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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

Concepts

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

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Index

Other data formats

One of things that makes R great is the wealth of high-quality add-on packages. As you might expect, there are many of these add-on packages with the ability to import data in a multitude of other formats. Whether it's an arcane markup language, a proprietary binary file, Excel spreadsheet, and so on, there is almost certainly an R package out there for you to handle it. But how do you find them?

One way is to browse the community maintained CRAN Task Views (https://cran.r-project.org/web/views/). A Task View is a way to browse for packages related to a particular topic, domain, or special interest. The germane Task View, here, is the Web Technologies Task View (https://cran.r-project.org/web/views/WebTechnologies.html). You'll notice that jsonlite and the XML package are mentioned on the first page.

The easiest way to discover these packages, though, is through your favorite web browser. For example, if you are looking for a package to import YAML data (yet another data...

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