R 使用多个无功值

我正在尝试创建一个闪亮的R应用程序，用户在其中输入两个日期：开始日期和结束日期（假设用户将选择某一周的任何一个日期）。通过选择日期，用户将能够看到在这些天内，他将从下周的商品列表中卖出多少商品。我得到了一周内每天总销售额的百分比数据。利用这一点，并利用过去一周的每种商品的销售数据，我试图创建这个应用程序。然而，我认为我在使用被动表达式时犯了一些错误。任何帮助都将不胜感激。我提供了下面的代码

ui.R
library(shiny)
shinyUI(fluidPage(
  sidebarLayout(
    sidebarPanel(
      dateInput('Start_Date',label = "starting on:",value = Sys.Date())
      dateInput('End_Date',label = "Ending on:",value = Sys.Date())
    ),
    mainPanel(
      tableoutput("mytable")
      )
  )
  ))

server.R
library(shiny)
library(stats)
shinyServer(function(input, output) {
  Days<-c("Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday")
  Percent_sales_by_day<-c(.10,.14,.14,.14,.14,.17,.17)
  Data_days<-data.frame(Days,Percent)
  items_sold<-c("A","B","C","D")
  sales_last_week<-c("100","200","300","800")
  Data_sales<-data.frame(items_sold,sales_last_week)
  Day_vector<-reactive({
    weekdays(seq(as.Date(input$Start_Date),as.Date(input$End_Date),by = "days")) 
  })
  Daily_split_vector<-reactive({
    library(dplyr)
    Data_days%>%
      filter(Days %in% Day_vector())
    Data_days$Percent_sales_by_day
  })
  Daily_split_value<-reactive({
    sum(Daily_split_vector())
  })
  Forecast<-reactive({
    Data_sales%>%
      mutate(sales_last_week=sales_last_week* Daily_split_value())
  })
  output$mytable<-renderTable({
    Forecast()
  })
  })

ui.R
图书馆（闪亮）
shinyUI（fluidPage）(
侧边栏布局(
侧栏面板(
dateInput（'开始日期'，label=“开始日期：”，value=Sys.Date（））
dateInput（'End_Date'，label=“Ending on:”，value=Sys.Date（））
),
主面板(
表格输出（“mytable”）
)
)
))
服务器.R
图书馆（闪亮）
图书馆（统计）
shinyServer（功能（输入、输出）{
Days我对您的基本目标不是100%清楚，但不管下面的代码是否为我运行。我试图对我所做的所有更改进行评论-它们大多只是一些小的语法错误-但如果您希望我澄清任何事情，请告诉我


ui.R:

library(shiny)
##
shinyUI(fluidPage(
  sidebarLayout(
    sidebarPanel(

      dateInput(
        'Start_Date',
        label = "starting on:",
        value = Sys.Date()
      ), ## added comma
      dateInput(
        'End_Date',
        label = "Ending on:",
        value = Sys.Date())
    ),

    mainPanel(
      tableOutput("mytable") ## 'tableOutput' not 'tableoutput'
    )

  )
))

library(shiny)
library(dplyr)
options(stringsAsFactors=F)  ## try to avoid factors unless you
                             ## specifically need them
##
shinyServer(function(input, output) {

  Days <- c(
    "Sunday","Monday","Tuesday","Wednesday",
    "Thursday","Friday","Saturday")

  Percent_sales_by_day <- c(
    .10,.14,.14,.14,.14,.17,.17)

  Data_days <- data.frame(
    Days,
    Percent_sales_by_day) ## changed from 'Percent'

  items_sold <- c("A","B","C","D")

  sales_last_week <- c(
    100,200,300,800) ## changed from character (???) to numeric type

  Data_sales <- data.frame(
    items_sold,
    sales_last_week)

  Day_vector <- reactive({
    weekdays(
      seq.Date(
        as.Date(input$Start_Date),
        as.Date(input$End_Date),
        by = "day")) 
  })

  Daily_split_vector <- reactive({
    Data_days %>%
      filter(Days %in% Day_vector()) %>% ## added pipe
   ## Data_days$Percent_sales_by_day  ## changed this line
      select(Percent_sales_by_day)    ## to this line
  })

  Daily_split_value <- reactive({
    sum(Daily_split_vector())
  })

  Forecast <- reactive({
    Data_sales%>%
      mutate(
        sales_last_week=sales_last_week* Daily_split_value())
  })

  output$mytable <- renderTable({
    Forecast()
  })
})


server.R:

library(shiny)
##
shinyUI(fluidPage(
  sidebarLayout(
    sidebarPanel(

      dateInput(
        'Start_Date',
        label = "starting on:",
        value = Sys.Date()
      ), ## added comma
      dateInput(
        'End_Date',
        label = "Ending on:",
        value = Sys.Date())
    ),

    mainPanel(
      tableOutput("mytable") ## 'tableOutput' not 'tableoutput'
    )

  )
))

library(shiny)
library(dplyr)
options(stringsAsFactors=F)  ## try to avoid factors unless you
                             ## specifically need them
##
shinyServer(function(input, output) {

  Days <- c(
    "Sunday","Monday","Tuesday","Wednesday",
    "Thursday","Friday","Saturday")

  Percent_sales_by_day <- c(
    .10,.14,.14,.14,.14,.17,.17)

  Data_days <- data.frame(
    Days,
    Percent_sales_by_day) ## changed from 'Percent'

  items_sold <- c("A","B","C","D")

  sales_last_week <- c(
    100,200,300,800) ## changed from character (???) to numeric type

  Data_sales <- data.frame(
    items_sold,
    sales_last_week)

  Day_vector <- reactive({
    weekdays(
      seq.Date(
        as.Date(input$Start_Date),
        as.Date(input$End_Date),
        by = "day")) 
  })

  Daily_split_vector <- reactive({
    Data_days %>%
      filter(Days %in% Day_vector()) %>% ## added pipe
   ## Data_days$Percent_sales_by_day  ## changed this line
      select(Percent_sales_by_day)    ## to this line
  })

  Daily_split_value <- reactive({
    sum(Daily_split_vector())
  })

  Forecast <- reactive({
    Data_sales%>%
      mutate(
        sales_last_week=sales_last_week* Daily_split_value())
  })

  output$mytable <- renderTable({
    Forecast()
  })
})

库（闪亮）
图书馆（dplyr）
选项（stringsAsFactors=F）##除非您
##特别需要它们
##
shinyServer（功能（输入、输出）{
天