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Data Visualization with Python and JavaScript : Scrape, Clean, Explore and Transform Your Data

Data Visualization with Python and JavaScript : Scrape, Clean, Explore and Transform Your Data

Data Visualization with Python and JavaScript : Scrape, Clean, Explore and
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Data Visualization with Python and JavaScript : Scrape, Clean, Explore and Transform Your Data Paperback - 2016

by Dale, Kyran

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O'Reilly Media, Incorporated. Used - Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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From the publisher

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

About the author

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 favourite 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.

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