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Data Visualization with D3.js Cookbook

You're reading from   Data Visualization with D3.js Cookbook Turn your digital data into dynamic graphics with this exciting, leading-edge cookbook. Packed with recipes and practical guidance it will quickly make you a proficient user of the D3 JavaScript library.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781782162162
Length 338 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Nick Zhu Nick Zhu
Author Profile Icon Nick Zhu
Nick Zhu
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with D3.js FREE CHAPTER 2. Be Selective 3. Dealing with Data 4. Tipping the Scales 5. Playing with Axes 6. Transition with Style 7. Getting into Shape 8. Chart Them Up 9. Lay Them Out 10. Interacting with your Visualization 11. Using Force 12. Know your Map 13. Test Drive your Visualization A. Building Interactive Analytics in Minutes Index

Using the time scale

Often, we perform analysis on a data set that is time- and date-sensitive, therefore, D3 provides a built-in time scale to help perform this type of mapping. In this recipe, we will learn how to use D3 time scale.

Getting Ready

Open your local copy of the following file in your web browser:

https://github.com/NickQiZhu/d3-cookbook/blob/master/src/chapter4/time-scale.html

How to do it...

First, let's take a look at the following code example:

<div id="time" class="clear">
    <span>Linear Time Progression<br></span>
    <span>Mapping [01/01/2013, 12/31/2013] to [0, 900]<br></span>
</div>

<script type="text/javascript">
    var start = new Date(2013, 0, 1), // <-A 
        end = new Date(2013, 11, 31),
        range = [0, 1200],
        time = d3.time.scale().domain([start, end]) // <-B
            .rangeRound(range), // <-C
        max = 12,
        data = [];

    for (var...
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