SAS vs Python
Developers should learn SAS when working in data-heavy fields such as clinical research, banking, or government sectors where it is an industry standard for regulatory compliance and complex statistical analysis meets python is widely used in the industry and worth learning. Here's our take.
SAS
Developers should learn SAS when working in data-heavy fields such as clinical research, banking, or government sectors where it is an industry standard for regulatory compliance and complex statistical analysis
SAS
Nice PickDevelopers should learn SAS when working in data-heavy fields such as clinical research, banking, or government sectors where it is an industry standard for regulatory compliance and complex statistical analysis
Pros
- +It is particularly valuable for tasks like data cleaning, statistical modeling, and generating reproducible reports in environments that require robust, validated analytical tools
- +Related to: statistical-analysis, data-management
Cons
- -Specific tradeoffs depend on your use case
Python
Python is widely used in the industry and worth learning
Pros
- +Widely used in the industry
- +Related to: django, flask
Cons
- -Specific tradeoffs depend on your use case
The Verdict
These tools serve different purposes. SAS is a tool while Python is a language. We picked SAS based on overall popularity, but your choice depends on what you're building.
Based on overall popularity. SAS is more widely used, but Python excels in its own space.
Disagree with our pick? nice@nicepick.dev