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Online R to SAS Converter

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Additional Instructions

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 on the "Convert" button.
The converted SAS code 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 Code:

SAS Code:

Example 2 - Even or Odd

A well commented function to check if a number if odd or even.

R Code:

SAS Code:

Differences

The following are some 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.

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