README.md

In Davide-bll/Shinymod: Help building Shiny modules

Automatic Data Visualization with Shiny Modules.

Install package

To install the package, you can use

devtools::install_github(Davide-bll/Shinymod)

Main modules

Plot Module

Modules for building basic automatic datavisualization dashboard. It includes BoxPlots, Histograms, and Scatter Plot.

A Dataframe is expected in input, wide and long format. The default value of the panel type plot is aggregate, which shows the variable selected without differentiating the groups the observations belong to. You can deal with one "group" at a time, by selcting the criteria of differentiating.

As an exmaple, consider the CO2 dataframe, which has this structure:

| obs | conc | uptake | treatment | |------------| ------------- | ------------- |---------------| | 1 | Value | Value | treat1 | | 2 | Value | Value | treat2 |

you can visualize the scatter plot conc vs treatment without differentiating the treatment values of differenciating them. A basic dashboard would be:

require(shiny)
require(shinymod)

if(interactive()) {

ui <- fluidPage(

  typeplotUi("type")


)

server <- function(input, output, session) {

  callModule(typeplot, "type", data = CO2)

}


shinyApp(ui, server)

}

or just type:

help(typeplot)

If you want to observe the scatter plot, choose plot_2var from the type of visualization panel, and you'll get something like:

Since aggregate is the default value of typeplot, you'll see all the observation plotted. If you want to differentiate the treatments, just select the column treatments from the typeplot panel:

To see a more concrete of a data exploration app, see this data exploarion app, which load a local file, (csv, txt, or feather), and do some basic filtering and automatic Data visualization.

The code for the App is at this file

Davide-bll/Shinymod documentation built on April 17, 2021, 8:42 a.m.