All components of R come in packages (compressed files with code and data inside) that are stored in one of two places on a computer: (1) a user's personal library OR (2) in a system-wide library available to all users. You'll be placing packages in your personal library as you don't have administrative credentials on the Mac Mini.
When R is installed it comes with 'base' packages for working with files, simple
graphing, statistics, and working with the operating system (likely macOS in your case).
When you start a new session (aka "instance") these 'base' packages are loaded
from your library. Other packages, like those you download from tidyverse or elsewhere, can
be loaded with the R command library
library(foo)
library(boo)
library(tidyverse)
There are many-many-many-many R packages out there. Most, but not all, are uploaded by volunteers to CRAN (comprehensive R archive network). Brace yourself before looking...
Other packages are distributed from other places - notably github like Bigelow's account at BLOS Github At Bigelow's gihub site there are 100 repositories of packages (for a variety of languages like R, Python, java, etc). Some are public for all to see and some are private.
Within an R session (like a session within RStudio) you can install packages using ...
# see https://cran.r-project.org/web/packages/RColorBrewer/index.html
install.packages("RColorBrewer")
... but generally we have installed all that you need already. If you do need to install a package on your own, you may be prompted to select one of the many-many-many CRAN mirror servers which will then serve up the package you want to download. I usually select one that is physically close (like eastern North America). If you need help please just ask!
We use R packages dplyr,
magrittr and
readr They belong to
a large family of packages, called the tidyverse, designed to play well together.
Here is the link to tidyverse
It's important to keep in mind that as in any language there are different ways to skin a cat. The tidyverse team thinks they have the best way which is why they say on their front page "tidyverse is an opinionated collection of R packages designed for data science".
After you get a chance to check out tidyverse you might want to try out a free online tutorial
If you get stumped you can always google, but I also suggest you give RSeek.org a try ...
http://rseek.org/?q=tidyr+tutorial
In fact, be sure to add RSeek as one of your browser's search engines.
The raster is one of the R's answers to handling gridded spatial data. It comes with a nice vignette