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)

What to Look For

Okay, stories. Check. Now what kind of stories do you tell with data? Well, the specifics vary by dataset, but generally speaking, you should always be on the lookout for these two things whatever your graphic is for: patterns and relationships.


Stuff changes as time goes by. You get older, your hair grays, and your sight starts to get kind of fuzzy (Figure 1-5). Prices change. Logos change. Businesses are born. Businesses die. Sometimes these changes are sudden and without warning. Other times the change happens so slowly you don’t even notice.

Figure 1-5: A comic look at aging


Whatever it is you’re looking at, the change itself can be interesting as can the changing process. It is here you can explore patterns over time. For example, say you looked at stock prices over time. They of course increase and decrease, but by how much do they change per day? Per week? Per month? Are there periods when the stock went up more than usual? If so, why...