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Learning R Programming

You're reading from   Learning R Programming Language, tools, and practical techniques

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Product type Paperback
Published in Oct 2016
Publisher Packt
ISBN-13 9781785889776
Length 582 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Kun Ren Kun Ren
Author Profile Icon Kun Ren
Kun Ren
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Toc

Table of Contents (16) Chapters Close

Preface 1. Quick Start FREE CHAPTER 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...

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