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You're reading from  Data Visualization with D3 and AngularJS

Product typeBook
Published inApr 2015
Reading LevelIntermediate
Publisher
ISBN-139781784398484
Edition1st Edition
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Authors (2):
Erik Hanchett
Erik Hanchett
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Erik Hanchett

Erik Hanchett is a software developer, blogger, and perpetual student who has been writing code for over 10 years. He currently resides in Reno Nevada, with his wife and two kids. He blogs about software development at ProgramWithErik.com. I would like to thank my wife Susan for helping me stay motivated. My friend F.B. Woods for all his help on the English language and Dr. Bret Simmons for teaching me the value of a personal brand. I would also like to thank all my friends and family that encouraged me along the way.
Read more about Erik Hanchett

Christoph Körner
Christoph Körner
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Christoph Körner

Christoph Körner previously worked as a cloud solution architect for Microsoft, specializing in Azure-based big data and machine learning solutions, where he was responsible for designing end-to-end machine learning and data science platforms. He currently works for a large cloud provider on highly scalable distributed in-memory database services. Christoph has authored four books: Deep Learning in the Browser for Bleeding Edge Press, as well as Mastering Azure Machine Learning (first edition), Learning Responsive Data Visualization, and Data Visualization with D3 and AngularJS for Packt Publishing.
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Summary


In this chapter, you learned various interaction techniques to enhance the usability of charts and to make them fully accessible.

First, we saw the concept of event listeners and events in JavaScript and how they are used with D3.js. We used the .on(event, callback) method to attach event callbacks directly on selection of elements. All the details about the triggered event are available in the d3.event object. When dealing with relative coordinates, the d3.mouse(container) function becomes quite handy because it returns the mouse coordinates relative to the container.

Then, we implemented a simple cursor for the chart directive that strictly follows the mouse position. We can easily compute the values on the axis by using the scale.invert() method. In the second cursor implementation, we also needed to compute the nearest value of the dataset to our current position on the axis. To achieve this, we used the d3.bisector() method with an accessor for the x value of the dataset values...

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Data Visualization with D3 and AngularJS
Published in: Apr 2015Publisher: ISBN-13: 9781784398484

Authors (2)

author image
Erik Hanchett

Erik Hanchett is a software developer, blogger, and perpetual student who has been writing code for over 10 years. He currently resides in Reno Nevada, with his wife and two kids. He blogs about software development at ProgramWithErik.com. I would like to thank my wife Susan for helping me stay motivated. My friend F.B. Woods for all his help on the English language and Dr. Bret Simmons for teaching me the value of a personal brand. I would also like to thank all my friends and family that encouraged me along the way.
Read more about Erik Hanchett

author image
Christoph Körner

Christoph Körner previously worked as a cloud solution architect for Microsoft, specializing in Azure-based big data and machine learning solutions, where he was responsible for designing end-to-end machine learning and data science platforms. He currently works for a large cloud provider on highly scalable distributed in-memory database services. Christoph has authored four books: Deep Learning in the Browser for Bleeding Edge Press, as well as Mastering Azure Machine Learning (first edition), Learning Responsive Data Visualization, and Data Visualization with D3 and AngularJS for Packt Publishing.
Read more about Christoph Körner