R Markdown provides a unified authoring framework for data science, combining your code, its results, and your prose commentary. R Markdown documents are fully reproducible and support dozens of output formats, like PDFs, Word files, slideshows, and more.
R Markdown files are designed to be used in three ways:
For communicating to decision makers, who want to focus on the conclusions, not the code behind the analysis.
For collaborating with other data scientists (including future you!), who are interested in both your conclusions, and how you reached them (i.e., the code).
As an environment in which to do data science, as a modern day lab notebook where you can capture not only what you did, but also what you were thinking.
R Markdown integrates a number of R packages and external tools. This
means that help is, by and large, not available through
as you work through this chapter, and use R Markdown in the future, keep
these resources close to hand:
R Markdown Cheat Sheet: available in the RStudio IDE under Help → Cheatsheets → R Markdown Cheat Sheet
R Markdown Reference Guide: available in the RStudio IDE under Help → Cheatsheets → R Markdown Reference Guide
Both cheatsheets are also available at http://rstudio.com/cheatsheets.
You need the rmarkdown package, but you don’t need to explicitly install it or load it, as RStudio automatically does both when needed.
This is an R Markdown ...