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 jаvascript developers--how to create the ideal toolchain for the job. By providing engaging examples and stressing hard-earned best practices, this guide teaches you how to leverage the power of best-of-breed Python and jаvascript libraries.
Python provides accessible, powerful, and mature libraries for scraping, cleaning, and processing data. And while jаvascript is the best language when it comes to programming web visualizations, its data processing abilities can't compare with Python's. Together, these two languages are a perfect complement for creating a modern web-visualization toolchain. This book gets you started.
You'll learn how to:

Obtain data you need programmatically, using scraping tools or web APIs: Requests, Scrapy, Beautiful Soup

Clean and process data using Python's heavyweight data processing libraries within the NumPy ecosystem: Jupyter notebooks with pandas+Matplotlib+Seaborn

Deliver the data to a browser with static files or by using Flask, the lightweight Python server, and a RESTful API

Pick up enough web development skills (HTML, CSS, JS) to get your visualized data on the web

Use the data you've mined and refined to create web charts and visualizations with Plotly, D3, Leaflet, and other libraries