我正在研究葡萄酒数据集（https://github.com/Honghe/notebook_mermaid），我需要准备一个小项目来传递一个主题......
所以 - 这个数据集有一列有3个值（1,2或3）。这些例子是葡萄酒类。
我必须转换它们的值才能准备Logistic回归（所以 - 值0或1）。我想选择两个值（例如1和3）并使Logistic回归依赖于其他值（例如酒精）。
此刻我还是那样：
shinyUI(navbarPage("Wine Data Set Analysis",
tabPanel("Data Import and configuration",
sidebarLayout(sidebarPanel(
fileInput("file","Upload CSV file",multiple = FALSE),
tags$hr(),
h5(helpText("Select the parameters of your file below")),
checkboxInput(inputId = 'header', label = 'Header', value = FALSE),
radioButtons(inputId = 'sep', label = 'Separator',
choices = c(Comma=',',Semicolon=';',Tab='\t', Space=''), selected = ',')
),
mainPanel(uiOutput("tb1"))
) ),
tabPanel("Logistic Regression",
sidebarLayout(sidebarPanel(
helpText("Select values for Logistic Regression"),
uiOutput("var_select"),
uiOutput("rest_var_selectx"),
uiOutput("one"),
uiOutput("proba")
# uiOutput("var1_select"),
# uiOutput("rest_var_select")
),
mainPanel( helpText("The result is: "),
verbatimTextOutput("other_val_show"),
helpText("The plot to visualise the regression"),
plotOutput("plotx")
)))
))
服务器：
library(shiny)
library(ggplot2)
library(dplyr)
# Define server logic required to draw a histogram
shinyServer(function(input, output, session) {
data <- reactive({
file1 <- input$file
if(is.null(file1)){return()}
read.table(file=file1$datapath, sep=input$sep, header = input$header)
})
output$table <- renderTable({
if(is.null(data())){return ()}
data()
})
output$tb1 <- renderUI({
tableOutput("table")
})
output$var_select<-renderUI({
checkboxGroupInput("ind_var_select","Select Independent Variation", choices = c("0", "0.5", "1"), selected = c("0", "0.5"))
})
output$rest_var_selectx<-renderUI({
checkboxGroupInput("other_var_selectx","Select other Variationx",choices =as.list(names(data())))
})
wybrane <- reactive({
if(input$ind_var_select == "0")
{
if (input$ind_var_select == "0.5")
{
as.factor(data1$Class)
dane1<- factor(levels(data1$Class), labels = c("0","1"))
data1$Cl<-as.numeric(dane1)
dane <- sprintf("%s~%s",data1$Cl, paste0(input$other_var_selectx,collapse="+"))
print(dane)
#print(nrow(dplyr::select(f,input$ind_var_select)))
logreg <-glm(as.formula(form),family=binomial(),data=f)
print(summary(logreg))
output$plotx<-renderPlot({
# kolumna<-input$other_var_select,
# dane<-f$kolumna,
# ggplot2::ggplot(f,aes(x=unlist(dplyr::select(f,input$other_var_select)),
# y=unlist(dplyr::select(f,input$ind_var_select))))+geom_point()+geom_smooth(method="glm",method.args=list(family="binomial"))
#
})
}
}
})
答案 0 :(得分：1)
我不会让它变得如此复杂，而只是使用ifelse。我相信你想象这样的事情
library(shiny)
library(ggplot2)
library(dplyr)
shinyApp(
ui = navbarPage("Wine Data Set Analysis",
tabPanel("Data Import and configuration",
sidebarLayout(sidebarPanel(
fileInput("file","Upload CSV file",multiple = FALSE),
tags$hr(),
h5(helpText("Select the parameters of your file below")),
checkboxInput(inputId = 'header', label = 'Header', value = FALSE),
radioButtons(inputId = 'sep', label = 'Separator',
choices = c(Comma=',',Semicolon=';',Tab='\t', Space=''), selected = ',')
),
mainPanel(uiOutput("tb1"))
) ),
tabPanel("Logistic Regression",
sidebarLayout(sidebarPanel(
helpText("Select values for Logistic Regression"),
uiOutput("var_select"),
uiOutput("rest_var_selectx"),
uiOutput("one"),
uiOutput("proba")
# uiOutput("var1_select"),
# uiOutput("rest_var_select")
),
mainPanel( helpText("The result is: "),
verbatimTextOutput("other_val_show"),
helpText("The plot to visualise the regression"),
plotOutput("plotx")
)))
),
server = function(input, output, session) {
data <- reactive({
file1 <- input$file
if(is.null(file1)){return()}
read.table(file=file1$datapath, sep=input$sep, header = input$header)
})
output$table <- renderTable({
if(is.null(data())){return ()}
data()
})
output$tb1 <- renderUI({
tableOutput("table")
})
output$var_select<-renderUI({
checkboxGroupInput("ind_var_select","Select Independent Variation", choices = c( "1", "2","3"), selected = c("1", "3"))
})
output$rest_var_selectx<-renderUI({
checkboxGroupInput("other_var_selectx","Select other Variationx",choices =as.list(names(data())))
})
wybrane <- reactive({
dta <- data()
dta$Cl<-ifelse(dta$V1 %in% input$ind_var_select,1,0)
dane <- sprintf("%s~%s",dta$Cl, paste0(input$other_var_selectx,collapse="+"))
print(dane)
#print(nrow(dplyr::select(f,input$ind_var_select)))
logreg <-glm(as.formula(paste0("Cl ~ ",paste0(input$other_var_selectx,collapse = " + "))),family=binomial(),data=dta)
print(summary(logreg))
dta
})
output$plotx<-renderPlot({
req(!is.null(input$ind_var_select) &&
!is.null(input$other_var_selectx))
f = wybrane()
ggplot2::ggplot(f,aes_string(x=input$other_var_selectx,
y="Cl"))+geom_point()+geom_smooth(method="glm",method.args=list(family="binomial"))
})
}
)
希望这有帮助！