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Table Of Contents

Learning D3.js 5 Mapping - Second Edition

By : Newton, Oscar Villarreal, Verspohl

2 (1)

Buy this Book

Learning D3.js 5 Mapping

2 (1)

By: Newton, Oscar Villarreal, Verspohl

Buy this Book

Overview of this book

D3.js is a visualization library used for the creation and control of dynamic and interactive graphical forms. It is a library used to manipulate HTML and SVG documents as well as the Canvas element based on data. Using D3.js, developers can create interactive maps for the web, that look and feel beautiful. This book will show you how build and design maps with D3.js and gives you great insight into projections, colors, and the most appropriate types of map. The book begins by helping you set up all the tools necessary to build visualizations and maps. Then it covers obtaining geographic data, modifying it to your specific needs, visualizing it with augmented data using D3.js. It will further show you how to draw and map with the Canvas API and how to publish your visualization. By the end of this book, you'll be creating maps like the election maps and the kind of infographics you'll find on sites like the New York Times.

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

Gathering Your Cartography Toolbox

Quick bootstrap

Step-by-step bootstrap

Using the web browser as a development tool

Summary

Creating Images from Simple Text

The SVG coordinate system

Line

Rectangle

Circle

Polygon

Path

Transform

Grouping

Text

Summary

Producing Graphics from Data - the Foundations of D3

Creating basic SVG elements

The enter() function

The update function

The exit() function

Fetch

Summary

Creating a Map

Foundation - creating your basic map

Experiment 1 – adjusting the bounding box

Experiment 2 – creating choropleths

Experiment 3 – adding click events to our visualization

Experiment 4 – using updates and transitions to enhance our visualization

Experiment 5 – adding points of interest

Experiment 6 – adding visualizations as a point of interest

Summary

Click-Click Boom! Applying Interactivity to Your Map

Events and how they occur

Experiment 1 – hover events and tooltips

Experiment 2 – tooltips with visualizations

Experiment 3 – panning and zooming

Experiment 4 – orthographic projections

Experiment 5 – rotating orthographic projections

Experiment 6 – dragging orthographic projections

Summary

Finding and Working with Geographic Data

Geodata file types

Summary

Testing

Code organization and reusable assets

Project structure

Writing testable code

Unit testing

Creating resilient visualization code

Summary

Drawing with Canvas and D3

Introducing Canvas

Animating the Canvas

Summary

Mapping with Canvas and D3

Choosing Canvas or SVG

Visualizing flight paths with Canvas and D3

Summary

Adding Interactivity to Your Canvas Map

Why Canvas interaction is different

Drawing the world on a Canvas

Making the world move

Finding the Canvas object under the mouse - Picking

Visualizing data per country and adding a tooltip

Summary

Shaping Maps with Data - Hexbin Maps

Reviewing map visualization techniques

Value and use of the hexagon

Making a hexbin map

Summary

Publishing Your Visualization with GitHub Pages

What we will publish

Understanding the type of content you can publish

Hosting your code on GitHub

Publishing your project on GitHub Pages

Summary

Fetch

The D3 Fetch API is built off the Fetch specification also implemented in vanilla JavaScript as fetch(). It’s an alternative to Asynchronous Javascript and XML (AJAX), which was used in previous versions of D3 to retrieve external data. Like AJAX, Fetch allows the developer to obtain data from the background of the web page. This technique is extremely useful in map development because geographic datasets can be very large. Acquiring the data from the background will help produce a refined user experience. In addition, in Chapter 6, Finding and Working with Geographic Data, we will cover techniques to compress the size of geographic data.

Separating the data from the code base will also provide the following advantages: