Question

如何通过多个变量过滤数据帧的行，在变换的数据框上运行模型，并渲染结果？

我已经想出如何通过多个变量简单地过滤数据框并显示为表格：

server <- function(input, output) {
  output$summary <- renderTable({  
  df <- Heating

  if (input$regiontype != "All") {
    df <- df[df$region == input$regiontype,]
  }
  if (input$roomsize != "All") {
    df <- df[df$rooms == input$roomsize,]
  }

  df
  })
}

我还想出了如何通过一个变量过滤数据框，运行模型并打印结果：

#### PART 3 - Define server logic
server <- function(input, output) {

  output$summary <- renderPrint({

    df <- Heating

    ### Subset data
    df.subset <- reactive({ a <- subset(df, region == input$regiontype)
    return(a)})

    ### Model 
    estimates <- mlogit(depvar ~ ic + oc | 0, data= df.subset(), shape = "wide", choice = "depvar", varying = c(3:12))
    summary(estimates)

  })      
}

但是，如何将这些组合在一个已被一个或多个变量过滤的数据框上运行模型？

我将提供以下两种版本的脚本：的 1。按多个变量

过滤数据框

### PART 1 - Load Libraries and Data
library(shiny)           # For running the app
library(mlogit)

#### data
data("Heating", package = "mlogit")

#### PART 2 - Define User Interface for application
ui <- fluidPage(

  ## Application title
  titlePanel("Housing Preference"),

  ## Sidebar with user input elements
  sidebarLayout(
    sidebarPanel(
      p("Select the inputs"), # Header
      #Reg
      selectInput('regiontype', 'Region', choices = c("All",
                                                      "Northern coastal region"= "ncostl", 
                                                      "Southern coastal region" = "scostl", 
                                                      "Mountain region"  = "mountn",
                                                      "Central valley region"= "valley") #, 
                  #multiple=TRUE, 
                  #selectize=TRUE
      ),

      #Room Size
      selectInput('roomsize', 'Room Size', choices = c("All",
                                                       "2"= 2, 
                                                       "3" = 3, 
                                                       "4"  = 4,
                                                       "5"= 5 ,
                                                       "6"=6,
                                                       "7"=7)
                  #multiple=TRUE, 
                  #selectize=TRUE
      )



    ),

    ## Show a plot
    mainPanel(
      tableOutput("summary")
    )
  )
)

#### PART 3 - Define server logic
  server <- function(input, output) {
    output$summary <- renderTable({  
      df <- Heating

      if (input$regiontype != "All") {
        df <- df[df$region == input$regiontype,]
      }
      if (input$roomsize != "All") {
        df <- df[df$rooms == input$roomsize,]
      }

      df
    })
  }

### PART 4 - Run the application 
shinyApp(ui = ui, server = server)

2。按一个变量，运行模型和打印结果过滤：

### PART 1 - Load Libraries and Data
library(shiny)           # For running the app
library(mlogit)

#### data
data("Heating", package = "mlogit")

#### PART 2 - Define User Interface for application
ui <- fluidPage(

  ## Application title
  titlePanel("Housing Preference"),

  ## Sidebar with user input elements
  sidebarLayout(
    sidebarPanel(
      p("Select the inputs"), # Header
      #Reg
      selectInput('regiontype', 'Region', choices = c("All",
                                                      "Northern coastal region"= "ncostl", 
                                                      "Southern coastal region" = "scostl", 
                                                      "Mountain region"  = "mountn",
                                                      "Central valley region"= "valley") #, 
                  #multiple=TRUE, 
                  #selectize=TRUE
      ),

      #Room Size
      selectInput('roomsize', 'Room Size', choices = c("All",
                                                       "2"= 2, 
                                                       "3" = 3, 
                                                       "4"  = 4,
                                                       "5"= 5 ,
                                                       "6"=6,
                                                       "7"=7)
                  #multiple=TRUE, 
                  #selectize=TRUE
      )



    ),

    ## Show a plot
    mainPanel(
      verbatimTextOutput("summary")
    )
  )
)

#### PART 3 - Define server logic
server <- function(input, output) {

  output$summary <- renderPrint({

    df <- Heating

    ### Subset data
    df.subset <- reactive({ a <- subset(df, region == input$regiontype)
    return(a)})

    ### Model 
    estimates <- mlogit(depvar ~ ic + oc | 0, data= df.subset(), shape = "wide", choice = "depvar", varying = c(3:12))
    summary(estimates)

  })      
}

### PART 4 - Run the application 
shinyApp(ui = ui, server = server)

Answer 1

你可以像这样组合它们：
我更喜欢dplyr过滤方式，因为我感觉更舒服。

output$summary <- renderPrint({
                            region_type_selected <- input$regiontype
                            room_size_selected <- input$roomsize

                            ### Subset data
                            library(dplyr)
                            if(region_type_selected != "All"){
                                            df <- Heating %>% filter(region == region_type_selected)               
                            }

                            if(room_size_selected != "All"){
                                            df <- Heating %>% filter(rooms == room_size_selected)               
                            }

                            ### Model 
                            estimates <- mlogit(depvar ~ ic + oc | 0, data= df, shape = "wide", choice = "depvar", varying = c(3:12))
                            summary(estimates)

            })

Shiny R：通过两个变量过滤数据框并运行模型

1 个答案: