How to use distributionModule

library(board)

Introduction

board’s distributionModule shows selected variables distribution (and additional information too)

In this article, we’ll use bloodTest dataset of datatoys

This article is based on 0.0.2 Version of board.

Declare module

board’s module assumes that used in the Shiny application.

and You can use snippet(type shinyapp) to build very basic shiny application.

library(shiny)

ui <- fluidPage(
 
)

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

shinyApp(ui, server)

This application will show nothing.

So let’s add distributionModule in ui

ui <- fluidPage(
  mod_distributionModule_ui(
    id = 'distModule'
  )
)

also, distributionModule in server.

server <- function(input, output, session) {
  mod_distributionModule_server(
    id = 'distModule', 
    inputData = reactive(datatoys::bloodTest) 
  )
}

So final (which is very basic) code will like this.

library(shiny)

ui <- fluidPage(
  mod_distributionModule_ui(
    id = 'distModule'
  )
)

server <- function(input, output, session) {
  mod_distributionModule_server(
    id = 'distModule', 
    inputData = reactive(datatoys::bloodTest) # remotes::install_github('statgarten/datatoys')
  )
}

shinyApp(ui, server) # run application

You should notice 2 things.

1. both id in ui and server should be same.
2. inputData in server should be format of reactive

Structure of distributionModule

distributionModule is consisted with Result Area and Control Area

and below using flow.

1. Declare module (we did already)
2. Set column to show distribution, and finish! (“reactive” result will shown)

Usage of distributionModule

Let’s change Variable like image below

Note that, many of distributionModule’s function is effective with Numeric value. So it will be better if you change data’s type as expected (Sex could be better with Factor not Numeric)

result will also be changed. (even it doesn’t have much )

Description of statistics

If distribution uses Numeric variable,

It shows these statistics. ( see second figure )

• Count
• Mean
• Median
• Standard deviation (Std)
• Quantile values (0: Min, 25, 50: Median, 75, 100: Max)
• Outlier values
  • value smaller than 288 may considered as outlier. which has 34891 count.
  • value larger than 380 may considered as outlier. which has 11130 count.

For any issue or suggestion, please make issue in board’s github.