CodeConvert

Online SAS to PowerShell Converter

upload icon 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 SAS to PowerShell in a click of a button. To use this converter, take the following steps -

Type or paste your SAS code in the input box.
Click the convert button.
The resulting PowerShell code from the conversion will be displayed in the output box.

Key differences between SAS and PowerShell

Characteristic	SAS	PowerShell
Syntax	Uses a specific syntax for data manipulation and statistical analysis, often considered less intuitive for general programming.	Uses a command-line interface with a syntax that is more similar to traditional programming languages, designed for automation and configuration management.
Paradigm	Primarily procedural and declarative, focused on data analysis and statistical modeling.	Object-oriented and functional, designed for task automation and configuration management.
Typing	Dynamically typed, with a focus on data types relevant to statistical analysis.	Dynamically typed, but supports strong typing with .NET types, allowing for more complex data structures.
Performance	Optimized for large-scale data processing and statistical computations, often faster for specific data tasks.	Performance can vary based on the task; not primarily optimized for data analysis but efficient for automation tasks.
Libraries and frameworks	Includes built-in procedures and functions for statistical analysis, but has limited external libraries.	Integrates with .NET libraries and has a wide range of modules available for various tasks, including automation and cloud management.
Community and support	Has a dedicated user base, but is more niche; support is often through official channels and paid resources.	Has a large and active community, with extensive documentation, forums, and free resources available.
Learning curve	Can be steep for those unfamiliar with statistical concepts; requires understanding of data analysis principles.	Generally considered easier for those with a background in scripting or programming; extensive resources available for learning.

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