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Learning R Programming

You're reading from   Learning R Programming Language, tools, and practical techniques

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Product type Paperback
Published in Oct 2016
Publisher Packt
ISBN-13 9781785889776
Length 582 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Kun Ren Kun Ren
Author Profile Icon Kun Ren
Kun Ren
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Toc

Table of Contents (16) Chapters Close

Preface 1. Quick Start FREE CHAPTER 2. Basic Objects 3. Managing Your Workspace 4. Basic Expressions 5. Working with Basic Objects 6. Working with Strings 7. Working with Data 8. Inside R 9. Metaprogramming 10. Object-Oriented Programming 11. Working with Databases 12. Data Manipulation 13. High-Performance Computing 14. Web Scraping 15. Boosting Productivity

Analysing HTML code and extracting data

In the previous sections, we learned the basics of HTML, CSS, and XPath. To scrape real-world web pages, the problem now becomesa question of writing the proper CSS or XPath selectors. In this section, we introduce some simple ways to figure out working selectors.

Suppose we want to scrape all available R packages at https://cran.rstudio.com/web/packages/available_packages_by_name.html. The web page looks simple. To figure out the selector expression, right-click on the table and select Inspect Element in the context menu, which should be available in most modern web browsers:

Analysing HTML code and extracting data

Then the inspector panel shows up and we can see the underlying HTML of the web page. In Firefox and Chrome, the selected node is highlighted so it can be located more easily:

Analysing HTML code and extracting data

The HTML contains a unique <table> so we can directly use table to select it and use html_table() to extract it out as a data frame:

page <- read_html("https://cran.rstudio.com/web/packages...
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