README.Rmd

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output: github_document
bibliography: ref.bib  
---

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knitr::opts_chunk$set(
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# tukeyedar

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The `tukeyedar` package houses data exploration tools. Many functions are inspired by work published by
@eda1977, @understanding_eda1983, @applied_eda1981, and @visdata1993. Note that this package is in beta mode, so use at your own
discretion. 

## Installation

You can install the development version of tukeyedar from [GitHub](https://github.com/) with:

```{r eval = FALSE}
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.

```{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 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 examples:

```{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)
```

------------------------------------------------------------------------