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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

Product type Paperback

Published in Mar 2018

Publisher Packt

ISBN-13 9781788393720

Length 570 pages

Edition 2nd Edition

Languages

R

Tools

ggplot

Concepts

Data Analysis

Author (1):

Tony Fischetti

View More author details

Table of Contents (19) Chapters

Preface

1. RefresheR

2. The Shape of Data FREE CHAPTER

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

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Working with Popular R Packages

In this book thus far, we’ve used over 30 packages with functionalities ranging from data visualization to MCMC to connecting R to other languages. In this chapter, we will be focusing on a few very popular R packages that we haven't mentioned before, or that we only mentioned in passing. These packages—namely data.table, dplyr, and tidyr—are very widely used and revered in R circles.

These packages, which stress speed of computation and ease of use (at least after an initial learning curve) are essential components to many useRs' workflows. Note, however, that R was an extraordinarily effective and popular tool before these packages came on the scene and even if these packages were to somehow magically disappear from public memory, R would live on. Therefore, this chapter may be thought of as optional material. I...

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