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talk_id talk_slug talk_type talk_tags session_slug talk_title talk_title_short talk_materials_url speakers
22082
achieving-seamless-workflow-r-python
regular
interop
modeling
public-sector
story
python
Achieving a seamless workflow between R, Python and SAS from within RStudio
Achieving a seamless workflow between R, Python and SAS from within RStudio
name affiliation url username photo bio
Melissa Van Bussel
Statistics Canada
melissa_van_bussel
/assets/img/2022Conf/_talks/22082_melissa-van-bussel.jpg
Melissa Van Bussel is an accredited [Associate Statistician](https://ssc.ca/en/accreditation) (A. Stat.) and an Analyst at [Statistics Canada](https://www.statcan.gc.ca/en/start), Canada's official statistical agency. She completed her M. Sc. in Statistics at Carleton University, and her B. Sc. H. in Mathematics and Computing Systems with a Specialization in Statistics at Trent University. Melissa is passionate about all things Data Science and Teaching (and especially where those two things interact!). She makes [educational YouTube videos](https://www.youtube.com/c/ggnot2) in her spare time, covering topics such as R programming and Machine Learning.

Some of my best friends use Python...and all of my coworkers use SAS.

Statistics Canada is the official statistical agency of Canada and employs over 6,000 employees. Statistics Canada has a legal obligation to ensure that personal information collected for statistical purposes is kept strictly confidential. An internal system which prevents the release of confidential information is only implemented in SAS. As such, many Analysts and Data Scientists at Statistics Canada must use the SAS programming language as part of their workflow. It is therefore imperative to find ways to work with open source programming languages and SAS seamlessly. I will present a method for achieving a harmonious workflow between R, Python, and SAS, all within RStudio.