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Webinars Data Science Essentials
Reproducible Reporting
November 21, 2017
It doesn't matter how great your analysis is unless you can share it with others – easily. R Markdown and knitr make it easy to intermingle code and text to generate compelling reports and presentations that are never out of date. Combine R Markdown with packrat to ensure that your reports are reproducible day in and day out, no matter what other R packages you have installed.
The Next Generation of R Markdown Jeff Allen, RStudio
Knitr Ninja Yihui Xie, RStudio
Packrat – A Dependency Management System for R Kevin Ushey, RStudio
Jeff’s background is in Computer Science and bioinformatics; it was there that he first encountered R in 2007. After spending many years as an RStudio user and evangelist, he joined the team in 2013
Yihui Xie is a software engineer at RStudio. He earned his PhD from the Department of Statistics, Iowa State University. He is interested in interactive statistical graphics and statistical computing. As an active R user, he has authored several R packages, such as knitr, bookdown, blogdown, xaringan, tinytex, rolldown, animation, DT, tufte, formatR, fun, xfun, mime, highr, servr, and Rd2roxygen. He also co-authored a few other R packages, including shiny, rmarkdown, rticles, and leaflet. He has authored two books, “Dynamic Documents with knitr” (Xie 2015), and “bookdown: Authoring Books and Technical Documents with R Markdown” (Xie 2016), and co-authored two books, “blogdown: Creating Websites with R Markdown” (Xie, Hill, and Thomas 2017), and “R Markdown: The Definitive Guide” (Xie, Allaire, and Grolemund 2018).
Kevin is a software engineer on the RStudio IDE team. He is an active member of the R community, member of the Rcpp core team, and has contributed to a wide variety of packages in the R ecosystem. He is the maintainer of the popular reticulate, renv, packrat, and RcppParallel R packages.
