mirror of
https://github.com/agdamsbo/REDCapCAST.git
synced 2024-11-21 21:10:22 +01:00
implemented specification of categorical variables (logicals are converted to factor)
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fe9918dc10
commit
f5965a2748
@ -62,10 +62,12 @@ read_input <- function(file, consider.na = c("NA", '""', "")) {
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} else if (ext == "dta") {
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} else if (ext == "dta") {
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df <- haven::read_dta(file = file)
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df <- haven::read_dta(file = file)
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} else if (ext == "ods") {
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} else if (ext == "ods") {
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df <- readODS::read_ods(file = file)
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df <- readODS::read_ods(path = file)
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} else if (ext == "rds") {
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df <- readr::read_rds(file = file)
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}else {
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}else {
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stop("Input file format has to be on of:
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stop("Input file format has to be on of:
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'.csv', '.xls', '.xlsx', '.dta' or '.ods'")
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'.csv', '.xls', '.xlsx', '.dta', '.rds' or '.ods'")
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}
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}
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},
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},
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error = function(e) {
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error = function(e) {
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@ -0,0 +1,10 @@
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name: redcapcast
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title:
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username: agdamsbo
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account: agdamsbo
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server: shinyapps.io
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hostUrl: https://api.shinyapps.io/v1
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appId: 11351429
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bundleId:
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url: https://agdamsbo.shinyapps.io/redcapcast/
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version: 1
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@ -21,8 +21,35 @@ server <- function(input, output, session) {
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dat <- shiny::reactive({
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dat <- shiny::reactive({
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shiny::req(input$ds)
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shiny::req(input$ds)
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read_input(input$ds$datapath) |>
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out <- read_input(input$ds$datapath)
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parse_data()
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# Saves labels to reapply later
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labels <- lapply(out, get_attr)
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out <- out |>
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## Parses data with readr functions
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parse_data() |>
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## Converts logical to factor, which overwrites attributes
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##
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dplyr::mutate(dplyr::across(dplyr::where(is.logical), forcats::as_factor))
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if (!is.null(input$factor_vars)) {
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out <- out |>
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dplyr::mutate(
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dplyr::across(
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dplyr::all_of(input$factor_vars),
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forcats::as_factor
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)
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)
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}
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# Old attributes are appended
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out <- purrr::imap(out,\(.x,.i){
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set_attr(.x,labels[[.i]])
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}) |>
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dplyr::bind_cols()
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out
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})
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})
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# getData <- reactive({
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# getData <- reactive({
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@ -48,19 +75,66 @@ server <- function(input, output, session) {
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shiny::outputOptions(output, "uploaded", suspendWhenHidden = FALSE)
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shiny::outputOptions(output, "uploaded", suspendWhenHidden = FALSE)
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output$factor_vars <- shiny::renderUI({
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shiny::req(input$ds)
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selectizeInput(
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inputId = "factor_vars",
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selected = colnames(dat())[sapply(dat(), is.factor)],
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label = "Covariables to format as categorical",
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choices = colnames(dat()),
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multiple = TRUE
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)
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})
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output$data.tbl <- gt::render_gt(
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output$data.tbl <- gt::render_gt(
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dd() |>
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dd() |>
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purrr::pluck("data") |>
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purrr::pluck("data") |>
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head(20) |>
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head(20) |>
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dplyr::tibble() |>
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# dplyr::tibble() |>
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gt::gt()
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gt::gt() |>
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gt::tab_style(
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style = gt::cell_text(weight = "bold"),
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locations = gt::cells_column_labels(dplyr::everything())
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) |>
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gt::tab_header(
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title = "Imported data preview",
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subtitle = "The first 20 subjects of the supplied dataset for reference."
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)
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)
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)
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output$meta.tbl <- gt::render_gt(
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output$meta.tbl <- gt::render_gt(
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dd() |>
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dd() |>
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purrr::pluck("meta") |>
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purrr::pluck("meta") |>
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dplyr::tibble() |>
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# dplyr::tibble() |>
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gt::gt()
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dplyr::mutate(
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dplyr::across(
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dplyr::everything(),
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\(.x) {
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.x[is.na(.x)] <- ""
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return(.x)
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}
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)
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) |>
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dplyr::select(1:8) |>
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gt::gt() |>
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gt::tab_style(
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style = gt::cell_text(weight = "bold"),
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locations = gt::cells_column_labels(dplyr::everything())
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) |>
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gt::tab_header(
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title = "Generated metadata",
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subtitle = "Only the first 8 columns are modified using REDCapCAST. Download the metadata to see everything."
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) |>
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gt::tab_style(
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style = gt::cell_borders(
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sides = c("left", "right"),
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color = "grey80",
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weight = gt::px(1)
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),
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locations = gt::cells_body(
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columns = dplyr::everything()
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)
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)
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)
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)
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# Downloadable csv of dataset ----
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# Downloadable csv of dataset ----
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@ -73,7 +147,7 @@ server <- function(input, output, session) {
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# Downloadable csv of data dictionary ----
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# Downloadable csv of data dictionary ----
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output$downloadMeta <- shiny::downloadHandler(
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output$downloadMeta <- shiny::downloadHandler(
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filename = "datadictionary_ready.csv",
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filename = paste0("REDCapCAST_DataDictionary_", Sys.Date(), ".csv"),
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content = function(file) {
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content = function(file) {
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write.csv(purrr::pluck(dd(), "meta"), file, row.names = FALSE, na = "")
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write.csv(purrr::pluck(dd(), "meta"), file, row.names = FALSE, na = "")
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}
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}
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@ -6,7 +6,7 @@ ui <-
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title = "Easy REDCap database creation",
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title = "Easy REDCap database creation",
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sidebar = bslib::sidebar(
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sidebar = bslib::sidebar(
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width = 300,
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width = 300,
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shiny::h5("1) Database meta data"),
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shiny::h5("Metadata casting"),
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shiny::fileInput(
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shiny::fileInput(
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inputId = "ds",
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inputId = "ds",
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label = "Upload spreadsheet",
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label = "Upload spreadsheet",
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@ -16,6 +16,7 @@ ui <-
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".xls",
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".xls",
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".xlsx",
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".xlsx",
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".dta",
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".dta",
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".rds",
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".ods"
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".ods"
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)
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)
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),
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),
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@ -29,6 +30,20 @@ ui <-
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# This has been solved by adding an arbitrary button to load data - which was abandoned again
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# This has been solved by adding an arbitrary button to load data - which was abandoned again
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shiny::conditionalPanel(
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shiny::conditionalPanel(
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condition = "output.uploaded=='yes'",
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condition = "output.uploaded=='yes'",
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shiny::radioButtons(
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inputId = "specify_factors",
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label = "Specify categorical variables?",
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selected = "no",
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inline = TRUE,
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choices = list(
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"No" = "no",
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"Yes" = "yes"
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)
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),
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shiny::conditionalPanel(
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condition = "input.specify_factors=='yes'",
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uiOutput("factor_vars")
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),
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# condition = "input.load_data",
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# condition = "input.load_data",
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# shiny::helpText("Below you can download the dataset formatted for upload and the
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# shiny::helpText("Below you can download the dataset formatted for upload and the
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# corresponding data dictionary for a new data base, if you want to upload manually."),
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# corresponding data dictionary for a new data base, if you want to upload manually."),
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