Как отобразить информационное окно Dynami c перед загрузкой каких-либо данных?

Question

Я хочу создать Shinydashboard, который требует, чтобы пользователь загрузил файл csv и ввел «емкость». Панель управления должна производить расчет и отображать доход, транзакцию и процент занятости на странице «Обзор», которая отображает 3 информационных окна.

В настоящий момент страница «Обзор» пуста перед загрузкой файла csv и вводит числовые значения c в "вместимость". Как только оба требования будут выполнены, все информационное окно появится и отобразит расчет.

Однако я бы хотел, чтобы на странице «Обзор» отображалось все информационное окно даже без загруженного файла csv и предоставленной емкости (конечно, информационное окно будет показывать НУЛЬ ). После загрузки файла csv и предоставления емкости значения инфобокса изменятся соответственно.

Чего не хватает в моих кодах? Оцените ваш совет.

library(shinydashboard)
library(tidyverse)
library(lubridate)

ui <- dashboardPage(
  dashboardHeader(title = "B. Times Square"),
  dashboardSidebar(
    sidebarMenu(
      menuItem(text = "Overview", tabName = "overview", icon = icon("balance-scale-right")),
      menuItem(text = "File Upload", tabName = "data", icon = icon("file-upload"))
    )
  ),

  dashboardBody(
    tabItems(
      tabItem(tabName = "overview",
                fluidRow(
                  infoBoxOutput(outputId = "i.revenue"),
                  infoBoxOutput(outputId = "i.transaction"),
                  infoBoxOutput(outputId = "i.rate")
                )
              ), 
      tabItem(tabName = "data",
          column(width = 4,
                   fluidRow(
                     inputPanel(
                       fileInput(inputId = "csv", label = "File upload:", accept = ".csv"),
                       numericInput(inputId = "capacity", label = "Capacity", value = 0)
                     )
                   )
                 )

server <- function(input, output) {

  df.transaction <- reactive({
    req(input$csv$datapath)

    data_type <- list(
      id = col_character(),
      status = col_character(),
      book_channel = col_character(),
      book_datetime = col_datetime(),
      check_in = col_date(),
      check_out = col_date(),
      total_amount = col_double()
    )

    data_1 <- read_csv(input$csv$datapath, col_types = data_type) %>%
      filter(!(is.na(check_in) | is.na(total_amount)) & total_amount != 0) %>%
      # recode book_channel with acronym
      # recode status so that only "Book"/"Cancel" status remains
      mutate(book_channel = case_when(book_channel == "Flight Centre Travel Group" ~ "FCTG",
                                      book_channel == "HRS - Hotel Reservation Service" ~ "HRS",
                                      book_channel == "My Bookings/Entertainment Book" ~ "MBEB",
                                      book_channel == "WebBeds - Sunhotels" ~ "WebBeds-S",
                                      book_channel == "WebBeds - Destinations of the World" ~ "WebBeds-DOTW",
                                      book_channel == "Asian Overland Services" ~ "AOS",
                                      book_channel == "Egypt Express Travel" ~ "EET",
                                      book_channel == "MG Holiday (OLD)" ~ "MGH",
                                      TRUE ~ book_channel),
             book_channel = as_factor(book_channel),
             book_date = str_split(book_datetime, " ", simplify = TRUE)[,1],
             book_time = str_split(book_datetime, " ", simplify = TRUE)[,2],
             lead_time = time_length(interval(book_date, check_in), "day"),
             lead_time = if_else(lead_time < 0, 0, lead_time),
             overnight = time_length(interval(check_in, check_out), "day"),
             status = if_else(status %in% c("Booked", "Modified"), "Book", "Cancel"),
             status = as_factor(status)
             ) %>%
      select(id, status, book_channel, book_date, book_time, check_in, check_out, lead_time, overnight, total_amount)

  })

  df.occupancy <- reactive({
    req(input$csv$datapath)

    data_type_2 <- list(
      id = col_character(),
      status = col_character(),
      book_channel = col_character(),
      book_datetime = col_datetime(),
      check_in = col_date(),
      check_out = col_date(),
      total_amount = col_double()
    )

    data_2 <- read_csv(input$csv$datapath, col_types = data_type_2) %>%
      filter(!(is.na(check_in) | is.na(total_amount)) & total_amount != 0) %>%
      # recode book_channel with acronym
      # recode status so that only "Book"/"Cancel" status remains
      mutate(book_channel = case_when(book_channel == "Flight Centre Travel Group" ~ "FCTG",
                                      book_channel == "HRS - Hotel Reservation Service" ~ "HRS",
                                      book_channel == "My Bookings/Entertainment Book" ~ "MBEB",
                                      book_channel == "WebBeds - Sunhotels" ~ "WebBeds-S",
                                      book_channel == "WebBeds - Destinations of the World" ~ "WebBeds-DOTW",
                                      book_channel == "Asian Overland Services" ~ "AOS",
                                      book_channel == "Egypt Express Travel" ~ "EET",
                                      book_channel == "MG Holiday (OLD)" ~ "MGH",
                                      TRUE ~ book_channel),
             book_channel = as_factor(book_channel),
             status = if_else(status %in% c("Booked", "Modified"), "Book", "Cancel"),
             status = as_factor(status)
             ) %>%
      filter(status == "Book") %>%
      mutate(check_in = map2(check_in, check_out, ~ seq(.x, .y - 1, "day"))) %>%
      unnest(check_in) %>% group_by(id) %>% add_count() %>%
      mutate(check_out = check_out - rev(row_number() - 1),
             total_amount = total_amount / n) %>%
      select(- c(status, n))
  })

  output$i.revenue <- renderInfoBox({
    revenue.dollar <- df.transaction()$total_amount %>% sum() %>% round()

    infoBox(title = "Revenue", icon = icon("hand-holding-usd"), value = revenue.dollar)
  })

  output$i.transaction <- renderInfoBox({
    transaction.count <- df.transaction() %>% nrow()

    infoBox(title =  "Transaction", icon = icon("bed"), value = transaction.count)
  })

  output$i.rate <- renderInfoBox({
    occupancy <- df.occupancy() %>% nrow()
    occupancy <- round(occupancy * 100 / (input$capacity * 365))

    infoBox(title = "Occupancy %", icon = icon("percentage"), value = occupancy)
  })

}


shinyApp(ui = ui, server = server)