Come out next week!
RStudio Presents to ISoP New England
Come socialize with local pharmacometricians and learn about Shiny and R Markdown - Interactive apps and reproducible reports from R.
Location and Time
Date: September 22, 2016
Time: 5:30-8pm (dinner starts at ~6:15pm)
Registration link: http://www.go-isop.org/isop-new-england-local-event–sept-22
Location: The Summer Shack (149 Alewife Brook Pkwy, Cambridge, MA 02140, easily accessible from the Alewife T station on the Red Line)
Meet at at 5:30 for drinks (cash bar) followed by dinner at 6:15pm and a presentation by Nathan Stephens of RStudio. The cost is $50 for ISoP members or $60 for non-members (includes dinner).
Shiny and R Markdown - Interactive apps and reproducible reports from R
RStudio will be presenting an overview of RMarkdown, Shiny, and htmlwidgets. This is a great opportunity to learn and get inspired about new capabilities for creating compelling analyses of complex datasets.
R Markdown is an authoring format that enables easy creation of dynamic documents, presentations, and reports from R. It combines the core syntax of markdown with embedded R code chunks that are run so their output can be included in the final document. R Markdown documents are fully reproducible and can be automatically regenerated whenever underlying R code or data changes.
The presentation will also provide a sneak peek of our upcoming notebook capabilities. Creating and sharing work will be simple and compelling in this environment. You may also be interested to see the ability to combine work from multiple languages (like C++, Python, Bash, etc.) in a single document. Notebook capabilities will be released in the next few months. You can enable a pre-release from the preview version of the IDE by going to the Preference Menu, selecting RMarkdown, and checking the Enable RNotebook box. Please remember that this is pre-release code and use accordingly.
Nathan Stephens is the director of solutions engineering at RStudio. His background is in applied analytics and consulting. He has experience building data science teams, creating innovative data products, analyzing big data, and architecting analytic platforms. He was an early adopter of R and has introduced it into many organizations. Nathan holds an MS in statistics from Brigham Young University.