Visualize This

The FlowingData Guide to Design, Visualization, and Statistics

Nathan Yau (UCLA)

$74.95

Paperback

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English

John Wiley & Sons Inc
10 June 2024

Business applications; Information visualisation

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.

By: Nathan Yau (UCLA)
Imprint: John Wiley & Sons Inc
Country of Publication: United States
Edition: 2nd edition
Dimensions: Height: 234mm, Width: 185mm, Spine: 20mm
Weight: 748g
ISBN: 9781394214860
ISBN 10: 1394214863
Pages: 384
Publication Date: 10 June 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Introduction xv 1 Telling Stories with Data 1 More than Numbers 2 Ask Questions About the Data 8 Design 14 Wrapping Up 20 2 Choosing Tools to Visualize Data 21 Mixed Toolbox 22 Point- and- Click Visualization 23 Programming 31 Mapping 40 Illustration 45 Small Visualization Tools 49 Pencil and Paper 54 Survey Your Options 55 Wrapping Up 57 3 Handling Data 59 Data Preparations 60 Finding Data 60 Collecting Data 65 Loading Data 73 Formatting Data 74 Processing Data 86 Filtering and Aggregating Sampled Data 87 Wrapping Up 89 4 Visualizing Time 91 Trends 92 Events 112 Cycles 131 Wrapping Up 141 5 Visualizing Categories 143 Amounts 144 Parts of a Whole 159 Rank and Order 176 Categories and Time 180 Wrapping Up 192 6 Visualizing Relationships 193 Correlation 194 Differences 212 Multiple Variables 225 Connections 235 Wrapping Up 243 7 Visualizing Space 245 Working with Spatial Data 246 Locations 250 Spatial Distributions 266 Space and Time 283 Wrapping Up 293 8 Analyzing Data Visually 295 Gathering Information 296 Overviews 296 Exploring Details 324 Drawing Conclusions 336 Wrapping Up 337 9 Designing with Purpose 339 Good Visualization 340 Insight for Others 344 Wrapping Up 351 Index 353

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 www.flowingdata.com.