Reproducible Reporting

R Markdown and knitr make it easy to intermingle code and text to generate compelling reports and presentations that are never out of date.

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and knitr make it easy to intermingle code and text to generate compelling reports and presentations that are never out of date.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

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About the speakers

Jeff Allen

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

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 Ushey

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.