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2249ba06db
29 changed files with 1736 additions and 555 deletions
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@ -12,4 +12,3 @@
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^docs$
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^pkgdown$
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^dev$
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^data-raw$
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16
DESCRIPTION
16
DESCRIPTION
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@ -15,9 +15,9 @@ Imports:
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dplyr,
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glue,
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gtsummary,
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haven,
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here,
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quarto,
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haven,
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readODS,
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readr,
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shiny,
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@ -29,14 +29,17 @@ Imports:
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parameters,
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DT,
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performance,
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ggiraph,
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qqplotr,
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see,
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patchwork,
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easystats,
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DHARMa,
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IDEAFilter,
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sparkline,
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datamods,
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toastui,
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webshot,
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lubridate,
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bsicons,
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thematic,
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@ -45,11 +48,18 @@ Imports:
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classInt,
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htmltools,
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rlang,
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data.table,
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apexcharter,
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esquisse,
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janitor,
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flextable,
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gt,
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kableExtra,
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rankinPlot,
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sjPlot,
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gvlma,
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psych,
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jtools,
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Hmisc,
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ggstats,
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rempsyc,
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@ -64,7 +74,6 @@ Suggests:
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styler,
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devtools,
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rhub,
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webshot,
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usethis,
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roxygen2,
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pak,
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@ -78,6 +87,3 @@ URL: https://github.com/agdamsbo/FreesearchR, https://agdamsbo.github.io/Freesea
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BugReports: https://github.com/agdamsbo/FreesearchR/issues
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VignetteBuilder: knitr
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Config/testthat/edition: 3
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Depends:
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R (>= 3.5)
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LazyData: true
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@ -1 +1 @@
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app_version <- function()'v25.4.3.250423'
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app_version <- function()'Version: 25.4.3.250422'
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@ -695,7 +695,7 @@ line_break <- function(data, lineLength = 20, force = FALSE) {
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#' @export
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#'
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wrap_plot_list <- function(data, tag_levels = NULL) {
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if (ggplot2::is_ggplot(data[[1]])) {
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if (ggplot2::is.ggplot(data[[1]])) {
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if (length(data) > 1) {
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out <- data |>
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(\(.x){
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@ -732,7 +732,7 @@ wrap_plot_list <- function(data, tag_levels = NULL) {
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align_axes <- function(...) {
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# https://stackoverflow.com/questions/62818776/get-axis-limits-from-ggplot-object
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# https://github.com/thomasp85/patchwork/blob/main/R/plot_multipage.R#L150
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if (ggplot2::is_ggplot(..1)) {
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if (ggplot2::is.ggplot(..1)) {
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## Assumes list of ggplots
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p <- list(...)
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} else if (is.list(..1)) {
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@ -87,7 +87,7 @@ read_input <- function(file, consider.na = c("NA", '""', "")) {
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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 <- readxl::read_excel(file = file, na.strings = consider.na)
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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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@ -428,7 +428,7 @@ sort_by <- function(x, y, na.rm = FALSE, ...) {
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get_ggplot_label <- function(data, label) {
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assertthat::assert_that(ggplot2::is_ggplot(data))
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assertthat::assert_that(ggplot2::is.ggplot(data))
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data$labels[[label]]
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}
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@ -298,8 +298,7 @@ import_file_server <- function(id,
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)
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observeEvent(input$see_data, {
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tryCatch(
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{
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tryCatch({
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datamods:::show_data(default_parsing(temporary_rv$data), title = datamods:::i18n("Imported data"), type = show_data_in)
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},
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# warning = function(warn) {
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@ -313,10 +312,9 @@ import_file_server <- function(id,
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output$table <- toastui::renderDatagrid2({
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req(temporary_rv$data)
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tryCatch(
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{
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tryCatch({
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toastui::datagrid(
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data = setNames(head(temporary_rv$data, 5), make.names(names(temporary_rv$data), unique = TRUE)),
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data = setNames(head(temporary_rv$data, 5),make.names(names(temporary_rv$data),unique = TRUE)),
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theme = "striped",
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colwidths = "guess",
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minBodyHeight = 250
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@ -420,22 +418,13 @@ import_xls <- function(file, sheet, skip, na.strings) {
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sheet |>
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purrr::map(\(.x){
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readxl::read_excel(
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path = file,
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openxlsx2::read_xlsx(
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file = file,
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sheet = .x,
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na = na.strings,
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skip = skip,
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.name_repair = "unique_quiet",
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trim_ws = TRUE
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skip_empty_rows = TRUE,
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start_row = skip - 1,
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na.strings = na.strings
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)
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# openxlsx2::read_xlsx(
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# file = file,
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# sheet = .x,
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# skip_empty_rows = TRUE,
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# start_row = skip - 1,
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# na.strings = na.strings
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# )
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}) |>
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purrr::reduce(dplyr::full_join)
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},
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@ -46,7 +46,7 @@ plot_box_single <- function(data, pri, sec=NULL, seed = 2103) {
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if (is.null(sec)) {
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sec <- "All"
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data[[sec]] <- sec
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data[[y]] <- sec
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}
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discrete <- !data_type(data[[sec]]) %in% "continuous"
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@ -22,7 +22,7 @@ sankey_ready <- function(data, pri, sec, numbers = "count", ...) {
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data[c(pri, sec)] <- data[c(pri, sec)] |>
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dplyr::mutate(dplyr::across(!dplyr::where(is.factor), forcats::as_factor))
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out <- dplyr::count(data, !!dplyr::sym(pri), !!dplyr::sym(sec), .drop = FALSE)
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out <- dplyr::count(data, !!dplyr::sym(pri), !!dplyr::sym(sec))
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out <- out |>
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dplyr::group_by(!!dplyr::sym(pri)) |>
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|
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@ -73,17 +73,9 @@ str_remove_last <- function(data, pattern = "\n") {
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#' @examples
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#' ds <- data.frame(g = sample(LETTERS[1:2], 100, TRUE), first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)), last = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)))
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#' ds |> plot_sankey("first", "last")
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#' ds |> plot_sankey("first", "last", color.group = "sec")
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#' ds |> plot_sankey("first", "last", ter = "g", color.group = "sec")
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#' mtcars |>
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#' default_parsing() |>
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#' plot_sankey("cyl", "gear", "am", color.group = "pri")
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#' ## In this case, the last plot as the secondary variable in wrong order
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#' ## Dont know why...
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#' mtcars |>
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#' default_parsing() |>
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#' plot_sankey("cyl", "gear", "vs", color.group = "pri")
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plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors = NULL) {
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#' ds |> plot_sankey("first", "last", color.group = "y")
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#' ds |> plot_sankey("first", "last", z = "g", color.group = "y")
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plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "x", colors = NULL) {
|
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if (!is.null(ter)) {
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ds <- split(data, data[ter])
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} else {
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|
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@ -91,12 +83,16 @@ plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors
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}
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out <- lapply(ds, \(.ds){
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plot_sankey_single(.ds, pri = pri, sec = sec, color.group = color.group, colors = colors)
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plot_sankey_single(.ds, x = pri, y = sec, color.group = color.group, colors = colors)
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||||
})
|
||||
|
||||
patchwork::wrap_plots(out)
|
||||
}
|
||||
|
||||
default_theme <- function() {
|
||||
theme_void()
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}
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|
||||
#' Beautiful sankey plot
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#'
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#' @param color.group set group to colour by. "x" or "y".
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@ -110,26 +106,15 @@ plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors
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#' @examples
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#' ds <- data.frame(g = sample(LETTERS[1:2], 100, TRUE), first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)), last = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)))
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#' ds |> plot_sankey_single("first", "last")
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#' ds |> plot_sankey_single("first", "last", color.group = "sec")
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#' ds |> plot_sankey_single("first", "last", color.group = "y")
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#' data.frame(
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#' g = sample(LETTERS[1:2], 100, TRUE),
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#' first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)),
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#' last = sample(c(TRUE, FALSE, FALSE), 100, TRUE)
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#' ) |>
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#' plot_sankey_single("first", "last", color.group = "pri")
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#' mtcars |>
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#' default_parsing() |>
|
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#' str()
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#' plot_sankey_single("cyl", "vs", color.group = "pri")
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plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), colors = NULL, ...) {
|
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color.group <- match.arg(color.group)
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|
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data_orig <- data
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data[c(pri, sec)] <- data[c(pri, sec)] |>
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dplyr::mutate(dplyr::across(dplyr::where(is.factor), forcats::fct_drop))
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|
||||
# browser()
|
||||
|
||||
data <- data |> sankey_ready(pri = pri, sec = sec, ...)
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|
||||
library(ggalluvial)
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|
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@ -139,17 +124,11 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
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|
||||
if (is.null(colors)) {
|
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if (color.group == "sec") {
|
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main.colors <- viridisLite::viridis(n = length(levels(data_orig[[sec]])))
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## Only keep colors for included levels
|
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main.colors <- main.colors[match(levels(data[[sec]]), levels(data_orig[[sec]]))]
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||||
|
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main.colors <- viridisLite::viridis(n = length(levels(data[[sec]])))
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secondary.colors <- rep(na.color, length(levels(data[[pri]])))
|
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label.colors <- Reduce(c, lapply(list(secondary.colors, rev(main.colors)), contrast_text))
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} else {
|
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main.colors <- viridisLite::viridis(n = length(levels(data_orig[[pri]])))
|
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## Only keep colors for included levels
|
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main.colors <- main.colors[match(levels(data[[pri]]), levels(data_orig[[pri]]))]
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|
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main.colors <- viridisLite::viridis(n = length(levels(data[[pri]])))
|
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secondary.colors <- rep(na.color, length(levels(data[[sec]])))
|
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label.colors <- Reduce(c, lapply(list(rev(main.colors), secondary.colors), contrast_text))
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}
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|
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@ -167,11 +146,7 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
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if (color.group == "sec") {
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p <- p +
|
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ggalluvial::geom_alluvium(
|
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ggplot2::aes(
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fill = !!dplyr::sym(sec) # ,
|
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## Including will print strings when levels are empty
|
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# color = !!dplyr::sym(sec)
|
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),
|
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ggplot2::aes(fill = !!dplyr::sym(sec), color = !!dplyr::sym(sec)),
|
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width = 1 / 16,
|
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alpha = .8,
|
||||
knot.pos = 0.4,
|
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|
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@ -183,10 +158,7 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
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} else {
|
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p <- p +
|
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ggalluvial::geom_alluvium(
|
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ggplot2::aes(
|
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fill = !!dplyr::sym(pri) # ,
|
||||
# color = !!dplyr::sym(pri)
|
||||
),
|
||||
ggplot2::aes(fill = !!dplyr::sym(pri), color = !!dplyr::sym(pri)),
|
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width = 1 / 16,
|
||||
alpha = .8,
|
||||
knot.pos = 0.4,
|
||||
|
|
@ -210,7 +182,7 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
|
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labels = group_labels
|
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) +
|
||||
ggplot2::scale_fill_manual(values = colors[-1], na.value = colors[1]) +
|
||||
# ggplot2::scale_color_manual(values = main.colors) +
|
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ggplot2::scale_color_manual(values = main.colors) +
|
||||
ggplot2::theme_void() +
|
||||
ggplot2::theme(
|
||||
legend.position = "none",
|
||||
|
|
|
|||
BIN
R/sysdata.rda
BIN
R/sysdata.rda
Binary file not shown.
|
|
@ -1,4 +1,4 @@
|
|||
# FreesearchR <img style="float: right;" src="logo-text-white-250.png">
|
||||
# FreesearchR
|
||||
|
||||
<!-- badges: start -->
|
||||
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
|
||||
|
|
@ -48,5 +48,3 @@ Like any other project, this project was never possible without the great work o
|
|||
- [gtsummary](https://www.danieldsjoberg.com/gtsummary/): superb and flexible way to create publication-ready analytical and summary tables.
|
||||
|
||||
- [dreamRs](https://github.com/dreamRs): maintainers of a broad selection of great extensions and tools for [Shiny](https://shiny.posit.co/).
|
||||
|
||||
This project was all written by a human and not by any AI-based tools.
|
||||
|
|
|
|||
166
SESSION.md
166
SESSION.md
|
|
@ -1,166 +0,0 @@
|
|||
--------------------------------------------------------------------------------
|
||||
-------------------------------- R environment ---------------------------------
|
||||
--------------------------------------------------------------------------------
|
||||
|setting |value |
|
||||
|:-----------|:------------------------------------------|
|
||||
|version |R version 4.4.1 (2024-06-14) |
|
||||
|os |macOS 15.3.1 |
|
||||
|system |aarch64, darwin20 |
|
||||
|ui |RStudio |
|
||||
|language |(EN) |
|
||||
|collate |en_US.UTF-8 |
|
||||
|ctype |en_US.UTF-8 |
|
||||
|tz |Europe/Copenhagen |
|
||||
|date |2025-04-23 |
|
||||
|rstudio |2024.12.1+563 Kousa Dogwood (desktop) |
|
||||
|pandoc |3.6.4 @ /opt/homebrew/bin/ (via rmarkdown) |
|
||||
|quarto |1.6.40 @ /usr/local/bin/quarto |
|
||||
|FreesearchR |25.4.3.250423 |
|
||||
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
----------------------------------- packages -----------------------------------
|
||||
--------------------------------------------------------------------------------
|
||||
|package |loadedversion |date |source |
|
||||
|:-------------|:-------------|:----------|:--------------|
|
||||
|apexcharter |0.4.4 |2024-09-06 |CRAN (R 4.4.1) |
|
||||
|askpass |1.2.1 |2024-10-04 |CRAN (R 4.4.1) |
|
||||
|assertthat |0.2.1 |2019-03-21 |CRAN (R 4.4.1) |
|
||||
|backports |1.5.0 |2024-05-23 |CRAN (R 4.4.1) |
|
||||
|bayestestR |0.15.2 |2025-02-07 |CRAN (R 4.4.1) |
|
||||
|bit |4.6.0 |2025-03-06 |CRAN (R 4.4.1) |
|
||||
|bit64 |4.6.0-1 |2025-01-16 |CRAN (R 4.4.1) |
|
||||
|boot |1.3-31 |2024-08-28 |CRAN (R 4.4.1) |
|
||||
|broom |1.0.8 |2025-03-28 |CRAN (R 4.4.1) |
|
||||
|broom.helpers |1.20.0 |2025-03-06 |CRAN (R 4.4.1) |
|
||||
|bsicons |0.1.2 |2023-11-04 |CRAN (R 4.4.0) |
|
||||
|bslib |0.9.0 |2025-01-30 |CRAN (R 4.4.1) |
|
||||
|cachem |1.1.0 |2024-05-16 |CRAN (R 4.4.1) |
|
||||
|cellranger |1.1.0 |2016-07-27 |CRAN (R 4.4.0) |
|
||||
|class |7.3-23 |2025-01-01 |CRAN (R 4.4.1) |
|
||||
|classInt |0.4-11 |2025-01-08 |CRAN (R 4.4.1) |
|
||||
|cli |3.6.4 |2025-02-13 |CRAN (R 4.4.1) |
|
||||
|colorspace |2.1-1 |2024-07-26 |CRAN (R 4.4.1) |
|
||||
|commonmark |1.9.5 |2025-03-17 |CRAN (R 4.4.1) |
|
||||
|correlation |0.8.7 |2025-03-03 |CRAN (R 4.4.1) |
|
||||
|crayon |1.5.3 |2024-06-20 |CRAN (R 4.4.1) |
|
||||
|credentials |2.0.2 |2024-10-04 |CRAN (R 4.4.1) |
|
||||
|crosstalk |1.2.1 |2023-11-23 |CRAN (R 4.4.0) |
|
||||
|data.table |1.17.0 |2025-02-22 |CRAN (R 4.4.1) |
|
||||
|datamods |1.5.3 |2024-10-02 |CRAN (R 4.4.1) |
|
||||
|datawizard |1.0.2 |2025-03-24 |CRAN (R 4.4.1) |
|
||||
|desc |1.4.3 |2023-12-10 |CRAN (R 4.4.1) |
|
||||
|devtools |2.4.5 |2022-10-11 |CRAN (R 4.4.0) |
|
||||
|DHARMa |0.4.7 |2024-10-18 |CRAN (R 4.4.1) |
|
||||
|digest |0.6.37 |2024-08-19 |CRAN (R 4.4.1) |
|
||||
|dplyr |1.1.4 |2023-11-17 |CRAN (R 4.4.0) |
|
||||
|DT |0.33 |2024-04-04 |CRAN (R 4.4.0) |
|
||||
|e1071 |1.7-16 |2024-09-16 |CRAN (R 4.4.1) |
|
||||
|easystats |0.7.4 |2025-02-06 |CRAN (R 4.4.1) |
|
||||
|effectsize |1.0.0 |2024-12-10 |CRAN (R 4.4.1) |
|
||||
|ellipsis |0.3.2 |2021-04-29 |CRAN (R 4.4.1) |
|
||||
|esquisse |2.1.0 |2025-02-21 |CRAN (R 4.4.1) |
|
||||
|evaluate |1.0.3 |2025-01-10 |CRAN (R 4.4.1) |
|
||||
|farver |2.1.2 |2024-05-13 |CRAN (R 4.4.1) |
|
||||
|fastmap |1.2.0 |2024-05-15 |CRAN (R 4.4.1) |
|
||||
|fontawesome |0.5.3 |2024-11-16 |CRAN (R 4.4.1) |
|
||||
|forcats |1.0.0 |2023-01-29 |CRAN (R 4.4.0) |
|
||||
|FreesearchR |25.4.3 |NA |NA |
|
||||
|fs |1.6.6 |2025-04-12 |CRAN (R 4.4.1) |
|
||||
|generics |0.1.3 |2022-07-05 |CRAN (R 4.4.1) |
|
||||
|gert |2.1.5 |2025-03-25 |CRAN (R 4.4.1) |
|
||||
|ggplot2 |3.5.2 |2025-04-09 |CRAN (R 4.4.1) |
|
||||
|glue |1.8.0 |2024-09-30 |CRAN (R 4.4.1) |
|
||||
|gt |1.0.0 |2025-04-05 |CRAN (R 4.4.1) |
|
||||
|gtable |0.3.6 |2024-10-25 |CRAN (R 4.4.1) |
|
||||
|gtsummary |2.2.0 |2025-04-14 |CRAN (R 4.4.1) |
|
||||
|haven |2.5.4 |2023-11-30 |CRAN (R 4.4.0) |
|
||||
|here |1.0.1 |2020-12-13 |CRAN (R 4.4.1) |
|
||||
|hms |1.1.3 |2023-03-21 |CRAN (R 4.4.0) |
|
||||
|htmltools |0.5.8.1 |2024-04-04 |CRAN (R 4.4.1) |
|
||||
|htmlwidgets |1.6.4 |2023-12-06 |CRAN (R 4.4.0) |
|
||||
|httpuv |1.6.16 |2025-04-16 |CRAN (R 4.4.1) |
|
||||
|IDEAFilter |0.2.0 |2024-04-15 |CRAN (R 4.4.0) |
|
||||
|insight |1.2.0 |2025-04-22 |CRAN (R 4.4.1) |
|
||||
|jquerylib |0.1.4 |2021-04-26 |CRAN (R 4.4.0) |
|
||||
|jsonlite |2.0.0 |2025-03-27 |CRAN (R 4.4.1) |
|
||||
|KernSmooth |2.23-26 |2025-01-01 |CRAN (R 4.4.1) |
|
||||
|knitr |1.50 |2025-03-16 |CRAN (R 4.4.1) |
|
||||
|later |1.4.2 |2025-04-08 |CRAN (R 4.4.1) |
|
||||
|lattice |0.22-7 |2025-04-02 |CRAN (R 4.4.1) |
|
||||
|lifecycle |1.0.4 |2023-11-07 |CRAN (R 4.4.1) |
|
||||
|lme4 |1.1-37 |2025-03-26 |CRAN (R 4.4.1) |
|
||||
|magrittr |2.0.3 |2022-03-30 |CRAN (R 4.4.1) |
|
||||
|MASS |7.3-65 |2025-02-28 |CRAN (R 4.4.1) |
|
||||
|Matrix |1.7-3 |2025-03-11 |CRAN (R 4.4.1) |
|
||||
|memoise |2.0.1 |2021-11-26 |CRAN (R 4.4.0) |
|
||||
|mime |0.13 |2025-03-17 |CRAN (R 4.4.1) |
|
||||
|miniUI |0.1.2 |2025-04-17 |CRAN (R 4.4.1) |
|
||||
|minqa |1.2.8 |2024-08-17 |CRAN (R 4.4.1) |
|
||||
|modelbased |0.10.0 |2025-03-10 |CRAN (R 4.4.1) |
|
||||
|munsell |0.5.1 |2024-04-01 |CRAN (R 4.4.1) |
|
||||
|nlme |3.1-168 |2025-03-31 |CRAN (R 4.4.1) |
|
||||
|nloptr |2.2.1 |2025-03-17 |CRAN (R 4.4.1) |
|
||||
|openssl |2.3.2 |2025-02-03 |CRAN (R 4.4.1) |
|
||||
|openxlsx2 |1.14 |2025-03-20 |CRAN (R 4.4.1) |
|
||||
|parameters |0.24.2 |2025-03-04 |CRAN (R 4.4.1) |
|
||||
|patchwork |1.3.0 |2024-09-16 |CRAN (R 4.4.1) |
|
||||
|performance |0.13.0 |2025-01-15 |CRAN (R 4.4.1) |
|
||||
|phosphoricons |0.2.1 |2024-04-08 |CRAN (R 4.4.0) |
|
||||
|pillar |1.10.2 |2025-04-05 |CRAN (R 4.4.1) |
|
||||
|pkgbuild |1.4.7 |2025-03-24 |CRAN (R 4.4.1) |
|
||||
|pkgconfig |2.0.3 |2019-09-22 |CRAN (R 4.4.1) |
|
||||
|pkgload |1.4.0 |2024-06-28 |CRAN (R 4.4.0) |
|
||||
|processx |3.8.6 |2025-02-21 |CRAN (R 4.4.1) |
|
||||
|profvis |0.4.0 |2024-09-20 |CRAN (R 4.4.1) |
|
||||
|promises |1.3.2 |2024-11-28 |CRAN (R 4.4.1) |
|
||||
|proxy |0.4-27 |2022-06-09 |CRAN (R 4.4.1) |
|
||||
|ps |1.9.1 |2025-04-12 |CRAN (R 4.4.1) |
|
||||
|purrr |1.0.4 |2025-02-05 |CRAN (R 4.4.1) |
|
||||
|quarto |1.4.4 |2024-07-20 |CRAN (R 4.4.0) |
|
||||
|R6 |2.6.1 |2025-02-15 |CRAN (R 4.4.1) |
|
||||
|rbibutils |2.3 |2024-10-04 |CRAN (R 4.4.1) |
|
||||
|RColorBrewer |1.1-3 |2022-04-03 |CRAN (R 4.4.1) |
|
||||
|Rcpp |1.0.14 |2025-01-12 |CRAN (R 4.4.1) |
|
||||
|Rdpack |2.6.4 |2025-04-09 |CRAN (R 4.4.1) |
|
||||
|reactable |0.4.4 |2023-03-12 |CRAN (R 4.4.0) |
|
||||
|readODS |2.3.2 |2025-01-13 |CRAN (R 4.4.1) |
|
||||
|readr |2.1.5 |2024-01-10 |CRAN (R 4.4.0) |
|
||||
|readxl |1.4.5 |2025-03-07 |CRAN (R 4.4.1) |
|
||||
|reformulas |0.4.0 |2024-11-03 |CRAN (R 4.4.1) |
|
||||
|remotes |2.5.0 |2024-03-17 |CRAN (R 4.4.1) |
|
||||
|renv |1.1.4 |2025-03-20 |CRAN (R 4.4.1) |
|
||||
|report |0.6.1 |2025-02-07 |CRAN (R 4.4.1) |
|
||||
|rio |1.2.3 |2024-09-25 |CRAN (R 4.4.1) |
|
||||
|rlang |1.1.6 |2025-04-11 |CRAN (R 4.4.1) |
|
||||
|rmarkdown |2.29 |2024-11-04 |CRAN (R 4.4.1) |
|
||||
|rprojroot |2.0.4 |2023-11-05 |CRAN (R 4.4.1) |
|
||||
|rsconnect |1.3.4 |2025-01-22 |CRAN (R 4.4.1) |
|
||||
|rstudioapi |0.17.1 |2024-10-22 |CRAN (R 4.4.1) |
|
||||
|sass |0.4.10 |2025-04-11 |CRAN (R 4.4.1) |
|
||||
|scales |1.3.0 |2023-11-28 |CRAN (R 4.4.0) |
|
||||
|see |0.11.0 |2025-03-11 |CRAN (R 4.4.1) |
|
||||
|sessioninfo |1.2.3 |2025-02-05 |CRAN (R 4.4.1) |
|
||||
|shiny |1.10.0 |2024-12-14 |CRAN (R 4.4.1) |
|
||||
|shinybusy |0.3.3 |2024-03-09 |CRAN (R 4.4.0) |
|
||||
|shinyTime |1.0.3 |2022-08-19 |CRAN (R 4.4.0) |
|
||||
|shinyWidgets |0.9.0 |2025-02-21 |CRAN (R 4.4.1) |
|
||||
|stringi |1.8.7 |2025-03-27 |CRAN (R 4.4.1) |
|
||||
|sys |3.4.3 |2024-10-04 |CRAN (R 4.4.1) |
|
||||
|tibble |3.2.1 |2023-03-20 |CRAN (R 4.4.0) |
|
||||
|tidyr |1.3.1 |2024-01-24 |CRAN (R 4.4.1) |
|
||||
|tidyselect |1.2.1 |2024-03-11 |CRAN (R 4.4.0) |
|
||||
|toastui |0.4.0 |2025-04-03 |CRAN (R 4.4.1) |
|
||||
|tzdb |0.5.0 |2025-03-15 |CRAN (R 4.4.1) |
|
||||
|urlchecker |1.0.1 |2021-11-30 |CRAN (R 4.4.1) |
|
||||
|usethis |3.1.0 |2024-11-26 |CRAN (R 4.4.1) |
|
||||
|vctrs |0.6.5 |2023-12-01 |CRAN (R 4.4.0) |
|
||||
|vroom |1.6.5 |2023-12-05 |CRAN (R 4.4.0) |
|
||||
|whisker |0.4.1 |2022-12-05 |CRAN (R 4.4.1) |
|
||||
|withr |3.0.2 |2024-10-28 |CRAN (R 4.4.1) |
|
||||
|writexl |1.5.4 |2025-04-15 |CRAN (R 4.4.1) |
|
||||
|xfun |0.52 |2025-04-02 |CRAN (R 4.4.1) |
|
||||
|xml2 |1.3.8 |2025-03-14 |CRAN (R 4.4.1) |
|
||||
|xtable |1.8-4 |2019-04-21 |CRAN (R 4.4.1) |
|
||||
|yaml |2.3.10 |2024-07-26 |CRAN (R 4.4.1) |
|
||||
|zip |2.3.2 |2025-02-01 |CRAN (R 4.4.1) |
|
||||
|
|
@ -8,14 +8,13 @@ template:
|
|||
base_font: {google: "Montserrat"}
|
||||
heading_font: {google: "Public Sans"}
|
||||
# code_font: {google: "Open Sans"}
|
||||
# Adding the switch destroys the theme colors
|
||||
light-switch: false
|
||||
|
||||
navbar:
|
||||
bg: primary
|
||||
structure:
|
||||
left: [intro, reference, articles, roadmap, q_a, news]
|
||||
right: [search, github]
|
||||
right: [search, github, lightswitch]
|
||||
components:
|
||||
roadmap:
|
||||
text: Roadmap
|
||||
|
|
|
|||
|
|
@ -1,19 +0,0 @@
|
|||
## code to prepare `session` dataset goes here
|
||||
|
||||
session <- devtools::session_info()
|
||||
|
||||
platform <- c(session$platform,
|
||||
"FreesearchR"=paste(gsub("Version: ","",readLines(here::here('DESCRIPTION'))[3]),format(Sys.time(),format = '%y%m%d'),sep='.'))
|
||||
|
||||
platform <- data.frame(option=names(platform),value=Reduce(c,platform))
|
||||
|
||||
libs <- as.data.frame(session$packages)[names(session$packages) %in% c("package","loadedversion","date","source")]
|
||||
|
||||
rownames(libs) <- NULL
|
||||
|
||||
session_data <- list(
|
||||
platform=platform,
|
||||
libs=libs
|
||||
)
|
||||
|
||||
usethis::use_data(session_data,internal = TRUE, overwrite = TRUE)
|
||||
|
|
@ -10,7 +10,7 @@
|
|||
#### Current file: /Users/au301842/FreesearchR/R//app_version.R
|
||||
########
|
||||
|
||||
app_version <- function()'v25.4.3.250423'
|
||||
app_version <- function()'Version: 25.4.3.250422'
|
||||
|
||||
|
||||
########
|
||||
|
|
@ -1801,7 +1801,7 @@ line_break <- function(data, lineLength = 20, force = FALSE) {
|
|||
#' @export
|
||||
#'
|
||||
wrap_plot_list <- function(data, tag_levels = NULL) {
|
||||
if (ggplot2::is_ggplot(data[[1]])) {
|
||||
if (ggplot2::is.ggplot(data[[1]])) {
|
||||
if (length(data) > 1) {
|
||||
out <- data |>
|
||||
(\(.x){
|
||||
|
|
@ -1838,7 +1838,7 @@ wrap_plot_list <- function(data, tag_levels = NULL) {
|
|||
align_axes <- function(...) {
|
||||
# https://stackoverflow.com/questions/62818776/get-axis-limits-from-ggplot-object
|
||||
# https://github.com/thomasp85/patchwork/blob/main/R/plot_multipage.R#L150
|
||||
if (ggplot2::is_ggplot(..1)) {
|
||||
if (ggplot2::is.ggplot(..1)) {
|
||||
## Assumes list of ggplots
|
||||
p <- list(...)
|
||||
} else if (is.list(..1)) {
|
||||
|
|
@ -2497,7 +2497,7 @@ read_input <- function(file, consider.na = c("NA", '""', "")) {
|
|||
if (ext == "csv") {
|
||||
df <- readr::read_csv(file = file, na = consider.na)
|
||||
} else if (ext %in% c("xls", "xlsx")) {
|
||||
df <- readxl::read_excel(file = file, na.strings = consider.na)
|
||||
df <- openxlsx2::read_xlsx(file = file, na.strings = consider.na)
|
||||
} else if (ext == "dta") {
|
||||
df <- haven::read_dta(file = file)
|
||||
} else if (ext == "ods") {
|
||||
|
|
@ -2838,7 +2838,7 @@ sort_by <- function(x, y, na.rm = FALSE, ...) {
|
|||
|
||||
|
||||
get_ggplot_label <- function(data, label) {
|
||||
assertthat::assert_that(ggplot2::is_ggplot(data))
|
||||
assertthat::assert_that(ggplot2::is.ggplot(data))
|
||||
data$labels[[label]]
|
||||
}
|
||||
|
||||
|
|
@ -3368,8 +3368,7 @@ import_file_server <- function(id,
|
|||
)
|
||||
|
||||
observeEvent(input$see_data, {
|
||||
tryCatch(
|
||||
{
|
||||
tryCatch({
|
||||
datamods:::show_data(default_parsing(temporary_rv$data), title = datamods:::i18n("Imported data"), type = show_data_in)
|
||||
},
|
||||
# warning = function(warn) {
|
||||
|
|
@ -3383,10 +3382,9 @@ import_file_server <- function(id,
|
|||
|
||||
output$table <- toastui::renderDatagrid2({
|
||||
req(temporary_rv$data)
|
||||
tryCatch(
|
||||
{
|
||||
tryCatch({
|
||||
toastui::datagrid(
|
||||
data = setNames(head(temporary_rv$data, 5), make.names(names(temporary_rv$data), unique = TRUE)),
|
||||
data = setNames(head(temporary_rv$data, 5),make.names(names(temporary_rv$data),unique = TRUE)),
|
||||
theme = "striped",
|
||||
colwidths = "guess",
|
||||
minBodyHeight = 250
|
||||
|
|
@ -3490,22 +3488,13 @@ import_xls <- function(file, sheet, skip, na.strings) {
|
|||
|
||||
sheet |>
|
||||
purrr::map(\(.x){
|
||||
readxl::read_excel(
|
||||
path = file,
|
||||
openxlsx2::read_xlsx(
|
||||
file = file,
|
||||
sheet = .x,
|
||||
na = na.strings,
|
||||
skip = skip,
|
||||
.name_repair = "unique_quiet",
|
||||
trim_ws = TRUE
|
||||
skip_empty_rows = TRUE,
|
||||
start_row = skip - 1,
|
||||
na.strings = na.strings
|
||||
)
|
||||
|
||||
# openxlsx2::read_xlsx(
|
||||
# file = file,
|
||||
# sheet = .x,
|
||||
# skip_empty_rows = TRUE,
|
||||
# start_row = skip - 1,
|
||||
# na.strings = na.strings
|
||||
# )
|
||||
}) |>
|
||||
purrr::reduce(dplyr::full_join)
|
||||
},
|
||||
|
|
@ -3749,14 +3738,13 @@ plot_box <- function(data, pri, sec, ter = NULL) {
|
|||
#' @export
|
||||
#'
|
||||
#' @examples
|
||||
#' mtcars |> plot_box_single("mpg")
|
||||
#' mtcars |> plot_box_single("mpg","cyl")
|
||||
plot_box_single <- function(data, pri, sec=NULL, seed = 2103) {
|
||||
set.seed(seed)
|
||||
|
||||
if (is.null(sec)) {
|
||||
sec <- "All"
|
||||
data[[sec]] <- sec
|
||||
data[[y]] <- sec
|
||||
}
|
||||
|
||||
discrete <- !data_type(data[[sec]]) %in% "continuous"
|
||||
|
|
@ -4087,7 +4075,7 @@ sankey_ready <- function(data, pri, sec, numbers = "count", ...) {
|
|||
data[c(pri, sec)] <- data[c(pri, sec)] |>
|
||||
dplyr::mutate(dplyr::across(!dplyr::where(is.factor), forcats::as_factor))
|
||||
|
||||
out <- dplyr::count(data, !!dplyr::sym(pri), !!dplyr::sym(sec), .drop = FALSE)
|
||||
out <- dplyr::count(data, !!dplyr::sym(pri), !!dplyr::sym(sec))
|
||||
|
||||
out <- out |>
|
||||
dplyr::group_by(!!dplyr::sym(pri)) |>
|
||||
|
|
@ -4138,17 +4126,9 @@ str_remove_last <- function(data, pattern = "\n") {
|
|||
#' @examples
|
||||
#' ds <- data.frame(g = sample(LETTERS[1:2], 100, TRUE), first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)), last = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)))
|
||||
#' ds |> plot_sankey("first", "last")
|
||||
#' ds |> plot_sankey("first", "last", color.group = "sec")
|
||||
#' ds |> plot_sankey("first", "last", ter = "g", color.group = "sec")
|
||||
#' mtcars |>
|
||||
#' default_parsing() |>
|
||||
#' plot_sankey("cyl", "gear", "am", color.group = "pri")
|
||||
#' ## In this case, the last plot as the secondary variable in wrong order
|
||||
#' ## Dont know why...
|
||||
#' mtcars |>
|
||||
#' default_parsing() |>
|
||||
#' plot_sankey("cyl", "gear", "vs", color.group = "pri")
|
||||
plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors = NULL) {
|
||||
#' ds |> plot_sankey("first", "last", color.group = "y")
|
||||
#' ds |> plot_sankey("first", "last", z = "g", color.group = "y")
|
||||
plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "x", colors = NULL) {
|
||||
if (!is.null(ter)) {
|
||||
ds <- split(data, data[ter])
|
||||
} else {
|
||||
|
|
@ -4156,12 +4136,16 @@ plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors
|
|||
}
|
||||
|
||||
out <- lapply(ds, \(.ds){
|
||||
plot_sankey_single(.ds, pri = pri, sec = sec, color.group = color.group, colors = colors)
|
||||
plot_sankey_single(.ds, x = pri, y = sec, color.group = color.group, colors = colors)
|
||||
})
|
||||
|
||||
patchwork::wrap_plots(out)
|
||||
}
|
||||
|
||||
default_theme <- function() {
|
||||
theme_void()
|
||||
}
|
||||
|
||||
#' Beautiful sankey plot
|
||||
#'
|
||||
#' @param color.group set group to colour by. "x" or "y".
|
||||
|
|
@ -4175,26 +4159,15 @@ plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors
|
|||
#' @examples
|
||||
#' ds <- data.frame(g = sample(LETTERS[1:2], 100, TRUE), first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)), last = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)))
|
||||
#' ds |> plot_sankey_single("first", "last")
|
||||
#' ds |> plot_sankey_single("first", "last", color.group = "sec")
|
||||
#' ds |> plot_sankey_single("first", "last", color.group = "y")
|
||||
#' data.frame(
|
||||
#' g = sample(LETTERS[1:2], 100, TRUE),
|
||||
#' first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)),
|
||||
#' last = sample(c(TRUE, FALSE, FALSE), 100, TRUE)
|
||||
#' ) |>
|
||||
#' plot_sankey_single("first", "last", color.group = "pri")
|
||||
#' mtcars |>
|
||||
#' default_parsing() |>
|
||||
#' str()
|
||||
#' plot_sankey_single("cyl", "vs", color.group = "pri")
|
||||
plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), colors = NULL, ...) {
|
||||
color.group <- match.arg(color.group)
|
||||
|
||||
data_orig <- data
|
||||
data[c(pri, sec)] <- data[c(pri, sec)] |>
|
||||
dplyr::mutate(dplyr::across(dplyr::where(is.factor), forcats::fct_drop))
|
||||
|
||||
# browser()
|
||||
|
||||
data <- data |> sankey_ready(pri = pri, sec = sec, ...)
|
||||
|
||||
library(ggalluvial)
|
||||
|
|
@ -4204,17 +4177,11 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
|
|||
|
||||
if (is.null(colors)) {
|
||||
if (color.group == "sec") {
|
||||
main.colors <- viridisLite::viridis(n = length(levels(data_orig[[sec]])))
|
||||
## Only keep colors for included levels
|
||||
main.colors <- main.colors[match(levels(data[[sec]]), levels(data_orig[[sec]]))]
|
||||
|
||||
main.colors <- viridisLite::viridis(n = length(levels(data[[sec]])))
|
||||
secondary.colors <- rep(na.color, length(levels(data[[pri]])))
|
||||
label.colors <- Reduce(c, lapply(list(secondary.colors, rev(main.colors)), contrast_text))
|
||||
} else {
|
||||
main.colors <- viridisLite::viridis(n = length(levels(data_orig[[pri]])))
|
||||
## Only keep colors for included levels
|
||||
main.colors <- main.colors[match(levels(data[[pri]]), levels(data_orig[[pri]]))]
|
||||
|
||||
main.colors <- viridisLite::viridis(n = length(levels(data[[pri]])))
|
||||
secondary.colors <- rep(na.color, length(levels(data[[sec]])))
|
||||
label.colors <- Reduce(c, lapply(list(rev(main.colors), secondary.colors), contrast_text))
|
||||
}
|
||||
|
|
@ -4232,11 +4199,7 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
|
|||
if (color.group == "sec") {
|
||||
p <- p +
|
||||
ggalluvial::geom_alluvium(
|
||||
ggplot2::aes(
|
||||
fill = !!dplyr::sym(sec) # ,
|
||||
## Including will print strings when levels are empty
|
||||
# color = !!dplyr::sym(sec)
|
||||
),
|
||||
ggplot2::aes(fill = !!dplyr::sym(sec), color = !!dplyr::sym(sec)),
|
||||
width = 1 / 16,
|
||||
alpha = .8,
|
||||
knot.pos = 0.4,
|
||||
|
|
@ -4248,10 +4211,7 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
|
|||
} else {
|
||||
p <- p +
|
||||
ggalluvial::geom_alluvium(
|
||||
ggplot2::aes(
|
||||
fill = !!dplyr::sym(pri) # ,
|
||||
# color = !!dplyr::sym(pri)
|
||||
),
|
||||
ggplot2::aes(fill = !!dplyr::sym(pri), color = !!dplyr::sym(pri)),
|
||||
width = 1 / 16,
|
||||
alpha = .8,
|
||||
knot.pos = 0.4,
|
||||
|
|
@ -4275,7 +4235,7 @@ plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), co
|
|||
labels = group_labels
|
||||
) +
|
||||
ggplot2::scale_fill_manual(values = colors[-1], na.value = colors[1]) +
|
||||
# ggplot2::scale_color_manual(values = main.colors) +
|
||||
ggplot2::scale_color_manual(values = main.colors) +
|
||||
ggplot2::theme_void() +
|
||||
ggplot2::theme(
|
||||
legend.position = "none",
|
||||
|
|
@ -8439,7 +8399,7 @@ ui_elements <- list(
|
|||
shiny::uiOutput(outputId = "column_filter"),
|
||||
shiny::helpText("Variable ", tags$a(
|
||||
"data type",
|
||||
href = "https://agdamsbo.github.io/FreesearchR/articles/data-types.html",
|
||||
href = "https://agdamsbo.github.io/FreesearchR/articles/FreesearchR.html",
|
||||
target = "_blank",
|
||||
rel = "noopener noreferrer"
|
||||
), " filtering."),
|
||||
|
|
@ -8636,13 +8596,15 @@ ui_elements <- list(
|
|||
data_visuals_ui("visuals"),
|
||||
shiny::tagList(
|
||||
bslib::nav_spacer(),
|
||||
bslib::nav_item(
|
||||
# shiny::img(shiny::icon("book")),
|
||||
shiny::tags$a(
|
||||
href = "https://agdamsbo.github.io/FreesearchR/articles/visuals.html",
|
||||
"Notes (external)",
|
||||
target = "_blank",
|
||||
rel = "noopener noreferrer"
|
||||
bslib::nav_panel(
|
||||
title = "Notes",
|
||||
shiny::fluidRow(
|
||||
shiny::column(width = 2),
|
||||
shiny::column(
|
||||
width = 8,
|
||||
shiny::markdown(readLines("www/notes_visuals.md")),
|
||||
shiny::column(width = 2)
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
|
|
@ -8812,11 +8774,11 @@ ui <- bslib::page_fixed(
|
|||
style = "background-color: #14131326; padding: 4px; text-align: center; bottom: 0; width: 100%;",
|
||||
shiny::p(
|
||||
style = "margin: 1",
|
||||
"Data is only stored for analyses and deleted when the app is closed."
|
||||
"Data is only stored for analyses and deleted immediately afterwards."
|
||||
),
|
||||
shiny::p(
|
||||
style = "margin: 1; color: #888;",
|
||||
shiny::tags$a("AG Damsbo", href = "https://andreas.gdamsbo.dk/", target = "_blank", rel = "noopener noreferrer")," | ", app_version(), " | ", shiny::tags$a("License: AGPLv3", href = "https://github.com/agdamsbo/FreesearchR/blob/main/LICENSE.md", target = "_blank", rel = "noopener noreferrer"), " | ", shiny::tags$a("Source", href = "https://github.com/agdamsbo/FreesearchR/", target = "_blank", rel = "noopener noreferrer")
|
||||
"AG Damsbo | v", app_version(), " | ", shiny::tags$a("AGPLv3 license", href = "https://github.com/agdamsbo/FreesearchR/blob/main/LICENSE.md", target = "_blank", rel = "noopener noreferrer"), " | ", shiny::tags$a("Source on Github", href = "https://github.com/agdamsbo/FreesearchR/", target = "_blank", rel = "noopener noreferrer")
|
||||
),
|
||||
)
|
||||
)
|
||||
|
|
|
|||
|
|
@ -359,13 +359,15 @@ ui_elements <- list(
|
|||
data_visuals_ui("visuals"),
|
||||
shiny::tagList(
|
||||
bslib::nav_spacer(),
|
||||
bslib::nav_item(
|
||||
# shiny::img(shiny::icon("book")),
|
||||
shiny::tags$a(
|
||||
href = "https://agdamsbo.github.io/FreesearchR/articles/visuals.html",
|
||||
"Notes (external)",
|
||||
target = "_blank",
|
||||
rel = "noopener noreferrer"
|
||||
bslib::nav_panel(
|
||||
title = "Notes",
|
||||
shiny::fluidRow(
|
||||
shiny::column(width = 2),
|
||||
shiny::column(
|
||||
width = 8,
|
||||
shiny::markdown(readLines("www/notes_visuals.md")),
|
||||
shiny::column(width = 2)
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
|
|
@ -535,11 +537,11 @@ ui <- bslib::page_fixed(
|
|||
style = "background-color: #14131326; padding: 4px; text-align: center; bottom: 0; width: 100%;",
|
||||
shiny::p(
|
||||
style = "margin: 1",
|
||||
"Data is only stored for analyses and deleted when the app is closed."
|
||||
"Data is only stored for analyses and deleted immediately afterwards."
|
||||
),
|
||||
shiny::p(
|
||||
style = "margin: 1; color: #888;",
|
||||
shiny::tags$a("AG Damsbo", href = "https://andreas.gdamsbo.dk/", target = "_blank", rel = "noopener noreferrer")," | ", app_version(), " | ", shiny::tags$a("License: AGPLv3", href = "https://github.com/agdamsbo/FreesearchR/blob/main/LICENSE.md", target = "_blank", rel = "noopener noreferrer"), " | ", shiny::tags$a("Source", href = "https://github.com/agdamsbo/FreesearchR/", target = "_blank", rel = "noopener noreferrer")
|
||||
"AG Damsbo | v", app_version(), " | ", shiny::tags$a("AGPLv3 license", href = "https://github.com/agdamsbo/FreesearchR/blob/main/LICENSE.md", target = "_blank", rel = "noopener noreferrer"), " | ", shiny::tags$a("Source on Github", href = "https://github.com/agdamsbo/FreesearchR/", target = "_blank", rel = "noopener noreferrer")
|
||||
),
|
||||
)
|
||||
)
|
||||
|
|
|
|||
Binary file not shown.
|
Before Width: | Height: | Size: 28 KiB After Width: | Height: | Size: 31 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 28 KiB After Width: | Height: | Size: 31 KiB |
|
|
@ -1,4 +1,4 @@
|
|||
# Welcome <img style="float: right;" src="logo-text-white-250.png">
|
||||
# Welcome
|
||||
|
||||
This is the ***FreesearchR*** data analysis tool. We intend the ***FreesearchR*** to be a powerful and free tool for easy data evaluation and analysis at the hands of the clinician. If you need more advanced tools for regression models or plotting, you'll probably be better off using *R* or similar directly on your own machine.
|
||||
|
||||
|
|
@ -6,7 +6,7 @@ By intention, this tool has been designed to be simple to use with a minimum of
|
|||
|
||||
There are some simple steps to go through (see corresponding tabs in the top):
|
||||
|
||||
1. Import data to get started. This can be a spreadsheet/file on your machine, direct export from a REDCap server, sample data or data from a your local environment if run locally.
|
||||
1. Import data (a spreadsheet/file on your machine, direct export from a REDCap server, or a local file provided with a package) to get started.
|
||||
|
||||
1. Data inspection and modification (change variable classes, create new variables (categorical from numeric or time data, or completely new variables from the data)
|
||||
|
||||
|
|
@ -20,14 +20,10 @@ There are some simple steps to go through (see corresponding tabs in the top):
|
|||
|
||||
- Plot regression analysis coefficients
|
||||
|
||||
- Evaluate model assumptions
|
||||
- Evaluation of model assumptions
|
||||
|
||||
1. Export results
|
||||
1. Export the the analyses results for MS Word or [LibreOffice](https://www.libreoffice.org/) as well as the data with preserved metadata.
|
||||
|
||||
- Descriptive and regression analyses results for MS Word or [LibreOffice](https://www.libreoffice.org/)
|
||||
The full [project documentation is here](https://agdamsbo.github.io/FreesearchR/) for documenting the project, functions, road map and more. If you're interested in the source code, then [everything is open and you are free to read, copy, modify and improve](https://github.com/agdamsbo/FreesearchR), and please let us know if you want to contribute!
|
||||
|
||||
- Modified data with preserved metadata
|
||||
|
||||
- Code to recreate all steps locally
|
||||
|
||||
The full [project documentation is here](https://agdamsbo.github.io/FreesearchR/) and all code used is [freely available to read, copy, modify and improve](https://github.com/agdamsbo/FreesearchR) under an [open source license](https://github.com/agdamsbo/FreesearchR/blob/main/LICENSE.md)! Contributions are welcome and much appreciated and can be reporting issues, suggesting new functionality, improving code or any other feedback [here](https://github.com/agdamsbo/FreesearchR/issues).
|
||||
Contributions can be reporting issues, suggesting new functionality, improving code or any other feedback. [It all goes here](https://github.com/agdamsbo/FreesearchR/issues).
|
||||
|
|
|
|||
Binary file not shown.
|
Before Width: | Height: | Size: 22 KiB |
413
inst/apps/FreesearchR/www/notes_visuals.html
Normal file
413
inst/apps/FreesearchR/www/notes_visuals.html
Normal file
File diff suppressed because one or more lines are too long
11
inst/apps/FreesearchR/www/notes_visuals.md
Normal file
11
inst/apps/FreesearchR/www/notes_visuals.md
Normal file
|
|
@ -0,0 +1,11 @@
|
|||
# Basic visualisations
|
||||
|
||||
The goal of ***FreesearchR*** is to keep things simple. Visuals can get very complicated. We provide a selection of plots, that helps visualise typical clinical and will be enough for most use cases, and for publishing to most journals.
|
||||
|
||||
If you want to go further, have a look at these sites with suggestions and sample code for data plotting:
|
||||
|
||||
- [*R* Charts](https://r-charts.com/): Extensive gallery with great plots
|
||||
|
||||
- [*R* Graph gallery](https://r-graph-gallery.com/): Another gallery with great graphs
|
||||
|
||||
- [graphics principles](https://graphicsprinciples.github.io/): Easy to follow recommendations for clear visuals.
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 22 KiB |
|
|
@ -32,7 +32,7 @@ plot_ridge(data, x, y, z = NULL, ...)
|
|||
|
||||
sankey_ready(data, pri, sec, numbers = "count", ...)
|
||||
|
||||
plot_sankey(data, pri, sec, ter = NULL, color.group = "pri", colors = NULL)
|
||||
plot_sankey(data, pri, sec, ter = NULL, color.group = "x", colors = NULL)
|
||||
|
||||
plot_scatter(data, pri, sec, ter = NULL)
|
||||
|
||||
|
|
@ -103,7 +103,6 @@ mtcars |> plot_box(pri = "mpg", sec = "cyl", ter = "gear")
|
|||
mtcars |>
|
||||
default_parsing() |>
|
||||
plot_box(pri = "mpg", sec = "cyl", ter = "gear")
|
||||
mtcars |> plot_box_single("mpg")
|
||||
mtcars |> plot_box_single("mpg","cyl")
|
||||
mtcars |> plot_hbars(pri = "carb", sec = "cyl")
|
||||
mtcars |> plot_hbars(pri = "carb", sec = NULL)
|
||||
|
|
@ -122,16 +121,8 @@ data.frame(
|
|||
sankey_ready("first", "last")
|
||||
ds <- data.frame(g = sample(LETTERS[1:2], 100, TRUE), first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)), last = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)))
|
||||
ds |> plot_sankey("first", "last")
|
||||
ds |> plot_sankey("first", "last", color.group = "sec")
|
||||
ds |> plot_sankey("first", "last", ter = "g", color.group = "sec")
|
||||
mtcars |>
|
||||
default_parsing() |>
|
||||
plot_sankey("cyl", "gear", "am", color.group = "pri")
|
||||
## In this case, the last plot as the secondary variable in wrong order
|
||||
## Dont know why...
|
||||
mtcars |>
|
||||
default_parsing() |>
|
||||
plot_sankey("cyl", "gear", "vs", color.group = "pri")
|
||||
ds |> plot_sankey("first", "last", color.group = "y")
|
||||
ds |> plot_sankey("first", "last", z = "g", color.group = "y")
|
||||
mtcars |> plot_scatter(pri = "mpg", sec = "wt")
|
||||
mtcars |> plot_violin(pri = "mpg", sec = "cyl", ter = "gear")
|
||||
}
|
||||
|
|
|
|||
|
|
@ -30,15 +30,11 @@ Beautiful sankey plot
|
|||
\examples{
|
||||
ds <- data.frame(g = sample(LETTERS[1:2], 100, TRUE), first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)), last = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)))
|
||||
ds |> plot_sankey_single("first", "last")
|
||||
ds |> plot_sankey_single("first", "last", color.group = "sec")
|
||||
ds |> plot_sankey_single("first", "last", color.group = "y")
|
||||
data.frame(
|
||||
g = sample(LETTERS[1:2], 100, TRUE),
|
||||
first = REDCapCAST::as_factor(sample(letters[1:4], 100, TRUE)),
|
||||
last = sample(c(TRUE, FALSE, FALSE), 100, TRUE)
|
||||
) |>
|
||||
plot_sankey_single("first", "last", color.group = "pri")
|
||||
mtcars |>
|
||||
default_parsing() |>
|
||||
str()
|
||||
plot_sankey_single("cyl", "vs", color.group = "pri")
|
||||
}
|
||||
|
|
|
|||
|
|
@ -46,7 +46,7 @@ test_that("create_plot works", {
|
|||
p <- p_list[[1]] + ggplot2::labs(title = "Test plot")
|
||||
|
||||
expect_equal(length(p_list), 2)
|
||||
expect_true(ggplot2::is_ggplot(p))
|
||||
expect_true(ggplot2::is.ggplot(p))
|
||||
|
||||
# Includes helper functions
|
||||
# wrap_plot_list
|
||||
|
|
@ -60,7 +60,7 @@ test_that("create_plot works", {
|
|||
)
|
||||
|
||||
lapply(p_list, \(.x){
|
||||
expect_true(ggplot2::is_ggplot(.x))
|
||||
expect_true(ggplot2::is.ggplot(.x))
|
||||
})
|
||||
|
||||
purrr::map2(p_list, list(11, 11), \(.x, .y){
|
||||
|
|
|
|||
|
|
@ -12,7 +12,6 @@ knitr::opts_chunk$set(
|
|||
collapse = TRUE,
|
||||
comment = "#>"
|
||||
)
|
||||
options(rmarkdown.html_vignette.check_title = FALSE)
|
||||
```
|
||||
|
||||
```{r setup}
|
||||
|
|
|
|||
|
|
@ -1,35 +0,0 @@
|
|||
---
|
||||
title: "Session info"
|
||||
output: rmarkdown::html_vignette
|
||||
vignette: >
|
||||
%\VignetteIndexEntry{session}
|
||||
%\VignetteEngine{knitr::rmarkdown}
|
||||
%\VignetteEncoding{UTF-8}
|
||||
---
|
||||
|
||||
```{r, include = FALSE}
|
||||
knitr::opts_chunk$set(
|
||||
collapse = TRUE,
|
||||
comment = "#>"
|
||||
)
|
||||
options(rmarkdown.html_vignette.check_title = FALSE)
|
||||
```
|
||||
|
||||
```{r setup}
|
||||
library(FreesearchR)
|
||||
```
|
||||
|
||||
This is the session info on the primary build machine. Inspect loaded packages and the latest build info.
|
||||
|
||||
## Platform info
|
||||
|
||||
```{r}
|
||||
FreesearchR:::session_data$platform |> knitr::kable()
|
||||
```
|
||||
|
||||
|
||||
## Libraries
|
||||
|
||||
```{r}
|
||||
FreesearchR:::session_data$libs|> knitr::kable()
|
||||
```
|
||||
|
|
@ -1,55 +0,0 @@
|
|||
---
|
||||
title: "On visuals"
|
||||
output: rmarkdown::html_vignette
|
||||
vignette: >
|
||||
%\VignetteIndexEntry{visuals}
|
||||
%\VignetteEngine{knitr::rmarkdown}
|
||||
%\VignetteEncoding{UTF-8}
|
||||
---
|
||||
|
||||
```{r, include = FALSE}
|
||||
knitr::opts_chunk$set(
|
||||
collapse = TRUE,
|
||||
comment = "#>"
|
||||
)
|
||||
options(rmarkdown.html_vignette.check_title = FALSE)
|
||||
```
|
||||
|
||||
```{r setup}
|
||||
library(FreesearchR)
|
||||
```
|
||||
|
||||
## Basic visualisations
|
||||
|
||||
The goal of ***FreesearchR*** is to keep things simple. Visuals can get very complicated. We provide a selection of plots, that helps visualise typical clinical and will be enough for most use cases, and for publishing to most journals.
|
||||
|
||||
If you want to go further, have a look at these sites with suggestions and sample code for data plotting:
|
||||
|
||||
- [*R* Charts](https://r-charts.com/): Extensive gallery with great plots
|
||||
|
||||
- [*R* Graph gallery](https://r-graph-gallery.com/): Another gallery with great graphs
|
||||
|
||||
- [graphics principles](https://graphicsprinciples.github.io/): Easy to follow recommendations for clear visuals.
|
||||
|
||||
|
||||
### Available plots
|
||||
|
||||
Below are the available plot types listed.
|
||||
|
||||
```{r echo = FALSE, eval = TRUE}
|
||||
c("continuous", "dichotomous", "categorical") |>
|
||||
lapply(\(.x){
|
||||
dplyr::bind_cols(
|
||||
dplyr::tibble("Data type"=.x),
|
||||
supported_plots() |>
|
||||
lapply(\(.y){
|
||||
if (.x %in% .y$primary.type){
|
||||
.y[c("descr","note")]|> dplyr::bind_cols()
|
||||
}
|
||||
})|>
|
||||
dplyr::bind_rows() |>
|
||||
setNames(c("Plot type","Description")))
|
||||
}) |>
|
||||
dplyr::bind_rows() |>
|
||||
knitr::kable()
|
||||
```
|
||||
Loading…
Add table
Reference in a new issue