Visualize This: The FlowingData Guide to Design, Visualization, and Statistics
Author: Nathan Yau (Author)
Publisher finelybook 出版社: Wiley
Edition 版本: 2nd
Publication Date 出版日期: 2024-05-29
Language 语言: English
Print Length 页数: 384 pages
ISBN-10: 1394214863
ISBN-13: 9781394214860
Book Description
One of the most influential data visualization books―updated with new techniques, technologies, and examples
Visualize This demonstrates how to explain data visually, so that you can present and communicate information in a way that is appealing and easy to understand. Today, there is a continuous flow of data available to answer almost any question. Thoughtful charts, maps, and analysis can help us make sense of this data. But the data does not speak for itself. As leading data expert Nathan Yau explains in this book, graphics provide little value unless they are built upon a firm understanding of the data behind them. Visualize This teaches you a data-first approach from a practical point of view. You’ll start by exploring what your data has to say, and then you’ll design visualizations that are both remarkable and meaningful.
With this book, you’ll discover what tools are available to you without becoming overwhelmed with options. You’ll be exposed to a variety of software and code and jump right into real-world datasets so that you can learn visualization by doing. You’ll learn to ask and answer questions with data, so that you can make charts that are both beautiful and useful. Visualize This also provides you with opportunities to apply what you learn to your own data. This completely updated, full-color second edition:
- Presents a unique approach to visualizing and telling stories with data, from data visualization expert Nathan Yau
- Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design
- Details tools that can be used to visualize data graphics for reports, presentations, and stories, for the web or for print, with major updates for the latest R packages, Python libraries, JavaScript libraries, illustration software, and point-and-click applications
- Contains numerous examples and descriptions of patterns and outliers and explains how to show them
Information designers, analysts, journalists, statisticians, data scientists―as well as anyone studying for careers in these fields―will gain a valuable background in the concepts and techniques of data visualization, thanks to this legendary book.
From the Back Cover
LEARN HOW TO CREATE GRAPHICS THAT TELL MEANINGFUL STORIES WITH DATA
Designing charts and graphics is, first and foremost, about understanding data― sometimes monumental amounts of data. In Visualize This, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to gather, parse, and format data, so you can design high quality graphics that maximize the data’s storytelling potential.
Inside, you’ll learn how to use technologies like R, Python, Excel, and JavaScript to create eye-catching visualizations that communicate their message clearly and accurately. Discover how to showcase outliers, find patterns in datasets, create informational maps, and more. With real-world examples and hands-on activities, you’ll hone your skills as an information designer.
In this updated edition of his classic book, Nathan Yau encourages you to think creatively as you:
- Present data with visual representations that allow your audience to see the unexpected
- Find the stories your data can tell
- Explore different data sources and determine effective formats for presentation
- Experiment with and compare different visualization tools
- Look for trends and patterns in your data and select appropriate ways to chart them
- Establish clear goals to guide your visualizations
Visit the companion web site at http://www.book.flowingdata.com/vt2/ for code samples, downloadable data files, and interactive examples.
About the Author
Nathan Yau earned his PhD in Statistics at UCLA. His goal is to make data available and useful to everyone, regardless of data background. He believes that visualization is the best way to do this. You can follow his data experiments at http://www.flowingdata.com.
