Page break rmarkdown inside chunk11/4/2023 ![]() Practice running the chunks individually. 29.2.1 ExercisesĬreate a new Quarto document using File > New File > Quarto Document. The following sections dive into the three components of a Quarto document in more details: the markdown text, the code chunks, and the YAML header. RStudio will launch a wizard that you can use to pre-populate your file with useful content that reminds you how the key features of Quarto work. qmd file, select File > New File > Quarto Document… in the menu bar. qmd:įigure 29.4: Diagram of Quarto workflow from qmd, to knitr, to md, to pandoc, to output in PDF, MS Word, or HTML formats. This is a Quarto file – a plain text file that has the extension. ![]() You need the Quarto command line interface (Quarto CLI), but you don’t need to explicitly install it or load it, as RStudio automatically does both when needed. In a way, Quarto reflects everything that was learned from expanding and supporting the R Markdown ecosystem over a decade. You’re not wrong! Quarto unifies the functionality of many packages from the R Markdown ecosystem (rmarkdown, bookdown, distill, xaringan, etc.) into a single consistent system as well as extends it with native support for multiple programming languages like Python and Julia in addition to R. If you’re an R Markdown user, you might be thinking “Quarto sounds a lot like R Markdown”. Instead, as you work through this chapter, and use Quarto in the future, you should refer to the Quarto documentation. This means that help is, by-and-large, not available through ?. Quarto is a command line interface tool, not an R package. Quarto files are designed to be used in three ways:įor communicating to decision-makers, who want to focus on the conclusions, not the code behind the analysis.įor collaborating with other data scientists (including future you!), who are interested in both your conclusions, and how you reached them (i.e. the code).Īs 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. Quarto documents are fully reproducible and support dozens of output formats, like PDFs, Word files, presentations, and more. ![]() Quarto provides a unified authoring framework for data science, combining your code, its results, and your prose.
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