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  • Book Overview & Buying Learning Responsive Data Visualization
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Learning Responsive Data Visualization

Learning Responsive Data Visualization

By : Hanchett, Körner
4.3 (3)
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Learning Responsive Data Visualization

Learning Responsive Data Visualization

4.3 (3)
By: Hanchett, Körner
Buy this Book

Overview of this book

Using D3.js and Responsive Design principles, you will not just be able to implement visualizations that look and feel awesome across all devices and screen resolutions, but you will also boost your productivity and reduce development time by making use of Bootstrap—the most popular framework for developing responsive web applications. This book teaches the basics of scalable vector graphics (SVG), D3.js, and Bootstrap while focusing on Responsive Design as well as mobile-first visualizations; the reader will start by discovering Bootstrap and how it can be used for creating responsive applications, and then implement a basic bar chart in D3.js. You will learn about loading, parsing, and filtering data in JavaScript and then dive into creating a responsive visualization by using Media Queries, responsive interactions for Mobile and Desktop devices, and transitions to bring the visualization to life. In the following chapters, we build a fully responsive interactive map to display geographic data using GeoJSON and set up integration testing with Protractor to test the application across real devices using a mobile API gateway such as AWS Device Farm. You will finish the journey by discovering the caveats of mobile-first applications and learn how to master cross-browser complications.
Table of Contents (11 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Getting Started with Responsive Design, Bootstrap, and D3.js
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1. Getting Started with Responsive Design, Bootstrap, and D3.js
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What is Responsive Design?
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Bootstrap – a popular mobile first CSS framework
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Vector graphics in the browser with SVG
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Creating graphics with D3.js
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Summary
2
2. Creating a Bar Chart Using D3.js and SVG
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2. Creating a Bar Chart Using D3.js and SVG
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Getting started with D3.js
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Drawing shapes with D3
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Creating Scales and Axis
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A simple bar chart
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Summary
3
3. Loading, Filtering, and Grouping Data
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3. Loading, Filtering, and Grouping Data
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Preprocessing data
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Loading and parsing remote data
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Grouping data
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Summary
4
4. Making the Chart Responsive Using Bootstrap and Media Queries
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4. Making the Chart Responsive Using Bootstrap and Media Queries
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Units and lengths in the browser
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Responsive charts
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Using Bootstrap's Media Queries
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Summary
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5. Building Responsive Interactions
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5. Building Responsive Interactions
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Using an event system
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Panning and zooming
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Summary
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6. Designing Transitions and Animations
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6. Designing Transitions and Animations
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Is there a web standard for animations?
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Creating animations with JavaScript
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Transitions
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Shape tweens
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Summary
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7. Creating Maps and Cartographic Visualizations Using GeoJSON
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7. Creating Maps and Cartographic Visualizations Using GeoJSON
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Overview of cartographic visualizations
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Data representation for topology and geographic features
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Maps and projections
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Helpful tools for creating maps in D3
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Types of geographic visualization
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Summary
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8. Testing Responsive Visualizations
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8. Testing Responsive Visualizations
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A guide on testing visualizations
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Manual testing and debugging
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Automated testing and Continuous Integration
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A testing strategy for visualizations
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Summary
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9. Solving Cross-Browser Issues
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9. Solving Cross-Browser Issues
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A solution to cross-browser compatibility issues
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Cross-browser Media Queries
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Cross-browser SVG features
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Handle touch and mouse events with ease
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Summary
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Index
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Index

Preprocessing data

In this chapter, you will learn about preprocessing and that it is an important step when you deal with real-world data. If we want to design a robust visualization that can handle different remote data sources, we need to make sure we process the data beforehand. Datasets can have outliers, can be noisy, can have different representations, can have nested objects, can be flat, and so on. You can see that this list is very long.

Thus, whenever we deal with real data, we need to process it before using it in a visualization; this step is called preprocessing.

Filtering data to remove outliers

As a first preprocessing step, we will look at filters. Filters are array operators that return an array containing a subset of the original elements. In the following figure, we see an example of such an operation:

Filtering data to remove outliers

Filtering a dataset

Let's try an example. We load the following array from a remote data source:

var data = [
  {x: 1, y: 6},
  {x: 2, y: undefined},
  {x: 3, y: 4},
...
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Learning Responsive Data Visualization
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