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- Herausgeber: Packt Publishing
- Kategorie: Fachliteratur
- Sprache: Englisch
Master D3.js and create amazing visualizations with the Data Visualization with D3 4.x Cookbook. Written by professional data engineer Nick Zhu, this D3.js cookbook features over 65 recipes. ? Solve real-world visualization problems using D3.js practical recipes ? Understand D3 fundamentals ? Includes illustrations, ready-to-go code samples and pre-built chart recipes
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Seitenzahl: 360
Veröffentlichungsjahr: 2017
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Table of Contents
Data Visualization with D3 4.x Cookbook - Second Edition
Data Visualization with D3 4.x Cookbook - Second Edition
Copyright © 2017 Packt Publishing
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Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author(s), nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: October 2013
Second edition: February 2017
Production reference: 1220217
Published by Packt Publishing Ltd.
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ISBN 978-1-78646-825-3
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Credits
Author
Nick Zhu
Copy Editor
Dhanya Baburaj
Reviewer
Scott Becker
Project Coordinator
Ritika Manoj
Commissioning Editor
Wilson Dsouza
Proofreader
Safis Editing
Acquisition Editor
Shweta Pant
Indexer
Mariammal Chettiyar
Content Development Editor
Arun Nadar
Graphics
Jason Monteiro
Technical Editor
Sachit Bedi
Production Coordinator
Deepika Naik
About the Author
Nick Zhu is a professional programmer and data engineer with more than a decade experience in software development, big data, and machine learning. Currently, he is one of the founders and CTO of Yroo.com - meta search engine for online shopping. He is also the creator of dc.js—a popular multidimensional charting library built on D3.
About the Reviewer
Scott Becker is a partner at Olio Apps, a software consulting company in Portland Oregon. He has built numerous systems including a marketplace for geospatial datasets, HIPAA compliant video services for the medical industry, and visualizations of breaches in data security products. He is currently building a next generation time tracking system atwww.shoutbase.com. He has also produced a video course on data visualization with D3.js available at deveo.tv.
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Preface
D3.js is a JavaScript library designed to display digital data in dynamic graphical form. It helps you bring data to life using HTML, SVG, and CSS. D3 allows great control over the final visual result, and it is the hottest and most powerful web-based data visualization technology on the market today.
D3 v4 is the latest release of the D3 library. This second edition cookbook has been completely updated to cover and leverage the D3 v4 API, modular data structure, as well as revamped force implemented. It is designed to provide you with all the guidance you need to get to grips with data visualization with D3. With this book, you will create breathtaking data visualization with professional efficiency and precision with the help of practical recipes, illustrations, and code samples.
This cookbook starts off by touching upon data visualization and D3 basics before gradually taking you through a number of practical recipes covering a wide range of topics you need to know about D3.
You will learn the fundamental concepts of data visualization, functional JavaScript, and D3 fundamentals, including element selection, data binding, animation, and SVG generation. You will also learn how to leverage more advanced techniques such as interpolators, custom tweening, timers, queueing, hierarchy, force manipulation, and so on. This book also provides a number of pre-built chart recipes with ready-to-go sample code to help you bootstrap quickly.
What this book covers
Chapter 1, Getting Started with D3.js, is designed to get you up and running with D3.js, covering fundamental aspects, such as what D3.js is, and how to set up a typical D3.js data visualization environment.
Chapter 2, Be Selective, covers one of the most fundamental tasks you need to perform with any data visualization project using D3: selection. Selection helps you target certain visual elements on the page.
Chapter 3, Dealing with Data, explores the most essential question in any data visualization project: how to represent data in both programming constructs and its visual metaphor.
Chapter 4, Tipping the Scales, covers the one key task that you need to perform over and over again as a data visualization developer, that is, mapping values in your data domain to visual domain, which is the focus of this chapter.
Chapter 5, Playing with Axes, explores the usage of the axes component and some related techniques commonly used in the visualization based on the Cartesian coordinates system.
Chapter 6, Transition with Style, deals with a saying that is arguably one of the most important cornerstones of data visualization, "a picture is worth a thousand words." This chapter covers transition and animation support provided by the D3 library.
Chapter 7, Getting into Shape, deals with Scalable Vector Graphic (SVG), which is a mature World Wide Web Consortium (W3C) standard widely used in visualization projects.
Chapter 8, Chart Them Up, explores one of the oldest and trusted companions in data visualization: charts. Charts are a well-defined and well-understood graphical representation of data.
Chapter 9, Lay Them Out, focuses on the D3 layout. D3 layouts are algorithms that calculate and generate placement information for a group of elements capable of generating some of the most complex and interesting visualizations.
Chapter 10, Interacting with Your Visualization, focuses on D3 human visualization interaction support or, in other words, how to add computational steering capability to your visualization.
Chapter 11, Using Force, covers one of the most fascinating aspects of D3: force. Force simulation is one of the most awe-inspiring techniques that you can add to your visualization.
Chapter 12, Know Your Map, introduces the basic D3 cartographic visualization techniques and how to implement a fully functional geographic visualization in D3.
Chapter 13, Test Drive Your Visualization, guides you to implement your visualization like a pro with Test-Driven Development (TDD).
Appendix A, Building Interactive Analytics in Minutes, serves as an introduction to Crossfilter.js and DC.js on interactive dimensional charting.
What you need for this book
Who this book is for
If you are a developer or an analyst familiar with HTML, CSS, and JavaScript, and you wish to get the most out of D3, then this book is for you. This book can also serve as a desktop quick-reference guide for experienced data visualization developers.
Sections
In this book, you will find several headings that appear frequently (Getting ready, How to do it, How it works, There's more, and See also).
To give clear instructions on how to complete a recipe, we use these sections as follows:
Getting ready
This section tells you what to expect in the recipe, and describes how to set up any software or any preliminary settings required for the recipe.
How to do it…
This section contains the steps required to follow the recipe.
How it works…
This section usually consists of a detailed explanation of what happened in the previous section.
There's more…
This section consists of additional information about the recipe in order to make the reader more knowledgeable about the recipe.
See also
This section provides helpful links to other useful information for the recipe.
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Chapter 1. Getting Started with D3.js
In this chapter, we will cover:
Introduction
This chapter is designed to get you up and running with D3.js and covers fundamental aspects, such as what D3.js is and how to set up a typical D3.js data visualization environment. One particular section is also devoted to covering some lesser known areas of JavaScript that D3.js relies heavily on.
What is D3? D3 refers to Data-Driven Documents, and according to the official D3 Wiki:
D3 (Data-Driven Documents or D3.js) is a JavaScript library for visualizing data using web standards. D3 helps you bring data to life using SVG, Canvas and HTML. D3 combines powerful visualization and interaction techniques with a data-driven approach to DOM manipulation, giving you the full capabilities of modern browsers and the freedom to design the right visual interface for your data.
-D3 Github Wiki (2016, August)
In a sense, D3 is a specialized JavaScript library that allows you to create amazing data visualizations using a simple (data driven) approach by leveraging the existing Web standards. D3.js was created by Mike Bostock (https://bost.ocks.org/mike/ ) and superseded his previous work on a different JavaScript data visualization library called Protovis. For more information on how D3 was created and on the theory that influenced both Protovis and D3.js, please check out the links in the following information box. Here, in this book, we will focus more on how to use D3.js to power your visualization. Initially, some aspects of D3 maybe a bit confusing due to its different approach for data visualization. I hope that over the course of this book, a large number of topics, both basic and advanced, will make you comfortable and effective with D3. Once it is properly understood, D3 can improve your productivity and expressiveness with data visualizations by orders of magnitude.
Note
For a more formal introduction to the idea behind D3, refer to the Declarative Language Design for Interactive Visualization paper published by Mike Bostock on IEEE InfoVis 2010 at http://vis.stanford.edu/papers/protovis-design . If you are interested to know how D3 came about, I recommend that you check out the D3: Data-Driven Document paper published by Mike Bostock, Vadim Ogievestsky, and Jeffery Heer on IEEE InfoVis 2011 at http://vis.stanford.edu/papers/d3 . Protovis, the predecessor of D3.js, also created by Mike Bostock and Jeff Heer of the Stanford Visualization Group can be found at https://mbostock.github.io/protovis/ .
Setting up a simple D3 development environment
The first thing you will need when you start a D3-powered data visualization project is a working development environment. In this recipe, we will show you how a simple D3 development environment can be set up within minutes.
Getting ready
Before we start, make sure that you have your favorite text editor installed and ready on your computer.
How to do it...
We''ll start by downloading D3.js through the following steps:
This is all you need to create, in its simplest form, a D3-powered data visualization development environment. With this setup, you can essentially open the HTML file using your favorite text editor to start your development and also to view your visualization by opening the file in your browser.
Note
The source code for this recipe can be found at https://github.com/NickQiZhu/d3-cookbook-v2/tree/master/src/chapter1/simple-dev-env .
How it works...
D3 JavaScript library is very self-sufficient. It has no dependency on any other JavaScript library except what your browser already provides.
Note
If your visualization's target browser environment includes Internet Explorer 9, it is recommended that you use the compatibility library Aight, which can be found at https://github.com/shawnbot/aight , and Sizzle selector engine, which can be found at http://sizzlejs.com/ .
Having the following character encoding instruction in the header section was critical before D3 v4 release since the older version of D3 used UTF-8 symbols, such as π, in its source; however, with D3 v4.x, it is no longer necessary. It is still considered a good practice however, since other JavaScript libraries you will include might be using UTF-8 symbols, as shown in the following example:
<meta charset=""utf-8"">Note
D3 is completely open source under a custom license agreement created by its author Michael Bostock. This license is pretty similar to the popular MIT license, with only one exception where it explicitly states that Michael Bostock's name cannot be used to endorse or promote products derived from this software without his permission.
There's more...
Throughout this cookbook, numerous recipe code examples will be provided. All example source code is provided and hosted on GitHub (https://github.com/ ), a popular open source social coding repository platform.
How to get source code
The easiest way to get all the recipe source code that you will need is to clone the Git repository (https://github.com/NickQiZhu/d3-cookbook-v2 ) for this book. If you are not planning to set up a development environment for the recipes, then you can safely skip this section.
Note
In case you are not familiar with Git, its clone concept is similar to the checkout concept in other version control software. However, cloning does a lot more than simply checking out the files. It also copies all branches and histories to your local machine, effectively cloning the entire repository to your local machine so you can work even when you are completely offline with this cloned repository in your own environment.
First, install a Git client on your computer. You can find a list of Git client software at https://git-scm.com/downloads , and a detailed guide on how to install it on different operating systems at https://git-scm.com/book/en/Getting-Started-Installing-Git .
Note
Another popular way to get Git and GitHub working is to install the GitHub client, which gives you a richer set of features than simply Git. However, at the time of writing this book, GitHub only offered client software for Windows and Mac OS; refer to https://desktop.github.com/ .
Once the Git client is installed, simply issuing the following command will download all recipe source code to your computer:
> git clone [email protected]:NickQiZhu/d3-cookbook-v2.gitSetting up an NPM-based development environment
The simple setup demonstrated in the previous recipe is enough for implementing most recipes in this book. However, when you work on a more complex data visualization project that requires the use of a number of JavaScript libraries, the simple solution we discussed before might become a bit clumsy and unwieldy. In this section, we will demonstrate an improved setup using Node Packaged Modules (NPM), a de facto JavaScript library repository management system. If you are as impatient as me and want to get to the meaty part of the book, the recipes, you can safely skip this section and come back when you need to set up a more production-ready environment for your project.
Getting ready
Before we start, please make sure that you have NPM properly installed. NPM comes as part of the Node.js installation. You can download Node.js from https://nodejs.org/ . Select the correct Node.js binary build for your OS. Once installed, the following npm command will become available in your terminal console:
> npm -v 2.15.8The preceding command prints out the version number of your NPM client to indicate that the installation is successful.
How to do it...
With the NPM installed, we can now create a package descriptor file to automate some of the manual setup steps:
How it works...
Most of the fields in the package.json file are for informational purpose only, such as its name, description, home page, author, and the repository. The name and the version fields will be used if you decide to publish your library into an NPM repository in the future. What we really care about, at this point, are the dependencies and devDependencies fields:
Note
D3 is a self-sufficient library with zero external runtime dependency. However, this does not mean that it cannot work with other popular JavaScript libraries. I regularly use D3 with other libraries to make my job easier, for example, JQuery, Zepto.js, Underscore.js, and ReactJs to name a few.
Note
Detailed NPM package JSON file documentation can be found at https://docs.npmjs.com/files/package.json .
Executing the npm install command will automatically trigger NPM to download all dependencies that your project requires, including your dependencies' dependencies recursively. All dependency libraries will be downloaded into the node_modules folder under your project's root folder. When this is done, you can just simply create your HTML file as shown in the previous recipe, and load your D3 JavaScript library directly from node_modules/d3/build/d3.js.
The source code for this recipe with an automated build script can be found at https://github.com/NickQiZhu/d3-cookbook-v2/tree/master/src/chapter1/npm-dev-env .
Relying on NPM is a simple and yet more effective way to save yourself from all the trouble of downloading JavaScript libraries manually and the constant need for keeping them up to date. However, an astute reader may have already noticed that with this power we can easily push our environment setup to the next level. What if you are building a large visualization project where thousands of lines of JavaScript code will be created? Then obviously, our simple setup described here will no longer be sufficient. However, modular JavaScript development by itself can fill an entire book; therefore, we will not try to cover this topic since our focus is on data visualization and D3. In later chapters, when unit test-related recipes is discussed, we will expand the coverage on this topic to show how our setup can be enhanced to run automated build and unit tests.
Tip
D3 v4.x is very modular; so if you only need a part of the D3 library for your project, you can also selectively include D3 submodule as your dependency. For example, if you only need d3-selection module in your project, then you can use the following dependency declaration in your package.json file: "dependencies": { "d3-selection":"1.x"}
There's more...
Although in previous sections it was mentioned that you can just open the HTML page that you have created using your browser to view your visualization result directly, this approach does have its limitations. This simple approach stops working once we need to load data from a separate data file (this is what we will do in later chapters, and it is also the most likely case in your daily working environment) due to the browser's built-in security policy. To get around this security constraint, it is highly recommended that you set up a local HTTP server so your HTML page and the data file can be accessed from this server instead of being loaded from a local file system directly.
Setting up a local HTTP server
There are probably more than a dozen different ways to set up an HTTP server on your computer based on the operating system you use and the software package you decide to use to act as an HTTP server. Here, I will attempt to cover some of the most popular setups.
Python Simple HTTP server
This is my favorite for development and fast prototyping. If you have Python installed on your OS, which is usually the case with any Unix/Linux/Mac OS distribution, then you can simply type the following command in your terminal with Python 2:
> python -m SimpleHTTPServer 8888Alternatively, type the following command with Python 3 distribution:
> python -m http.server 8888This little python program will launch an HTTP server and start serving any file right from the folder where this program is launched. This is by far the easiest way to get an HTTP server running on any OS.
Note
If you don't have python installed on your computer yet, you can get it from https://www.python.org/getit/ . It works on all modern OS, including Windows, Linux, and Mac.
Node.js HTTP server
If you have Node.js installed, perhaps as part of the development environment setup exercise we did in the previous section, then you can simply install the http-server module. Similar to the Python Simple HTTP Server, this module will allow you to launch a lightweight HTTP server from any folder and start serving pages right away.
First, you need to install the http-server module using the following command:
> npm install http-server -gThe -g option in this command will install http-server module globally, so it will become available in your command-line terminal automatically. Once this is done, you can launch the server from any folder you are in by simply issuing the following command:
> http-server -p 8888This command will launch a Node.js-powered HTTP server on the default port 8080, or if you want, you can use the -p option to provide a custom port number for it.
Note
If you are running the npm install command on Linux, Unix, or Mac OS, you may need to run the command in the sudo mode or as root in order to use the -g global installation option.
