R/eventAnalysisPage.R

In altairwei/wiztimebook: Tools that help you analyze daily event time records.

#' Create event analysis page UI
#' 
#' @param id Namespace for the page.
#' 
#' @importFrom shiny NS tagList fluidRow column plotOutput uiOutput textInput
#' @importFrom shinydashboard box
eventAnalysisPageUI <- function(id) {
  ns <- NS(id)
  tagList(
    fluidRow(
      column(width = 4,
             box(width = NULL, title = "Controls",
                 textInput(inputId = ns("name_filter"), label = "Search"),
                 uiOutput(outputId = ns("progress_candidates")))
      ),
      column(width = 8,
             box(width = NULL, plotOutput(outputId = ns("event_plot"))),
             box(width = NULL, shiny::tableOutput(outputId = ns("event_table")))
      )
      
    )
  )
}


#' Server logic of event analysis page
#'
#' @param input,output,session Arguments passed by \code{shiny::callModule} .
#' @param df A data frame.
#' 
#' @importFrom dplyr filter mutate
#' @importFrom stringr str_detect
#' @importFrom forcats fct_relevel
#' @importFrom ggplot2 ggplot aes geom_col ylab coord_flip
#' @importFrom shiny reactive req renderUI renderPlot
#' @importFrom shinyjqui sortableCheckboxGroupInput
eventAnalysisPage <- function(input, output, session, df) {
  
  filtered <- reactive({
    req(input$name_filter)
    df() %>% filter(str_detect(Event, input$name_filter))
  })
  
  output$progress_candidates <- renderUI({
    df_filtered <- filtered()
    ns <- session$ns
    all_prgs = unique(df_filtered$Progress)
    return(sortableCheckboxGroupInput(
      inputId = ns("event_progress"),
      label = "Choose progress to show:",
      choices = all_prgs,
      selected = all_prgs,
      inline = FALSE
    ))
  })
  
  selected_prgs <- reactive({
    input$event_progress_order[input$event_progress_order %in% input$event_progress]
  })
  
  output$event_plot <- renderPlot({
    df_filtered <- filtered()
    if (nrow(df_filtered) != 0) {
      df_filtered %>%
        filter(Progress %in% selected_prgs()) %>%
        mutate(Progress = fct_relevel(Progress, rev(selected_prgs()))) %>%
        ggplot(aes(x = Progress, y = as.numeric(Time, "hours"))) +
        geom_col() + ylab("Hours") + coord_flip()
    }
  })
  
  output$event_table <- shiny::renderTable({
    df_filtered <- filtered()
    if (nrow(df_filtered) != 0) {
      list_event_progress(df_filtered)
    }
  })
}