R data packages are a wonderfully portable way of sharing data with others. Instead of providing your collaborators with several csv files and a lengthy data dictionary, you should consider building an R data package. With this approach, your potential user only needs to install the package and then load it with library(package_name) to access both the data and the documentation.
For the first mini-project of Math 241, the students created their own R data packages. Check out their GitHub repositories, which contain the package, installation instructions, and a useful example of how to use the package to answer interesting questions:
coral: Provides us with a tidy version of data from the extensive (but also overwhelming) Coral Trait database. Learn all about the species and characteristics of the corals of the world without leaving your R session.
DcTreePops: Contains spatial data on the trees and people of Washington D.C. Use these data to explore fascinating relationships between population and tree density.
denverweed: Strives to give (let’s quote the ReadMe) “insight into the trials and tribulations undergone by America’s favorite smokeable/tokeable 5-to-13 leafletted plant”. Need I say more.
elephants: Showcases, you guessed it, elephants! Use these data to learn all about those beautiful gray creatures.
india.air: Strives to make Indian air pollution data easily accessible. These data are all ready to be transformed into poetic line graphs of various pollution measurements across major cities in India!
pitchR: Is for all the sabermetric nuts out there! Consider this your R data source for baseball stats.
RCLC: Provides its user with an easy-to-use dataset of the book checkouts from the Reed College libraries. Former Reedies should use these data to see if their thesis has been checked out recently!
suncats: Features information on cats registered with the Sunshine Coast region of Queensland, Australia. This package is perfect for all the cat lovers out there!
TarantinoData: Provides Quentin Tarantino fans with the ultimate data of the profanities in his films. Spoiler alert: There are a lot of rows in this dataset!
topPolluters: Gives easy access to data on the top US polluters of 2018 and the impacted communities. Use these data to shine a light on important environmental justice issues!