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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

Extracting data from web pages using CSS selectors

In R, the easiest-to-use package for web scraping is rvest. Run the following code to install the package from CRAN:

install.packages("rvest") 

First, we load the package and use read_html() to read data/single-table.html and try to extract the table from the web page:

library(rvest) 
## Loading required package: xml2 
single_table_page <- read_html("data/single-table.html") 
single_table_page 
## {xml_document} 
## <html> 
## [1] <head>\n  <title>Single table</title>\n</head> 
## [2] <body>\n  <p>The following is a table</p>\n  <table i ... 

Note that single_table_page is a parsed HTML document, which is a nested data structure of HTML nodes.

A typical process for scraping information from such a web page using rvest functions is: First, locate the HTML nodes from which we need to extract data. Then, use either the CSS selector or XPath expression to filter the HTML...

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