在Shiny中計算日期范圍的平均值和中位數

Question

想要計算僅按數據表的選定日期范圍分組的數字變量的均值和中位數，而不是小葉數據。 傳單地圖有效（只需要縮小以查看假的長/拉圖，但現在不擔心）。

我為數據的中間數/平均值的總和創建了第二個數據幀df10 。

到目前為止，嘗試改變輸入函數為平均值創建單獨的變量，但發現它很麻煩，不需要我的需要。

嘗試使用colMeans(dataset()[,which(sapply(dataset(), class) != "Date")])這里Shiny計算數據框中列的平均值

錯誤是"invalid 'x' type in 'x && y" 。 它與colmeans有關

### Generate a dataset ###
start_date <- as.Date('2018-01-01')  
end_date <- as.Date('2019-05-10')   
set.seed(1984)
date1 <- as.Date(sample( as.numeric(start_date): as.numeric(end_date), 988, 
                         replace = T), origin = '1970-01-01')
group <- rep(letters[1:26], each = 38)
x1 <- runif(n = 988, min = 3.26, max = 10)
x2 <- runif(n = 988, min = 3.26, max = 10)
x3 <- runif(n = 988, min = 3.26, max = 10)
x4 <- runif(n = 988, min = 3.26, max = 10)
x5 <- runif(n = 988, min = 3.26, max = 10)
latitude <- runif(988,40.75042,50.75042)
longitude <- runif(988,-73.98928,-63.98928)

dataframe <- cbind(data.frame(date1,group,x1,x2,x3,x4,x5,latitude,longitude))

df10 <- cbind(data.frame(date1,group,x1,x2,x3,x4,x5))
library(lubridate)
dataframe$date <- ymd(dataframe$date1)
df10$date <- ymd(df10$date1)

library(shiny)
library(leaflet)
library(DT)
dataframe$defectrateLvl <- cut(dataframe$x1, 
                               c(3.26,6,100), include.lowest = T,
                               labels = c('3.26-6x','6x+')) 
beatCol <- colorFactor(palette = c('yellow', 'red'), dataframe$defectrateLvl)


ui <- fluidPage(
  dateInput(inputId = "date", label="Select a date", value = "2019-03-01", min = "2018-01-01", max = "2019-05-10",
            format = "yyyy-mm-dd", startview = "month",
            language = "en", width = NULL),
  leafletOutput("map"),
  fluidRow(
    dateRangeInput("daterange","Date range:",start=Sys.Date()-10, end=Sys.Date() -1),
    DT::dataTableOutput("tbl")
  )
)

server <- shinyServer(function (input, output,session) {
  dailyData <- reactive(dataframe[dataframe$date == format(input$date, '%Y/%m/%d'), ] )
  output$map <- renderLeaflet({
    dataframe <- dailyData()  # Added this in attempt to integrate
    dataframe %>% leaflet() %>% 
      setView(lng = -73.98928, lat = 40.75042, zoom = 10) %>%
      addProviderTiles("CartoDB.Positron", options = providerTileOptions(noWrap = TRUE)) %>%
      addCircleMarkers(
        lng=~dataframe$longitude, # Longitude coordinates
        lat=~dataframe$latitude, # Latitude coordinates
        #radius=~defectrateLvl, # Total count
        popup =~ dataframe$group,
        color = ~beatCol(dataframe$defectrateLvl),
        fillOpacity=0.5 # Circle Fill Opacity
      )
  })  
  output$tbl<-DT::renderDataTable({
    dataset <- reactive({df10 })
    dataset() %>% group_by(group) %>% 
      filter(date > input$daterange[1],
             date < input$daterange[2])
    #sapply(Filter(is.numeric, df6), mean)
    colMeans(dataset()[,which(sapply(dataset(), class) !="date","date1","group")])
  })

})


shinyApp(ui, server)

我希望數值變量可以通過均值進行匯總，如果可能的話，可以通過中位數進行匯總，但此時不太重要。 任何幫助將不勝感激。

Answer 1

該錯誤是由最后一個函數引起的。

colMeans(df[,which(sapply(df, class) !="date","date1","group")])

此代碼將該函數應用於不屬於類xy的所有列。 "date"或"group"是列名。

ColMeans還會生成一個數字向量，這會導致錯誤，因為DT只能顯示矩陣或data.frame。 我為您提供了一個創建數據幀的代碼。 但是在genrell中我會考慮使用dplyr來創建你的結果。 這更容易。

這是一個有效的解決方案，但是您必須更改dateinputs，因為預定義的選擇會創建一個包含0行的data.frame。

library(lubridate)
library(shiny)
library(leaflet)
library(DT)
library(dplyr)

### Generate a dataset ###
start_date <- as.Date('2018-01-01')  
end_date <- as.Date('2019-05-10')   
set.seed(1984)
date1 <- as.Date(sample( as.numeric(start_date): as.numeric(end_date), 988, 
                         replace = T), origin = '1970-01-01')
group <- rep(letters[1:26], each = 38)
x1 <- runif(n = 988, min = 3.26, max = 10)
x2 <- runif(n = 988, min = 3.26, max = 10)
x3 <- runif(n = 988, min = 3.26, max = 10)
x4 <- runif(n = 988, min = 3.26, max = 10)
x5 <- runif(n = 988, min = 3.26, max = 10)
latitude <- runif(988,40.75042,50.75042)
longitude <- runif(988,-73.98928,-63.98928)

dataframe <- cbind(data.frame(date1,group,x1,x2,x3,x4,x5,latitude,longitude))

df10 <- cbind(data.frame(date1,group,x1,x2,x3,x4,x5))
dataframe$date <- ymd(dataframe$date1)
df10$date <- ymd(df10$date1)


dataframe$defectrateLvl <- cut(dataframe$x1, 
                               c(3.26,6,100), include.lowest = T,
                               labels = c('3.26-6x','6x+')) 
beatCol <- colorFactor(palette = c('yellow', 'red'), dataframe$defectrateLvl)


ui <- fluidPage(
    dateInput(inputId = "date", label="Select a date", value = "2019-03-01", min = "2018-01-01", max = "2019-05-10",
              format = "yyyy-mm-dd", startview = "month",
              language = "en", width = NULL),
    leafletOutput("map"),
    fluidRow(
        dateRangeInput("daterange","Date range:",start=Sys.Date()-10, end=Sys.Date() -1),
        DT::dataTableOutput("tbl")
    )
)

server <- shinyServer(function (input, output,session) {
    dailyData <- reactive(dataframe[dataframe$date == format(input$date, '%Y/%m/%d'), ] )
    output$map <- renderLeaflet({
        dataframe <- dailyData()  # Added this in attempt to integrate
        dataframe %>% leaflet() %>% 
            setView(lng = -73.98928, lat = 40.75042, zoom = 10) %>%
            addProviderTiles("CartoDB.Positron", options = providerTileOptions(noWrap = TRUE)) %>%
            addCircleMarkers(
                lng=~dataframe$longitude, # Longitude coordinates
                lat=~dataframe$latitude, # Latitude coordinates
                #radius=~defectrateLvl, # Total count
                popup =~ dataframe$group,
                color = ~beatCol(dataframe$defectrateLvl),
                fillOpacity=0.5 # Circle Fill Opacity
            )
    })  

    dataset <- reactive({df10 })

    output$tbl <-DT::renderDataTable({
        df <- dataset()

        df <- df %>% 
            group_by(group) %>% 
            filter(date > input$daterange[1],
                   date < input$daterange[2])
        #sapply(Filter(is.numeric, df6), mean)
        result <- data.frame(colMeans(df[which(sapply(df, class)=="numeric")]))
        colnames(result)[1] <- "Result"
        result
        #colMeans(df[,which(sapply(df, class) !="date","date1","group")])
    })

})


shinyApp(ui, server)