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R for Data Science by Garrett Grolemund, Hadley Wickham

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Chapter 21. R Markdown

Introduction

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 ?. Instead, 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.

Prerequisites

You need the rmarkdown package, but you don’t need to explicitly install it or load it, as RStudio automatically does both when needed.

R Markdown Basics

This is an R Markdown ...

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