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)

Over Space and Time

The examples so far enable you to visualize a lot of data types, whether it be qualitative or quantitative. You can vary colors, categories, and symbols to fit the story you’re trying to tell; annotate your maps to highlight specific regions or features; and aggregate to zoom in on counties or countries. But wait, there’s more! You don’t have to stop there. If you incorporate another dimension of data, you can see changes over both time and space.

In Chapter 4, “Visualizing Patterns over Time,” you visualized time more abstractly with lines and plots, which is useful, but when location is attached to your data, it can be more intuitive to see the patterns and changes with maps. It’s easier to see clustering or groups of regions that are near in physical distance.

The best part is that you can incorporate what you’ve already learned to visualize your data over space and time.

Small Multiples

You saw this technique in...