https://github.com/rpodcast/shinysaurus

Visualizing the datasauRus dozen in Shiny
https://github.com/rpodcast/shinysaurus

r rstats shiny

Last synced: about 1 month ago
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Visualizing the datasauRus dozen in Shiny

• Host: GitHub
• URL: https://github.com/rpodcast/shinysaurus
• Owner: rpodcast
• License: other
• Created: 2020-10-16T00:09:59.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2020-11-30T13:32:12.000Z (about 4 years ago)
• Last Synced: 2024-08-13T07:14:28.917Z (4 months ago)
• Topics: r, rstats, shiny
• Language: R
• Homepage: https://rpodcast.shinyapps.io/shinysaurus
• Size: 4.79 MB
• Stars: 10
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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• jimsghstars - rpodcast/shinysaurus - Visualizing the datasauRus dozen in Shiny (R)

README

        
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# shinysaurus

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)

ShinySaurus is an interactive application built with the R statistical computing language that lets you dive in to a very important issue in statistics with a fun web interface!  Each of the data sets present in this application come from the [Datasaurus Dozen](http://www.thefunctionalart.com/2016/08/download-datasaurus-never-trust-summary.html) collection authored by [Alberto Cairo](http://albertocairo.com), in which traditional summary statistics such as the average, standard deviation, and correlation are __very__ similar across the data sets, even with each giving a very different picture in the form of a scatterplot!

Within the application you can explore these data sets invidually and see how the aforementioned summary statistics are impacted by selection of data points. For some fun, you can visit the animate tab to produce detailed transition data sets between the different Datasaurus sets powered by the [{metamer}](https://eliocamp.github.io/metamer/) and [{plotly}](https://plotly-r.com/) packages.

A detailed walk-through of the application can be found in episode 32 of the [TidyX](https://www.youtube.com/watch?v=c7dZqyhd4a4) Screencast series!

To view the deployed version of the app, visit [rpodcast.shinyapps.io/shinysaurus](https://rpodcast.shinyapps.io/shinysaurus)

## References

Here is a collection of links I used as I created the application

* https://eliocamp.github.io/codigo-r/en/2019/01/statistical-metamerism/

* https://eliocamp.github.io/metamer/

* https://itsalocke.com/datasaurus/

* https://talks.cpsievert.me/20191115/#1

* https://plotly-r.com/index.html

* https://github.com/RinteRface/bs4Dash

## Installation

You can install the development version of the package using the following command:

``` r

# install.packages("remotes")

remotes::install_github("rpodcast/shinysaurus")

```

## Code of Conduct

  

Please note that the shinysaurus project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.