希望获得一些专业知识。以下代码段执行以下操作：
但是，Shiny将列标题分配给数据框，并且我已经尝试了一切可能的方法来更改它们，但似乎没有任何效果。
有人可以告诉我我在做什么错吗？
df_sel（）-这是选择变量的函数
ui <- fluidPage(
# App title ----
titlePanel(title = h1("Variable Selection Example", align = "center")),
# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar panel for inputs ----
sidebarPanel(
# Input: Select a file ----
fileInput("uploaded_file", "Choose CSV File",
multiple = TRUE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
# Horizontal line ---- This allows the user to create a bunch of repeated values for the numerica inputs they later create
sliderInput("months", "Forecast Months:",
min = 0, max = 60,
value = 1),
tags$hr(),
# Input: Checkbox if file has header ----
checkboxInput("header", "Header", TRUE),
# Input: Select separator ----
radioButtons("sep", "Separator",
choices = c(Semicolon = ";",
Comma = ",",
Tab = "\t"),
selected = ","),
# Horizontal line ----
tags$hr(),
# Input: Select number of rows to display ----
radioButtons("disp", "Display",
choices = c(All = "all",
Head = "head"),
selected = "all"),
# Select variables to display ----
uiOutput("checkbox")
),
# Main panel for displaying outputs ----
mainPanel(
uiOutput("input_ui"), #numeric inputs
tableOutput("table1")) #table to display input values
)
)
server <- function(input, output, session) {
#assign csv file to dataframe df
df <- reactive({
req(input$uploaded_file)
read.csv(input$uploaded_file$datapath,
header = input$header,
sep = input$sep)
})
# Dynamically generate UI input when data is uploaded ----
output$checkbox <- renderUI({
checkboxGroupInput(inputId = "select_var",
label = "Select variables",
choices = setdiff(names(df()), input$select_dev),
selected = setdiff(names(df()), input$select_dev))
})
# Select columns to print ----
df_sel <- reactive({
req(input$select_var)
df_sel <- df() %>% select(input$select_var)
})
output$input_ui <- renderUI({ #this creates dynamic numeric inputs based on the variables selected by the user
pvars <- df_sel()
varn = names(df_sel())
lapply(seq(pvars), function(i) {
numericInput(inputId = paste0("range", pvars[i]),
label = varn,
value = 0)
})
})
numbers <- reactive({ #this creates a reactive dataframe for the numbers
pvars <- df_sel()
num = as.integer(ncol(pvars))
print(num)
pred <- data.frame(lapply(1:num, function(i) {
input[[paste0("range", pvars[i])]]
}))
n = input$months #pull number from that slider up in the UI section
pd = data.frame(pred, i=rep(1:n,ea=NROW(input$months)))
pd[1:(length(pd)-1)]
#colnames(pd, c(df_sel())) #this does not seem to work at all!!!
})
output$table1 <- renderTable({
numbers()
fv = numbers()
print(dim(fv)) #check the dimensions of the table
print(fv) # chcek the table is populating correctly.
#df1 <- fv #show the table
})
}
# Create Shiny app ----
shinyApp(ui = ui, server = server)
答案 0 :(得分：0)
我想出了一个解决自己问题的方法。如果有人可以改进它，请告诉我。此代码在R.Server部分中。
#This creates sliders from the selected variables from the reactive function called
#"df_sel()". Note the use of "tagList". The RenderUI function below creates as
#many sliders as variables selected, and passes in the correct variable name.
#It selects the last data value from each column, since this is time series data,
#the last data value \ (most recent) was desired.
output$scplan <- renderUI({
vars <- df_sel()
n = nrow(vars)
tagList(lapply(colnames(vars), function(z) {
sliderInput(
sprintf("%s",z),
label = z,
min = ceiling(min(vars[[z]])), # min value is the minimum of the column
max = ceiling(max(vars[[z]])), # max is the max of the column
value = vars[[z]][[n]])
}))
#this reactive function creates a dataframe from variables that were selected from
#checkboxes. The user moves the sliders to generate the values, and the code
#repeats the values for as many "input$months" as were selected.
sp_numbers <- reactive({
vars <- df_sel()
num = as.integer(ncol(vars))
sp_pred <- data.frame(lapply(colnames(vars), function(z) {
input[[z]]
}))
names(sp_pred) <- colnames(vars)
n = input$sp_months
df_sp_pred = data.frame(sp_pred, z=rep(z:n,ea=NROW(input$sp_months)))
df_sp_pred[1:(length(df_sp_pred)-1)] #this removes the last column which just shows the repeat count
})
#this code renders the table of the dataframe created above.
output$spo_table <- renderTable({
sp_numbers()
})