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

Data frames


A data frame represents a set of data with a number of rows and columns. It looks like a matrix but its columns are not necessarily of the same type. This is consistent with the most commonly seen formats of datasets: each row, or data record, is described by multiple columns of various types.

The following table is an example that can be fully characterized by a data frame.

Name

Gender

Age

Major

Ken

Male

24

Finance

Ashley

Female

25

Statistics

Jennifer

Female

23

Computer Science

Creating a data frame

To create a data frame, we can call data.frame() and supply the data of each column by a vector of the corresponding type:

persons <- data.frame(Name = c("Ken", "Ashley", "Jennifer"),
  Gender = c("Male", "Female", "Female"),
  Age = c(24, 25, 23),
  Major = c("Finance", "Statistics", "Computer Science"))
persons
##   Name     Gender  Age  Major
## 1 Ken      Male    24   Finance
## 2 Ashley   Female  25   Statistics
## 3 Jennifer Female  23   Computer Science...