Two members of our team will attend rstudio::conf, chat with them if you have questions about rOpenSci.
A guide to modern reproducible data science
Karthik Ram (Tidyverse-ext, session 1)
Have you ever had a challenging time cloning someone’s data analysis repo and easily re-running the analysis without fiddling with missing packages, mismatched versions, external dependencies, unavailable data or a whole host of other issues? Would you like your own work to be reproducible where someone else can access your data, code, workflow, models and provenance and easily re-create your results without consulting you? Then this is the talk for you. You’ll learn about creating custom computing environments that can be shared and instantly with remote users, packaging small to medium data inside and outside packages, and creating simple to complex workflows to track the provenance of your results.
A preview of Rtools 4.0
Jeroen Ooms (Programming, session 4)
Rtools is getting a major upgrade. In addition to the latest gcc, it now includes a full build system and package manager to build, install, and distribute external c/c++/fortran libraries needed by R packages. Thereby it bridges the long-standing gap between Windows and MacOS/Linux with respect to the availability of high quality, up-to-date system libraries. In this talk, we will show how to build and install system libraries with Rtools, and manage your Rtools build environment. It should be interesting both for Windows users as well as non-Windows package authors that are interested in reducing the pain of making things work on Windows.
Resources
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