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Visualize This

Visualize This

By : Nathan Yau‚ÄØ
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Visualize This

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)
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Good Visualization

Although people have been charting and graphing data for centuries, only in the past few decades have researchers been studying what works and what doesn’t. In that respect, visualization is a relatively new field. There still isn’t a consensus on what visualization actually is. Is visualization something that has been generated by a computer following a set of rules? If a person has a hand in the design process, does that make it not a visualization? Are information graphics visualization, or do they belong in their own category?

Look online, and you can find lots of threads discussing differences and similarities between information graphics and visualization or essays that try to define what visualization is. It always leads to a never-ending back and forth without resolution. These opposing opinions lead to varied criteria for what makes a data graphic good or bad.

Statisticians and analysts, for example, generally think of visualization as traditional...

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Visualize This
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