Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R Web Scraping Quick Start Guide

You're reading from   R Web Scraping Quick Start Guide Techniques and tools to crawl and scrape data from websites

Arrow left icon
Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789138733
Length 114 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Olgun Aydin Olgun Aydin
Author Profile Icon Olgun Aydin
Olgun Aydin
Arrow right icon
View More author details
Toc

Learning about data on the internet

Data is an essential part of any research, whether it be academic, marketing, or scientific . The World Wide Web (WWW) contains all kinds of information from different sources. Some of these are social, financial, security, and academic resources and are accessible via the internet.

People may want to collect and analyse data from multiple websites. These different websites that belong to specific categories display information in different formats. Even with a single website, you may not be able to see all the data at once. The data may be spanned across multiple pages under various sections.

Most websites do not allow you to save a copy of the data to your local storage. The only option is to manually copy and paste the data shown by the website to a local file in your computer. This is a very tedious process that can take lot of time.

Web scraping is a technique by which people can extract data from multiple websites to a single spreadsheet or database so that it becomes easier to analyse or even visualize the data. Web scraping is used to transform unstructured data from the network into a centralized local database.

Well-known companies, including Google, Amazon, Wikipedia, Facebook, and many more, provide APIs (Application Programming Interfaces) that contain object classes that facilitate interaction with variables, data structures, and other software components. In this way, data collection from those websites is fast and can be performed without any web scraping software.

One of the most used features when performing web scraping of the semi-structured of web pages are naturally rooted trees that are labeled. On this trees, the tags represent the appropriate labels for the HTML markup language syntax, and the tree hierarchy represents the different nesting levels of the elements that make up the web page. The display of a web page using an ordered rooted tree labeled with a label is referred to as the DOM (Document Object Model), which is largely edited by the WWW Consortium.

The general idea behind the DOM is to represent HTML web pages via plain text with HTML tags, with custom key words defined in the sign language. This can be interpreted by the browser to represent web-specific items. HTML tags can be placed in a hierarchical structure. In this hierarchy, nodes in the DOM are captured by the document tree that represents the HTML tags. We will take a look at DOM structures while we focus on XPath rules.

You have been reading a chapter from
R Web Scraping Quick Start Guide
Published in: Oct 2018
Publisher: Packt
ISBN-13: 9781789138733
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime