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tukeyedar

The tukeyedar package houses data exploration tools. Many functions are inspired by work published by Tukey (1977), Hoaglin (1983), Velleman and Hoaglin (1981), and Cleveland (1993).

This package was initially developed for an introductory course in Exploratory Data Analysis (EDA). As such, many of its functions have not undergone the rigorous testing and validation typically required for research or production use. Users are advised to exercise caution and verify results independently before applying the package in critical or high-stakes contexts.

Installation

You can install the development version of tukeyedar from GitHub with:

install.packages("remotes")
remotes::install_github("mgimond/tukeyedar")

Note that the vignettes will not be automatically generated with the above command, however, the vignettes are available on this website (see next section). If you want a local version of the vignettes, add the build_vignettes = TRUE parameter.

remotes::install_github("mgimond/tukeyedar", build_vignettes = TRUE)

If, for some reason the vignettes are not created, you might want to re-install the package with the force=TRUE parameter.

remotes::install_github("mgimond/tukeyedar", build_vignettes = TRUE, force=TRUE)

Vignettes

It’s strongly recommended that you read the vignettes. These can be accessed from this website:

If you chose to have the vignettes locally created when you installed the package, then you can view them locally via vignette("RLine", package = "tukeyedar"). If you use a dark themed IDE, the vignettes may not render very well so you might opt to view them in a web browser via the functions RShowDoc("RLine", package = "tukeyedar").

Using the functions

All functions start with eda_. For example, to generate a three point summary plot of the mpg vs. disp from the mtcars dataset, type:

library(tukeyedar)
eda_3pt(mtcars, disp, mpg)

Note that most functions are pipe friendly. For examples:

# Using R >= 4.1
mtcars |>  eda_3pt(disp, mpg)

# Using magrittr (or any of the tidyverse packages)
library(magrittr)
mtcars %>% eda_3pt(disp, mpg)
Cleveland, William. 1993. Visualizing Data. Hobart Press.
Hoaglin, Mosteller, D. C. 1983. Understanding Robust and Exploratory Data Analysis. Wiley.
Tukey, John W. 1977. Exploratory Data Analysis. Addison-Wesley.
Velleman, P. F., and D. C. Hoaglin. 1981. Applications, Basics and Computing of Exploratory Data Analysis. Boston: Duxbury Press.