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.
Author(s): Nathan Yau
Edition: 2
Publisher: Wiley
Year: 2024
Language: English
Commentary: Publisher's PDF
Pages: 384
City: Hoboken, NJ
Tags: Data Analysis; Data Visualization; Best Practices; Design; Storytelling
Cover
Title Page
Copyright Page
About the Author
About the Technical Editor
Acknowledgments
Contents
Introduction
Learning Data Visualization
How to Use This Book
Chapter 1 Telling Stories with Data
More Than Numbers
Statistically Informative
Entertaining
Emotional
Compelling
Ask Questions About the Data
Verification
Exploration
Communication
Design
Purpose
Audience
Devices
Clarity and Insight
Trade-Offs
Wrapping Up
Chapter 2 Choosing Tools to Visualize Data
Mixed Toolbox
Point-and-Click Visualization
Options
Trade-Offs
Programming
Options
Trade-Offs
Mapping
Options
Trade-Offs
Illustration
Options
Trade-Offs
Small Visualization Tools
Options
Trade-Offs
Pencil and Paper
Trade-Offs
Survey Your Options
Wrapping Up
Chapter 3 Handling Data
Data Preparations
Finding Data
Search Engines
General Data Applications
Researchers
Governments
Catalogs and Lists
Topical References
Collecting Data
Copy and Paste
Manual Collection
Scraping
Scraping a Website
Loading Data
Formatting Data
Data Formats
Formatting Tools
Formatting with Code
Switching Between Data Formats
Processing Data
Filtering and Aggregating Sampled Data
Wrapping Up
Chapter 4 Visualizing Time
Trends
Bar Chart for Time
Making a Bar Chart
Line Chart
Making a Line Chart
Step Chart
Making a Step Chart
Smoothing
Using a Spline
Events
Timeline
Making a Timeline
Dot Plot
Making a Dot Plot
Cycles
Multi-Line Chart
Making a Multi-Line Chart
Heatmap
Making a Heatmap
Wrapping Up
Chapter 5 Visualizing Categories
Amounts
Bar Chart for Categories
Making a Bar Chart for Categories
Editing the Chart
Scaled Symbols
Using Scaled Symbols
Editing the Chart
Parts of a Whole
Pie Chart
Making a Pie Chart
Donut Chart
Making a Donut Chart
Square Pie
Making a Square Pie Chart
Treemap
Making a Treemap
Editing the Chart
Rank and Order
Categories and Time
Stacked Bar Chart
Making a Stacked Bar Chart
Formatting the Data
Making the Chart
Stacked Area Chart
Making a Stacked Area Chart
Alluvial Diagram
Making an Alluvial Diagram
Bump Chart
Wrapping Up
Chapter 6 Visualizing Relationships
Correlation
Scatterplot
Making a Scatterplot
Bubble Plot
Making a Bubble Plot
Differences
Barbell Chart
Making a Barbell Chart
Difference Chart
Making a Difference Chart
Highlighting Differences
Multiple Variables
Heatmap for Multiple Variables
Making a Heatmap for Multiple Variables
Parallel Coordinates
Making Parallel Coordinates
Separating Views
Connections
Network Graph
Making a Network Graph
Wrapping Up
Chapter 7 Visualizing Space
Working with Spatial Data
Geocoding Addresses
Map Projections
Locations
Points
Mapping Points
Scaled Symbols
Adding Scaled Symbols
Lines
Adding Lines
Spatial Distributions
Choropleth Map
Making a Choropleth Map
Cartogram
Making a Cartogram
Dot Density Map
Making a Dot Density Map
Space and Time
Sequence of Maps
Animated Map
Making an Animated Map
Wrapping Up
Chapter 8 Analyzing Data Visually
Gathering Information
Overviews
Summaries
Making a Box Plot
Distributions
Quality of the Data
Adjusting Questions
Exploring Details
Comparisons
Patterns
Uncertainty
Outliers
Drawing Conclusions
Wrapping Up
Chapter 9 Designing with Purpose
Good Visualization
Infinite Options
Visualization Components
Insight for Others
Visual Hierarchy
Aesthetics
Visual Metaphors
Annotation
Accessibility
Wrapping Up
Index
EULA
