How to use this tool?
This free online converter lets you convert code from R to SAS in a click of a button. To use this converter, take the following steps -
- Type or paste your R code in the input box.
- Click the convert button.
- The resulting SAS code from the conversion will be displayed in the output box.
Examples
The following are examples of code conversion from R to SAS 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.
R
SAS
Example 2 - Even or Odd
A well commented function to check if a number if odd or even.
R
SAS
Key differences between R and SAS
Characteristic | R | SAS |
---|---|---|
Syntax | R has a syntax that is similar to the S programming language, which is designed for data analysis and graphics. It uses a functional programming style and has a wide range of built-in functions for statistical analysis. | SAS has a syntax that is similar to the SQL programming language, which is designed for data management and analysis. It uses a procedural programming style and has a wide range of built-in functions for statistical analysis. |
Paradigm | R is a functional programming language that is designed for data analysis and graphics. It emphasizes the use of functions and data structures to manipulate data. | SAS is a procedural programming language that is designed for data management and analysis. It emphasizes the use of procedures and data steps to manipulate data. |
Typing | R is a dynamically typed language, which means that the data type of a variable is determined at runtime. | SAS is a statically typed language, which means that the data type of a variable is determined at compile time. |
Performance | R can be slower than SAS for large datasets and complex computations, but it has improved significantly in recent years with the development of packages like data.table and dplyr. | SAS is known for its speed and efficiency in handling large datasets and complex computations. |
Libraries and frameworks | R has a large and active community that has developed many packages for statistical analysis, data visualization, and machine learning, such as ggplot2, dplyr, and caret. | SAS has a large and established library of procedures and functions for statistical analysis, data management, and reporting. |
Community and support | R has a large and active community of users and developers who contribute to the development of packages and provide support through forums and mailing lists. | SAS has a smaller but dedicated community of users and developers who provide support through forums and user groups. |
Learning curve | R has a steep learning curve for beginners due to its syntax and functional programming style, but there are many resources available for learning, such as online courses, books, and tutorials. | SAS has a relatively low learning curve for beginners due to its simple syntax and user-friendly interface, but it can become more complex for advanced users. |