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在 R 中的 Shiny 中部署 dataTableOutput 和 plot; “整理” dataTableOutput

[英]Deploying dataTableOutput and plot in Shiny in R; "tidying" the dataTableOutput

我正在一個閃亮的應用程序中開發一個功能,該功能顯示一個dataTableOutput和一個與之關聯的繪圖。 該圖按組和日期顯示唯一 ID 的計數,而表格顯示與過濾的時間和日期相關的數據。 表中的列標題是數據中的日期,這些數據是使用帶有tidyrpivot_wider函數創建的。 這是一些示例代碼:-

數據

#relevant libraries
library(wakefield)#for generating the Status variable
library(dplyr)
library(stringi)
library(Pareto)
library(uuid)
library(ggplot2)
library(data.table)
library(shiny)
library(DT)


#mock data creation
set.seed(1)
#data<-data.frame()
Date<-seq(as.Date("2015-01-01"), as.Date("2015-12-31"), by = "1 day")
Date<-sample(rep(Date,each=10),replace = T)

event<-r_sample_factor(x = c("Wrestling", "Drama", 
                                    "Information", "Football", "Rugby", "Movie", "Music", "News"), n=length(Date))

channel<-r_sample_factor(x = c("Channel 1", "Channel 2", "Channel 3", "Channel 4"), n=length(Date))

Hour<-r_sample_factor(x = c(0:23), n=length(Date))

Group<-r_sample_factor(x = c("A","B","C","D","E"), n=length(Date))

#creating user ID

set.seed(1)

n_users <- 100
n_rows <- 3650

relative_probs <- rPareto(n = n_users, t = 1, alpha = 0.3, truncation = 500) 
unique_ids <- UUIDgenerate(n = n_users)

AnonID <- sample(unique_ids, size = n_rows, prob = relative_probs, replace = TRUE)


data<-data.frame(AnonID,Group,Date,Hour,channel,event)
data$Hour<-as.numeric(data$Hour)
head(data)

閃亮代碼


#ui================================
ui<-fluidPage(
  titlePanel("Example panel"),
  tabsetPanel(
    tabPanel("example text",
             sidebarPanel(width = 4,
                          dateRangeInput("daterange","Select dates", format = "yyyy-mm-dd",
                                         start = min("2015-01-01"),
                                         end = max("2015-01-10")),
                          numericInput("hourmin", "Select mininum hour",10,0,23),
                          numericInput("hourmax", "Select maximum hour", 22,0,23),
                          pickerInput("channel", "Select channel",
                                      choices = unique(channel), options = list('actions-box'=T,'live-search'=T),multiple = T)),#end of sidebarPanel
             mainPanel(
               column(width = 10, plotOutput("barplot", width = "100%")),
                      column(width = 8, dataTableOutput("table"))
             )#end of mainPanel
                          
             )
             )#end of tabPanel
  )#end of tabsetPanel
)#end of fluidPage


#server===========================================

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

  
 rv <- reactiveVal(NULL)  
  
  observe({
    
    rv(data)
  
    output$table<-renderDataTable({
      rv()%>%
      arrange(desc(Date))%>%
      filter(Date>=input$daterange[1] & Date<=input$daterange[2])%>%
      filter(Hour>=input$hourmin & Hour<=input$hourmax)%>%
      filter(channel %in% input$channel)%>%  
      group_by(channel,Hour,Date)%>%
      arrange(Hour,Date)%>%
      summarise(Programme=event, .groups = 'drop')%>%
      mutate(rn=rowid(Hour,Date))%>%
      pivot_wider(names_from = Date,values_from = Programme)%>%
      select(-rn)
    })
    
    output$barplot<-renderPlot({
      
      rv()%>%
        filter(Date>=input$daterange[1] & Date<=input$daterange[2])%>%
        filter(Hour>=input$hourmin & Hour<=input$hourmax)%>%
        filter(channel %in% input$channel)%>%
        group_by(Date,Group)%>%
        summarise(UniqueID=n_distinct(AnonID))%>%
        ggplot()+
        geom_bar(aes(x=Date,y=UniqueID, fill=Group), stat = "identity", position = "dodge")
        
      
    })
    
    })#end of observe
  }

shinyApp(ui,server)

這是輸出:-

在此處輸入圖片說明

你可以看到數據表,我創建了一種“電視指南”,顯示了節目的日期和時間。 但是,我認為缺少字段有點礙眼。 與其用其他文本填充它們,我想知道是否有更好的方法來顯示這樣的表格,以便幾乎沒有/沒有空白空間並且使它更簡潔?

其次,我想知道如何使它具有交互性。 我希望能夠點擊數據表的單元格/行,結果是在給定的時間和日期使用新的UniqueID計數被動地更新繪圖? 這是否容易實施,如果可以,有人可以告訴我如何實施嗎? 謝謝你 :)

你應該考慮問兩個不同的問題。 對於第一部分,您可以同時顯示小時和事件,這樣您就可以為每個通道顯示一行。 然后您可以在表格底部提供密鑰,因為每個事件只顯示前 3 個字母。 嘗試這個

output$table<-renderDT({
      rv()%>%
        arrange(desc(Date))%>%
        filter(Date>=input$daterange[1] & Date<=input$daterange[2])%>%
        filter(Hour>=input$hourmin & Hour<=input$hourmax)%>%
        filter(channel %in% input$channel)%>%  
        group_by(channel,Date)%>%
        arrange(Date)%>%
        summarise(Programme=paste0(Hour,":",substr(event,1,3)), .groups = 'drop')%>%
        #mutate(rn=rowid(Date))%>%
        pivot_wider(names_from = Date,values_from = Programme) # %>%
        #select(-rn)
    })

輸出

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