Audience and Overview
As educators, we designed this book to be accessible for new learners, to introduce key concepts in data visualization and reinforce them with hands-on examples. We assume no prior knowledge other than a basic familiarity with computers and some vague memories of secondary school mathematics. Based on feedback we’ve received from an earlier draft, many readers across the globe have taught themselves with this book, and others educators are already using it as a textbook to teach their students.
Our subtitle, “Interactive Storytelling from Spreadsheets to Code,” reflects how the scope of the book progresses from strengthening basic skills to editing open-source code templates, while continually maintaining our focus on telling true and meaningful data stories. We explain both the why and the how of visualization, and encourage critical thinking about how data is socially constructed, and whose interests are served or ignored.
Unlike many computer books that focus on selling you a specific software application, this book introduces you to over twenty different visualization tools, all of them free and easy-to-learn. We also offer guiding principles on how to make wise choices among digital tools as they continue to evolve in the future. By working through the sample datasets and tutorials, you will create more than a dozen different interactive charts, maps, and tables, and share these data stories with other readers on the public web.
Advice for Hands-On Learning
Learn by following our step-by-step tutorials on a laptop or desktop computer with an internet connection. Most of the tools introduced in the book are web-based, and we recommend you use an up-to-date version of Firefox, Chrome, Safari, or Edge browsers. We advise against using Internet Explorer as this older browser is no longer correctly supported by many web services. A Mac or a Windows computer will allow you to complete all tutorials, but if you use a Chromebook or Linux computer, you still should be able to complete most of them, and we’ll point out any limitations in specific sections. While it may be possible to complete some tutorials on a tablet or smartphone device, we do not recommend it because these smaller devices will prevent you from completing several key steps.
If you’re working on a laptop, consider buying or borrowing an external mouse that plugs into your computer. We’ve met several people who find it much easier to click, hover, and scroll with an external mouse than a laptop’s built-in trackpad. If you’re new to working with computers–or teaching newer users with this book—consider starting with basic computer and mouse tutorial skills from the Goodwill Community Foundation. Also, if you’re reading a digital version of this book on a laptop, consider connecting a second computer monitor, or working with a tablet or second computer alongside you. This allows you to read the book in one screen and build data visualizations in the other screen.
The chapters in this book build up toward our central goal: telling true and meaningful stories with data.
Introduction asks why data visualization matters, and shows how charts, maps, and words can draw us further into a story or deceive us from the truth.
Chapter 1: Choose Tools to Tell Your Data Story helps you to navigate your way through the process of sketching out your story and selecting which visualization tools you need to tell it effectively.
Chapter 2: Strengthen Your Spreadsheet Skills starts with basics and moves on to ways of organizing and analyzing data with pivot tables and lookup formulas, as well as geocoding add-on tools and collecting data with online forms.
Chapter 3: Find and Question Your Data offers concrete strategies for locating reliable information, while raising deeper questions about what data truly represents and whose interests it serves.
Chapter 4: Clean Up Messy Data introduces ways to spot and fix inconsistencies and duplicates with spreadsheets and more advanced tools, and also how to extra tables from digital documents.
Chapter 5: Make Meaningful Comparisons provides common-sense strategies to begin analyzing and normalizing your data, while watching out for biased methods.
Chapter 6: Chart Your Data teaches how to create visualizations with easy-to-learn drag-and-drop tools, and which ones work best with different data stories.
Chapter 7: Map Your Data focuses on building different types of visualizations that include a spatial element, and the challenges of designing true and meaningful maps.
Chapter 8: Table Your Data explains how to create interactive tables that include thumbnail visualizations called sparklines.
Chapter 9: Embed on the Web connects prior chapters by demonstrating how to copy and modify embed codes to publish your visualizations online and share your work with wider audiences.
Chapter 10: Edit and Host Code with GitHub walks through the web interface for this popular platform for modifying and sharing open-source visualization code templates.
Chapter 11: Chart.js and Highcharts Templates brings together open-source code templates to create charts you can customize and host anywhere on the web.
Chapter 12: Leaflet Map Templates gathers open-source code templates to build a wider variety of maps to communicate your data story.
Chapter 13: Transform Your Map Data takes a deeper look into geospatial data and easy-to-learn tools to customize data for your maps.
Chapter 14: Detect Lies and Reduce Bias explores how to lie with charts and maps, to teach you how to do a better job of telling the truth.
Chapter 15: Tell and Show Your Data Story brings together all of the prior chapters to emphasize how data visualization is not simply about numbers, but truthful narratives that persuade readers how and why your interpretation matters.
Appendix A: How to Fix Common Problems serves as a guide for when your visualization tool or code does not work, which is also a great way to learn how it works.
Appendix B: Publishing with Bookdown describes our workflow for creating this book using Bookdown, GitHub, and Zotero.