Data Visualization with D3 4.x Cookbook

Data Visualization with D3 4.x Cookbook - Second Edition

By : Nick Zhu

Buy this Book

Data Visualization with D3 4.x Cookbook - Second Edition

By: Nick Zhu

Buy this Book

Overview of this book

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

Data Visualization with D3 4.x Cookbook - Second Edition

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

Free Chapter

Getting Started with D3.js

Introduction

Setting up a simple D3 development environment

Setting up an NPM-based development environment

Understanding D3-style JavaScript

Be Selective

Introduction

Selecting a single element

Selecting multiple elements

Iterating through a selection

Performing subselection

Function chaining

Manipulating the raw selection

Dealing with Data

Introduction

Binding an array as data

Binding object literals as data

Binding functions as data

Working with arrays

Filtering with data

Sorting with data

Loading data from a server

Asynchronous data loading using queue

Tipping the Scales

Introduction

Using continuous scales

Using the time scale

Using the ordinal scale

Interpolating a string

Interpolating colors

Interpolating compound objects

Playing with Axes

Introduction

Working with basic axes

Customizing ticks

Drawing grid lines

Dynamic rescaling of axes

Transition with Style

Introduction

Animating a single element

Animating multiple elements

Using ease

Using tweening

Using transition chaining

Using transition filter

Listening to transitional events

Working with timer

Getting into Shape

Introduction

Creating simple shapes

Using a line generator

Using line curve

Changing line tension

Using an area generator

Using area curve

Using an arc generator

Implementing arc transition

Chart Them Up

Introduction

Creating a line chart

Creating an area chart

Creating a scatterplot chart

Creating a bubble chart

Creating a bar chart

Lay Them Out

Introduction

Building a pie chart

Building a stacked area chart

Building a treemap

Building a tree

Building an enclosure diagram

Interacting with Your Visualization

Introduction

Interacting with mouse events

Interacting with a multi-touch device

Implementing zoom and pan behavior

Implementing drag behavior

Using Force

Introduction

Using gravity and charge

Customizing velocity

Setting the link constraint

Using force to assist visualization

Manipulating force

Building a force-directed graph

Knowing Your Map

Introduction

Projecting the US map

Projecting the world map

Building a choropleth map

Test Drive Your Visualization

Introduction

Getting Jasmine and setting up the test environment

Test driving your visualization - chart creation

Test driving your visualization - SVG rendering

Test driving your visualization - pixel-perfect bar rendering

Building Interactive Analytics in Minutes

Introduction

The crossfilter.js library

Dimensional charting - dc.js

Customer Reviews

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The crossfilter.js library

Crossfilter is also a library created by D3's author Mike Bostock, initially used to power analytics for Square Register.

Crossfilter is a JavaScript library for exploring large multivariate datasets in browser. Crossfilter supports extremely fast (<30ms) interaction with coordinated views, even with datasets containing a million or more records.

-Crossfilter Wiki (August 2013)

In other words, Crossfilter is a library that you can use to generate data dimensions on large and typically flat multivariate datasets. So what is a data dimension? A data dimension can be considered as a type of data grouping or categorization while each dimensional data element is a categorical variable. Since this is still a pretty abstract concept, let's take a look at the following JSON dataset and see how it can be transformed into dimensional dataset using Crossfilter. Assume that we have the following flat dataset in JSON describing payment transactions in a bar:

[ 
  {...

Data Visualization with D3 4.x Cookbook - Second Edition

By : Nick Zhu

Data Visualization with D3 4.x Cookbook - Second Edition

By: Nick Zhu

Overview of this book

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