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https://github.com/dgkf/shinyDataFilter

data-agnostic, shiny-idiomatic filter module
https://github.com/dgkf/shinyDataFilter

hacktoberfest module r shiny

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data-agnostic, shiny-idiomatic filter module

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# shinyDataFilter

[![CRAN](https://img.shields.io/cran/v/shinyDataFilter.svg)](https://cran.r-project.org/package=shinyDataFilter)
[![R-CMD-check](https://github.com/dgkf/shinyDataFilter/workflows/R-CMD-check/badge.svg)](https://github.com/dgkf/shinyDataFilter/actions)
[![Codecov](https://img.shields.io/codecov/c/github/dgkf/shinyDataFilter/master.svg)](https://app.codecov.io/gh/dgkf/shinyDataFilter)

data-agnostic, shiny-idiomatic filter module

![shinyDataFilter](https://user-images.githubusercontent.com/18220321/77127982-b6a9fe80-6a0b-11ea-8233-e77e0f362d70.gif)

Built on top of [Joe Cheng](https://github.com/jcheng5)'s excellent [R/Pharma 2018 shiny demo](https://github.com/jcheng5/rpharma-demo) and experimenting with pushing his concept of hyper-modular shiny components as far as we could. In addition to what Joe showed off at the time, this shiny module comes with drag-and-drop reordering and overlayed visualizations of each filter variable's data qualities.

# Getting started

## Installation

```{r, eval=FALSE}
# install.packages("devtools")
devtools::install_github("dgkf/shinyDataFilter")
```

## Example App

Then, run this sample app to build filters with `shinyDataFilter`:

```{r, eval=FALSE}
library(shiny)
app <- system.file("examples", "basic_app", "app.R", package = "shinyDataFilter")
shinyAppFile(app)
```

If you'd like to inspect the code for the app

```{r, eval = FALSE}
file.edit(app) # or
file.show(app)
```