R shiny filter data based on user input-CodePudding

I have an application with 3 input types: a dropdown, a date range and group check box. I am able to filter and plot data based on the dropdown and date range but having trouble with the checkbox.I have implemented a group checkbox with values Stage1, Stage2. If user selects stage 1 then data from these 3 columns [status_stage1_2019|status_stage1_2021|status_stage1_2022 == 1] should be subsetted. Likewise for stage 2. Here is my data

mydata<-structure(list(Id = structure(c(1L, 11L, 19L, 27L, 28L, 29L, 
30L, 31L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 12L, 13L, 14L, 
15L, 16L, 17L, 18L, 20L, 21L, 22L, 23L, 24L, 25L, 26L), .Label = c("DB-1", 
"DB-11", "DB-12", "DB-13", "DB-14", "DB-15", "DB-16", "DB-17", 
"DB-18", "DB-19", "DB-2", "DB-20", "DB-23", "DB-25", "DB-26", 
"DB-27", "DB-28", "DB-29", "DB-3", "DB-30", "DB-31", "DB-32", 
"DB-34", "DB-35", "DB-36", "DB-37", "DB-4", "DB-5", "DB-6", "DB-7", 
"DB-9"), class = "factor"), examiner = structure(c(1L, 1L, 1L, 
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("Alex", 
"Jhon", "Kim", "Maymoon", "Mike"), class = "factor"), Relationship = structure(c(4L, 
2L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 2L, 1L, 3L, 
3L, 2L, 3L, 3L, 3L, 3L, 4L, 1L, 2L, 2L, 2L, 2L, 3L, 1L), .Label = c("father", 
"mother", "self", "sibling"), class = "factor"), application_date = structure(c(10L, 
6L, 8L, 3L, 6L, 3L, 7L, 15L, 20L, 2L, 20L, 3L, 14L, 11L, 2L, 
8L, 10L, 5L, 20L, 14L, 13L, 11L, 17L, 12L, 1L, 16L, 19L, 9L, 
18L, 21L, 4L), .Label = c("1/10/19", "1/15/19", "11/13/18", "11/15/18", 
"11/20/18", "11/27/18", "11/28/18", "11/30/18", "12/20/18", "12/4/18", 
"12/6/18", "12/7/18", "2/14/19", "2/25/19", "2/26/19", "3/12/19", 
"3/14/19", "3/21/19", "3/22/19", "4/3/19", "4/5/19"), class = "factor"), 
    gender = structure(c(2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
    1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 
    2L, 1L, 1L, 1L, 1L, 1L, 2L), .Label = c("female", "male"), class = "factor"), 
    stage1_date = structure(c(8L, 3L, 6L, 2L, 3L, 7L, 3L, 10L, 
    13L, 11L, 13L, 2L, 10L, 3L, 11L, 5L, 1L, 3L, 7L, 17L, 12L, 
    1L, 14L, 9L, 5L, 16L, 15L, 4L, 16L, 1L, 3L), .Label = c("", 
    "1/10/19 21:40", "1/10/19 21:45", "1/17/19 19:26", "1/31/19 20:25", 
    "1/9/19 19:50", "1/9/20 14:50", "2/21/19 21:15", "2/6/19 20:36", 
    "3/15/19 16:50", "3/21/19 18:21", "3/4/19 16:30", "4/26/19 19:20", 
    "4/8/19 12:40", "4/8/19 12:41", "5/1/19 18:05", "7/30/19 15:10"
    ), class = "factor"), stage2_date = structure(c(1L, 1L, 1L, 
    1L, 4L, 1L, 9L, 1L, 2L, 1L, 10L, 7L, 8L, 1L, 1L, 1L, 5L, 
    1L, 1L, 6L, 2L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L), .Label = c("", 
    "5/11/21 17:37", "5/11/21 17:42", "5/11/21 17:50", "5/11/21 17:52", 
    "5/14/21 16:07", "5/15/21 16:07", "5/16/21 16:07", "5/21/21 17:46", 
    "5/21/21 17:47"), class = "factor"), status_stage1_2019 = c(1L, 
    1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    0L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L
    ), status_stage1_2020 = c(0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), status_stage1_2021 = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
    ), status_stage1_2022 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), status_stage2_2020 = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
    ), status_stage2_2021 = c(0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 
    1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L), status_stage2_2022 = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
    )), class = "data.frame", row.names = c(NA, -31L))

Here is my code

server <- function(input, output, session) {
  #Summarize Data and then Plot
  data <- reactive({
    
    req(input$examiner)
   
    mydata %>%
      dplyr::filter(
        examiner %in% input$examiner ,
        stage1_date >= input$daterange[1] &
          stage1_date <= input$daterange[2]
      ) %>%
      group_by(Relationship) %>% summarize(Total = n())
    
  })
output$selected_var <- renderText({ 
    paste("You have chosen ", input$examiner)
  }) 
  #Plot 
  output$plot <- renderPlot({
    req(data())
    g <- ggplot(data(), aes( y = Total, x = Relationship))
    g   geom_bar(stat = "sum")
  })
}
ui <- basicPage(
  titlePanel("My Dashboard"),
  helpText("Shows my data"),
  sidebarPanel(
    selectInput(inputId = "examiner",
                label = h5("Select examiner"),
                choices = c(as.character(mydata$examiner))
    ),
    dateRangeInput("daterange",
                   h5("SelectDates"),
                   format="yyyy-mm-dd",
                   start = "2001-01-01"
    ),
    checkboxGroupInput("stage",
                  h5("Select stage"),
                  choices = c("Stage1","Stage2"),
                  selected = c("Stage1","Stage2")
                  )
    ),
  
  mainPanel(
    textOutput("selected_var"),
    plotOutput("plot")
    
  )
)

CodePudding user response：

If the group check box name is 'stage', then we may use if_any to loop over the 'status_' columns based on the input from 'stage' as well as loop across the 'stage1_date', 'stage2_date' from the 'stage' values to create the logical expression

library(stringr)
library(lubridate)
server <- function(input, output, session) {
  #Summarize Data and then Plot
  data <- reactive({
    
    req(input$examiner)
    req(input$stage)
    stage_date <- tolower(input$stage)
    
    mydata %>%
      dplyr::mutate(across(ends_with("_date"), as.Date, format = "%m/%d/%y %H:%M")) %>%
      dplyr::filter(
        examiner %in% input$examiner,
        if_any(matches(str_c('status_', stage_date)), ~ 
                 .x ==1),
        if_all(all_of(str_c(stage_date, '_date')), ~ 
                  .x >=  input$daterange[1] &
                  .x <= input$daterange[2]
         )
         
        ) %>%
      group_by(Relationship) %>%
      summarize(Total = n(), .groups = "drop")
    
    
    
  })
  
  output$selected_var <- renderText({ 
    paste("You have chosen ", input$examiner)
  }) 
  #Plot 
  output$plot <- renderPlot({
    req(data())
    print(nrow(data()))
    g <- ggplot(data(), aes( y = Total, x = Relationship))
    g   geom_bar(stat = "sum")
  })
}