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)

Mapping

Some overlap exists between the covered visualization tools and the ones that you use to map geographic data. However, the amount of geographic data has increased significantly in the past years as has the number of ways you can map. With mobile location services on the rise, there will be more data with latitude and longitude coordinates attached to it. Maps are also an incredibly intuitive way to visualize data, and this deserves a closer look.

Mapping in the early days of the web wasn’t easy; it wasn’t elegant either. Remember the days you would go to MapQuest, look up directions, and get this small static map? Yahoo had the same thing for a while.

It wasn’t until a couple of years later until Google provided a slippy map implementation (Figure 3-23). The technology was around for a while, but it wasn’t useful until most people’s Internet speed was fast enough to handle the continuous updating. Slippy maps are what we’re used to nowadays...