The Ultimate Guide to the rmarkdown Package in R

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Explore valuable documentation and insights to make the most of the rmarkdown package in R. Get ready to unlock the full potential of the rmarkdown package!

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What is the rmarkdown package?

In this section, we’ll delve into the fundamental aspects and key features of the package.

The rmarkdown package provides a dynamic report generation capability in R. It is used to convert R Markdown files into a variety of formats including HTML, pdf, and Microsoft Word documents.

Title: Dynamic Documents for R
Description: Convert R Markdown documents into a variety of formats.
Author: JJ Allaire [aut], Yihui Xie [aut, cre] (), Christophe Dervieux [aut] (), Jonathan McPherson [aut], Javier Luraschi [aut], Kevin Ushey [aut], Aron Atkins [aut], Hadley Wickham [aut], Joe Cheng [aut], Winston Chang [aut], Richard Iannone [aut] (), Andrew Dunning [ctb] (), Atsushi Yasumoto [ctb, cph] (, Number sections Lua filter), Barret Schloerke [ctb], Carson Sievert [ctb] (), Devon Ryan [ctb] (), Frederik Aust [ctb] (), Jeff Allen [ctb], JooYoung Seo [ctb] (), Malcolm Barrett [ctb], Rob Hyndman [ctb], Romain Lesur [ctb], Roy Storey [ctb], Ruben Arslan [ctb], Sergio Oller [ctb], Posit Software, PBC [cph, fnd], jQuery UI contributors [ctb, cph] (jQuery UI library; authors listed in inst/rmd/h/jqueryui/AUTHORS.txt), Mark Otto [ctb] (Bootstrap library), Jacob Thornton [ctb] (Bootstrap library), Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Alexander Farkas [ctb, cph] (html5shiv library), Scott Jehl [ctb, cph] (Respond.js library), Ivan Sagalaev [ctb, cph] (highlight.js library), Greg Franko [ctb, cph] (tocify library), John MacFarlane [ctb, cph] (Pandoc templates), Google, Inc. [ctb, cph] (ioslides library), Dave Raggett [ctb] (slidy library), W3C [cph] (slidy library), Dave Gandy [ctb, cph] (Font-Awesome), Ben Sperry [ctb] (Ionicons), Drifty [cph] (Ionicons), Aidan Lister [ctb, cph] (jQuery StickyTabs), Benct Philip Jonsson [ctb, cph] (pagebreak Lua filter), Albert Krewinkel [ctb, cph] (pagebreak Lua filter)
Maintainer: Yihui Xie

How to install the rmarkdown package?

In this section, we’ll walk you through the process of installing and loading the rmarkdown package. By following these steps, you can seamlessly add new functions, datasets, and other resources to your R environment for a more robust workflow.

# Install the {Package} package if it's not already installed
if (!require("{Package}")) {
    install.packages("{Package}")
}


# Load the {Package} package
library("{Package}")

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What package information should you know?

In this section, we’ll go over the technical aspects of the rmarkdown package.

Key features

Datasets: Many R packages include built-in datasets that you can use to familiarize yourself with their functionalities. To identify built-in datasets. To identify the datasets for the rmarkdown package, visit our database of R datasets.
Vignettes: R vignettes are documents that include examples for using a package. To view the list of available vignettes for the rmarkdown package, you can visit our visit our database of R vignettes.
Citation: Citing R packages in your publications is important as it recognizes the contributions of the developers. To find citation information for the rmarkdown package, visit our database of R package citations.

Technical details

License type: GPL-3. For license details, visit the Open Source Initiative website.
Compilation requirements: Some R packages include internal code that must be compiled for them to function correctly. The rmarkdown package does not have compilation requirements.
Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The rmarkdown package has the following required dependencies: R (>= 3.0).
Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The rmarkdown package has the following suggested dependencies: digest, dygraphs, fs, rsconnect, downlit (>= 0.4.0), katex (>= 1.4.0), sass (>= 0.4.0), shiny (>= 1.6.0), testthat (>= 3.0.3), tibble, vctrs, cleanrmd, withr (>= 2.4.2).
External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The rmarkdown package does not use any external sources.
Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The rmarkdown package has the following imported packages: bslib (>= 0.2.5.1), evaluate (>= 0.13), fontawesome (>= 0.5.0), htmltools (>= 0.5.1), jquerylib, jsonlite, knitr (>= 1.22), methods, stringr (>= 1.2.0), tinytex (>= 0.31), tools, utils, xfun (>= 0.36), yaml (>= 2.1.19).
Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The rmarkdown package has no enhancements.

How to get help with the rmarkdown package?

In this section, we’ll discuss a variety of available resources for getting help with the rmarkdown package.

Key resources

The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("rmarkdown") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
Package website: The rmarkdown package has a dedicated website. You can visit: https://github.com/rstudio/rmarkdown, https://pkgs.rstudio.com/rmarkdown/.
Developer support: You can email Yihui Xie . For contact information, visit our R community directory.

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Discussion forums: Online forums are excellent platforms to ask questions, share knowledge, and troubleshoot issues. The most popular forums for R programmers are StackOverflow and Posit Community.

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