Book Image

Practical Data Wrangling

By : Allan Visochek
Book Image

Practical Data Wrangling

By: Allan Visochek

Overview of this book

Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them. You’ll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You’ll work with different data structures and acquire and parse data from various locations. You’ll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases. The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the end of the book, you’ll have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way.
Table of Contents (16 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

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...