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Learning R Programming

You're reading from  Learning R Programming

Product type Book
Published in Oct 2016
Publisher Packt
ISBN-13 9781785889776
Pages 582 pages
Edition 1st Edition
Languages
Author (1):
Kun Ren Kun Ren
Profile icon Kun Ren

Table of Contents (21) Chapters

Learning R Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Quick Start 2. Basic Objects 3. Managing Your Workspace 4. Basic Expressions 5. Working with Basic Objects 6. Working with Strings 7. Working with Data 8. Inside R 9. Metaprogramming 10. Object-Oriented Programming 11. Working with Databases 12. Data Manipulation 13. High-Performance Computing 14. Web Scraping 15. Boosting Productivity

Summary


In this chapter, you learned how to read and write data in various formats, how to visualize data with plot functions, and how to apply basic models on the data. Now, you know the basic tools and interface of working with data. However, you may learn more data analysis tools from other sources.

For statistical and econometric models, I recommend that you read not only text books of statistics and econometrics but also R books that focus on statistical analysis. For machine learning models such as artificial neural networks, support vector machines, and random forests, I recommend that you read machine learning books and go to CRAN Task View: Machine Learning & Statistical Learning (https://cran.r-project.org/web/views/MachineLearning.html).

Since this book is focused on the R programming language rather than any specific model, we will continue our journey in the next chapter by going deeper into R. If you are not familiar with how R code works, you can hardly predict what will...

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