我有一个功能强大的闪亮应用程序，当我尝试将数据框导入为csv而不是在应用程序内部创建时，该应用程序会崩溃。我将无法正常工作的代码注释掉了。 数据：
DF2 = data.frame(agency_postcode = factor(rep(c(12345,45678,24124,32525,32325),2)),
car_group=factor(rep(c("Microcar","City car","Supermini","Compact","SUV"),2)),
transmission=factor(rep(c("automatic","manual"),5)))
csv：
write.csv(DF2,"C:/Users/User/Documents/Test//cars2.csv", row.names = FALSE)
错误：
Warning: Error in get_col_types: Unsupported object type: NULL Can't extract column types.
和应用：
#ui.r
library(shiny)
library(rhandsontable)
ui <- fluidPage(
titlePanel("RHandsontable"),
sidebarLayout(
sidebarPanel(
fileInput("file1", "Choose CSV File",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
actionButton("sr","Search")
),
mainPanel(
rHandsontableOutput("test")
)
)
)
#server.r
library(shiny)
library(rhandsontable)
server <- function(input, output) {
# Assigning blank values to reactive variable as all the values need to be listed first
values <- reactiveValues(postcode = "",cargroup = "",date="",days="",transmission="",driver_age="",tabledata = data.frame())
d<-reactive({
inFile <- input$file1
if (is.null(inFile))
return(NULL)
DF<- read.csv(inFile$datapath,stringsAsFactors = T)
for(i in 1:ncol(DF)){
DF[,i]<-as.factor(DF[,i])
}
DF
})
observeEvent(values$postcode,{
DF2 = data.frame(agency_postcode = factor(rep(c(12345,45678,24124,32525,32325),2)),
car_group=factor(rep(c("Microcar","City car","Supermini","Compact","SUV"),2)),
transmission=factor(rep(c("automatic","manual"),5)))
# When the user selects any value from the dropdown, filter the table and update the value of reactive df
if(values$postcode!=""){
values$tabledata <- d()[ which(d()$agency_postcode ==values$postcode), ]
}else{
# When the postcode value is blank, meaning the user hasn't selected any, the table
# will render without the third column
values$tabledata <- d()[,-3]
}
})
observeEvent(values$cargroup,{
DF2 = data.frame(agency_postcode = factor(rep(c(12345,45678,24124,32525,32325),2)),
car_group=factor(rep(c("Microcar","City car","Supermini","Compact","SUV"),2)),
transmission=factor(rep(c("automatic","manual"),5)))
values$tabledata <- d()
# When the user selects any value from the dropdown, filter the table and update the value of reactive df
if(values$cargroup!=""){
values$tabledata <- d()[ which(d()$car_group ==values$cargroup), ]
}else{
# When the cargroup value is blank, meaning the user hasn't selected any, the table
# will render without the third column
values$tabledata <- d()[,-3]
}
})
# Observer for changes made to the hot
observeEvent(input$sr,{
col <- input$test$changes$changes[[1]][[2]]
# Changes made in first column
if(col==0){
values$postcode <- input$test$changes$changes[[1]][[4]]
}
# Changes made in second column
if(col==1){
values$cargroup <- input$test$changes$changes[[1]][[4]]
}
})
# Render the hot object
output$test <- renderRHandsontable({
rhandsontable(values$tabledata[1,], rowHeaders = NULL, width = 550, height = 300)%>%
hot_col(colnames(values$tabledata))
})
}
***基于NULL的编辑（2）
output$test <- renderUI({
if (is.null(input$file1)){
return("Add file")
}
else{
rhandsontable(values$tabledata[1,], rowHeaders = NULL, width = 550, height = 300)%>%
hot_col(colnames(values$tabledata))
}
})
答案 0 :(得分：1)
我已使用here提供的答案中的代码，并将其更新为包括.csv上传的代码。希望这会有所帮助。
用于创建df和保存.csv的代码段
test <- data.frame(agency_postcode = factor(rep(c(12345,45678,24124,32525,32325),2)),
car_group=factor(rep(c("Microcar","City car","Supermini","Compact","SUV"),2)),
transmission=factor(rep(c("automatic","manual"),5)))
write.csv(test,paste0("C:/Users/",Sys.getenv("USERNAME"),"/Desktop/Sample.csv"))
对于闪亮的应用程序，用户界面部分可以相同。下面是更新的服务器代码。
server <- function(input, output) {
# Assigning blank values to reactive variable as all the values need to be listed first
values <- reactiveValues(postcode = "",cargroup = "",tabledata = data.frame(), sourcedata = data.frame())
# Let's add another reactive df called sourcedata. This will have our parent data
# The dataframe table data will be the parsed data passed to create handsontable object
values$sourcedata <- data.frame(agency_postcode = factor(rep(c(12345,45678,24124,32525,32325),2)),
car_group=factor(rep(c("Microcar","City car","Supermini","Compact","SUV"),2)),
transmission=factor(rep(c("automatic","manual"),5)))
observe({
inFile <- input$file1
if (is.null(inFile))
return(NULL)
sourceData <- read.csv(inFile$datapath,stringsAsFactors = TRUE)
sourceData$agency_postcode <- as.factor(sourceData$agency_postcode)
sourceData$car_group <- as.factor(sourceData$car_group)
sourceData$transmission <- as.factor(sourceData$transmission)
# if any .csv files are uploaded, update the value of sourceData from the hardcoded dataframe
values$sourcedata <- sourceData
values$tabledata <- sourceData[,-3]
}
)
observeEvent(values$postcode,{
DF2 = values$sourcedata
# When the user selects any value from the dropdown, filter the table and update the value of reactive df
if(values$postcode!=""){
values$tabledata <- DF2[ which(DF2$agency_postcode ==values$postcode), ]
}else{
# When the postcode value is blank, meaning the user hasn't selected any, the table
# will render without the third column
values$tabledata <- DF2[,-3]
}
})
observeEvent(values$cargroup,{
DF2 = values$sourcedata
# When the user selects any value from the dropdown, filter the table and update the value of reactive df
if(values$cargroup!=""){
values$tabledata <- DF2[ which(DF2$car_group ==values$cargroup), ]
}else{
# When the cargroup value is blank, meaning the user hasn't selected any, the table
# will render without the third column
values$tabledata <- DF2[,-3]
}
})
# Observer for changes made to the hot
observeEvent(input$test$changes$changes,{
col <- input$test$changes$changes[[1]][[2]]
# Changes made in first column
if(col==0){
values$postcode <- input$test$changes$changes[[1]][[4]]
}
# Changes made in second column
if(col==1){
values$cargroup <- input$test$changes$changes[[1]][[4]]
}
})
# Render the hot object
output$test <- renderRHandsontable({
rhandsontable(values$tabledata[1,], rowHeaders = NULL, width = 550, height = 300)%>%
hot_col(colnames(values$tabledata))
})
}
希望这会有所帮助。