如何根據用戶輸入更改顯示錶輸入

Question

我有一段代碼，我需要顯示不同的表，具體取決於R中SelectInput命令的userinput。 我只想在userinput爲Level 2時顯示錶base_level2並顯示base_level3當用戶選擇selectInput級別3 我不確定被動命令是否幫助我，但在那個時候我真的很困惑我該怎麼做。 預先感謝大家。

ui.R

library(shiny) library(radarchart) library(fmsb) 
# Define UI for random distribution application 

shinyUI(pageWithSidebar( headerPanel('A competency profiling model 
    for Software engineers'), sidebarPanel(

selectInput("dataset", "Choose Level of competence :", 
      choices = c("Level 2", "Level 3"), selected = "Level 2"), 

radioButtons("selectedCategory","Make your choice of Skills : ", rownames(x), selected = "Professional skills"), 
checkboxGroupInput('selectedLevels', 'Who to include', 
        names(scores[]), selected="Technical Junior"), 
sliderInput("Candidate", "Candidate number:", 
      min = 1, max = 50, value = 1)), 
mainPanel(
    tabsetPanel(type="tabs", 
      tabPanel('Level2/Level3 RCD frame', tableOutput("table")), 
      tabPanel("Candidates ACD frame ", tableOutput("candidate")), 
      tabPanel("Radar Plot #1", chartJSRadarOutput("radar", width = "450", height = "300"), width = 7), 
      tabPanel("Radar Plot #2" ,plotOutput("triangle", width = "100%", height = "900px"), width = 7), 
      tabPanel("Clustering Plots",plotOutput("cluster", width = "100%", height = "900px"), width = 7), 
      tabPanel("Correlation Plots",plotOutput("corellation",width = 

"100%", height = 
"900px"),width = 7), 
       tabPanel("Classification Tree", plotOutput("class",width = "100%", height = "900px"),width = 7)) 
      ) 


    ) 


) 

server.R

function(input, output) { 


    datasetInput <- reactive({ 
    switch(input$dataset, 
      "Level 2" = as.matrix(base_level2), 
      "Level 3" = as.matrix(base_level3) 
      ) 
    }) 

    output$table <- renderTable({(datasetInput)},rownames=TRUE,striped = TRUE,hover = TRUE, bordered = TRUE) 

Answer 1

增加了一些假的數據，使其工作，通過固定在HubertL的意見確定的語法錯誤，它工作得很好：

library(shiny) 
library(radarchart) 
library(fmsb) 

# Fake Data 
x <- data.frame(skilz = c("Professional Skills","Technical Skills","Soft Skills"),a = c(1,2,3),b = c(11,12,13),row.names = "skilz") 
scores <- c("Technical Junior" = 1,"Technical Senior" = 2) 
base_level2 <- data.frame(x = c(1,2,3),y = c(4,5,6),z = c(7,8,9)) 
base_level3 <- data.frame(x = c(11,12,13),y = c(14,15,16),z = c(17,18,19)) 

# Define UI for random distribution application 

u <- shinyUI(pageWithSidebar(headerPanel('A competency profiling model for Software engineers'), 
    sidebarPanel(
     selectInput("dataset","Choose Level of competence :", 
        choices = c("Level 2","Level 3"),selected = "Level 2"), 

     radioButtons("selectedCategory","Make your choice of Skills : ",rownames(x),selected = "Professional skills"), 
     checkboxGroupInput('selectedLevels','Who to include', 
          names(scores[]),selected = "Technical Junior"), 
     sliderInput("Candidate","Candidate number:", 
        min = 1,max = 50,value = 1)), 
    mainPanel(
     tabsetPanel(type = "tabs", 
        tabPanel('Level2/Level3 RCD frame',tableOutput("table")), 
        tabPanel("Candidates ACD frame ",tableOutput("candidate")), 
        tabPanel("Radar Plot #1",chartJSRadarOutput("radar",width = "450",height = "300"),width = 7), 
        tabPanel("Radar Plot #2",plotOutput("triangle",width = "100%",height = "900px"),width = 7), 
        tabPanel("Clustering Plots",plotOutput("cluster",width = "100%",height = "900px"),width = 7), 
        tabPanel("Correlation Plots",plotOutput("corellation",width = "100%",height = 
     "900px"),width = 7),tabPanel("Classification Tree",plotOutput("class",width = "100%",height = "900px"),width = 7))) 
) 
) 

s <- 
function(input,output) { 


    datasetInput <- reactive({ 
    switch(input$dataset, 
     "Level 2" = as.matrix(base_level2), 
     "Level 3" = as.matrix(base_level3) 
     ) 
    }) 

    output$table <- renderTable({(datasetInput()) }, 
       rownames = TRUE,striped = TRUE,hover = TRUE,bordered = TRUE) 
} 

shinyApp(ui=u,server=s) 

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