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 about a number of built-in functions for manipulating character vectors and converting between date/time objects and their string representations. You also learned about the basic idea of regular expressions, a very powerful tool to check and filter string data and extract information from raw texts.

With the vocabulary we built in this and previous chapters, we are now able to work with basic data structures. In the next chapter, you will learn about some tools and techniques to work with data. We will get started with reading and writing simple data files, producing graphics of various types, applying basic statistical analysis and data-mining models on simple datasets, and using numeric methods to solve root-solving and optimization problems.