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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

Leave a review - let other readers know what you think

Index

Exercises

Write a function called dt_table similar to the table function in base R. The arguments will be a data.table, and a string specifying a column name. Do the same thing for tibbles and call it dp_table.
Read some of the documentation for data.table and dplyr/tidyr . Of the former, learn about .SD and .SDcols. Of the later, learn about the separate_ functions. These are life-savers.
Learn about some of the other popular packages of the tidyverse. What do all of these have in common, again?
Describe the four major voting bloc "cleavages" defined by Lipset and Rokkan in Party systems and voter alignments. Since its publication in 1967, have any other potential cleavage points emerged in your nation or state? How do these cleavages manifest themselves in political party differences?

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