根据R Shiny中的现有列创建新列

时间:2019-02-26 18:13:29

标签: r shiny conditional shinydashboard

我让用户将数据集上载到我的R Shiny应用程序中,然后让他指定该数据集的时间变量以及它是按月还是按季度出现。用户上载的数据在服务器内称为model_data。然后,我想在model_data中创建一个名为time_var_use的新列,该列将是用户选择的时间变量,但会转换为yearmon(对于月度数据)或yearqtr(对于季度数据)格式。

我正在努力创建这个新变量time_var_use,并根据input$time_threshold的唯一值更新我的输入之一time_var_use

此闪亮应用的代码如下:

     library(shiny)
     library(shinydashboard)
     library(dplyr)
     library(tidyr)
     library(ggplot2)
     library(ggrepel)
     library(scales)
     library(lubridate)
     library(knitr)
     library(foreign)
     library(DT)
     library(caret)
     library(car)
     library(data.table)
     library(digest)
     library(jsonlite)
     library(httr)
     library(reshape2)
     library(zoo)
     library(sqldf)
     library(boot)
     library(openxlsx)
     library(readxl)

     options(shiny.maxRequestSize = 30000*1024^2)
     options(scipen = 999)

  ### Define app

1。 UI设计

    ui <- dashboardPage(

     dashboardHeader(title = "My app"),

     dashboardSidebar(

 sidebarMenu(

   menuItem("Upload Data", tabName = "data_upload", icon = icon("folder- 
  open"))

 )

 ),

     dashboardBody(

tags$head(tags$style(HTML('.main-header .logo {

                          font-family: "Bliss Pro Light", Times, "Times New Roman", serif;

                          font-weight: bold;

                          font-size: 30px;

                          }

                          '))),

tabItems(

  tabItem(tabName = "data_upload",

          fluidRow(

            box(title = "Modelling data", status = "primary",

                fileInput(inputId = "main_data", label = "Upload the data for modelling", accept = c('.csv', 'text/comma-separated-values,text/plain', 'text/csv', 'csv')),

                checkboxInput(inputId = "header", label = "The data has headers", value = TRUE),

                radioButtons(inputId = "sep", label = "Delimiter:", choices = c("Comma" = ",","Semicolon" = ";","Tab" = "\t"), selected = ";")

            )
          ),
          fluidRow(

            box(title = "Divide modelling data into estimation & validation sample", status = "primary", width = 12,

                selectizeInput(inputId = "time_var", label = "Select the time variable", choices = "", multiple = FALSE),

                #frequency of the data

                tags$b("Choose the frequency of your data"),

                radioButtons(inputId = "frequency", label = "", choices = c("Monthly", "Quarterly"), selected = "Quarterly"),

                #time format based on frequency - choices

                tags$b("Select the time series variable format"),

                conditionalPanel(condition = "input.frequency == 'Monthly'",

                                 radioButtons(inputId = "format_monthly", label = "",

                                              choices = c("month Year, e.g. Jan 2014 or January 2014" = "format_1", "month/day/Year, e.g. 2/26/2019" = "format_2"),

                                              selected = "format_1")

                ),

                conditionalPanel(condition = "input.frequency == 'Quarterly'",

                                 radioButtons(inputId = "format_quarterly", label = "",

                                              choices = c("Year quarter, e.g. 2014q3 or 2014Q3" = "format_3", "month/day/Year, e.g. 2/26/2019" = "format_4"),

                                              selected = "format_3")

                ),

                selectizeInput(inputId = "time_threshold", label = "Select time threshold for estimation and validation", choices = "", multiple = FALSE),

                h6("Data before this threshold will be used for estimation, data after this threshold will be used for validation.")

           )
          )
         )
        )
       )
      )

2。服务器设计

server <- function(input, output, session) {

 model_data <- reactive({

infile <- input$main_data



if (is.null(infile))

  return(NULL)

read.csv(infile$datapath, header = input$header, sep = input$sep, stringsAsFactors = FALSE)

  })

  # update time_var choices
  observe({

vchoices <- names(model_data())

updateSelectizeInput(session = session, inputId = "time_var", choices = vchoices)

  })

  observeEvent(input$frequency, {

  if (input$frequency == "Monthly") {

   if (input$format_monthly == "format_1") {
      model_data()[, "time_var_use"] <- as.yearmon(model_data()[, input$time_var])
    }

    else if (input$format_monthly == "format_2") {
      model_data()[, "time_var_use"] <- as.yearmon(as.Date(model_data()[, input$time_var], "%m/%d/%Y"))
    }

 }

  if (input$frequency == "Quarterly") {

    if (input$format_quarterly == "format_3") {
      model_data()[, "time_var_use"] <- as.yearqtr(model_data()[, input$time_var])
   }

    else if (input$format_quarterly == "format_4") {
      model_data()[, "time_var_use"] <- as.yearqtr(as.Date(model_data()[, input$time_var], "%m/%d/%Y"))
 }

   }

updateSelectizeInput(session, inputId = "time_threshold",

                     choices = as.character(unique(model_data()[, "time_var_use"])),

                     server = TRUE)

   })


     }

3。创建ShinyApp

shinyApp(ui, server)

部分无效的代码是observeEvent(),位于服务器环境的末尾。我试图在time_var_use内创建observeEvent列,然后用它更新input$time_threshold的值。

我不知道如何在此处附加要上传到应用程序的示例CSV文件(来自上面的model_data),所以我只是从下面的此示例CSV文件复制数据:

     time var1 var2      var3
     2015q1    8    1 0.6355182
     2015q1   12    0 0.5498784
     2015q1   23    1 0.9130934
     2015q1  152    1 0.8938210
     2015q2  563    1 0.2335470
     2015q3    8    0 0.5802677
     2015q4    2    0 0.8514926
     2016q1    1    1 0.4712101
     2016q1   14    0 0.9747804
     2016q2   13    1 0.8571699
     2016q2   14    1 0.8738486
     2016q3   53    0 0.8467971
     2016q4   75    0 0.3191140
     2016q4   15    0 0.9608926

基于time列,我的目的是在应用程序中创建time_var_use列,然后将其值用于其他输入。

0 个答案:

没有答案