The original markup was done by a subeditor using a blue pencil on a handwritten or typed manuscript. To fully appreciate the magic of Markdown and where it came from, it’s useful to just briefly visit the notion of a Markup language. We’ll now talk about Markdown, code chunks, and the YAML header in turn. Generate a sample R Markdown file, in the correct directory, look at the contents, and make sure you can render it on your system using the “Knit” to HTML button in the top command bar. Work through the example above yourselves. This is what the raw and rendered output look side-by-side: Notice that the YAML header is not printed (at least not verbatim) while some of the code is printed (some is hidden), and we also see code output, including a plot! This is the rendered output from the R Markdown document, which is translated from Markdown into HTML behind the scenes, and displayed using a built in web-browser. Now click the Knit button in one of the top bars, and a document should show up in a pop-up in the Viewer pane. Click the Save button and save the files as demo.Rmd inside your newly created directory. Take a look at the R Markdown document, and notice that there seems to be some sort of header bounded by three dashes (=> YAML), followed by R code wrapped in strange constructs with backticks and curly brackets (=> Code chunks), and formatted written text (=> Markdown).īefore we can render the output, we need to save the document. Go to File => New File => R Markdown, change the Title to “Markdown demo”, and click OK. Here are the instructions: I’ll run through them, and then we’ll open Breakout rooms so you can try it out yourself. RStudio lets you create an example R Markdown document with a couple of clicks. (You don’t need to do this now: we’ll make it part of the first Breakout Room in just a moment…)īefore we go into details, let’s first see a quick demonstration of what we’re talking about. Then make this your working directory, using “Set as Working Directory” from the More options: We need to install this but don’t need to load it: We’ll focus on HTML output, but will also glance at other possibilities for the output format: with R Markdown, it is possible to create not just technical reports, but also slide decks, websites, books, scientific articles, dissertations, and so on.Īt the core of the R Markdown ecosystem is the rmarkdown package. The YAML header, which encodes metadata about the output, such as the desired output format and specific formatting features. Markdown, a very lightweight text formatting language.Ĭode chunks, which allow us to incorporate R code that can be executed and whose results we can display in text, figures, and tables. To understand R Markdown, we need to learn about three new things: It’s also an example of reproducible research since you share not just a Word file, say, with example code, but an active document in which the code actually runs and the results are reproduced. This makes RMarkdown a great computer lab notebook, since you can explain what you’re doing and why (to colleagues or your future self). And the R code you insert in the document runs inside the document and the results go to the document itself, not to the console or (in the case of plots) to the Plots pane in RStudio. You can even generate formatted bibliographies. You can structure your document with headings and subheadings. You can insert formatted text around your code in an R Markdown file. The webpage you are looking at now was written (almost) completely in R Markdown.Īt the most basic level, instead of using comments interleaved with your code in an R script: Furthermore, you can easily export this document in a large variety of formats, including HTML, PDF, Word, RTF, etc. Its signature capability is that is can print formatted text, run R code, and display the results, all inside a single document. R Markdown consists of an amazing ecosystem of R packages to produce many types of technical content.
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