Data Visualization with Python and JavaScript e-bog
436,85 DKK
(inkl. moms 546,06 DKK)
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...
E-bog
436,85 DKK
Forlag
O'Reilly Media
Udgivet
7 december 2022
Længde
568 sider
Genrer
Computer programming / software engineering
Sprog
English
Format
epub
Beskyttelse
LCP
ISBN
9781098111823
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 SoupClean and process data using Python's heavyweight data processing libraries within the NumPy ecosystem: Jupyter notebooks with pandas+Matplotlib+SeabornDeliver the data to a browser with static files or by using Flask, the lightweight Python server, and a RESTful APIPick up enough web development skills (HTML, CSS, JS) to get your visualized data on the webUse the data you've mined and refined to create web charts and visualizations with Plotly, D3, Leaflet, and other libraries