How to use this tool?
This free online converter lets you convert code from Ruby to R in a click of a button. To use this converter, take the following steps -
- Type or paste your Ruby 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 Ruby 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.
Ruby
R
Example 2 - Even or Odd
A well commented function to check if a number if odd or even.
Ruby
R
Key differences between Ruby and R
Characteristic | Ruby | R |
---|---|---|
Syntax | Ruby has a more flexible and concise syntax compared to R. | R has a syntax that is more geared towards statistical analysis and data manipulation. |
Paradigm | Ruby is a multi-paradigm language that supports object-oriented, functional, and imperative programming. | R is primarily a functional programming language with support for object-oriented programming. |
Typing | Ruby is dynamically typed, meaning that variable types are determined at runtime. | R is also dynamically typed, but it has some support for static typing through packages like Rcpp. |
Performance | Ruby is generally slower than R due to its interpreted nature and garbage collection. | R is optimized for data analysis and can be faster than Ruby for certain tasks, especially when using optimized libraries like data.table. |
Libraries and frameworks | Ruby has a large and active community that has developed many popular libraries and frameworks, such as Ruby on Rails. | R has a large collection of packages for data analysis and visualization, such as ggplot2 and dplyr. |
Community and support | Ruby has a large and supportive community that is active in developing new libraries and frameworks. | R has a large and active community of data analysts and statisticians who contribute to the development of new packages and tools. |
Learning curve | Ruby has a relatively low learning curve due to its simple and flexible syntax. | R has a steeper learning curve due to its syntax and focus on statistical analysis, but there are many resources available for learning. |