#### 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.
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Contents
Chapter 1: Telling Stories with Data
Chapter 2: Handling Data
Chapter 3: Choosing Tools to Visualize Data
Chapter 4: Visualizing Patterns over Time
Chapter 5: Visualizing Proportions
Chapter 6: Visualizing Relationships
Chapter 7: Spotting Differences
Chapter 8: Visualizing Spatial Relationships
Chapter 9: Designing with a Purpose
Introduction

Discrete Points in Time

Temporal data can be categorized as discrete or continuous. Knowing which category your data belongs to can help you decide how to visualize it. In the discrete case, values are from specific points or blocks of time, and there is a finite number of possible values. For example, the percentage of people who pass a test each year is discrete. People take the test, and that’s it. Their scores don’t change afterward, and the test is taken on a specific date. Something like temperature, however, is continuous. It can be measured at any time of day during any interval, and it is constantly changing.

In this section you look at chart types that help you visualize discrete temporal data, and you see concrete examples on how to create these charts in R and Illustrator. The beginning will be the main introduction, and then you can apply the same design patterns throughout the chapter. This part is important. Although the examples are for specific charts, you...