#### 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

Continuous Data

Visualizing continuous time series data is similar to visualizing discrete data. You do, after all, still have a discrete number of data points, even if the dataset is continuous. The structure of continuous and discrete is the same. The difference between the two is what they represent in the physical world. As previously covered, continuous data represents constantly changing phenomena, so to this end, you want to visualize the data in a way that shows that.

Connect the Dots

You’re probably familiar with this one. The time series chart is similar to drawing points, except you also connect the points with lines. Often, you don’t show the points. Figure 4-33 shows the geometry of the popular chart type.

You have the nodes, or points, that take on X- and Y-coordinates, and then the edges, or connecting lines that help you see trends in your data. It’s usually a good idea to start the value axis at zero because starting anywhere else could affect the...