Displaying data in the chart based on plotly_click in R shiny

Question

Please run this script below, the following R script gives a shiny dashboard with two boxes. I want to reduce the width between two boxes and display data in the right chart. The data should be based on the on click event that we see in the ggplotly function. Also plotly can be used to do the job, I guess. I want the code to fast and efficient at the same time.

## 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)

@Mal_a, Thanks for replying, see I know about plotly_click, the help that I need is to tweak the logic under "output$trace_table" in the R script to display the cases and activites with timestamp in the table. — Ashmin Kaul
– Ashmin Kaul, Commented Dec 21, 2017 at 8:38

Mal_a · Accepted Answer · 2017-12-21 09:17:13Z

3

I have created an easy example how You can use coupled events from plotly with some sample data that is close to Your needs:

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)])
    })

  }
)

As You can see by pressing on the first plot we get the subset of data below in the table (x and y values), further you can use it to merge with the primary data to display timestamps etc. .

edited Dec 21, 2017 at 9:17

answered Dec 21, 2017 at 9:07

Mal_a

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2 Comments

Ashmin Kaul Over a year ago

I appreciate your efforts, but my requirement is a little different, see the above script that I have posted gives your a complete trace explorer with data table showing proper result if you make use of the "patients" eventlog i.e. replace "patients_eventlog" with patients. Solution is there, but I have a data where I only have caseID, activity and Timestamp. So I can only create a simple_eventlog to fit my need which I have done with the plot, regarding the data to be displayed, logic is there for the patients eventlog, I just need your help in changing the logic a little.

Ashmin Kaul Over a year ago

you can please replace a1, a2 and a12 variables and replace a1 with "patient", a2 with "handling" and a3 with "time" column. This shall give an idea about the way I want the data to be displayed. Please help.

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