Skip to main content

Exploring Control Structures in R Programming: Learn How to Use While Loops and Statements Like Repeat, Break, Continue, Next and Return to Enhance Your Code!

The Beginner’s Guide to Control Structures (While Loops, Repeat, Break, Continue, Next and Return) in R Programming:

Control structures are an essential aspect of programming in any language, including R. In R, control structures help programmers to define the flow of a program's logic. In addition to if-else statements, switch cases, and for loops, R also supports while loops and statements such as repeat, break, continue, next, and return. This blog post will explain how to use these control structures in R and provide practice material for learners.


While Loop:

The while loop is used to execute a block of code repeatedly as long as the specified condition remains true. The syntax of the while loop in R is as follows:

while (condition) {
  # Execute code as long as the condition is true
}

For example, consider the following code that prints the numbers from 1 to 5 using a while loop:

i <- 1

while (i <= 5) {
  print(i)
  i <- i + 1
}

Output:
[1] 1
[1] 2
[1] 3
[1] 4
[1] 5

Repeat, Break, Continue, Next and Return statements:

The repeat statement is used to execute a block of code repeatedly until a specified condition is met. The syntax of the repeat statement in R is as follows:

repeat {
  # Execute code repeatedly
  if (condition) {
    break # Exit the loop if the condition is true
  }
}

The break statement is used to exit a loop prematurely if a specified condition is met. The syntax of the break statement in R is as follows:

for (i in 1:5) {
  if (i == 3) {
    break # Exit the loop if i is equal to 3
  }
  print(i)
}

The continue statement is used to skip the current iteration of a loop and move on to the next iteration. The syntax of the continue statement in R is as follows:

for (i in 1:5) {
  if (i == 3) {
    continue # Skip the iteration if i is equal to 3
  }
  print(i)
}

The return statement is used to exit a function and return a value. The syntax of the return statement in R is as follows:

my_function <- function(x, y) {
  if (x == y) {
    return("x is equal to y")
  }
  return("x is not equal to y")
}

The next statement in R is used to skip the current iteration of a loop and move on to the next iteration. This statement is typically used in for loops, while loops, and repeat loops to skip over certain iterations based on a specified condition. For example, consider the following code that uses a for loop to print all even numbers from 1 to 10:

for (i in 1:10) {
  if (i %% 2 != 0) {
    next # Skip the iteration if i is odd
  }
  print(i)
}

Output:
[1] 2
[1] 4
[1] 6
[1] 8
[1] 10

In this code, the modulo operator (%%) is used to determine if a number is even or odd. If the number is odd, the next statement is used to skip the current iteration of the loop and move on to the next iteration. As a result, only even numbers are printed to the console.

Practice Material:

Here are a few practice exercises to help you get started:

  • Write a program that calculates the sum of the first 10 natural numbers using a while loop.
  • Write a program that takes a list of numbers as input and returns the sum of all even numbers in the list. Use a repeat loop to prompt the user to enter a number until they enter -1 to break the loop. Use a continue statement to skip odd numbers in the loop.
  • For more practice you should start swirl's lessons in  R Programming. Complete download process of swirl and R Programming is here, click on the link!
  • You can look in to the practice and reading material that is provided in the text book, click here to download the textbook.
  • Lecture slides can be downloaded from here. It would be great if you go through them too.

These practice materials are suitable for you to get hands-on experience with while loops and repeat, break, continue, next, and return statements in R programming. Good luck with your learning!
Labels:

Comments

Post a Comment

Type your comment here.
However, Comments for this blog are held for moderation before they are published to blog.
Thanks!

Popular posts from this blog

Introduction to R Markdown

The Beginner’s Guide to R Markdown! We’ve spent a lot of time getting R and R Studio working, learning about Functionalities of R Studio and R Packages - you are practically an expert at this! There is one major functionality of R/R Studio that we would be remiss to not include in your introduction to R -  Markdown! Functionalities in R Studio Introduction to R Packages What is R Markdown? R Markdown is a way of creating fully reproducible documents, in which both text and code can be combined. In fact, these lessons are written using R Markdown! That’s how we make things: bullets bold italics links or run inline r code And by the end of this lesson, you should be able to do each of those things too, and more! Despite these documents all starting as plain text, you can render them into HTML pages, or PDFs, or Word documents, or slides! The symbols you use to signal, for example,  bold  or  italics  is compatible with all of those formats. Wh...
Post a Comment
Read more

What is Data? And What is Data Science Process?

The Beginner’s Guide to Data & Data Science Process About Data: In our First Video today we talked about Data and how the Cambridge English Dictionary and Wikipedia defines Data, then we looked on few forms of Data that are: Sequencing data   Population census data ( Here  is the US census website and  some tools to help you examine it , but if you aren’t from the US, I urge you to check out your home country’s census bureau (if available) and look at some of the data there!) Electronic medical records (EMR), other large databases Geographic information system (GIS) data (mapping) Image analysis and image extrapolation (A fun example you can play with is the  DeepDream software  that was originally designed to detect faces in an image, but has since moved on to more  artistic  pursuits.) Language and translations Website traffic Personal/Ad data (e.g.: Facebook, Netflix predictions, etc.) These data forms need a lot of preprocessin...
1 comment
Read more

Introduction to Functions and Arguments in R Programming: Part 2

The Beginner’s Guide to Functions in R Programming: Functions are an essential part of programming, and they play a critical role in R programming. In R, a function is a set of instructions that perform a specific task. Functions in R can have several arguments, and their evaluation can be lazy or eager. In this blog post, we will explore functions in R, including their  "dot-dot-dot" or ellipsis  argument, lazy evaluation, and more . Ellipsis or "dot-dot-dot" Argument in R Functions The "dot-dot-dot" or ellipsis argument in R programming is a special argument that can be used in functions to represent a variable number of additional arguments that are not explicitly defined in the function. The ellipsis argument is represented by three dots ... and is typically used at the end of the function's argument list. When the function is called, any additional arguments provided by the user after the defined arguments are collected by the ellipsis argument an...
Post a Comment
Read more