Data Visualization With Python & JavaScript

by Kyran Dale

Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s table-based list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own web-based data visualizations—and know either Python or JavaScript— this is the book for you.

Genres: Programming, Coding, Technology, Nonfiction, Technical, Reference

582 pages, Paperback

First published March 25, 2016

Reviews

[Ahmed · Rating 4 out of 5]

This is a unique book in the world of data, as it shows the full workflow of a modern data analyst -- from data scraping to clean up to storage to web visualization. It is also the first book I've seen that bridges the gap between front-end web developers familiar with HTML/CSS/Javascript and traditional Python data analysts more used to libraries like NumPy and Pandas. For this reason alone it's worth reading.

The one drawback to the text is the author's code base on Github isn't exactly that well organized -- making it hard to run the code for each chapter. That said it offers very useful "big picture" context for anyone looking to dive deeper into modern day data visualization.

[Eric Mesa · Rating 4 out of 5]

While a book about web technologies is undoubtablely going to get out of date (especially when Javascript is involved), I would definitely recommend this book if you want to do some data visualization either as part of your job or for an undergrad, grad, or PhD project. While I would probably use FastAPI rather than Flask, I heard recently that the Javascript library the author uses, D3, is still one of the best in class libraries for this kind of work.

The author guides you through the process by building a website to visualize Nobel Prize winners. The early steps where the author teaches you how to obtain and how to clean data are very important and, to some extent, will never go out of style. The same can be said of the author's section explaining how to select the best visualizations.

It's very well written and I highly recommend.

[Delhi Irc]

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Accession No: DL029947