Achieving a seamless workflow between R, Python and SAS from within RStudio
summary
Seamless R–Python–SAS scripting in RStudio is practical: the recommended route uses SASPy (requires Java and usually admin rights) to call SAS from Python and back into R; lightweight alternatives include SASmarkdown (lets documents show SAS code but offers no data interchange) or enabling SAS’s proc iml with ImportDataSetFromR/ExportDataSetToR to move data between SAS and R (Enterprise Guide may need admin). A proven workaround is an internal R package that writes temp files, runs SAS, and returns an R data frame; IT later enabled SASPy at the organization.
AI-written summary · about
chapters (5)
related talks
15mAchieving a seamless workflow between R, Python and SAS from within RStudio
35mEffective Python and R collaboration
17mPolyglot Data Science: Why and How to Combine R and Python
37mRewriting your R analysis code in Python
18mYes, you can use Python with RStudio Team!
32mInterfacing R and Python
22mUsing Python & R in Harmony
21mNew language features in RStudio