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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
Author Profile Icon Tony Fischetti
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

R scripting

The absolute first thing you should know about standard R workflows is that programs are not generally written directly at the interactive R interpreter. Instead, R programs are usually written in a text file (with an .r or .R file extension). These are usually referred to as R scripts. When these scripts are completed, the commands in this text file are usually executed all at once - we'll get to see how, soon. During development of the script, however, the programmer usually executes portions of the script interactively to get feedback and confirm proper behavior. This interactive component to R scripting allows for building each command or function iteratively.

I've known some serious R programmers who copy and paste from their favorite text editor into an interactive R session to achieve this effect. To most people, particularly beginners, the better...

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