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Online C++ to R Converter

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Additional Instructions

How to use this tool?

This free online 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++ has a syntax that is similar to C, but with additional features such as classes and templates.	R has a syntax that is designed for data analysis and statistical computing, with a focus on vectorization and functional programming.
Paradigm	C++ supports multiple programming paradigms, including procedural, object-oriented, and generic programming.	R is primarily a functional programming language, but also supports object-oriented programming.
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 high-performance language that can be used for systems programming and other performance-critical applications.	R is not as fast as C++ for general-purpose programming, but is optimized for data analysis and statistical computing.
Libraries and frameworks	C++ has a large number of libraries and frameworks available for a wide range of applications, including game development, scientific computing, and web development.	R has a large number of libraries and frameworks available for data analysis and statistical computing, including the popular ggplot2 and dplyr packages.
Community and support	C++ has a large and active community of developers, with many online resources and forums available for support.	R has a large and active community of data analysts and statisticians, with many online resources and forums available for support.
Learning curve	C++ has a steep learning curve, due to its complex syntax and support for multiple programming paradigms.	R has a moderate learning curve, due to its focus on data analysis and statistical computing, but can be challenging for those without a strong background in statistics.

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