https://github.com/mgimond/tukeyedar
An R package of Tukey inspired exploratory data analysis functions
https://github.com/mgimond/tukeyedar
eda r tukey
Last synced: 6 months ago
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An R package of Tukey inspired exploratory data analysis functions
- Host: GitHub
- URL: https://github.com/mgimond/tukeyedar
- Owner: mgimond
- License: other
- Created: 2017-12-25T18:08:20.000Z (over 8 years ago)
- Default Branch: main
- Last Pushed: 2025-08-01T14:51:34.000Z (12 months ago)
- Last Synced: 2025-08-01T16:34:46.574Z (12 months ago)
- Topics: eda, r, tukey
- Language: R
- Homepage: https://mgimond.github.io/tukeyedar/
- Size: 135 MB
- Stars: 13
- Watchers: 2
- Forks: 1
- Open Issues: 3
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
bibliography: ref.bib
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# tukeyedar
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://github.com/mgimond/tukeyedar/actions/workflows/R-CMD-check.yaml)
The `tukeyedar` package houses data exploration tools. Many functions are inspired by work published by
@eda1977, @understanding_eda1983, @applied_eda1981, and @visdata1993.
> 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
The package is available from [GitHub](https://github.com/mgimond/tukeyedar/). It can be installed using the following command:
```{r eval = FALSE}
install.packages("remotes")
remotes::install_github("mgimond/tukeyedar")
```
Note that the vignettes may 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.
```{r eval = FALSE}
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.
```{r eval = FALSE}
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:
- [A detailed rundown of the resistant line function](https://mgimond.github.io/tukeyedar/articles/RLine.html)
- [The median polish](https://mgimond.github.io/tukeyedar/articles/polish.html)
- [The empirical QQ plot](https://mgimond.github.io/tukeyedar/articles/qq.html)
- [The symmetry QQ plot](https://mgimond.github.io/tukeyedar/articles/symqq.html)
- [The residual-fit spread plot](https://mgimond.github.io/tukeyedar/articles/rfs.html)
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 `tukeyedar` 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:
```{r, fig.height=2.6, fig.width = 3.2, eval=FALSE}
library(tukeyedar)
eda_3pt(mtcars, disp, mpg)
```
Note that most functions are *pipe* friendly. For example:
```{r eval=FALSE}
# Using R >= 4.1
mtcars |> eda_3pt(disp, mpg)
# Using magrittr (or any of the tidyverse packages)
library(magrittr)
mtcars %>% eda_3pt(disp, mpg)
```
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