Data Visualization With Python and Javascript : Scrape, Clean, Explore, and Transform Your Data

Dale, Kyran

ISBN 10: 1098111877 / ISBN 13: 9781098111878

Edité par O'Reilly Media, 2023

A propos de cet article

N° de réf. du vendeur 44547033-n

Détails bibliographiques

Titre : Data Visualization With Python and ...

Éditeur : O'Reilly Media

Date d'édition : 2023

Reliure : Couverture souple

Etat : New

Edition : 2ème Édition

A propos de ce titre

Synopsis :

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. 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 JavaScript libraries.

Python provides accessible, powerful, and mature libraries for scraping, cleaning, and processing data. And while JavaScript 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

À propos de l?auteur:

Kyran Dale is a jobbing programmer, ex-research scientist, recreational hacker, independent researcher, occasional entrepreneur, cross-country runner and improving jazz pianist. During 15 odd years as a research scientist he hacked a lot of code, learned a lot of libraries and settled on some favorite tools. These days he finds Python, JavaScript, and a little C++ goes a long way to solving most problems out there. He specializes in fast-prototyping and feasibility studies, with an algorithmic bent but is happy to just build cool things.