This is the code repository for Modern R Programming Cookbook, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
Chapter 1 does not contain any code.
The code will look like the following:
M1 <- matrix(1:9, nrow=3, ncol= 3, byrow=TRUE)
D1 <- data.frame(x1= c(1,3,2,4,5), x2= c("Cricket", "Football", "Basketball", "Rugby", "Baseball" ))
This book requires the following to be set up:
Base R RStudio IDE Microsoft R Client R tools for Visual Studio PostgreSQL database server
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent