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Data Analysis with R, Second Edition - Second Edition

You're reading from  Data Analysis with R, Second Edition - Second Edition

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Pages 570 pages
Edition 2nd Edition
Languages

Table of Contents (24) Chapters

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. RefresheR 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 1. Other Books You May Enjoy Index

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 to transform the textual representation of raw data. Regular expressions are—at once—the plural form of a single regular expression, a powerful tool, an idea, and a language for describing patterns in text.

You might ask yourself: How do I work with this? You might first...

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