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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

Online repositories

Look back to the Web Technologies Task View we talked about in the previous section. There are a tremendous amount of R packages specifically designed to import data directly from specialized sources on the web. Among these are packages to search for and retrieve the full text of academic articles in the Public Library of Science journals (rplos), to search for and download the full text of Wikipedia articles (WikipediR), to download data about Berlin from the German government (BerlinData), to interface with the Chromosome Counts Database (chromer), to download historical financial data (quantmod), and to access the information in the PubChem chemistry database (rpubchem).

These examples notwithstanding, given that there are many hundreds of immense repositories of public data, it is far too much to expect the R community to have a package specially built for every single one. Luckily, with the ability to handle many different data formats under our belt, we can just...

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