to reduce. You want to find groups within the dataset or population. The challenge is that you don’t always know where to start looking in the faces or the connecting lines, so it’d be nice if you could cluster objects, based on several criteria. This is one of the goals of multidimensional scaling (MDS). Take everything into account, and then place units that are more similar closer together on a plot.

Entire books are written on this topic, so explanations can get technical, but for the sake of simplicity, I’ll keep it at a high level and leave the math for another day. That said, MDS is one of the first concepts I learned in graduate school, and it is worth learning the mechanics behind it, if you’re into that sort of thing.

For more details on the method, look up multidimensional scaling or principal components analysis.

Imagine that you’re in an empty, square...