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 -

  1. Type or paste your C++ 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.

Key differences between C++ and R

CharacteristicC++R
SyntaxC++ 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.
ParadigmC++ supports multiple programming paradigms, including procedural, object-oriented, and generic programming.R is primarily a functional programming language, but also supports object-oriented programming.
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 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 frameworksC++ 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 supportC++ 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 curveC++ 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.