Python and R made easy for the SAS Programmer

Janet Li1 and Varaprasad Ilapogu2
1Pfizer, 2Ephicacy consultancy group


Many of the day-to-day tasks and responsibilities of the statistical programmer of a pharmaceutical research and development group or contract research organization (CRO) include importing/exporting data, deriving variables and creating analysis data sets, and creating clinical study report (CSR) materials such as tables, listings, and figures (TLFs). These outputs are used for submission to regulatory agencies and are generally programmed in SAS. There is a growing movement and acceptance towards using Python and R in the Clinical SAS programming world. In our paper, we explore tips and tricks on how to use Python and R in conjunction with SAS to more effectively and efficiently deliver statistical programming outputs. We intend to provide examples of common SAS procedures and syntax that are used in the creation of analysis datasets and TLFs and translate them to Python and R to help the beginner Python and/or R programmer familiarize themselves with the alternative way of programming these statistical outputs.