D3 Data-Driven Documents Pocket Primer
Pocket Primer Series Read Description

D3 Data-Driven Documents Pocket Primer

Oswald Campesato
Paperback
July 2015
9781938549656
More details
  • Publisher
    Mercury Learning and Information
  • Published
    29th July 2015
  • ISBN 9781938549656
  • Language English
  • Pages 200 pp.
  • Size 6" x 9"
$27.95
Add to Cart
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July 2015
9781683922742
More details
  • Publisher
    Mercury Learning and Information
  • Published
    29th July 2015
  • ISBN 9781683922742
  • Language English
  • Pages 200 pp.
  • Size 6" x 9"
$74.95
E-Book

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July 2015
9781942270690
More details
  • Publisher
    Mercury Learning and Information
  • Published
    29th July 2015
  • ISBN 9781942270690
  • Language English
  • Pages 200 pp.
  • Size 6" x 9"
$27.95
Add to Cart

As part of the Pocket Primer series, this book provides an overview of the major aspects and the source code to use D3. This Pocket Primer is primarily for self-directed learners who want to learn D3 and serves as a starting point for deeper exploration of its programming.

Features:

• Includes a companion disc with appendices, source code, and figures
• Contains material devoted to D3 on mobile devices, using D3 with Ajax, HTML5 Web Sockets, NodeJS, and covers D3 application programming interfaces and other toolkits
• Provides a solid introduction to D3 via complete code samples

eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at info@merclearning.com.

1) Introduction to D3
2) Arrays, Mouse Events and Animation Effects
3) Working with Bar Charts in D3
4) Other Chart Types and Data Formats
5) SVG Essentials
6) Introduction to CSS3 Graphics and Animation
7) D3 with CSS3, SVG and HTML5 Canvas
8) D3 with Ajax, HTML5 Web Sockets, and NodeJS
9) Miscellaneous D3 Application Programming Interfaces and Other Toolkits
10) HTML5 Mobile Applications on Android and iOS
On the CD-ROM.
Index.

Oswald Campesato

Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).