#StandWithUkraine - Stop the Russian invasion
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Organization of the Book
We’ve organized the chapters of this book to serve as an introductory hands-on guide to data visualization, from spreadsheets to code. Also, we assume no prior skills other than general familiarity with operating a computer and a vague memory of secondary school mathematics, along with an innate curiosity about telling stories with data. Imagine the book in four parts.
In part one, you’ll develop foundational skills about envisioning your data story, along with the tools and data you’ll need to tell it. We’ll gradually move from Chapter 1: Choose Tools to Tell Your Data Story to Chapter 2: Strengthen Your Spreadsheet Skills to Chapter 3: Find and Question Your Data to Chapter 4: Clean Up Messy Data to Chapter 5: Make Meaningful Comparisons. These chapters feature hands-on tutorials to enrich learning by doing.
In part two, you’ll build lots of visualizations with easy-to-learn drag-and-drop tools, and find out which types work best with different data stories. We’ll start with Chapter 6: Chart Your Data, Chapter 7: Map Your Data, and Chapter 8: Table Your Data and develop your understanding of the interpretive style that each one emphasizes. In Chapter 9: Embed on the Web, you’ll learn how to insert all of these interactive visualizations on common web platforms, to invite readers to explore your data and share your work more widely.
In part three, you’ll advance to working with more powerful tools, specifically code templates, that give you more control over customizing the appearance of your visualizations and where you host them online. We’ll start with Chapter 10: Edit and Host Code with GitHub, and walk you through the easy web interface for this popular open-source coding platform. Then you’ll build using Chapter 11: Chart.js and Highcharts Templates and Chapter 12: Leaflet Map Templates, and discover more advanced spatial tools in Chapter 13: Transform Your Map Data. At the end of the book we include an Appendix: Fix Common Problems to consult when you accidentally break your code, which is also a great way to learn how it works.
In part four, we’ll wrap up all of the visualization skills you’ve developed by returning to the central theme of this introduction: telling true and meaningful stories with data. In Chapter 14: Detect Lies and Reduce Bias, you’ll learn how to lie with charts and maps in order to do a better job of telling the truth. Finally, Chapter 15: Tell and Show Your Data Story emphasizes how the goal of data visualization is not simply to make pictures about numbers, but to craft a truthful narrative that convinces readers how and why your interpretation matters.
Now you have a clearer sense of our primary goal for this book. We aim for you to learn how to tell true and meaningful stories with interactive data visualizations, while being mindful of the ways that people can use them to mislead. In the next chapter, let’s get started on clarifying the data story you wish to tell, and factors to consider when choosing tools to do the job.