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Practical Data Wrangling

You're reading from   Practical Data Wrangling Expert techniques for transforming your raw data into a valuable source for analytics

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787286139
Length 204 pages
Edition 1st Edition
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Author (1):
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 Visochek Visochek
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Visochek
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Table of Contents (16) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Programming with Data FREE CHAPTER 2. Introduction to Programming in Python 3. Reading, Exploring, and Modifying Data - Part I 4. Reading, Exploring, and Modifying Data - Part II 5. Manipulating Text Data - An Introduction to Regular Expressions 6. Cleaning Numerical Data - An Introduction to R and RStudio 7. Simplifying Data Manipulation with dplyr 8. Getting Data from the Web 9. Working with Large Datasets

Understanding XML


XML, like JSON, is a hierarchical data format that allows a nested data structure. If you have worked with HTML before, you might be familiar with the general structure and syntax of XML, which HTML is based on.

An XML dataset consists of a nested tree of elements where each element may contain text with a particular value, another element or a collection of additional elements. Each element in the tree may also contain any number of attributes which describe the element.

Each element is represented by an opening tag and a closing tag. An opening tag indicates the beginning of an XML element. It is written by writing the name of the tag inside angle brackets. The following is what an XML opening tag looks like:

<tagname>

A closing tag follows the opening tag and indicates the end of an element. It is written by specifying the name of a tag inside angle brackets with a / before the name. The following is what an XML closing tag looks like:

</tagname>

Note

In other parts...

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