Online C++ to R Converter
Click to select or drop your input code file here.
You can also type the input code below.
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 the convert button.
- The resulting R code from the conversion 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++
R
Example 2 - Even or Odd
A well commented function to check if a number if odd or even.
C++
R
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. |
