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Data Visualization with Python and JavaScript - 2nd Edition by  Kyran Dale (Paperback) - 1 of 1

Data Visualization with Python and JavaScript - 2nd Edition by Kyran Dale (Paperback)

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About this item

Highlights

  • How do you turn raw, unprocessed, or malformed data into dynamic, interactive web visualizations?
  • Author(s): Kyran Dale
  • 566 Pages
  • Computers + Internet,

Description



About the Book



"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."--Publisher marketing.



Book 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
Dimensions (Overall): 9.1 Inches (H) x 6.9 Inches (W) x 1.2 Inches (D)
Weight: 1.98 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 566
Genre: Computers + Internet
Publisher: O'Reilly Media
Format: Paperback
Author: Kyran Dale
Language: English
Street Date: January 17, 2023
TCIN: 86890157
UPC: 9781098111878
Item Number (DPCI): 247-14-9778
Origin: Made in the USA or Imported
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Shipping details

Estimated ship dimensions: 1.2 inches length x 6.9 inches width x 9.1 inches height
Estimated ship weight: 1.98 pounds
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Q: Does the book include practical examples?

submitted by AI Shopping Assistant - 3 days ago
  • A: Yes, it provides engaging examples and best practices for leveraging Python and JavaScript in data visualization.

    submitted byAI Shopping Assistant - 3 days ago
    Ai generated

Q: What libraries are recommended for creating web visualizations?

submitted by AI Shopping Assistant - 3 days ago
  • A: Recommended libraries include Plotly, D3, and Leaflet for creating interactive web visualizations.

    submitted byAI Shopping Assistant - 3 days ago
    Ai generated

Q: What programming languages are covered in this book?

submitted by AI Shopping Assistant - 3 days ago
  • A: The book covers Python and JavaScript, focusing on their use in data visualization.

    submitted byAI Shopping Assistant - 3 days ago
    Ai generated

Q: What types of data processing techniques are discussed?

submitted by AI Shopping Assistant - 3 days ago
  • A: It discusses scraping, cleaning, and processing data using Python's libraries like pandas and NumPy.

    submitted byAI Shopping Assistant - 3 days ago
    Ai generated

Q: What is the target audience for this book?

submitted by AI Shopping Assistant - 3 days ago
  • A: The book is aimed at data scientists, analysts, and developers familiar with Python and JavaScript.

    submitted byAI Shopping Assistant - 3 days ago
    Ai generated

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