The old-fashioned way to work in RStudio is to have a
script window on the right and the console window on the left. The
console operates like a terminal, with text commands given as input and
text output immediately below.
Comments in the console are preceded by a # sign. You
can have them anywhere in the line, but they are ignored by R.
Two tricks here:
Ctrl + R, which searches the history. If you type a
few characters the search will filter based on them, which is a quick
way to narrow down what you want.The alternative paradigm we are working with minimizes the need for a console since notes, code, and output are all entered in the journal/script window.
This is an R Markdown file. Think of it as a code notebook where you
can take notes, write code, and produce a reproducible document that
records your work. R Markdown is a file format for making dynamic
documents with R. It allows you to combine code, results, and narrative
in a single document, making it an essential tool for reproducible
research and dynamic reporting. R Markdown files have the extension
.Rmd. R Markdown is useful for working with code and text
in RStudio. But more than that, it is used to author various output
formats, including:
NB: There is a more advanced version of R Markdown called Quarto, but we will not be using it in this course.
For more details on using R Markdown, see http://R Markdown.rstudio.com. For a quick reference, click File -> Help -> Markdown Quick Reference. For a PDF cheat sheet, click File -> Help -> Cheat Sheets -> R Markdown Cheat Sheet. For the best free book on Markdown called R Markdown: The Definitive Guide by Yihui Xie, J. J. Allaire, and Garrett Grolemund, see https://bookdown.org/yihui/R Markdown/.
R Markdown provides a seamless way to integrate text, code, and results, ensuring that your analysis is transparent and reproducible. It is highly flexible, allowing you to produce different types of documents (reports, presentations, websites) from the same source file. This versatility makes it a popular choice among researchers and data analysts. Using R Markdown ensures that your work is easily shareable and that others can replicate your analysis without difficulty.
To create a new R Markdown document in RStudio:
File -> New File -> R Markdown.OK to generate a new R Markdown file with some
example content.Knit button to render the document into the
desired output format.An R Markdown document consists of three main components:
R Markdown is based on Markdown which is first and foremost a lightweight markup language with plain text formatting syntax. Here are some basic elements you should already see me using in this document:
# for H1,
## for H2, and so on.** or
__.* or
_.- or * for
unordered lists, and numbers for ordered lists.[Link Text](URL)A code chunk is a specially delimited section of the file and allow you to embed R code in your R Markdown document. You can add one by moving the cursor to a blank line and choosing Code > Insert Chunk from the RStudio menu, clicking the +C button at the top right of the editor window, or pressing CTRL-I (on Windows/Linux) or CMD-Option-I (on Mac). An empty chunk will appear:
Code chunks are delimited by three backticks (found to the left of
the 1 key on US and UK keyboards) at the start and end. Each chunk
starts with three backticks followed by {r} to indicate the
R language, and ends with three backticks. Write your code
inside the code chunks. Write your notes and other material
around them, as shown here.
You can control the behavior and appearance of code chunks using
chunk options. For example, echo=FALSE will hide the code
but show the output, and eval=FALSE will prevent the code
from being executed.
## [1] "2025-04-29"Sys.Date()When you click the Knit button (the icon at the top of the RStudio window that looks like a ball of thread and needle), a document is generated that includes both content and the output of any embedded R code chunks within the document.
Let’s go deeper into a typical way we’d begin an R Markdown document.
To begin, we set up some options. Notice that the braces at the start
of the code chunk have additional options. The language r
is required. The setup is a label for your code chunk.
Labels are useful for briefly describing what the chunk does. Label
names must be unique (no two chunks in the same document can have the
same label) and cannot contain spaces. After the comma, the option
include=FALSE is set, which tells R to run this code but
not include the output in the final document.
Then we must load some libraries we will be using. If we do not load them, R will not be able to find the functions contained in these libraries. Currently, we’re just using the gapminder package.
If we execute code inside a chunk, we get output right below the
chunk. For example, here is the output of the head()
function applied to the gapminder dataset.
head(gapminder,n=20)## # A tibble: 20 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Afghanistan Asia 1952 28.8 8425333 779.
## 2 Afghanistan Asia 1957 30.3 9240934 821.
## 3 Afghanistan Asia 1962 32.0 10267083 853.
## 4 Afghanistan Asia 1967 34.0 11537966 836.
## 5 Afghanistan Asia 1972 36.1 13079460 740.
## 6 Afghanistan Asia 1977 38.4 14880372 786.
## 7 Afghanistan Asia 1982 39.9 12881816 978.
## 8 Afghanistan Asia 1987 40.8 13867957 852.
## 9 Afghanistan Asia 1992 41.7 16317921 649.
## 10 Afghanistan Asia 1997 41.8 22227415 635.
## 11 Afghanistan Asia 2002 42.1 25268405 727.
## 12 Afghanistan Asia 2007 43.8 31889923 975.
## 13 Albania Europe 1952 55.2 1282697 1601.
## 14 Albania Europe 1957 59.3 1476505 1942.
## 15 Albania Europe 1962 64.8 1728137 2313.
## 16 Albania Europe 1967 66.2 1984060 2760.
## 17 Albania Europe 1972 67.7 2263554 3313.
## 18 Albania Europe 1977 68.9 2509048 3533.
## 19 Albania Europe 1982 70.4 2780097 3631.
## 20 Albania Europe 1987 72 3075321 3739.When you click the Knit button, a document is generated that includes both content and the output of any embedded R code chunks within the document. You can knit to HTML or PDF.
Try knitting this document now by clicking the “Knit” button in the RStudio toolbar, or choosing File > Knit Document from the RStudio menu.
Now that we have an HTML file, we can publish it to the web with a few clicks using RPubs. How cool is that?
Let’s try knitting to a PDF, too. Notice the fonts change to a serif font (specifically, Computer Modern, written by Don Knuth in the 1980s!) more appropriate for the printed page.
Now let’s explore some other parts of the RStudio interface.
Let’s start with the Global Options. Click on the “Tools” menu, then “Global Options”. You can change the appearance of RStudio, the default working directory, and many other settings here.
While most of the default settings are fine, let’s make some quick changes that I think will give you a better time.
The RStudio toolbar provides buttons for common tasks such as saving,
opening files, and knitting documents. Many tasks can also be performed
using keyboard shortcuts, which are useful for speeding up your
workflow. For example, you can use Ctrl + B for bold text
or Ctrl + I for italic text. Additionally, you can create
headers by typing # followed by a space for a first-level
header, ## for a second-level header, and so on.
RStudio provides two modes for editing R Markdown documents: source mode and visual mode.
Source Mode: This is the default mode where you write R Markdown code directly. It offers full control over the document’s content and structure.
Visual Mode: RStudio’s visual mode was introduced in 2021. It offers a Word processor-like WYSIWYG (What You See Is What You Get) interface for editing R Markdown documents, making it easier for users to format text, insert footnotes1, add images, and insert tables without needing to write raw Markdown syntax. This mode allows users to switch between source mode, where they can edit the raw R Markdown code, and visual mode, where they can see a live preview of the formatted document as they make changes. Visual mode streamlines the document creation process, particularly for those who are more comfortable with graphical interfaces, ensuring that the final output looks polished and professional with minimal effort. This is a useful tool, but you should be comfortable working in both interfaces.
There are keyboard shortcuts for all basic editing tasks which are
already available in the toolbar. Visual mode supports both traditional
keyboard shortcuts (e.g. ^B for bold or ^I for Italic) as well as
markdown shortcuts (using markdown syntax directly). For example,
enclose Bold text in asterisks or press CTRL-B to make
something bold. Or type ## and press space
to create a second level heading. Or select some text and press CTRL-K
to transform it into a hyperlink.
Use the forward slash (“/”) to insert many common items like lists, code chunks, and more.
Click the outline button on the top right of the RStudio window to
get a hierarchical overview of the current R Markdown document. This
feature helps you quickly navigate to different sections of your
document. Alternatively, you can use the section selector button at the
bottom middle of the RStudio interface to jump to specific
sections.
Like this one.↩︎