Another free and collaborative tool for creating interactive charts is Datawrapper, which has several advantages over Google Sheets. First, you can start creating in Datawrapper right away in your browser, even without creating an account, and its four-step process is intuitive for many new users. Second, you can add credit bylines, links to data sources, and even allow visitors to download the data from a button inside your Datawrapper visualizations that you publish online, which makes your work more credible and accessible. Third, Datawrapper supports a wider array of interactive chart types than Google Sheets, as well as maps, which we’ll discuss in chapter 7 and tables, in chapter 8. With Datawrapper, you can build all of the basic charts we’ve constructed so far in this chapter, as well as three new types we’ll cover below: annotated charts, range charts, and scatter and bubble charts. Later, you’ll learn how to embed interactive Datawrapper charts on your website in Chapter 9.
While no single tool does everything, we recommend that you consider using both Google Sheets and Datawrapper, which turns this pair of easy-to-use tools into a visualization powerhouse. First, use Google Sheets as your spreadsheet to organize and analyze your data as described in Chapter 2, record your detailed source notes and save raw data files as described in Chapter 3, and clean up your data as described in Chapter 4. Although Datawrapper can transpose data (swap the rows and columns), it cannot create pivot tables or lookup and merge data as spreadsheets can do. Second, import your data from Google Sheets to Datawrapper to create visualizations, because the latter tool offers you more control over their appearance, annotations, and additional features described below. You’ll discover that Datawrapper plays nicely with Google Sheets by accepting a direct link to data stored there. Together, Google Sheets and Datawrapper are a powerful combination.
In addition, we strongly recommend the high-quality Datawrapper Academy support pages, the extensive gallery of examples, and well-designed training materials. Reading these will not only teach you which buttons to press, but more importantly, how to design better visualizations that tell true and meaningful stories about your data. While writing this book, we learned a great deal from Datawrapper Academy, and we give credit and specific links in sections below. Finally, one more plus is that Datawrapper Core is open-source code, though that does not apply to most of the platform’s plugins to create charts and maps.
Now you’re ready to use Datawrapper to create new types of charts that step beyond the basics. But if Datawrapper or the chart types in this section do not meet your needs, refer back to Table 6.1 for other tools and tutorials, or prior chapters on spreadsheets, sourcing, and cleaning up data.