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Practical Web Scraping for Data Science : Best Practices and Examples with Python by Bart Baesens and Seppe vanden Broucke (2018, Trade Paperback)
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Practical Web Scraping for Data Science: Best Practices and Examples with Python (Paperback or Softback). Your source for quality books at reduced prices. ISBN: 9781484235812. Publication Date: 6/10/2018.
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About this product
Product Identifiers
PublisherApress L. P.
ISBN-101484235819
ISBN-139781484235812
eBay Product ID (ePID)242951408
Product Key Features
Number of PagesXvi, 306 Pages
Publication NamePractical Web Scraping for Data Science : Best Practices and Examples with Python
LanguageEnglish
Publication Year2018
SubjectProbability & Statistics / General, Databases / General, Programming Languages / Python
TypeTextbook
Subject AreaMathematics, Computers
AuthorBart Baesens, Seppe Vanden Broucke
FormatTrade Paperback
Dimensions
Item Weight215.3 Oz
Item Length10 in
Item Width7 in
Additional Product Features
Number of Volumes1 vol.
IllustratedYes
Table Of ContentPart I: Web Scraping Basics.- 1. Introduction.- 2. The Web Speaks HTTP.- 3. Stirring the HTML and CSS Soup.- Part II: Advanced Web Scraping.- 4. Delving Deeper in HTTP.- 5. Dealing with JavaScript.- 6. From Web Scraping to Web Crawling.- Part III: Managerial Concerns and Best Practices.- 7. Managerial and Legal Concerns.- 8. Closing Topics.- 9. Examples.
SynopsisThis book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full understanding. The authors recommend web scraping as a powerful tool for any data scientist's arsenal, as many data science projects start by obtaining an appropriate data set. Starting with a brief overview on scraping and real-life use cases, the authors explore the core concepts of HTTP, HTML, and CSS to provide a solid foundation. Along with a quick Python primer, they cover Selenium for JavaScript-heavy sites, and web crawling in detail. The book finishes with a recap of best practices and a collection of examples that bring together everything you've learned and illustrate various data science use cases. What You'll Learn Leverage well-established best practices and commonly-used Python packages Handle today's web, including JavaScript, cookies, and common web scraping mitigation techniques Understand the managerial and legal concerns regarding web scraping Who This Book is For A data science oriented audience that is probably already familiar with Python or another programming language or analytical toolkit (R, SAS, SPSS, etc). Students or instructors in university courses may also benefit. Readers unfamiliar with Python will appreciate a quick Python primer in chapter 1 to catch up with the basics and provide pointers to other guides as well.
LC Classification NumberQA76.73.P98
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