Book Image

Modern R Programming Cookbook

By : Jaynal Abedin
Book Image

Modern R Programming Cookbook

By: Jaynal Abedin

Overview of this book

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.
Table of Contents (10 chapters)

Using for loop for iterations

The most convenient way to perform iterative operation in R is the use of a for loop. Suppose you are given a dataset with five variables representing five different diseases for 10 people. All your variables are binary. Your task is to calculate the frequency of each variable as well as the cross-frequency of all pair-wise variables. Using a for loop, you can easily complete this task. In this recipe, you will implement a for loop to calculate the disease frequency and the frequency of all pair-wise variables.

Getting ready

Let’s consider you are given the following dataset mat:

mat<-matrix(sample(c(0,1),50,replace = T),nrow = 10,ncol=5)
rownames(mat) <-...