How do you turn raw, unprocessed, or malformed data into dynamic, interactive web visualizations? In this practical book, author Kyran Dale shows data scientists and analysts--as well as Python and JavaScript developers--how to create the ideal toolchain for the job.

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.

Jul 22, 2016 · 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 ...

Jun 20, 2023 · Data visualization with Python and Javascript : scrape, clean, explore & transform your data by Dale, Kyran, author

This repo contains the code to accompany the O'Reilly book Data Visualisation with Python and JavaScript. It's currently being refined, prior to the book's release in early July 2016.

Jun 30, 2016 · 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...

Mar 25, 2016 · With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript librariesâ??including Scrapy, Matplotlib, Pandas, Flask, and D3â??for crafting engaging, browser-based visualizations.

Although the Data Visualization Book suggests using Python 2, Jonathan recommends using Python 3.7 or later, in order to take advantage of the latest features. There were major changes between versions 2 and 3 that make 3.x not backwards compatible with 2.x.

With Plotly in Python, users can produce interactive visualizations using a few simple commands, which enhances both productivity and creativity in data analysis. Similarly, Plotly.js, the JavaScript counterpart, offers powerful tools for web-based applications, allowing developers to create responsive and engaging dashboards.

This book aims to get you up to speed with what is, in my opinion, the most powerful data visualization stack going: Python and JavaScript. You’ll learn enough about big libraries like Pandas and D3 to start crafting your own web data visualizations and refining your own toolchain.