Book Image

Learning R Programming

By : Kun Ren
Book Image

Learning R Programming

By: Kun Ren

Overview of this book

R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset. Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques.
Table of Contents (21 chapters)
Learning R Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

Summary


In this chapter, you learned how to work basic objects by demonstrating the use of built-in functions. They are the vocabulary of R in practice. You learned some basic functions to test and get object types and to access and reshape data dimensions. You learned about a number of logical operators and functions to filter data.

To work with numeric data structures, you learned basic math functions, built-in numeric methods to find roots and do calculus, and some statistical functions to perform random sampling and make summaries of data. You also understood the apply-family functions that make it easier to iterate and collect results.

Another important category of data is string, which is represented by character vectors. In the next chapter, you will learn string-manipulation techniques to facilitate text analysis.