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

Matrix


A matrix is a vector represented and accessible in two dimensions. Therefore, what applies to vectors is most likely to apply to a matrix. For example, each type of vector (for example, numeric vector or logical vectors) has its matrix version, that is, there are numeric matrices, logical matrices, and so on.

Creating a matrix

We can call matrix() to create a matrix from a vector by setting up one of its two dimensions:

matrix(c(1, 2, 3, 2, 3, 4, 3, 4, 5), ncol = 3)
##      [,1] [,2] [,3]
## [1,]   1    2    3
## [2,]   2    3    4
## [3,]   3    4    5

By specifying ncol = 3, we mean that the provided vector should be regarded as a matrix with 3 columns (and 3 rows automatically). You may feel the original vector is not as straightforward as its representation. To make the code more user-friendly, we can write the vector in multiple lines:

matrix(c(1, 2, 3,  4, 5, 6,  7, 8, 9), nrow = 3, byrow = FALSE)
##     [,1] [,2] [,3]
## [1,]  1    4    7
## [2,]  2    5    8
## [3,] ...