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请在下面运行此脚本，以下 R 脚本提供了一个带有两个框的闪亮仪表板。我想减小两个框之间的宽度并在右侧图表中显示数据。数据应该基于我们在 ggplotly 函数中看到的点击事件。我猜也可以用 plotly 来完成这项工作。我希望代码同时快速高效。

## app.R ##
library(shiny)
library(shinydashboard)
library(bupaR)
library(eventdataR)
library(lubridate)
library(dplyr)
library(XML)
library(edeaR)
library(xml2)
library(data.table)
library(ggplot2)
library(ggthemes)
library(glue)
library(tibble)
library(miniUI)
library(tidyr)
library(shinyTime)
library(magrittr)
library(plotly)
library(DT)
library(splitstackshape)
library(scales)

patients$patient = as.character(patients$patient)
a1 = patients$patient
a2 = patients$handling
a3 = patients$time
a123 = data.frame(a1,a2,a3)
patients_eventlog = simple_eventlog(a123, case_id = "a1",activity_id = "a2", 
timestamp = "a3")

dta <- reactive({
tr <- data.frame(traces(patients_eventlog, output_traces = T, output_cases = 
F))
tr.df <- cSplit(tr, "trace", ",")
tr.df$af_percent <-
percent(tr.df$absolute_frequency/sum(tr.df$absolute_frequency))
pos <- c(1,4:ncol(tr.df))
tr.df <- tr.df[,..pos]
tr.df <- melt(tr.df, id.vars = c("trace_id","af_percent"))
tr.df
})
patients10 <- reactive({
patients11 <- arrange(patients_eventlog, a1)
patients12 <- patients11 %>% arrange(a1, a2,a3)
patients12 %>%
group_by(a1) %>%
mutate(time = as.POSIXct( a2, format = "%m/%d/%Y %H:%M"),diff_in_sec =  a2 - 
lag( a2)) %>% 
mutate(diff_in_sec = ifelse(is.na(diff_in_sec),0,diff_in_sec)) %>% 
mutate(diff_in_hours = as.numeric(diff_in_sec/3600)) %>% 
mutate(diff_in_days = as.numeric(diff_in_hours/24))
})
ui <- dashboardPage(
dashboardHeader(title = "Trace Chart"),
dashboardSidebar(
width = 0
),
dashboardBody(
box(title = "Trace Chart", status = "primary",height = "455" ,solidHeader = 
T,
    plotlyOutput("trace_plot"),style = "height:420px; overflow-y: 
scroll;overflow-x: scroll;"),

box( title = "Trace Summary", status = "primary", height = "455",solidHeader 
= T, 
     dataTableOutput("trace_table"))
)
)
server <- function(input, output) 
{ 
output$trace_plot <- renderPlotly({
mp1 = ggplot(data = dta(), aes(x = variable,y = trace_id, fill = value,
                               label = value,
                               text=paste("Variable:",variable,"<br> Trace 
                                          ID:",trace_id,"<br> 
Value:",value,"<br> Actuals:",af_percent))) +
  geom_tile(colour = "white") +
  geom_text(colour = "white", fontface = "bold", size = 2) +
  scale_fill_discrete(na.value="transparent") +
  theme(legend.position="none") + labs(x = "Traces", y = "Activities")
ggplotly(mp1, tooltip=c("text"), height = 1226, width = 1205)
})
output$trace_table <- renderDataTable({
req(event_data("plotly_click"))
Values <- dta() %>% 
  filter(trace_id == event_data("plotly_click")[["y"]]) %>% 
  select(value)

valueText <- paste0(Values[[1]] %>% na.omit(),collapse = "")
agg <- aggregate(a3~a1, data = patients10(), FUN = function(y){paste0(unique(y),collapse = "")})

currentPatient <- agg$a1[agg$a3 == valueText]

patients10_final <- patients10() %>%
  filter(a1 %in% currentPatient)
datatable(patients10_final, options = list(paging = FALSE, searching = FALSE))
})
}
shinyApp(ui, server)
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1 回答 1

3

我创建了一个简单的示例，您可以如何将耦合事件plotly与一些接近您需求的示例数据一起使用：

library(shiny)
library(plotly)
library(DT)
set.seed(100)
data <- data.frame(A=sample(c('a1','a2','a3'),10,replace=T),
                   B=1:10,
                   C=11:20,
                   D=21:30)
shinyApp(
  ui = fluidPage(
plotlyOutput("trace_plot"),
  DT::dataTableOutput('tbl')),
  server = function(input, output) {

    output$trace_plot <- renderPlotly({
      plot_ly(data, x=~A,y=~B,z=~C, source = "subset") %>% add_histogram2d()})

    output$tbl <- renderDataTable({
      event.data <- event_data("plotly_click", source = "subset")

      if(is.null(event.data) == T) return(NULL)
      print(event.data[ ,c(3:4)])
    })

  }
)

正如您可以通过按下第一个图看到的，我们在表中获得了下面的数据子集（x 和 y 值），您还可以使用它与主要数据合并以显示时间戳等。

于 2017-12-21T09:07:23.313 回答