Why R? Webinars are back for Season 2! After over more than 20 000 views in past season we are eager to start a new set of R webinars! All videos from the past series can be watched on our youtube.com/WhyRFoundation channel. See this post to find out about upcoming webinars in September. The aim of webinars is to promote Why R? 2020 Conference (Remote) that is planned for 24-27 September 2020.
Reproducible research with workflowr: a framework for organizing, versioning, and sharing your data analysis projects
Have you ever struggled to re-run your own code or scripts you received from a collaborator? You’re not alone! Fortunately, there are best practices that you can adopt to help you develop more reproducible R code. In this talk, I’ll share some of these best practices, and then describe how the R package workflowr (https://jdblischak.github.io/workflowr/) automates these tasks for you so that you can focus on your analyses. The workflowr framework combines R Markdown for literate programming and Git for version control. I’ll demonstrate how workflowr makes it easier for you to organize your project files, version your code, and share your results online.
John Blischak is a Freelance Scientific Software Developer based out of Akron, Ohio, USA. He received his PhD in Genetics from the University of Chicago, where he became interested in reproducible and transparent computational workflows. Along with co-authors Peter Carbonetto and Matthew Stephens, he has developed the R package workflowr to facilitate reproducible research and promote open science.
- donate: whyr.pl/donate/
- channel: youtube.com/WhyRFoundation
- date: every Thursday 8:00 pm UTC+2
- format: 45 minutes long talk streamed on YouTube + 10 minutes for Q&A
- comments: ask questions on YouTube live chat
2020-09-24 Pause for 2020.whyr.pl Conference (Remote)
- Why R? 2020 Conference (Remote)
- Website: 2020.whyr.pl
2020-09-17 Me, Myself and my Rprofile
2020-09-10 Data Science for Social Justice
2020-09-03 Reproducible research with workflowr: a framework for organizing, versioning, and sharing your data analysis projects
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