Wednesday Half-Day Class Isaiah Lankham and Matthew Slaughter

Everything is better with friends: Executing SASĀ® code in Python scripts with SASPy, and turbocharging your SAS programming with open-source tooling

Presented: Wednesday September 4, 2019, 8:00am-11:30am

Co-presented by:
Isaiah Lankham is a polyglot data analyst for the University of California’s Office of the President in Oakland, CA, specializing in data analysis and visualization using Tableau, SAS, and Python. Initially trained as a mathematician and educator, Isaiah is also an adjunct faculty member for the Statistics Department at California State University, East Bay, regularly teaching graduate SAS programming courses.

Matthew SlaughterMatthew Slaughter is Research Analyst at the Kaiser Permanente Center for Health Research in Portland, OR, where he provides programming, analytical, and data management support to health research projects on topics such as chronic pain, vaccine safety, and colorectal cancer.


Turbocharge your SAS programming with open-source tooling, and learn to use GitHub for finding (or even contributing!) to open-source software.

SASPy is a module developed by SAS Institute for the Python programming language, providing an alternative interface to the SAS system. With SASPy, SAS procedures can be executed in Python scripts using Python syntax, and data can be transferred between SAS datasets and their Python DataFrame equivalent. This allows SAS programmers to take advantage of the flexibility of Python for flow control, and Python programmers can incorporate SAS analytics into their scripts and applications.

This hands-on tutorial walks through examples of common data-analysis tasks using both regular SAS code and SASPy within a Python script, highlighting important tradeoffs for each and emphasizing the value of being a polyglot programmer fluent in multiple languages. Along the way, we’ll also practice using Git to interact with code repositories on GitHub, including a detailed overview of forking, cloning, and branching projects. Participants will also be equipped to contribute to open-source projects hosted on GitHub, like SASPy.

This class is aimed at SAS programmers of all skill levels, including those with no prior experience using Python or Git/GitHub. Participants wishing to follow along using their own computer will receive complete setup instructions for the open-source software used (including Git, PyCharm Community Edition, and Python 3.7).

Intended Audience:
All Levels

Tools Discussed:
Base SAS and SAS/STAT (as part of a SAS 9.4 installation) and SASPy (a Python module developed by SAS Institute)

Familiarity with Base SAS, including DATA and PROC steps

Attendee Learning Outcomes:
After successfully completing this class, attendees will be equipped for the following:

    • Interacting with open-source software on GitHub, including forking, cloning, and branching code repositories
    • Using SAS and Python together with SASPy, include understanding the trade-offs of completing common data-science tasks in SAS and Python
    • Exploring the structure of open-source projects like SASPy
    • Contributing to open-source projects like SASPy, including unit testing

Class Outline:
1. Overview of GitHub and Open-Source Philosophy
2. Python Primer for SAS Programmers
3. How to setup SASPy
4. How to import and export SAS data within Python scripts using SASPy
5. How to use SASPy convenience methods for executing SAS code within Python
6. How to develop a complete Python application incorporating SAS analytics using
7. How to contribute to open-source projects like SASPy