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Data Visualization with Python and JavaScript.azw3下载

  • 更新:2024-07-28 19:10:56
  • 大小:10.11MB
  • 推荐:★★★★★
  • 来源:网友上传分享
  • 类别:Python - 后端
  • 格式:AZW3

资源介绍

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, browser-based visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s table-based list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own web-based data visualizations—and know either Python or JavaScript— this is the book for you. Learn how to manipulate data with Python Understand the commonalities between Python and JavaScript Extract information from websites by using Python’s web-scraping tools, BeautifulSoup and Scrapy Clean and explore data with Python’s Pandas, Matplotlib, and Numpy libraries Serve data and create RESTful web APIs with Python’s Flask framework Create engaging, interactive web visualizations with JavaScript’s D3 library Table of Contents Chapter 1 Development Setup Chapter 2 A Language-Learning Bridge Between Python and JavaScript Chapter 3 Reading and Writing Data with Python Chapter 4 Webdev 101 Chapter 5 Getting Data off the Web with Python Chapter 6 Development Setup Chapter 7 A Language-Learning Bridge Between Python and JavaScript Chapter 8 Reading and Writing Data with Python Chapter 9 Webdev 101 Chapter 10 Getting Data off the Web with Python Chapter 11 Heavyweight Scraping with Scrapy Chapter 12 Introduction to NumPy Chapter 13 Introduction to Pandas Chapter 14 Cleaning Data with Pandas Chapter 15 Visualizing Data with Matplotlib Chapter 16 Exploring Data with Pandas Chapter 17 Delivering the Data Chapter 18 RESTful Data with Flask Chapter 19 Imagining a Nobel Visualization Chapter 20 Building a Visualization Chapter 21 Introducing D3—The Story of a Bar Chart Chapter 22 Visualizing Individual Prizes Chapter 23 Mapping with D3 Chapter 24 Visualizing Individual Winners Chapter 25 The Menu Bar Chapter 26 Conclusion