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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
Languages
Tools
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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

Summary


In summary, the dplyr package builds on the R language to make an even more expressive and concise language for data manipulation. In this chapter, the estimate for the total road length in 2011 is the same as in the previous chapter, but the code used to get there is more concise and easier to follow. This can mean less time spent on navigating numerous processing steps and variable names, and more time spent organizing the data.

This concludes the second section of this book, which dealt with a more formulated approach to data wrangling. If you've read up to this point, congratulations! You now have a broad understanding of the tools, approaches, and skills involved in manipulating data.

In the remaining part of the book, I will discuss advanced methods for retrieving and storing data. First, large sources of data are often made available through web interfaces called APIs. I will discuss how to use APIs to retrieve data in the next chapter.

Second, working with large amounts of data...

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