我正在Rstudio中使用Shiny编写我的第一个代码，它需要一个文件输入（CSV文件，并在主面板中打印绘图。打印绘图后，我试图打印传递给绘图以观察其变量的变量的值我无法执行的值，它将在Rstudio控制台中打印出来；其次，我正在寻找创建这些变量的数据框，并下载包含这些值的CSV文件。希望我已经解释了该查询。我正在复制下面的代码

我能够在浏览器中打印绘图。但是变量正在控制台（rstudio）中打印出来，我需要在绘图下的浏览器窗口中使用它们，并下载包含这些变量数据框的CSV文件。如果有人可以指导我，我将不胜感激。

structure(list(Point1 = c(9999,9999,433.333,1433.333,33.333,4283.333,0.033,1323.333,883.333,0.633,133.333,0.003,4023.333,423.333,4323.333,2073.333,123.333,3363.333,0.333,423.333),Point2 = c(4433.333,4433.333,4133.333,3.333,1283.333,4358.333,NA,123.333),OUTP1 = c(NA,1L,1L),Types = c(NA,3L,2L,3L)),.Names = c("Point1","Point2","OUTP1","Types"),class = "data.frame",row.names = c(NA,-51L
))

options(scipen=999)
library(survival)

ui <- bootstrapPage(
titlePanel("Survival analysis step1"),tags$hr(),sidebarPanel(
fileInput("file1","Choose CSV File",multiple = FALSE,accept = c("text/csv","text/comma-separated-values,text/plain",".csv")),checkboxInput("header","Header",TRUE),radioButtons("sep","Separator",choices = c(Comma = ",",Semicolon = ";",Tab = "\t"),selected = ","),radioButtons("quote","Quote",choices = c(None = "","Double Quote" = '"',"Single Quote" = "'"),selected = '"'),radioButtons("disp","Display",choices = c(Head = "head",All = "all"),selected = "head")
 ),mainPanel(
plotOutput('plot'),textOutput("selected_var")
     )
               )
server <- function(input,output) {
output$plot <- renderPlot({

req(input$file1)

testpeanut1 <- read.csv(input$file1$datapath,header = input$header,sep = input$sep,quote = input$quote)
    print(dput(testpeanut1))
testpeanut1[is.na(testpeanut1)]<-"0"
testpeanut1$modified_Point1<-ifelse(as.numeric(testpeanut1$Types) ==2,as.numeric(testpeanut1$Point2),as.numeric(testpeanut1$Point1))
testpeanut1$modified_Point2<-ifelse(as.numeric(testpeanut1$Types) ==2,as.numeric(testpeanut1$Point1),as.numeric(testpeanut1$Point2))
set.seed(1234567)
testpeanut1$Survial_analysis_obj<-Surv(as.numeric(testpeanut1$modified_Point2),as.numeric(testpeanut1$modified_Point1),as.numeric(testpeanut1$Types),type="interval")
model_log_N_obj<-survreg(formula= testpeanut1$Survial_analysis_obj~1,data=testpeanut1,dist="lognormal")
new1<-data.frame(1)
predmodel_log_N_obj<-predict(model_log_N_obj,newdata=new1,type='quantile',p=seq(0.001,0.99,by=0.0001),se.fit=TRUE)


    plot(predmodel_log_N_obj$fit,seq(0.001,type="l",col=2,lty=1,lwd=2,xlim=c(0.00001,100000000),main="Plot description",xlab="Caption",ylab = "probability",log="x",xaxt = "n",yaxt = "n") 
lines(exp(log(predmodel_log_N_obj$fit)+1.96* (predmodel_log_N_obj$se.fit)/ predmodel_log_N_obj$fit),lty=2)
lines(exp(log(predmodel_log_N_obj$fit)-1.96* (predmodel_log_N_obj$se.fit)/ predmodel_log_N_obj$fit),lty=2)

ED01_log_N_obj<-predict(model_log_N_obj,p=0.01,se.fit=TRUE) #0.18
print(ED01_log_N_obj)
ED01_log_N_CL_obj <- exp(log(ED01_log_N_obj$fit)-1.96* (ED01_log_N_obj$se.fit)/ ED01_log_N_obj$fit)
print(ED01_log_N_CL_obj)
#ED01 upper confidence level - 0.75
ED01_log_N_CU_obj<- exp(log(ED01_log_N_obj$fit)+1.96* (ED01_log_N_obj$se.fit)/ ED01_log_N_obj$fit)
print(ED01_log_N_CU_obj)

df<-data.frame(ED01_log_N_CU_obj)
df$ED01_log_N_CL_obj<-ED01_log_N_CL_obj
df$ED01_log_N_objfit<-ED01_log_N_obj$fit

dput(testpeanut1)    
})

output$selected_var <- renderText("ED01_log_N_obj") 
}

shinyApp(ui = ui,server = server)

单击按钮等或作为下载链接，可在浏览器和CSV文件中打印并打印变量。