Online R Compiler

Online R Compiler

Online R Compiler

R is a powerful programming language for statistical computing, data analysis, and graphics. The R Compiler is a software tool that converts high-level R source code into machine-level instructions that the computer can execute. With the R programming compiler, you can write efficient and optimized code, analyze large data sets, and create stunning visualizations. It scans the high-level code line by line and detects different errors, making the identification and fixing of issues much easier. Whether you’re a seasoned data analyst or a beginner, the R language Compiler is essential for anyone working with data or statistics.

Working of the R Compiler 

Below are several steps that can assist you in utilizing the R Compiler efficiently:

SIGN IN: To use the features of the R programming compiler, you need to sign in to the Intellipaat Platform. Doing this lets you use more features and keep track of your earlier codes. The upper-right corner of the website has a sign-in button, which you must click on.

CODE EDITOR: In the code editor, you can write R code that enables interactive visualization by utilizing the R syntax.

RUN: Construct the code in the editor and opt for the correct compiler version for running your R program. To run your code, click the “RUN” button.

SAVE: By selecting the ‘SAVE’ button in the top right corner of the page, you can save your R code. Users can access the saved codes using the ‘MY SNIPPETS’ button on the website.

STDIN & STDOUT: To provide input to your R code, utilize the R Compiler’s Standard Input (stdin) terminal. The compiler’s Standard Output (stdout) displays the code output.

SHARE: You can distribute your R code to others using the ‘SHARE’ button in the top right corner of the page. It is possible to share R code in read-only format, letting people view and examine it without modifying it.

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Learn R – Brief Overview

R syntax

Here is some basic R syntax for beginners:

  • Assigning Values to Variables: In R, you can assign values to variables using the assignment operators “<-” or “=.”


x <- 5
y = 10

  • Basic Arithmetic Operations: R supports all basic arithmetic operations such as addition, subtraction, multiplication, division, and exponentiation.


a <- 5
b <- 3
c <- a + b   # addition
d <- a - b   # subtraction
e <- a * b   # multiplication
f <- a / b   # division
g <- a ^ b   # exponentiation

  • Data Types: R supports various data types such as numeric, character, logical, integer, and complex.


a <- 5.6     # numeric
b <- "hello" # character
c <- TRUE    # logical
d <- 2L      # integer
e <- 3+4i    # complex

  • Conditional Statements: R supports conditional statements such as if-else.


a <- 5
if(a > 10){
    print("a is greater than 10")
} else {
   print("a is smaller than or equal to 10")

  • Loops: R supports loops such as for and while loops.


# for loop
for(i in 1:5){
# while loop
i <- 1
while(i <= 5){
   i <- i + 1

  • Functions:  It has a wide range of built-in R functions that can be used to perform various operations. Additionally, users can write their own functions in R.


# Built-in function
a <- c(1, 2, 3, 4, 5)
sum(a)   # calculates the sum of all numbers in vector a
# User-defined function
multiply <- function(x, y){
    z <- x * y

multiply(5, 2)  # returns 10

  • Vectors: A vector is a basic data structure in R that can hold a collection of values of the same data type.


a <- c(1, 2, 3, 4, 5)   # numeric vector
b <- c("red", "green", "blue")   # character vector
c <- c(TRUE, FALSE, TRUE)   # logical vector

  • Matrices: A matrix is a 2-dimensional array in R that can hold a collection of values of the same data type.


a <- matrix(c(1, 2, 3, 4, 5, 6), nrow=2, ncol=3)   # 2x3 matrix

  • Data Frames: A data frame is a tabular data structure in R that can hold different data types.


a <- data.frame(
    name=c("John", "Mary", "Bob"),
    age=c(25, 30, 35),
    married=c(FALSE, TRUE, TRUE)

  • Packages: R has a vast collection of packages that extend its functionality. To use a package, you first need to install it and then load it using the library function.


# Install a package
# Load a package

These are just a few basic R syntax examples for beginners. By learning and practicing more complex syntax, you can become proficient in R programming and data analysis.

Learn R programming from scratch with our R Programming Tutorials for absolute beginners.

How to Write a Program in R?

You may employ the following steps to write a program in R:
Open an R IDE or R Console: You can use an Integrated Development Environment (IDE) such as RStudio or a console such as R GUI to write and execute R code.

Define your Problem Statement: Before writing your program, you should clearly define the problem you are trying to solve.

Write your Code: Based on the problem statement, write the necessary code in R. Break your code into smaller, manageable tasks and write functions if necessary.

Test your Code: Test your code with different inputs to ensure that it works as expected.

Save your Program: Save your program as a ‘.R’ file so you can reuse it later or share it with others.

Here is a sample program that calculates the sum of all even numbers between 1 and 10 using a for loop:

# Define a function to calculate the sum of even numbers
sum_even_numbers <- function(n){
  sum <- 0
  for(i in 1:n){
    if(i %% 2 == 0){
      sum <- sum + i
# Call the function with n=10
result <- sum_even_numbers(10)
# Print the result

In this program, we defined a function ‘sum_even_numbers’ that takes a parameter ‘n,’ loops from 1 to n, and calculates the sum of all even numbers using the modulus operator. We then called the function with ‘n=10’ and printed the result.

By following these steps, you can write effective and efficient programs in R to solve various problems.

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How to Compile and Run the R Programs Online?

Here are the following steps that will help you to compile and run R programs online:

  • Choose an Online R Compiler: Select an online platform or tool that provides an R compiler or interpreter. Some examples include RStudio Cloud, Rextester, or Ideone.
  • Open the Online R Compiler: Utilize a web browser to connect to the preferred online R compiler platform. Visit the website or platform that hosts the R compiler.
  • Write your R Code: Within the online R compiler, you will typically find an editor or input area where you can write your R code. Use this space to enter your R program. Make sure your code follows R syntax rules.
  • Compile and Run: Look for a button or option to compile and run your R program. It may be labeled as “Run,” “Execute,” or something similar. Click on this button to initiate the compilation and execution process.
  • View the Output: Once the program has been executed, the online R compiler will display the output of your R program. It may appear in a separate output area or console. Review the output to check if the program executed correctly and produced the desired results.

You can now utilize an online R compiler platform to compile and execute your R programs by adhering to these instructions.

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