- By default, R Markdown produces standalone HTML files with no external dependencies, using data: URIs to incorporate the contents of linked scripts, stylesheets, images, and videos. This means you can share or publish the file just like you share Office documents or PDFs.
- QuestionWithin a code chunk in an R Markdown (.Rmd) document how do you parse a string containing new line characters n, to display the text on new lines?Data and exampleI would like to pars.
- The author of the packages knitr and bookdown suggests knitr::kable as the most appropriate solution for multi-format output from R Markdown, particularly if you want tables with captions and automatic labels for internal reference+link. See here – FairMiles Oct 31 '17 at 18:34.
Interactive documents are a new way to build Shiny apps. An interactive document is an R Markdown file that contains Shiny widgets and outputs. You write the report in markdown, and then launch it as an app with the click of a button.
This article will show you how to write an R Markdown report.
RStudio’s knit button renders a file to the first format listed in its output field. You can render to additional formats by clicking the dropdown menu beside the knit button. 29.2 Output options Each output format is associated with an R function. R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Does macbook air continue to download while sleeping. The companion article, Introduction to interactive documents, will show you how to turn an R Markdown report into an interactive document with Shiny components.
R Markdown
R Markdown is a file format for making dynamic documents with R. An R Markdown document is written in markdown (an easy-to-write plain text format) and contains chunks of embedded R code, like the document below.
R Markdown files are designed to be used with the rmarkdown package. rmarkdown comes installed with the RStudio IDE, but you can acquire your own copy of rmarkdown from CRAN with the command
R Markdown files are the source code for rich, reproducible documents. You can transform an R Markdown file in two ways.
knit - You can knit the file. The
rmarkdownpackage will call theknitrpackage.knitrwill run each chunk of R code in the document and append the results of the code to the document next to the code chunk. This workflow saves time and facilitates reproducible reports.Consider how authors typically include graphs (or tables, or numbers) in a report. The author makes the graph, saves it as a file, and then copy and pastes it into the final report. This process relies on manual labor. If the data changes, the author must repeat the entire process to update the graph.
In the R Markdown paradigm, each report contains the code it needs to make its own graphs, tables, numbers, etc. The author can automatically update the report by re-knitting.
convert - You can convert the file. The
rmarkdownpackage will use thepandocprogram to transform the file into a new format. For example, you can convert your .Rmd file into an HTML, PDF, or Microsoft Word file. You can even turn the file into an HTML5 or PDF slideshow.rmarkdownwill preserve the text, code results, and formatting contained in your original .Rmd file.Conversion lets you do your original work in markdown, which is very easy to use. You can include R code to knit, and you can share your document in a variety of formats.
In practice, authors almost always knit and convert their documents at the same time. In this article, I will use the term render to refer to the two step process of knitting and converting an R Markdown file.
Markdown Cheatsheet Pdf
You can manually render an R Markdown file with rmarkdown::render(). This is what the above document looks like when rendered as a HTML file.
In practice, you do not need to call rmarkdown::render(). You can use a button in the RStudio IDE to render your reprt. R Markdown is heavily integrated into the RStudio IDE.
Getting started
To create an R Markdown report, open a plain text file and save it with the extension .Rmd. You can open a plain text file in your scripts editor by clicking File > New File > Text File in the RStudio toolbar.
Be sure to save the file with the extension .Rmd. The RStudio IDE enables several helpful buttons when you save the file with the .Rmd extension. You can save your file by clicking File > Save in the RStudio toolbar.
R Markdown reports rely on three frameworks
- markdown for formatted text
knitrfor embedded R code- YAML for render parameters
The sections below describe each framework.
Markdown for formatted text
.Rmd files are meant to contain text written in markdown. Markdown is a set of conventions for formatting plain text. You can use markdown to indicate
- bold and italic text
- lists
- headers (e.g., section titles)
- hyperlinks
- and much more
The conventions of markdown are very unobtrusive, which make Markdown files easy to read. The file below uses several of the most useful markdown conventions.
The file demonstrates how to use markdown to indicate:
headers - Place one or more hashtags at the start of a line that will be a header (or sub-header). For example,
# Say Hello to markdown. A single hashtag creates a first level header. Two hashtags,##, creates a second level header, and so on.italicized and bold text - Surround italicized text with asterisks, like this
*without realizing it*. Surround bold text with two asterisks, like this**easy to use**.lists - Group lines into bullet points that begin with asterisks. Leave a blank line before the first bullet, like this
hyperlinks - Surround links with brackets, and then provide the link target in parentheses, like this
[Github](www.github.com).
You can learn about more of markdown’s conventions in the Markdown Quick Reference guide, which comes with the RStudio IDE.
To access the guide, open a .md or .Rmd file in RStudio. Then click the question mark that appears at the top of the scripts pane. Next, select “Markdown Quick Reference”. RStudio will open the Markdown Quick Reference guide in the Help pane.
Rendering
To transform your markdown file into an HTML, PDF, or Word document, click the “Knit” icon that appears above your file in the scripts editor. A drop down menu will let you select the type of output that you want.
When you click the button, rmarkdown will duplicate your text in the new file format. rmarkdown will use the formatting instructions that you provided with markdown syntax.
Once the file is rendered, RStudio will show you a preview of the new output and save the output file in your working directory.
Here is how the markdown script above would look in each output format.
Note: RStudio does not build PDF and Word documents from scratch. You will need to have a distribution of Latex installed on your computer to make PDFs and Microsoft Word (or a similar program) installed to make Word files.
knitr for embedded R code
The knitr package extends the basic markdown syntax to include chunks of executable R code. Why does visual studio mac download java sdk.
When you render the report, knitr will run the code and add the results to the output file. You can have the output display just the code, just the results, or both.
To embed a chunk of R code into your report, surround the code with two lines that each contain three backticks. After the first set of backticks, include {r}, which alerts knitr that you have included a chunk of R code. The result will look like this
When you render your document, knitr will run the code and append the results to the code chunk. knitr will provide formatting and syntax highlighting to both the code and its results (where appropriate).
As a result, the markdown snippet above will look like this when rendered (to HTML).
To omit the results from your final report (and not run the code) add the argument eval = FALSE inside the brackets and after r. This will place a copy of your code into the report.
To omit the code from the final report (while including the results) add the argument echo = FALSE. This will place a copy of the results into your report.
echo = FALSE is very handy for adding plots to a report, since you usually do not want to see the code that generates the plot.
echo and eval are not the only arguments that you can use to customize code chunks. You can learn more about formatting the output of code chunks at the rmarkdown and knitr websites.
Inline code
To embed R code in a line of text, surround the code with a pair of backticks and the letter r, like this.
knitr will replace the inline code with its result in your final document (inline code is always replaced by its result). The result will appear as if it were part of the original text. For example, the snippet above will appear like this:
YAML for render parameters
You can use a YAML header to control how rmarkdown renders your .Rmd file. A YAML header is a section of key: value pairs surrounded by --- marks, like below
The output: value determines what type of output to convert the file into when you call rmarkdown::render(). Note: you do not need to specify output: if you render your file with the RStudio IDE knit button.
output: recognizes the following values:
html_document, which will create HTML output (default)pdf_document, which will create PDF outputword_document, which will create Word output
If you use the RStudio IDE knit button to render your file, the selection you make in the gui will override the output: setting.
Slideshows
You can also use the output: value to render your document as a slideshow.
output: ioslides_presentationwill create an ioslides (HTML5) slideshowoutput: beamer_presentationwill create a beamer (PDF) slideshow
Note: The knit button in the RStudio IDE will update to show slideshow options when you include one of the above output values and save your .Rmd file.
rmarkdown will convert your document into a slideshow by starting a new slide at each header or horizontal rule (e.g., ***).
Visit rmakdown.rstudio.com to learn about more YAML options that control the render process.
Recap
R Markdown documents provide quick, reproducible reporting from R. You write your document in markdown and embed executable R code chunks with the knitr syntax.
You can update your document at any time by re-knitting the code chunks.
You can then convert your document into several common formats.
R Markdown Formatting
R Markdown documents implement Donald’s Knuth’s idea of literate programming and take the manual labor out of writing and maintaining reports. Moreover, they are quick to learn. You already know ecnough about markdown, knitr, and YAML to begin writing your own R Markdown reports.
In the next article, Introduction to interactive documents, you will learn how to add interactive Shiny components to an R Markdown report. This creates a quick workflow for writing light-weight Shiny apps.
To learn more about R Markdown and interactive documents, please visit rmarkdown.rstudio.com.
Note: This book has been published by Chapman & Hall/CRC. The online version of this book is free to read here (thanks to Chapman & Hall/CRC), and licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The document format “R Markdown” was first introduced in the knitr package (Xie 2015, 2021b) in early 2012. The idea was to embed code chunks (of R or other languages) in Markdown documents. In fact, knitr supported several authoring languages from the beginning in addition to Markdown, including LaTeX, HTML, AsciiDoc, reStructuredText, and Textile. Looking back over the five years, it seems to be fair to say that Markdown has become the most popular document format, which is what we expected. The simplicity of Markdown clearly stands out among these document formats.
However, the original version of Markdown invented by John Gruber was often found overly simple and not suitable to write highly technical documents. For example, there was no syntax for tables, footnotes, math expressions, or citations. Fortunately, John MacFarlane created a wonderful package named Pandoc (http://pandoc.org) to convert Markdown documents (and many other types of documents) to a large variety of output formats. More importantly, the Markdown syntax was significantly enriched. Now we can write more types of elements with Markdown while still enjoying its simplicity.
In a nutshell, R Markdown stands on the shoulders of knitr and Pandoc. The former executes the computer code embedded in Markdown, and converts R Markdown to Markdown. The latter renders Markdown to the output format you want (such as PDF, HTML, Word, and so on).
The rmarkdown package (Allaire, Xie, McPherson, et al. 2021) was first created in early 2014. During the past four years, it has steadily evolved into a relatively complete ecosystem for authoring documents, so it is a good time for us to provide a definitive guide to this ecosystem now. At this point, there are a large number of tasks that you could do with R Markdown:
Compile a single R Markdown document to a report in different formats, such as PDF, HTML, or Word.
Create notebooks in which you can directly run code chunks interactively.
Make slides for presentations (HTML5, LaTeX Beamer, or PowerPoint).
Produce dashboards with flexible, interactive, and attractive layouts.
Build interactive applications based on Shiny.
Write journal articles.
Author books of multiple chapters.
Generate websites and blogs.
There is a fundamental assumption underneath R Markdown that users should be aware of: we assume it suffices that only a limited number of features are supported in Markdown. By “features,” we mean the types of elements you can create with native Markdown. The limitation is a great feature, not a bug. R Markdown may not be the right format for you if you find these elements not enough for your writing: paragraphs, (section) headers, block quotations, code blocks, (numbered and unnumbered) lists, horizontal rules, tables, inline formatting (emphasis, strikeout, superscripts, subscripts, verbatim, and small caps text), LaTeX math expressions, equations, links, images, footnotes, citations, theorems, proofs, and examples. We believe this list of elements suffice for most technical and non-technical documents. It may not be impossible to support other types of elements in R Markdown, but you may start to lose the simplicity of Markdown if you wish to go that far.
R Markdown Text Formatting
Epictetus once said, “Wealth consists not in having great possessions, but in having few wants.” The spirit is also reflected in Markdown. If you can control your preoccupation with pursuing typesetting features, you should be much more efficient in writing the content and can become a prolific author. It is entirely possible to succeed with simplicity. Jung Jae-sung was a legendary badminton player with a remarkably simple playing style: he did not look like a talented player and was very short compared to other players, so most of the time you would just see him jump three feet off the ground and smash like thunder over and over again in the back court until he beats his opponents.
Please do not underestimate the customizability of R Markdown because of the simplicity of its syntax. In particular, Pandoc templates can be surprisingly powerful, as long as you understand the underlying technologies such as LaTeX and CSS, and are willing to invest time in the appearance of your output documents (reports, books, presentations, and/or websites). As one example, you may check out the PDF report of the 2017 Employer Health Benefits Survey. It looks fairly sophisticated, but was actually produced via bookdown(Xie 2016), which is an R Markdown extension. A custom LaTeX template and a lot of LaTeX tricks were used to generate this report. Not surprisingly, this very book that you are reading right now was also written in R Markdown, and its full source is publicly available in the GitHub repository https://github.com/rstudio/rmarkdown-book.
R Markdown Tutorial
R Markdown documents are often portable in the sense that they can be compiled to multiple types of output formats. Again, this is mainly due to the simplified syntax of the authoring language, Markdown. The simpler the elements in your document are, the more likely that the document can be converted to different formats. Similarly, if you heavily tailor R Markdown to a specific output format (e.g., LaTeX), you are likely to lose the portability, because not all features in one format work in another format.
Last but not least, your computing results will be more likely to be reproducible if you use R Markdown (or other knitr-based source documents), compared to the manual cut-and-paste approach. This is because the results are dynamically generated from computer source code. If anything goes wrong or needs to be updated, you can simply fix or update the source code, compile the document again, and the results will be automatically updated. You can enjoy reproducibility and convenience at the same time.