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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
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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

Summary


In this chapter, you've learned how to implement regular expressions in Python. In addition, you've learned a process for identifying  patterns and building appropriate pattern strings to recognizing particular patterns. To summarize, the first step to approaching a pattern recognition problem is to observe the data and Identify a pattern that can be represented with a regular expression. Once a pattern has been identified, the next step is to build a pattern string to capture the data and verify that the pattern string works well and as expected. Finally, the regular expression should be implemented expression to either clean, extract or filter text data.

This concludes the initial section of the book dealing with a generalized programming approach to data wrangling. In the next two chapters, I will take on a more formulated approach to data wrangling.

In the next chapter, Chapter 6, Cleaning Numerical Data - An Introduction to R and RStudio, I will introduce the R programming language...

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