mirror of
https://github.com/agdamsbo/REDCapCAST.git
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78 lines
1.9 KiB
R
78 lines
1.9 KiB
R
#' Launch the included Shiny-app for database casting and upload
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#'
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#' @description
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#' Wraps shiny::runApp()
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#'
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#' @param ... Arguments passed to shiny::runApp()
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#'
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#' @return shiny app
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#' @export
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#'
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#' @examples
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#' # shiny_cast()
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#'
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shiny_cast <- function(...) {
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appDir <- system.file("shiny-examples", "casting", package = "REDCapCAST")
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if (appDir == "") {
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stop("Could not find example directory. Try re-installing `REDCapCAST`.", call. = FALSE)
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}
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shiny::runApp(appDir = appDir, ...)
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}
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#' Helper to import files correctly
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#'
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#' @param filenames file names
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#'
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#' @return character vector
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#' @export
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#'
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#' @examples
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#' file_extension(list.files(here::here(""))[[2]])[[1]]
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#' file_extension(c("file.cd..ks","file"))
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file_extension <- function(filenames) {
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sub(pattern = "^(.*\\.|[^.]+)(?=[^.]*)", replacement = "",
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filenames,
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perl = TRUE)
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}
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#' Flexible file import based on extension
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#'
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#' @param file file name
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#' @param consider.na character vector of strings to consider as NAs
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#'
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#' @return tibble
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#' @export
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#'
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#' @examples
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#' read_input("https://raw.githubusercontent.com/agdamsbo/cognitive.index.lookup/main/data/sample.csv")
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read_input <- function(file, consider.na = c("NA", '""', "")) {
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ext <- file_extension(file)
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tryCatch(
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{
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if (ext == "csv") {
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df <- readr::read_csv(file = file, na = consider.na)
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} else if (ext %in% c("xls", "xlsx")) {
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df <- openxlsx2::read_xlsx(file = file, na.strings = consider.na)
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} else if (ext == "dta") {
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df <- haven::read_dta(file = file)
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} else if (ext == "ods") {
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df <- readODS::read_ods(file = file)
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} else {
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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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}
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},
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error = function(e) {
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# return a safeError if a parsing error occurs
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stop(shiny::safeError(e))
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}
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)
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df
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}
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