Office hours will always be held at the same Zoom link.

RStudio is an Integrated Development Environment (IDE) for R

• Helps you write code - makes suggestions
• Helps you view the output of your code
• Helps you find errors
• Is NOT a dropdown statistical tool (such as Stata)
  • See Rcmdr or Radiant

_[source]

RStudio used to be the name of a company that is now called Posit.

Easier working with R

• Syntax highlighting, code completion, and smart indentation
• Easily manage multiple working directories and projects

More information

• Workspace browser and data viewer
• Plot history, zooming, and flexible image and file export
• Integrated R help and documentation

First it is important to be familiar with the layout. When you first open RStudio, you will see 3 panes.

To save a copy of your code. You must open a file first - this will open a 4th pane. These files include Scripts or what are called R Markdown files.

You will see a popup that you can just say “OK” to for now.

Nice! now we have a place to save code! This is where we will mostly be working.

1. The Source/Editor: “Analysis” Script + Interactive Exploration
   • Static copy of what you did (reproducibility)
   • Top by default
2. The R Console: “interprets” whatever you type
   • Calculator
   • Try things out interactively, then add to your editor
   • Bottom by default

• Where files open to
• Have R code and comments in them
• Can highlight and press (CMD+Enter (Mac) or Ctrl+Enter (Windows)) to run the code

In a .R file (we call a script), code is saved on your disk

• Where code is executed (where things happen)
• You can type here for things interactively to test code
• Code is not saved on your disk

Super useful “cheat sheet”: LINK

It will look like this with text in it, unlike a script.

Although people will use scripts often, and they are good for more programmatic purposes, we generally don’t recommend them for Public Health Researchers.

For data analyses, R Markdown files are generally superior because they allow you to check your code and write more info about your code.

• Tells you what objects are in R
• What exists in memory/what is loaded?/what did I read in?

History

• Shows previous commands. Good to look at for debugging, but don’t rely on it.
  Instead use RMarkdown!
• Also type the “up” key in the Console to scroll through previous commands

• Files - shows the files on your computer of the directory you are working in
• Viewer - can view data or R objects
• Help - shows help of R commands
• Plots - pictures and figures
• Packages - list of R packages that are loaded in memory

If RStudio doesn’t look the way you want (or like our RStudio), then:

Click on the pane button, which looks like a waffle with 4 indentations. Scroll down to “Pane Layout”.

💻 RStudio Lab

To do this lab we need to:

• Download the file at the link above by clicking on it or go to the website schedule page
• Find the downloaded file on your computer
• Open the file in RStudio (double clicking the file name typically works)

These videos can help if you aren’t sure where your downloads are:

If you have a PC: https://youtu.be/we6vwB7DsNU

If you have a Mac: https://www.youtube.com/watch?v=Ao9e0cDzMrE

You can find these on the resource page of the class website.

R Markdown files (.Rmd) help generate reports that include your code and output. Think of them as fancier scripts.

1. Helps you describe your code
2. Allows you to check the output
3. Can create many different file types

Go to File → New File → R Markdown or click the green add file button.

Within R Markdown files are code “chunks”.

This is where you can type R code and run it!

Clicking the run (play) button runs the code in the chunk.

Ctrl + Enter on Windows or Command + Enter on Mac in your script evaluates that line of code

• generally see a preview of the output of the code just below the chunk
• see the code in the console

See the Help page of the website. You can adjust this and change your RStudio settings:

Tools > Global Options > Appearance

Running all chunks - this will create a report from the R Markdown document!

This generates a nice report that you can share with others who can open in any browser.

To create a new R code chunk:

• Use the insert code chunk button at the top of RStudio.

• Select R (default) as the language:

If you like keyboard shortcuts:

• Windows & Linux use Ctrl+Alt+I
• Mac use Command+Option+I

I is for insert.

You can run all chunks above a specific chunk using this button:

You can specify if a chunk will be seen in the report or not.

R studio can help you find issues in your code. Note that sometimes the error occurs earlier than RStudio thinks.

• Ctrl + Enter on Windows or Command + Enter on Mac in your script evaluates that line of code
  • It’s like copying and pasting the code into the console for it to run.
• Ctrl+1 on Windows or Command + 1 on Mac takes you to the script page
• Ctrl+2 on Windows or Command + 2 on Mac takes you to the console
• http://www.rstudio.com/ide/docs/using/keyboard_shortcuts

• you can test code in the console

• you can save code in a chunk in the editor (Markdown file)

When you type in a function name, a pop up will preview documentation to help you. It also helps you remember the name of the function if you don’t remember all of it!

If you know the name of a package or function:

Type ?package_name or ?function_name in the console to get information about packages and functions.

For example: ?readr or ?read_csv.

If you haven’t loaded a package yet into R than you may get a response that there is no documentation.

Typing in ??package_name can show you packages that you haven’t loaded yet.

• RStudio makes working in R easier
• the Editor (top) is for static code like scripts or R Markdown documents
• The console is for testing code (bottom) - best to save your code though!
• R markdown documents are really helpful for lots of reasons!
• R code goes within what is called a chunk (the gray box with a green play button)
• Code chunks can be modified so that they show differently in reports

🏠 Class Website

💻 Lab

Image by Gerd Altmann from Pixabay