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a| Grolemund, Garrett, e| author.
a| Reproducible Research and Reports with R Markdown h| [electronic resource] / c| Grolemund, Garrett.
a| 1st edition
b| O'Reilly Media, Inc., c| 2016.
a| 1 online resource (1 video file, approximately 2 hr., 9 min.)
a| two-dimensional moving image b| tdi 2| rdacontent
a| computer b| c 2| rdamedia
a| online resource b| cr 2| rdacarrier
a| video file
a| Online resource; Title from title screen (viewed May 6, 2016)
a| R Markdown does three main things pretty close to magic. First, it lets you make a completely reproducible, parameter-set and automatable R report. Second, it lets you export that report into a multitude of formats (HTML, Word, .js slide show, interactive web app, etc.). Third, it does the first two things really fast. Wishing for a way to document your code so it still makes sense to you or somebody else six months down the road? Presto! R Markdown does that. Hoping for a button you could click to reproduce your entire analysis with a new data set or parameter? Shazaam! R Markdown does that. Sick of having to copy and paste your results? Poof! R Markdown takes the pain away. If you’re an analyst, scientist, actuary, statistician, or a programmer familiar with R, you should add this package to your bag of tricks. Learn to create parameter-set reports that are fully reproducible and automatable Master knitr – the syntax used to embed R code and other languages into reports Discover how to export reports into HTML, PDF, Word or .js slideshows Learn techniques that improve the look of tables, slides, and visual themes in reports Combine R Markdown and Shiny to create interactive reports that update in real time Speed up your mastery of R Markdown using the R Markdown cheatsheet Garrett Grolemund is a Data Scientist with RStudio, one of the largest contributors of content and software related to the open source R language. He is Editor-in-Chief of the Shiny development center at shiny.rstudio.com. He wrote the popular lubridate R package; the R focused O'Reilly Media titles Hands-On Programming with R , R for Data Science (co-author), and Expert Data Wrangling with R .
a| Electronic videos.