Online C# to R Converter

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Additional Instructions

How to use this tool?

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

Type or paste your C# code in the input box.
Click on the "Convert" button.
The converted R code will be displayed in the output box.

Examples

The following are examples of code conversion from C# 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.

C# Code:

R Code:

Example 2 - Even or Odd

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

C# Code:

R Code:

Differences

The following are some key differences between C# and R.

Characteristic	C#	R
Syntax	C# 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.
Paradigm	C# 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.
Typing	C# 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.
Performance	C# 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 frameworks	C# 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 support	C# 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 curve	C# 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.

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