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Data Analysis with R, Second Edition

You're reading from   Data Analysis with R, Second Edition A comprehensive guide to manipulating, analyzing, and visualizing data in R

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Length 570 pages
Edition 2nd Edition
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Author (1):
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Tony Fischetti Tony Fischetti
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Tony Fischetti
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Table of Contents (19) Chapters Close

Preface 1. RefresheR FREE CHAPTER 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data To Reason About The World 6. Testing Hypotheses 7. Bayesian Methods 8. The Bootstrap 9. Predicting Continuous Variables 10. Predicting Categorical Variables 11. Predicting Changes with Time 12. Sources of Data 13. Dealing with Missing Data 14. Dealing with Messy Data 15. Dealing with Large Data 16. Working with Popular R Packages 17. Reproducibility and Best Practices 18. Other Books You May Enjoy

Regular expressions

Suppose you find that there are commas separating every third digit of the numbers in a numeric column. How would you remove them? Or suppose you needed to strip a currency symbol from values in columns that hold monetary values so that you can compute with them as numbers. These, and vastly more complicated text transformations, can be performed using a most powerful tool, regular expressions.

What are regular expressions?

Regular expressions (or regexes, as it is commonly abbreviated) is a formal grammar for describing patterns in text/strings. In general purpose programming languages, it is often used for things like verifying user input, but it is most often used in the context of statistical programming...

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