Introduction to R Markdown and Quarto

Note: R markdown will continue to be used, and this lesson is valuable to you, but I recommend Quarto. Quarto was announced at the 2022 R conference and is considered “the next generation” of R markdown. To learn more, see this FAQ .

R markdown and Quarto are very similar, so this is still a useful lesson, but you can easily switch over to using quarto once you start working on your own projects/analyses.

Markdown

Markdown is a lightweight markup language with plain text formatting syntax. It’s designed to be easy to write and easy to read, making it a popular choice for writing documentation, notes, and web content.

It’s used extensively throughout the internet, from social media platforms to coding repositories, and even in cutting-edge AI applications.

In fact, you’ve likely encountered Markdown without even realizing it. When you use certain formatting options on Reddit or GitHub, you’re using Markdown. Even the outputs from AI models like ChatGPT often utilize Markdown for structure and formatting. Its simplicity and versatility have made it the go-to choice for content creators, developers, and tech enthusiasts alike.

Check out this tutorial if you want to practice markdown

R Markdown

R Markdown is a document format that enables the integration of R code into a markdown document. It combines the core syntax of markdown (an easy-to-write plain text format) with embedded R chunks, allowing for the creation of dynamic documents that can both tell a story and run R code to produce analyses, visualizations, and more.

Why Use R Markdown?

Reproducibility: R Markdown documents are completely reproducible. When you share an R Markdown file, others can rerun the R code to obtain the same results.
Multiple Output Formats: From a single R Markdown document, you can produce a variety of outputs, including HTML, PDF, and Word documents.
Integration: Combine your narrative with R code. This means the text, R code, and results can all be found in one document, making for a neat, integrated workflow.

Getting Started with R Markdown

Installation: If you haven’t already, you’ll need to install the rmarkdown package:

install.packages("rmarkdown")

Creating a New R Markdown Document:
- In RStudio, go to File -> New File -> R Markdown.
- You’ll then see a dialog box. For now, keep the default output format as HTML and press OK.

this will open up a new R Markdown file in the RStudio script editor

it will have lots of info and examples to start you off

Basic Components of an R Markdown File

An R Markdown file has the extension .Rmd. It’s structured into two main parts:

YAML Header: At the top of the document, surrounded by ---, it contains meta-information and settings for the document, such as its title and output format.

---
title: "Your Document Title"
author: "Your Name"
date: "The Date"
output: html_document
---

yaml stands for “YAML Ain’t Markup Language” and is a human-readable data serialization language. It’s used to specify metadata and settings for the document. here, you can set things like the title, author, date, and output format, as well as other options like the theme, font size, and more.

fun fact

This lab manual has its own yaml file that I update each week to add content to.

Body: This contains the content of the document, with a mix of markdown text and R code chunks.

Formatting in R Markdown

Headers: Use # for a main header, ## for a sub-header, ### for a sub-sub-header, and so on.
Bold and Italics: Surround text with ** for bold and * for italics.
Lists: Use - or * for bullet points.
Links: Format links like this: [Link Text](URL).

R Code Chunks

R code is inserted into R Markdown documents using code chunks, which are surrounded by three backticks and the letter r in curly braces, like this:

this produces the following visual appearance when rendered, or knitted

summary(mtcars)

      mpg             cyl             disp             hp       
 Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
 1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
 Median :19.20   Median :6.000   Median :196.3   Median :123.0  
 Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
 3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
 Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
      drat             wt             qsec             vs        
 Min.   :2.760   Min.   :1.513   Min.   :14.50   Min.   :0.0000  
 1st Qu.:3.080   1st Qu.:2.581   1st Qu.:16.89   1st Qu.:0.0000  
 Median :3.695   Median :3.325   Median :17.71   Median :0.0000  
 Mean   :3.597   Mean   :3.217   Mean   :17.85   Mean   :0.4375  
 3rd Qu.:3.920   3rd Qu.:3.610   3rd Qu.:18.90   3rd Qu.:1.0000  
 Max.   :4.930   Max.   :5.424   Max.   :22.90   Max.   :1.0000  
       am              gear            carb      
 Min.   :0.0000   Min.   :3.000   Min.   :1.000  
 1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
 Median :0.0000   Median :4.000   Median :2.000  
 Mean   :0.4062   Mean   :3.688   Mean   :2.812  
 3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000  
 Max.   :1.0000   Max.   :5.000   Max.   :8.000

Compiling the Document

Once you’ve written your R Markdown file, press the “Knit” button in the toolbar at the top of the script editor. This will compile your R Markdown into your chosen output format.