Datasets from the Datasaurus Dozen

The Datasaurus Dozen is a set of datasets with the same summary statistics. They retain the same summary statistics despite having radically different distributions. The datasets represent a larger and quirkier object lesson that is typically taught via Anscombe's Quartet (available in the 'datasets' package). Anscombe's Quartet contains four very different distributions with the same summary statistics and as such highlights the value of visualisation in understanding data, over and above summary statistics. As well as being an engaging variant on the Quartet, the data is generated in a novel way. The simulated annealing process used to derive datasets from the original Datasaurus is detailed in "Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing" .

datasauRus

This package wraps the awesome Datasaurus Dozen datasets. The Datasaurus Dozen show us why visualisation is important – summary statistics can be the same but distributions can be very different. In short, this package gives a fun alternative to Anscombe’s Quartet, available in R as anscombe.

The original Datasaurus was created by Alberto Cairo. The other Dozen were generated using simulated annealing and the process is described in the paper “Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing” by Justin Matejka and George Fitzmaurice (open access materials including manuscript and code, official paper).

In the paper, Justin and George simulate a variety of datasets that the same summary statistics to the Datasaurus but have very different distributions.

Install

The latest stable version is available on CRAN

install.packages("datasauRus")

You can get the latest development version from GitHub, so use {devtools} to install the package

devtools::install_github("jumpingrivers/datasauRus")

Usage

You can use the package to produce Anscombe plots and more.

library("ggplot2")
library("datasauRus")
ggplot(datasaurus_dozen, aes(x = x, y = y, colour = dataset))+
  geom_point() +
  theme_void() +
  theme(legend.position = "none")+
  facet_wrap(~dataset, ncol = 3)

Code of Conduct

Please note that the datasauRus project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms