How to use pcaModule

Introduction

soroban’s pcaModule perform pca analysis and generates Biplot.

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

This article is based on 0.0.1 Version of soroban

Declare module

soroban’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 pcaModule in ui.

ui <- fluidPage(
  mod_pcaModule_ui(
    id = 'module'
  )
)

also, pcaModule in server.

server <- function(input, output, session) {
  mod_pcaModule_server(
    id = 'module', 
    inputData = reactive(datatoys::scholarship)
  )
}

So final (which is very basic) code will like this. (Assume data from AER loaded.)

library(shiny)

ui <- fluidPage(
  mod_pcaModule_ui(
    id = 'module'
  )
)

server <- function(input, output, session) {
  mod_pcaModule_server(
    id = 'module', 
    inputData = reactive(datatoys::scholarship) # 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 pcaModule

pcaModule is consisted with Control Area and Result Area

and below using flow.

1. Declare module (we did already)
2. select variable to analysis. (and if data has different scale, check normalize) 2-1. (Optional) adjust plot’s height (we consider modify UI in further version)
3. Draw

Usage of pcaModule

Using scholarship, we’ll see which factor makes university differ.

However, we should change data’s type first.

since PCA module requires options with types.

1. change 학제별 to factor. it has category with University and College.

mod_pcaModule_server(
    id = 'module', 
    inputData = reactive(datatoys::scholarship %>% mutate()) 
  )

2. fill variables like below image; they mean type of scholarship. (other are sum of schoar so they removed)

(대학명 means name of university, which will be used Label (optional))

then result will be shown.

note that some university shows like outlier, which means they provide more scholarships to student. (like Seoul Univ.)

After some move / zoom figure (it uses plotly so you can use their interactive feature), we can see many types of scholarship is provided forward Red that is university and Blue is college.

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