An R package that provides access to the code and data sets published by FiveThirtyEight https://github.com/fivethirtyeight/data. Note that while we received guidance from editors at 538, this package is not officially published by 538.
Get the latest released version from CRAN:
Or the development version from GitHub:
# If you haven't installed the remotes package yet, do so: # install.packages("remotes") remotes::install_github("rudeboybert/fivethirtyeight", build_vignettes = TRUE)
All data in the
fivethirtyeight package are lazy-loaded, so you can access any dataset without running
To see a detailed list of all 128 datasets, including information on the corresponding articles published on FiveThirtyEight.com, click here.
There are also 19 datasets that could not be included in
fivethirtyeight due to CRAN package size restrictions:
#>  "castle_solutions" "castle_solutions_2" #>  "castle_solutions_3" "comic_characters" #>  "goose" "house_district_forecast" #>  "mayweather_mcgregor_tweets" "mlb_elo" #>  "nba_all_elo" "nba_carmelo" #>  "nba_elo" "nfl_elo" #>  "quasi_winshares" "raptor_by_player" #>  "raptor_by_team" "ratings" #>  "senators" "spi_matches" #>  "twitter_presidents"
These 19 datasets are included in the
fivethirtyeightdata add-on package, which you can install by running:
install.packages('fivethirtyeightdata', repos = 'https://fivethirtyeightdata.github.io/drat/', type = 'source')
So for example, to load the
senators dataset, run:
fivethirtyeight package was featured in The fivethirtyeight R Package: “Tame Data” Principles for Introductory Statistics and Data Science Courses by Kim, Ismay, and Chunn (2018) published in Volume 11, Issue 1 of the journal “Technology Innovations in Statistics Education”.
Abstract: As statistics and data science instructors, we often seek to use data in our courses that are rich, real, realistic, and relevant. To this end we created the fivethirtyeight R package of data and code behind the stories and interactives at the data journalism website FiveThirtyEight.com. After a discussion on the conflicting pedagogical goals of “minimizing prerequisites to research” (Cobb 2015) while at the same time presenting students with a realistic view of data as it exists “in the wild,” we articulate how a desired balance between these two goals informed the design of the package. The details behind this balance are articulated as our proposed “Tame data principles for introductory statistics and data science courses.” Details of the package’s construction and example uses are included as well.
For some data sets, there are user-contributed example analyses in the form a package vignette. For example, look at “Bechdel analysis using the
tidyverse” based on the
bechdel dataset used in the article The Dollar-And-Cents Case Against Hollywood’s Exclusion of Women. For a complete list of vignettes run
vignette("user_contributed_vignettes", package = "fivethirtyeightdata")
bechdelvignette during his rstudio::conf talk in Orlando, Florida in January 2017. The video of his talk is available here.