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 access different types of databases from R. We introduced the basic usage of relational databases such as SQLite and non-relational databases such as MongoDB and Redis. With the understanding of major differences in their functionality and feature sets, we need to choose an appropriate database to work with in our projects according to our purpose and needs.

In many data-related projects, data storage and data importing are the initial steps, but data cleaning and data manipulation cost most of the time. In the next chapter, we will move on to data-manipulation techniques. You will learn about a number of packages that are specially tailored for handy but powerful data manipulation. To better work with these packages, we'll need a better understanding of how they work, which requires the sound knowledge introduced in the previous chapters.