Data Visualization with Python and JavaScript: Scrape, Clean, Explore, and Transform Your Data

by Kyran Dale

In a world that increasingly expects more than pre-rendered, static images, Python and Javascript are the perfect complement for turning data into rich, interactive visualizations. Developers need to know how to turn raw, unprocessed data often "dirty" or malformed into dynamic web visualizations. Author Kyran Dale teaches you how to leverage the power of best-of-breed Python and Javascript libraries to do so, using engaging examples and stressing hard-earned best-practices.

You'll learn how to: Get data programmatically, using scraping tools or web APIsClean and process data using Python's heavyweight data-processing librariesDeliver data to a browser using a lightweight Python server (Flask)Receive data and use it to create a web visualization, using D3, Canvas, or WebGL"

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

863 pages, Kindle Edition

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]

Location: ND6 IRC
Accession No: DL029947