RStudio Basics

Never worked with R?

If you have never worked with R, you can get a basic familiarity by going through this free tutorial. Takes about 4 hours.

You can also learn R straight from within R using the swirl package. This doesn’t require internet access except to install the package.

Here is another basic R introduction from ComputerWorld.

RStudio Overview

When you open RStudio you will see 4 panels:

RStudio-panels

Create an RStudio Project

1. In RStudio, choose “File->New Project…”
2. Then choose “New Directory” and then choose “Empty Project”
3. In the next dialog, choose a name (it is best to use only letters, numbers, dashes, and underscores, and include no spaces in the name).
   
4. Then click “Create Project”.

That should give you a new project.

Add a new script file

1. Add a new file using ‘File > New File > R Script’
2. Or you can click the new icon in top left corner.
3. Add some code to that file. Copy and paste in:

require(graphics)
## Annette Dobson (1990) "An Introduction to Generalized Linear Models".
## Page 9: Plant Weight Data.
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(lm.D9, las = 1)      # Residuals, Fitted, ...
par(opar)

Run the code

1. Select all the lines of code and select ‘Run’
2. Run all the code by selecting ‘Source’

Workflow basics

Read through the following sections of the R for Data Science book and work through the examples.

• Workflow basics: super basic review on how R works.
• Workflow: projects: info about organizing RStudio projects.
• Workflow: scripts: how to evaluate code in scripts.

R for Data Science is a great book to introduce you to working with data in R, but we are not going to be doing that in this workshop.