![]() When using VS Code there is not yet an integrated Render button for previewing documents. You can install the VS Code extension by searching for ‘quarto’ in the extensions panel or from the extension marketplace. The extension integrates directly with the R Extension to provide the following R-specific capabilites: The Quarto Extension for VS Code provides a variety of tools for working with. Options are also provided for creating a git repository and initializing an renv environment for the project. You can use this UI to create both vanilla projects as well as websites and books. If you want to create a new project for a Quarto document or set of documents, use the File : New Project… command, specify New Directory, then choose Quarto Project: ![]() Side-by-side preview works for both HTML and PDF output. The preview will update whenever you re-render the document. The preview will appear alongside the editor: If you prefer to automatically render whenever you save you can check the Render on Save option on the editor toolbar. Use the Render button to preview documents as you edit them: Use the File : New File : Quarto Document… command to create new Quarto documents: Alternatively, there is a version of Quarto built-in to RStudio that you can activate from R Markdown Preferences. If you have already installed the Quarto CLI then RStudio will detect this and enable Quarto features automatically. You can render Quarto documents in a variety of ways:įrom the system shell using the quarto render command: When a Quarto document is rendered, R code blocks are automatically executed. There are many options which control the behavior of code execution and output, you can read more about them in the article on Execution Options. RStudio notes that R is often taught in statistics and data science courses. You can produce a wide variety of output types from executable code blocks, including plots, tabular output from data frames, and plain text output (e.g. printing the results of statistical summaries). R is typically used in statistical computing. This document results in the following rendered output: These are cell level options that make the figure cross-referenceable. You’ll note that there are some special comments at the top of the code block. #| warning: false library(ggplot2) ggplot(airquality, aes(Temp, Ozone)) + geom_point() + geom_smooth( method = "loess") ``` ![]() ``` #| label: fig-airquality #| fig-cap: Temperature and ozone level. title: "ggplot2 demo" author: "Norah Jones" date: "" format: html: code-fold: true - # Air Quality further explores the impact of temperature on ozone level.
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