Book Image

Expert Data Visualization

By : Jos Dirksen
Book Image

Expert Data Visualization

By: Jos Dirksen

Overview of this book

Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecmascript 6 and Typescript
Table of Contents (10 chapters)

Voronoi based on a list of airports

In this section, we're going to create a Voronoi diagram based on geographical data. We'll use a list of all the airports in the world, and use their locations to create a Voronoi diagram. We can create maps using this approach that look like this:

You can still see the general shape of the continents, even though we did not plot any geographic data. The first thing to do is get the data and sanitize it.

Prepare the data

We first download the list of airports from This list contains information on all the airports and groups them by size. The data in this file looks like this: