parsing of different form formats, move to bslib with new sidebar

.Rbuildignore

@@ -13,3 +13,4 @@
 ^\.github$
 ^data/prioritized_sample\.xlsx$
 ^sample_data$
+^drafting$

.gitignore

@@ -8,3 +8,4 @@ docs
 data/prioritized_sample.xlsx
 sample_data
 app/rsconnect
+drafting

NAMESPACE

@@ -3,5 +3,7 @@
 S3method(plot,prioritized_groups_list)
 export(file_extension)
 export(grouping_plot)
+export(parse_prio_form)
+export(parse_string_form)
 export(prioritized_grouping)
 export(read_input)

NEWS.md

@@ -1,8 +1,22 @@
+## Version 24.10.2
+
+Working to allow direct import of online form results
+
+* NEW: `prio2groups()` is a helper function to widen and format to apply with
+valid format for `prioritized_grouping()` when importing the spreadsheet.
+
+Wish list of supported platforms:
+
+- Google Forms [WIP]
+- Teams
+- REDCap Survey
+
+
 ## Version 24.10.1
 
 First proper public version. The package is mainly build for an easy to use 
 shiny-interface, but can as easily be used directly in *R* with the main 
-`prioritized_grouping` function. This function is mainly a wrapper around the `ROI`
+`prioritized_grouping()` function. This function is mainly a wrapper around the `ROI`
 package and the `ROI.plugin.symphony` plugin. 
 
 File types accepted in the shiny-app are .csv, .xls(x) and .ods.

R/parse_formats.R

@@ -0,0 +1,101 @@
+#' Parse input data with columns of priorities to columns of groups
+#'
+#' @description
+#' This handles transforming data from a typical Google form to the format
+#' compatible with `prioritized_grouping()`.
+#'
+#' @param data data.frame or tibble
+#' @param id id column. Numeric index or column name. Default is 1.
+#' @param prio.cols priority columns. Numeric indices or column names.
+#' @param sort.cols flag to sort priority columns names/indices. Default=FALSE
+#'
+#' @return data.frame
+#' @export
+#'
+parse_prio_form <- function(data, id = 1, prio.cols,sort.cols=FALSE) {
+  if (is.character(prio.cols)) {
+    grp.index <- match(prio.cols, names(data))
+  } else {
+    grp.index <- prio.cols
+  }
+
+  if (sort.cols){
+    prio.cols <- sort(prio.cols)
+  }
+
+  new.names <- names(data)
+  new.names[grp.index] <- seq_along(grp.index)
+
+  data <- setNames(data, new.names)
+
+  out <- split(data, seq_len(nrow(data))) |>
+    lapply(\(.x){
+      # browser()
+
+      out <- as.data.frame(matrix(c(as.character(.x[[id]]), colnames(.x)[grp.index]), nrow = 1))
+      setNames(out, c(
+        "id",
+        # names(.x[id]),
+        unname(unlist(.x[grp.index]))
+      ))
+    }) |>
+    dplyr::bind_rows() |>
+    dplyr::mutate(dplyr::across(-1, as.integer))
+
+  # Sorting is not really needed, but a nice touch
+  out[c(names(out)[1], sort(names(out)[-1]))]
+}
+
+
+#' Parse input data from column of strings with prioritised group names
+#'
+#' @description
+#' This handles transforming data from a typical Microsoft form to the format
+#' compatible with `prioritized_grouping()`.
+#'
+#' @param data data.frame or tibble
+#' @param id id column. Numeric index of column name. Default is 1.
+#' @param string.col string column. Numeric index or column name.
+#' @param pattern regex pattern to use for splitting priorities string with
+#' `strsplit()`.
+#' Default is ";".
+#'
+#' @return data.frame
+#' @export
+#'
+parse_string_form <- function(data, id = 1, string.col,pattern=NULL) {
+  if (is.null(pattern)){
+    pattern <- ";"
+  }
+
+  if (length(string.col) != 1) {
+    stop("string.col is required, and has to have length 1")
+  }
+  if (is.character(string.col)) {
+    string.index <- match(string.col, names(data))
+  } else {
+    string.index <- string.col
+  }
+
+  # Cells with NAs are excluded.
+  # NAs happen if the priorities are not edited upon form submission, but a
+  # default order can not be guessed reliably if group naming is not ordered
+  # (like group N, group N+1...)
+  out <- data.frame(data[[id]], data[[string.index]]) |>
+    na.omit() |>
+    (\(.d){
+      split(.d, seq_len(nrow(.d)))
+    })() |>
+    lapply(\(.x){
+      grps <- unlist(strsplit(x=.x[[2]],split=pattern))
+      out <- as.data.frame(matrix(c(.x[[1]], seq_along(grps)), nrow = 1))
+      setNames(
+        out,
+        c("id", grps)
+      )
+    }) |>
+    dplyr::bind_rows()
+
+  # Sorting is not really needed, but a nice touch
+  out[c(names(out)[1], sort(names(out)[-1]))]
+}

R/prioritized_grouping.R

@@ -2,7 +2,7 @@ utils::globalVariables(c("group", "grp", "i", "j", "value"))
 
 #' Solve grouping based on priorities or costs.
 #'
-#' @param data data set in wide format. First column should bi ID, then one column
+#' @param data data set in wide format. First column should be ID, then one column
 #' for each group containing cost/priorities.
 #' @param cap_classes class capacity. Numeric vector length 1 or length=number
 #' of groups. If NULL equal group sizes are calculated. Default is NULL.
@@ -39,6 +39,11 @@ prioritized_grouping <-
            subject identifiers")
     }
 
+    # Converts tibble to data.frame
+    if ("tbl_df" %in% class(data)){
+      data <- as.data.frame(data)
+    }
+
     ## This program very much trust the user to supply correctly formatted data
     cost <- t(data[, -1]) # Transpose converts to matrix
     colnames(cost) <- data[, 1]
@@ -360,3 +365,4 @@ read_input <- function(file, consider.na = c("NA", '""', "")) {
 
   df
 }
+

app/server.R

@@ -1,5 +1,112 @@
 
 
+########
+#### Current file: R//parse_formats.R 
+########
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+parse_prio_form <- function(data, id = 1, prio.cols,sort.cols=FALSE) {
+  if (is.character(prio.cols)) {
+    grp.index <- match(prio.cols, names(data))
+  } else {
+    grp.index <- prio.cols
+  }
+
+  if (sort.cols){
+    prio.cols <- sort(prio.cols)
+  }
+
+  new.names <- names(data)
+  new.names[grp.index] <- seq_along(grp.index)
+
+  data <- setNames(data, new.names)
+
+  out <- split(data, seq_len(nrow(data))) |>
+    lapply(\(.x){
+      # browser()
+
+      out <- as.data.frame(matrix(c(as.character(.x[[id]]), colnames(.x)[grp.index]), nrow = 1))
+      setNames(out, c(
+        "id",
+        # names(.x[id]),
+        unname(unlist(.x[grp.index]))
+      ))
+    }) |>
+    dplyr::bind_rows() |>
+    dplyr::mutate(dplyr::across(-1, as.integer))
+
+  # Sorting is not really needed, but a nice touch
+  out[c(names(out)[1], sort(names(out)[-1]))]
+}
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+parse_string_form <- function(data, id = 1, string.col,pattern=NULL) {
+  if (is.null(pattern)){
+    pattern <- ";"
+  }
+
+  if (length(string.col) != 1) {
+    stop("string.col is required, and has to have length 1")
+  }
+  if (is.character(string.col)) {
+    string.index <- match(string.col, names(data))
+  } else {
+    string.index <- string.col
+  }
+
+  # Cells with NAs are excluded.
+  # NAs happen if the priorities are not edited upon form submission, but a
+  # default order can not be guessed reliably if group naming is not ordered
+  # (like group N, group N+1...)
+  out <- data.frame(data[[id]], data[[string.index]]) |>
+    na.omit() |>
+    (\(.d){
+      split(.d, seq_len(nrow(.d)))
+    })() |>
+    lapply(\(.x){
+      grps <- unlist(strsplit(x=.x[[2]],split=pattern))
+      out <- as.data.frame(matrix(c(.x[[1]], seq_along(grps)), nrow = 1))
+      setNames(
+        out,
+        c("id", grps)
+      )
+    }) |>
+    dplyr::bind_rows()
+
+  # Sorting is not really needed, but a nice touch
+  out[c(names(out)[1], sort(names(out)[-1]))]
+}
+
+
 ########
 #### Current file: R//prioritized_grouping.R 
 ########
@@ -45,6 +152,11 @@ prioritized_grouping <-
            subject identifiers")
     }
 
+    # Converts tibble to data.frame
+    if ("tbl_df" %in% class(data)){
+      data <- as.data.frame(data)
+    }
+
     ## This program very much trust the user to supply correctly formatted data
     cost <- t(data[, -1]) # Transpose converts to matrix
     colnames(cost) <- data[, 1]
@@ -368,6 +480,7 @@ read_input <- function(file, consider.na = c("NA", '""', "")) {
 }
 
 
+
 ########
 #### Current file: app/server_raw.R 
 ########
@@ -377,6 +490,11 @@ server <- function(input, output, session) {
   # source("https://git.nikohuru.dk/au-phd/PhysicalActivityandStrokeOutcome/raw/branch/main/side%20projects/assignment.R")
   # source(here::here("R/group_assign.R"))
 
+  v <- shiny::reactiveValues(
+    ds = NULL,
+    pre = NULL
+  )
+
   dat <- reactive({
     # input$file1 will be NULL initially. After the user selects
     # and uploads a file, head of that data file by default,
@@ -384,28 +502,95 @@ server <- function(input, output, session) {
 
     req(input$file1)
     # Make laoding dependent of file name extension (file_ext())
-    df <- read_input(input$file1$datapath)
+    out <- read_input(input$file1$datapath)
-    return(df)
+    v$ds <- "loaded"
+    return(out)
+  })
+
+  dat_parsed <- reactive({
+    req(input$file1)
+    if (input$input_type == "default") {
+      out <- dat()
+    } else if (input$input_type == "prio") {
+      req(input$id_var_prio)
+      req(input$prio_vars)
+
+      out <- parse_prio_form(
+        data = dat(),
+        id = input$id_var_prio,
+        prio.cols = input$prio_vars
+      )
+    } else if (input$input_type == "string") {
+      req(input$id_var_string)
+      req(input$string_var)
+
+      out <- parse_string_form(
+        data = dat(),
+        id = input$id_var_string,
+        string.col = input$string_var,
+        pattern = input$string_split
+      )
+    }
+    return(out)
+  })
+
+
+  output$id_var_prio <- shiny::renderUI({
+    selectInput(
+      inputId = "id_var_prio",
+      selected = 1,
+      label = "ID column",
+      choices = colnames(dat()),
+      multiple = FALSE
+    )
+  })
+
+  output$id_var_string <- shiny::renderUI({
+    selectInput(
+      inputId = "id_var_string",
+      selected = 1,
+      label = "ID column",
+      choices = colnames(dat()),
+      multiple = FALSE
+    )
+  })
+
+  output$prio_vars <- shiny::renderUI({
+    selectizeInput(
+      inputId = "prio_vars",
+      selected = NULL,
+      label = "Priority columns (select from first to lowest)",
+      choices = colnames(dat())[-match(input$id_var_prio, colnames(dat()))],
+      multiple = TRUE
+    )
+  })
+
+  output$string_var <- shiny::renderUI({
+    selectizeInput(
+      inputId = "string_var",
+      selected = NULL,
+      label = "Column of strings",
+      choices = colnames(dat())[-match(input$id_var_string, colnames(dat()))],
+      multiple = FALSE
+    )
   })
 
   dat_pre <- reactive({
-
     # req(input$file2)
     # Make laoding dependent of file name extension (file_ext())
     if (!is.null(input$file2$datapath)) {
-      df <- read_input(input$file2$datapath)
+      out <- read_input(input$file2$datapath)
-
-      return(df)
     } else {
-      return(NULL)
+      out <- NULL
     }
-
+    v$pre <- "loaded"
+    return(out)
   })
 
   groups <-
     reactive({
       grouped <- prioritized_grouping(
-        data = dat(),
+        data = dat_parsed(),
         excess_space = input$excess,
         pre_grouped = dat_pre()
       )
@@ -417,7 +602,8 @@ server <- function(input, output, session) {
     dplyr::case_match(input$overall.plot,
       "yes" ~ TRUE,
       "no" ~ FALSE,
-                      .default=NULL)
+      .default = NULL
+    )
   })
 
   output$raw.data.tbl <- renderTable({
@@ -432,17 +618,39 @@ server <- function(input, output, session) {
     dat()
   })
 
+  output$input_parsed <- renderTable({
+    dat_parsed()
+  })
+
   output$groups.plt <- renderPlot({
     grouping_plot(groups(), overall = plot.overall())
   })
 
+
+  output$uploaded <- shiny::reactive({
+    if (is.null(v$ds)) {
+      "no"
+    } else {
+      "yes"
+    }
+  })
+
+  output$pre_assigned <- shiny::reactive({
+    if (is.null(v$pre)) {
+      "no"
+    } else {
+      "yes"
+    }
+  })
+
+  shiny::outputOptions(output, "uploaded", suspendWhenHidden = FALSE)
+  shiny::outputOptions(output, "pre_assigned", suspendWhenHidden = FALSE)
+
   # Downloadable csv of selected dataset ----
   output$downloadData <- downloadHandler(
-    filename = "prioritized_grouping.csv",
+    filename = "prioritized_grouping.ods",
-
     content = function(file) {
-      write.csv(groups()$export, file, row.names = FALSE)
+      readODS::write_ods(as.data.frame(groups()$export), file)
     }
   )
-
 }

app/server_raw.R

@@ -3,6 +3,11 @@ server <- function(input, output, session) {
   # source("https://git.nikohuru.dk/au-phd/PhysicalActivityandStrokeOutcome/raw/branch/main/side%20projects/assignment.R")
   # source(here::here("R/group_assign.R"))
 
+  v <- shiny::reactiveValues(
+    ds = NULL,
+    pre = NULL
+  )
+
   dat <- reactive({
     # input$file1 will be NULL initially. After the user selects
     # and uploads a file, head of that data file by default,
@@ -10,28 +15,95 @@ server <- function(input, output, session) {
 
     req(input$file1)
     # Make laoding dependent of file name extension (file_ext())
-    df <- read_input(input$file1$datapath)
+    out <- read_input(input$file1$datapath)
-    return(df)
+    v$ds <- "loaded"
+    return(out)
+  })
+
+  dat_parsed <- reactive({
+    req(input$file1)
+    if (input$input_type == "default") {
+      out <- dat()
+    } else if (input$input_type == "prio") {
+      req(input$id_var_prio)
+      req(input$prio_vars)
+
+      out <- parse_prio_form(
+        data = dat(),
+        id = input$id_var_prio,
+        prio.cols = input$prio_vars
+      )
+    } else if (input$input_type == "string") {
+      req(input$id_var_string)
+      req(input$string_var)
+
+      out <- parse_string_form(
+        data = dat(),
+        id = input$id_var_string,
+        string.col = input$string_var,
+        pattern = input$string_split
+      )
+    }
+    return(out)
+  })
+
+
+  output$id_var_prio <- shiny::renderUI({
+    selectInput(
+      inputId = "id_var_prio",
+      selected = 1,
+      label = "ID column",
+      choices = colnames(dat()),
+      multiple = FALSE
+    )
+  })
+
+  output$id_var_string <- shiny::renderUI({
+    selectInput(
+      inputId = "id_var_string",
+      selected = 1,
+      label = "ID column",
+      choices = colnames(dat()),
+      multiple = FALSE
+    )
+  })
+
+  output$prio_vars <- shiny::renderUI({
+    selectizeInput(
+      inputId = "prio_vars",
+      selected = NULL,
+      label = "Priority columns (select from first to lowest)",
+      choices = colnames(dat())[-match(input$id_var_prio, colnames(dat()))],
+      multiple = TRUE
+    )
+  })
+
+  output$string_var <- shiny::renderUI({
+    selectizeInput(
+      inputId = "string_var",
+      selected = NULL,
+      label = "Column of strings",
+      choices = colnames(dat())[-match(input$id_var_string, colnames(dat()))],
+      multiple = FALSE
+    )
   })
 
   dat_pre <- reactive({
-
     # req(input$file2)
     # Make laoding dependent of file name extension (file_ext())
     if (!is.null(input$file2$datapath)) {
-      df <- read_input(input$file2$datapath)
+      out <- read_input(input$file2$datapath)
-
-      return(df)
     } else {
-      return(NULL)
+      out <- NULL
     }
-
+    v$pre <- "loaded"
+    return(out)
   })
 
   groups <-
     reactive({
       grouped <- prioritized_grouping(
-        data = dat(),
+        data = dat_parsed(),
         excess_space = input$excess,
         pre_grouped = dat_pre()
       )
@@ -43,7 +115,8 @@ server <- function(input, output, session) {
     dplyr::case_match(input$overall.plot,
       "yes" ~ TRUE,
       "no" ~ FALSE,
-                      .default=NULL)
+      .default = NULL
+    )
   })
 
   output$raw.data.tbl <- renderTable({
@@ -58,17 +131,39 @@ server <- function(input, output, session) {
     dat()
   })
 
+  output$input_parsed <- renderTable({
+    dat_parsed()
+  })
+
   output$groups.plt <- renderPlot({
     grouping_plot(groups(), overall = plot.overall())
   })
 
+
+  output$uploaded <- shiny::reactive({
+    if (is.null(v$ds)) {
+      "no"
+    } else {
+      "yes"
+    }
+  })
+
+  output$pre_assigned <- shiny::reactive({
+    if (is.null(v$pre)) {
+      "no"
+    } else {
+      "yes"
+    }
+  })
+
+  shiny::outputOptions(output, "uploaded", suspendWhenHidden = FALSE)
+  shiny::outputOptions(output, "pre_assigned", suspendWhenHidden = FALSE)
+
   # Downloadable csv of selected dataset ----
   output$downloadData <- downloadHandler(
-    filename = "prioritized_grouping.csv",
+    filename = "prioritized_grouping.ods",
-
     content = function(file) {
-      write.csv(groups()$export, file, row.names = FALSE)
+      readODS::write_ods(as.data.frame(groups()$export), file)
     }
   )
-
 }

app/ui.R

@@ -1,16 +1,75 @@
 library(shiny)
-ui <- fluidPage(
+library(bslib)
+
+panels <- list(
+  bslib::nav_panel(
+    title = "Input data",
+    h3("Costs/priorities overview"),
+    htmlOutput("input", container = span),
+    conditionalPanel(
+      condition = "output.pre_assigned=='yes'",
+      h3("Pre-assigned groups"),
+      # p("Appears empty if none is uploaded."),
+
+      htmlOutput("pre.groups", container = span)
+    )
+  ),
+  bslib::nav_panel(
+    title = "Parsed input",
+    htmlOutput("input_parsed")),
+  bslib::nav_panel(
+    title = "Summary",
+    shiny::plotOutput("groups.plt")
+  ),
+  bslib::nav_panel(
+    title = "Results",
+    htmlOutput("raw.data.tbl", container = span)
+  )
+)
+
+# tabPanel(
+#   "Input data Results",
+#   h3("Costs/prioritis overview"),
+#
+#
+#   htmlOutput("input", container = span),
+#   conditionalPanel(
+#     condition = "output.preassigned=='yes'",
+#     h3("Pre-assigned groups"),
+#     # p("Appears empty if none is uploaded."),
+#
+#     htmlOutput("pre.groups", container = span))
+#
+# ),
+# tabPanel(
+#   "Summary",
+#   h3("Grouping plot"),
+#   p("These plots are to summarise simple performance meassures for the assignment.
+#           'f' is group fill fraction and 'm' is mean cost in group."),
+#
+#   plotOutput("groups.plt")
+#
+# ),
+#
+# tabPanel(
+#   "Results",
+#   h3("Raw Results"),
+#   p("This is identical to the downloaded file (see panel on left)"),
+#
+#   htmlOutput("raw.data.tbl", container = span)
+#
+# )
+
+
+
+ui <- bslib::page_sidebar(
+  theme = bslib::bs_theme(bootswatch = "minty"),
   ## -----------------------------------------------------------------------------
   ## Application title
   ## -----------------------------------------------------------------------------
 
-  titlePanel("Group allocation based on individual subject prioritization.",
+  title = "Group allocation based on individual subject prioritization.",
-             windowTitle = "Prioritized grouping calculator"),
+  window_title = "Prioritized grouping calculator",
-  h5(
-    "Please note this calculator is only meant as a proof of concept for educational purposes,
-     and the author will take no responsibility for the results of the calculator.
-     Uploaded data is not kept, but please, do not upload any sensitive data."
-  ),
 
   ## -----------------------------------------------------------------------------
   ## Side panel
@@ -20,18 +79,14 @@ ui <- fluidPage(
   ## -----------------------------------------------------------------------------
   ## Single entry
   ## -----------------------------------------------------------------------------
-  sidebarLayout(
+  sidebar = bslib::sidebar(
-    sidebarPanel(
+    open = "open",
-      numericInput(
+    p(
-        inputId = "excess",
+      "Please note this calculator is only meant as a proof of concept for educational purposes,
-        label = "Excess space (%)",
+     and the author will take no responsibility for the results of the calculator.
-        value = 20,
+     Uploaded data is not kept, but please, do not upload any sensitive data."
-        step = 5
     ),
-      p("As default, the program will try to evenly distribute subjects in groups.
+    a(href = "https://git.nikohuru.dk/au-phd/PhysicalActivityandStrokeOutcome/src/branch/main/apps/Assignment", "Source", target = "_blank"),
-        This factor will add more capacity to each group, for an overall lesser cost,
-        but more uneven group numbers. More adjustments can be performed with the source script."),
-      a(href='https://git.nikohuru.dk/au-phd/PhysicalActivityandStrokeOutcome/src/branch/main/apps/Assignment', "Source", target="_blank"),
     ## -----------------------------------------------------------------------------
     ## File upload
     ## -----------------------------------------------------------------------------
@@ -48,10 +103,46 @@ ui <- fluidPage(
     ),
     strong("Columns: ID, group1, group2, ... groupN."),
     strong("NOTE: 0s will be interpreted as lowest score."),
-      p("Cells should contain cost/priorities.
+    # p("Cells should contain cost/priorities.
-         Lowest score, for highest priority.
+    #    Lowest score, for highest priority.
-        Non-ranked should contain a number (eg lowest score+1).
+    #   Non-ranked should contain a number (eg lowest score+1).
-         Will handle missings but try to avoid."),
+    #    Will handle missings but try to avoid."),
+    shiny::conditionalPanel(
+      condition = "output.uploaded=='yes'",
+      numericInput(
+        inputId = "excess",
+        label = "Excess space (%)",
+        value = 20,
+        step = 5
+      ),
+      p("As default, the program will try to evenly distribute subjects in groups.
+        This factor will add more capacity to each group, for an overall lesser cost,
+        but more uneven group numbers. More adjustments can be performed with the source script."),
+      shiny::radioButtons(
+        inputId = "input_type",
+        label = "Data input type",
+        selected = "default",
+        choices = list(
+          "Columns of groups" = "default",
+          "Columns of priorities (Google)" = "prio",
+          "Column of strings (Microsoft)" = "string"
+        )
+      ),
+      shiny::conditionalPanel(
+        condition = "input.input_type=='prio'",
+        uiOutput("id_var_prio"),
+        uiOutput("prio_vars")
+      ),
+      shiny::conditionalPanel(
+        condition = "input.input_type=='string'",
+        uiOutput("id_var_string"),
+        uiOutput("string_var"),
+        shiny::textInput(
+          inputId = "string_split",
+          label = "Pattern to split string",
+          value = ";"
+        )
+      ),
       shiny::radioButtons(
         inputId = "overall.plot",
         label = "Print overall mean grouping priorities/costs only?",
@@ -61,8 +152,17 @@ ui <- fluidPage(
           "No" = "no"
         )
       ),
-
+      shiny::radioButtons(
-
+        inputId = "pre_assign",
+        label = "Add pre-assigned grouping (paedagogical return)?",
+        selected = "no",
+        choices = list(
+          "Yes" = "yes",
+          "No" = "no"
+        )
+      ),
+      shiny::conditionalPanel(
+        condition = "input.pre_assign=='yes'",
         fileInput(
           inputId = "file2",
           label = "Choose data file for pre-assigned subjects",
@@ -71,61 +171,25 @@ ui <- fluidPage(
             ".csv", ".xls", ".xlsx"
           )
         ),
-      h6("Columns: ID, group"),
+        h6("Columns: ID, group")
-
+      ),
-
-
       ## -----------------------------------------------------------------------------
       ## Download output
       ## -----------------------------------------------------------------------------
 
       # Horizontal line ----
       tags$hr(),
-
       h4("Download results"),
 
       # Button
       downloadButton("downloadData", "Download")
-    ),
-
-    mainPanel(tabsetPanel(
-      ## -----------------------------------------------------------------------------
-      ## Plot tab
-      ## -----------------------------------------------------------------------------
-
-      tabPanel(
-        "Summary",
-        h3("Grouping plot"),
-        p("These plots are to summarise simple performance meassures for the assignment.
-          'f' is group fill fraction and 'm' is mean cost in group."),
-
-        plotOutput("groups.plt")
-
-      ),
-
-      tabPanel(
-        "Results",
-        h3("Raw Results"),
-        p("This is identical to the downloaded file (see panel on left)"),
-
-        htmlOutput("raw.data.tbl", container = span)
-
-      ),
-
-      tabPanel(
-        "Input data Results",
-        h3("Costs/prioritis overview"),
-
-
-        htmlOutput("input", container = span),
-
-        h3("Pre-assigned groups"),
-        p("Appears empty if none is uploaded."),
-
-        htmlOutput("pre.groups", container = span)
-
     )
-
+  ),
-    ))
+  bslib::navset_card_underline(
+    title = "Data and results",
+    panels[[1]],
+    panels[[2]],
+    panels[[3]],
+    panels[[4]]
   )
 )

man/parse_prio_form.Rd

@@ -0,0 +1,24 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/parse_formats.R
+\name{parse_prio_form}
+\alias{parse_prio_form}
+\title{Parse input data with columns of priorities to columns of groups}
+\usage{
+parse_prio_form(data, id = 1, prio.cols, sort.cols = FALSE)
+}
+\arguments{
+\item{data}{data.frame or tibble}
+
+\item{id}{id column. Numeric index or column name. Default is 1.}
+
+\item{prio.cols}{priority columns. Numeric indices or column names.}
+
+\item{sort.cols}{flag to sort priority columns names/indices. Default=FALSE}
+}
+\value{
+data.frame
+}
+\description{
+This handles transforming data from a typical Google form to the format
+compatible with \code{prioritized_grouping()}.
+}

man/parse_string_form.Rd

@@ -0,0 +1,26 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/parse_formats.R
+\name{parse_string_form}
+\alias{parse_string_form}
+\title{Parse input data from column of strings with prioritised group names}
+\usage{
+parse_string_form(data, id = 1, string.col, pattern = NULL)
+}
+\arguments{
+\item{data}{data.frame or tibble}
+
+\item{id}{id column. Numeric index of column name. Default is 1.}
+
+\item{string.col}{string column. Numeric index or column name.}
+
+\item{pattern}{regex pattern to use for splitting priorities string with
+\code{strsplit()}.
+Default is ";".}
+}
+\value{
+data.frame
+}
+\description{
+This handles transforming data from a typical Microsoft form to the format
+compatible with \code{prioritized_grouping()}.
+}

man/prioritized_grouping.Rd

@@ -13,7 +13,7 @@ prioritized_grouping(
 )
 }
 \arguments{
-\item{data}{data set in wide format. First column should bi ID, then one column
+\item{data}{data set in wide format. First column should be ID, then one column
 for each group containing cost/priorities.}
 
 \item{cap_classes}{class capacity. Numeric vector length 1 or length=number