How to use this tool?

This free online converter lets you convert code from Csharp to R in a click of a button. To use this converter, take the following steps -

  1. Type or paste your Csharp code in the input box.
  2. Click the convert button.
  3. The resulting R code from the conversion will be displayed in the output box.

Examples

The following are examples of code conversion from Csharp to R using this converter. Note that you may not always get the same code since it is generated by an AI language model which is not 100% deterministic and gets updated from time to time.

Example 1 - Is String Palindrome

Program that checks if a string is a palindrome or not.

Csharp

right arrow

R

Example 2 - Even or Odd

A well commented function to check if a number if odd or even.

Csharp

right arrow

R

Key differences between Csharp and R

CharacteristicCsharpR
SyntaxC# syntax is similar to C++ and Java, with curly braces and semicolons to denote code blocks and statements. It also supports LINQ (Language Integrated Query) for querying data.R syntax is designed for data analysis and statistical computing. It uses a functional programming style with a focus on vectors and data frames. R also has a wide range of built-in functions for data manipulation and analysis.
ParadigmC# supports object-oriented programming, as well as functional programming with the use of lambda expressions and LINQ.R is primarily a functional programming language, but it also supports object-oriented programming with the use of S3 and S4 classes.
TypingC# is a statically typed language, meaning that variable types are determined at compile time.R is a dynamically typed language, meaning that variable types are determined at runtime.
PerformanceC# is a compiled language, which generally results in faster performance than interpreted languages like R. It also has built-in support for multithreading and parallel processing.R is an interpreted language, which can result in slower performance than compiled languages like C#. However, R has many optimized libraries for data analysis and statistical computing that can improve performance.
Libraries and frameworksC# has a wide range of libraries and frameworks for various purposes, including .NET Framework, ASP.NET, Entity Framework, and Xamarin.R has a large collection of libraries for data analysis and statistical computing, including ggplot2, dplyr, and tidyr.
Community and supportC# has a large and active community, with many resources and forums available for support and learning.R also has a large and active community, with many resources and forums available for support and learning. However, it may be more specialized towards data analysis and statistical computing.
Learning curveC# has a moderate learning curve, especially for those with experience in C++ or Java. It also has many resources and tutorials available for beginners.R has a steeper learning curve, especially for those without a background in programming or statistics. However, it has many resources and tutorials available for beginners.