[1] 1 645 329Introduction to R
Using R Studio
An IDE for R
An integrated development environment is software that makes coding easier
- see objects you’ve imported and created
- autocomplete
- syntax highlighting
- run part or all of your code
Start fresh
- If you have used R previously, an old workspace may still be active when you open RStudio
- You always want to start with a fresh session
- Go to Tools -> Global Options, and under General, change these settings:
Tip
Now, you can just quit and restart RStudio if something goes wrong! You can also go to Session -> Restart R to clear your session.
Demo
Packages
- Some functions are built into R
mean(),lm(),table(), etc.
- They actually come from built-in packages
base,stats,graphics, etc.
- Anyone (yes, anyone) build their own package to add to the functionality of R
{ggplot2},{dplyr},{data.table},{survival}, etc.
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Packages
- You have to install a package once1
- You then have to load the package every time you want to use it
Packages
“You only have to buy the book once, but you have to go get it out of the bookshelf every time you want to read it.”
Several days later…
Package details
- When you use
install.packages, packages are downloaded from CRAN (The Comprehensive R Archive Network)- This is also where you downloaded R
- Packages can be hosted lots of other places, such as Bioconductor (for bioinformatics), and Github (for personal projects or while still developing)
- The folks at CRAN check to make things “work” in some sense, but don’t check on the statistical methods…
- But because R is open-source, you can always read the code yourself
- Two functions from different packages can have the same name… if you load them both, you may have some trouble
Demo
Using R
The biggest difference between R and Stata is that R can have many different objects in its environment
- datasets, numbers, figures, etc.
- you have to be explicit about storing and retrieving objects
- e.g., what dataset a variable belongs to
R uses <- to store objects in the environment
I call this the “assignment arrow”
Now vals holds those values
Warning
No assignment arrow means that the object will be printed to the console (and lost forever!)
Objects
We can retrieve those values by running just the name of the object
We can also perform operations on them using functions like mean()
[1] 325If we want to keep the result of that operation, we need to use <- again
Types of data (classes)
We could also create a character vector:
[1] "dog" "cat" "rhino"Or a logical vector:
[1] TRUE FALSE FALSETip
We’ll see more options as we go along!
Types of objects
We created vectors with the c() function (c stands for concatenate)
We could also create a matrix of values with the matrix() function:
[,1] [,2] [,3]
[1,] 234 12 183
[2,] 7456 654 753Indices
The numbers in square brackets are indices, which we can use to pull out values:
[1] "cat"We can pull out rows or columns from matrices:
[1] 7456 654 753[1] 234 7456Demo
Introduction to R