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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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Allan Visochek Allan Visochek
Author Profile Icon Allan Visochek
Allan Visochek
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Table of Contents (10) Chapters Close

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

Introducting regular expressions


A regular expression, or regex for short, is simply a sequence of characters that specifies a certain search pattern. Regular expressions have been around for quite a while and are a field of computer science in and of themselves.

In Python, regular expression operations are handled using Python's built in re module. In this section, I will walk through the basics of creating regular expressions and using them to  You can implement a regular expression with the following steps:

  1. Specify a pattern string.
  2. Compile the pattern string to a regular expression object.
  3. Use the regular expression object to search a string for the pattern.
  4. Optional: Extract the matched pattern from the string.

Writing and using a regular expression

The first step to creating a regular expression in Python is to import the re module:

import re

Python regular expressions are expressed using pattern strings, which are strings that specify the desired search pattern. In its simplest form, a pattern...

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