inst/app-descriptr/logic/logic_group_summary.R

# descriptive statistics
# observe({

#     updateSelectInput(session,
#                       inputId = "var_group",
#                       choices = names(data()),
#                       selected = '')

#     updateSelectInput(session,
#                       inputId = "var_grp_summary",
#                       choices = names(data()),
#                       selected = '')

# })

observeEvent(input$finalok, {

    num_data <- final_split$train[, sapply(final_split$train, is.numeric)]
    fact_data <- final_split$train[, sapply(final_split$train, is.factor)]

    if (is.null(dim(fact_data))) {
      k <- final_split$train %>% map(is.factor) %>% unlist()
      j <- names(which(k == TRUE))
      f_data <- tibble::as_data_frame(fact_data)
      colnames(f_data) <- j
      updateSelectInput(session,
                        inputId = "var_group",
                        choices = names(f_data))
    } else {
      updateSelectInput(session,
                      inputId = "var_group",
                      choices = names(fact_data))

    }

    if (is.null(dim(num_data))) {
        k <- final_split$train %>% map(is.numeric) %>% unlist()
        j <- names(which(k == TRUE))
        numdata <- tibble::as_data_frame(num_data)
        colnames(numdata) <- j
        updateSelectInput(session, inputId = "var_grp_summary",
          choices = names(numdata), selected = names(numdata))
      } else if (ncol(num_data) < 1) {
        updateSelectInput(session, inputId = "var_grp_summary",
          choices = '', selected = '')
      } else {
        updateSelectInput(session, inputId = "var_grp_summary",
          choices = names(num_data), selected = names(num_data))
      }


})

observeEvent(input$submit_part_train_per, {

    num_data <- final_split$train[, sapply(final_split$train, is.numeric)]
    fact_data <- final_split$train[, sapply(final_split$train, is.factor)]

    if (is.null(dim(fact_data))) {
      k <- final_split$train %>% map(is.factor) %>% unlist()
      j <- names(which(k == TRUE))
      f_data <- tibble::as_data_frame(fact_data)
      colnames(f_data) <- j
      updateSelectInput(session,
                        inputId = "var_group",
                        choices = names(f_data))
    } else {
      updateSelectInput(session,
                      inputId = "var_group",
                      choices = names(fact_data))

    }

    if (is.null(dim(num_data))) {
        k <- final_split$train %>% map(is.numeric) %>% unlist()
        j <- names(which(k == TRUE))
        numdata <- tibble::as_data_frame(num_data)
        colnames(numdata) <- j
        updateSelectInput(session, inputId = "var_grp_summary",
          choices = names(numdata), selected = names(numdata))
      } else if (ncol(num_data) < 1) {
        updateSelectInput(session, inputId = "var_grp_summary",
          choices = '', selected = '')
      } else {
        updateSelectInput(session, inputId = "var_grp_summary",
          choices = names(num_data), selected = names(num_data))
      }


})


# selected data
d_group_summary <- eventReactive(input$submit_gsummary, {
    # validate(need(input$var_group != '', 'Please select a grouping and summary variable.'))
    data <- final_split$train[, c(input$var_group,
                        input$var_grp_summary)]
})


gsummary_out <- eventReactive(input$submit_gsummary, {
  ko <- ds_group_summary(d_group_summary(),
                         !! sym(as.character(input$var_group)),
                         !! sym(as.character(input$var_grp_summary)))
  ko
})

g1_title <- eventReactive(input$submit_gsummary, {
  h3('Box Plot')
})

output$group1_title <- renderUI({
  g1_title()
})


output$group_summary <- renderPrint({
    gsummary_out()
})

output$box_group_summary <- renderPlot({
  plot(gsummary_out())
})

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xplorerr documentation built on Feb. 28, 2019, 5:05 p.m.