Using SAS Alongside Python for Data Analysis

[Caleb67]

For people working with both SAS and Python, how do you usually divide tasks between the two?

For example, would you use SAS for statistical analysis and data preparation and Python for visualization or machine learning, or keep most of the workflow within SAS?

For someone learning data science, which combination of SAS, SQL, Python and statistics would you recommend focusing on first?

[SASKiwi]

I suggest that the answers to this will depend a lot on your use case. If your requirement is ad-hoc analytics, then what you do in SAS versus Python might be based on your skill level in each. For analytics you want to productionise, then using SAS for the majority of workflow processes and embedding PROC PYTHON steps is an obvious option. 

[Stu_SAS]

Hey @Caleb67! The answer to this is to use the strengths of each language however you see fit for the task at hand. There is no one right answer here.

Sometimes I use SAS, sometimes I use Python, and sometimes I use SQL. Sometimes there's something that's much more elegant in SAS while there's something much easier to do in Python. You can mix and match both. Seasoned SAS programmers know how easy it is to bounce between the DATA step, SQL, and PROCs. You can absolutely do the same with Python!

I recently wrote about this in my latest article, Python your way: 6 ways to run Python in SAS Viya (The SAS Extension for VS Code). You also might find my recent talk at SAS Innovate 2026 relevant to your question because I also touch on this topic.