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20 commits

Author SHA1 Message Date
acbed08a0d
new version ready for release 2026-06-01 09:35:12 +02:00
e8307d3a2e
feat: major restructuring of the visuals module 2026-06-01 09:25:50 +02:00
dbf819c55a Merge branch 'dynamic-plots' 2026-06-01 09:24:12 +02:00
5e85902d4b
version ready for merging 2026-06-01 09:22:55 +02:00
1793a2650f
updated links 2026-06-01 09:22:27 +02:00
bcc4905354
adds 2026-05-30 20:00:42 +02:00
ab3df0eda6
new renders 2026-05-30 19:59:31 +02:00
5ca751d3ea
all plot helper functions are moved 2026-05-30 19:56:25 +02:00
f774b90d07
transformed for a new pragmatic compromise to dynamically load additional input options where available 2026-05-30 19:55:45 +02:00
f2a522dcb6
allows ... inputs in plot models 2026-05-29 11:47:15 +02:00
d1e0236437
new dynamic plotting working 2026-05-29 11:46:58 +02:00
0d4f51f176
upd 2026-05-27 20:23:58 +02:00
7f14447627
revised 2026-04-15 23:47:49 +02:00
41c855a71c
new version 2026-04-10 21:47:36 +02:00
af4e21b836
revised ui 2026-04-10 21:04:42 +02:00
b2745f5628
feat: default to 5 preview colors 2026-04-10 21:04:20 +02:00
1e19486af1
feat: revised color palette selection 2026-04-10 21:03:47 +02:00
4213487a77
v26.4.1 ready 2026-04-02 10:10:40 +02:00
0d9ad7457e
version 26.4.1 incomming 2026-04-01 23:42:39 +02:00
451f5bf9a8
fix: streamlined icons to use only phosphoricons 2026-04-01 23:41:23 +02:00
57 changed files with 8343 additions and 6626 deletions

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@ -17,3 +17,5 @@
^app*$ ^app*$
^page$ ^page$
^demo$ ^demo$
^\.positai$
^\.claude$

1
.gitignore vendored
View file

@ -16,3 +16,4 @@ app
page page
demo demo
visuals visuals
.positai

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@ -8,7 +8,7 @@ message: 'To cite package "FreesearchR" in publications use:'
type: software type: software
license: AGPL-3.0-or-later license: AGPL-3.0-or-later
title: 'FreesearchR: Easy data analysis for clinicians' title: 'FreesearchR: Easy data analysis for clinicians'
version: 26.3.6 version: 26.6.1
doi: 10.5281/zenodo.14527429 doi: 10.5281/zenodo.14527429
identifiers: identifiers:
- type: url - type: url

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@ -1,6 +1,6 @@
Package: FreesearchR Package: FreesearchR
Title: Easy data analysis for clinicians Title: Easy data analysis for clinicians
Version: 26.3.6 Version: 26.6.1
Authors@R: c( Authors@R: c(
person("Andreas Gammelgaard", "Damsbo",email="agdamsbo@clin.au.dk", role = c("aut", "cre"), person("Andreas Gammelgaard", "Damsbo",email="agdamsbo@clin.au.dk", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-7559-1154")), comment = c(ORCID = "0000-0002-7559-1154")),
@ -118,6 +118,7 @@ Collate:
'launch_FreesearchR.R' 'launch_FreesearchR.R'
'missings-module.R' 'missings-module.R'
'plot-download-module.R' 'plot-download-module.R'
'plot-helpers.R'
'plot_bar.R' 'plot_bar.R'
'plot_box.R' 'plot_box.R'
'plot_euler.R' 'plot_euler.R'

View file

@ -16,6 +16,7 @@ export(append_column)
export(append_list) export(append_list)
export(apply_labels) export(apply_labels)
export(argsstring2list) export(argsstring2list)
export(available_plots)
export(baseline_table) export(baseline_table)
export(class_icons) export(class_icons)
export(clean_common_axis) export(clean_common_axis)
@ -64,6 +65,7 @@ export(format_writer)
export(generate_colors) export(generate_colors)
export(get_data_packages) export(get_data_packages)
export(get_fun_options) export(get_fun_options)
export(get_input_params)
export(get_label) export(get_label)
export(get_list_elements) export(get_list_elements)
export(get_plot_options) export(get_plot_options)
@ -116,6 +118,7 @@ export(modify_qmd)
export(names2val) export(names2val)
export(overview_vars) export(overview_vars)
export(pipe_string) export(pipe_string)
export(plot_bar)
export(plot_bar_single) export(plot_bar_single)
export(plot_box) export(plot_box)
export(plot_box_single) export(plot_box_single)

12
NEWS.md
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@ -1,3 +1,15 @@
# FreesearchR 26.6.1
*NEW* The visuals module has been restructured to allow for more advanced inputs, which will be added in the future. Basically a more future proof design allowing for more adjustments, while striving to keep the simplicity. Have fun!
# FreesearchR 26.4.2
Bug fixes and revised color choices.
# FreesearchR 26.4.1
Minor adjustments and bug fixes including streamlining icon use to only use phosphoricons across the app.
# FreesearchR 26.3.6 # FreesearchR 26.3.6
*FIX* Plot single variable in Likert plot. *FIX* Plot single variable in Likert plot.

View file

@ -1 +1 @@
app_version <- function()'26.3.6' app_version <- function()'26.6.1'

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@ -76,7 +76,7 @@ create_column_ui <- function(id) {
actionButton( actionButton(
inputId = ns("compute"), inputId = ns("compute"),
label = tagList( label = tagList(
phosphoricons::ph("pencil"), i18n$t("Create column") phosphoricons::ph("pencil",weight = "bold"), i18n$t("Create column")
), ),
class = "btn-outline-primary", class = "btn-outline-primary",
width = "100%" width = "100%"
@ -84,7 +84,7 @@ create_column_ui <- function(id) {
actionButton( actionButton(
inputId = ns("remove"), inputId = ns("remove"),
label = tagList( label = tagList(
phosphoricons::ph("x-circle"), phosphoricons::ph("x-circle",weight = "bold"),
i18n$t("Cancel") i18n$t("Cancel")
), ),
class = "btn-outline-danger", class = "btn-outline-danger",

View file

@ -64,7 +64,7 @@ cut_variable_ui <- function(id) {
toastui::datagridOutput2(outputId = ns("count")), toastui::datagridOutput2(outputId = ns("count")),
actionButton( actionButton(
inputId = ns("create"), inputId = ns("create"),
label = tagList(phosphoricons::ph("scissors"), i18n$t("Create factor variable")), label = tagList(phosphoricons::ph("scissors",weight = "bold"), i18n$t("Create factor variable")),
class = "btn-outline-primary float-end" class = "btn-outline-primary float-end"
), ),
tags$div(class = "clearfix") tags$div(class = "clearfix")

View file

@ -309,21 +309,29 @@ class_icons <- function(x) {
lapply(x,class_icons) lapply(x,class_icons)
} else { } else {
if (identical(x, "numeric")) { if (identical(x, "numeric")) {
shiny::icon("calculator") phosphoricons::ph("calculator")
# shiny::icon("calculator")
} else if (identical(x, "factor")) { } else if (identical(x, "factor")) {
shiny::icon("chart-simple") phosphoricons::ph("chart-bar")
# shiny::icon("chart-simple")
} else if (identical(x, "integer")) { } else if (identical(x, "integer")) {
shiny::icon("arrow-down-1-9") phosphoricons::ph("list-numbers")
# shiny::icon("arrow-down-1-9")
} else if (identical(x, "character")) { } else if (identical(x, "character")) {
shiny::icon("arrow-down-a-z") phosphoricons::ph("text-aa")
# shiny::icon("arrow-down-a-z")
} else if (identical(x, "logical")) { } else if (identical(x, "logical")) {
shiny::icon("toggle-off") phosphoricons::ph("toggle-left")
# shiny::icon("toggle-off")
} else if (any(c("Date", "POSIXt") %in% x)) { } else if (any(c("Date", "POSIXt") %in% x)) {
shiny::icon("calendar-days") phosphoricons::ph("calendar")
# shiny::icon("calendar-days")
} else if (any("POSIXct", "hms") %in% x) { } else if (any("POSIXct", "hms") %in% x) {
shiny::icon("clock") phosphoricons::ph("clock")
# shiny::icon("clock")
} else { } else {
shiny::icon("table") phosphoricons::ph("calendar")
# shiny::icon("table")
}} }}
} }
@ -342,21 +350,29 @@ type_icons <- function(x) {
lapply(x,class_icons) lapply(x,class_icons)
} else { } else {
if (identical(x, "continuous")) { if (identical(x, "continuous")) {
shiny::icon("calculator") phosphoricons::ph("calculator")
# shiny::icon("calculator")
} else if (identical(x, "categorical")) { } else if (identical(x, "categorical")) {
shiny::icon("chart-simple") phosphoricons::ph("chart-bar")
# shiny::icon("chart-simple")
} else if (identical(x, "ordinal")) { } else if (identical(x, "ordinal")) {
shiny::icon("arrow-down-1-9") phosphoricons::ph("list-numbers")
# shiny::icon("arrow-down-1-9")
} else if (identical(x, "text")) { } else if (identical(x, "text")) {
shiny::icon("arrow-down-a-z") phosphoricons::ph("text-aa")
# shiny::icon("arrow-down-a-z")
} else if (identical(x, "dichotomous")) { } else if (identical(x, "dichotomous")) {
shiny::icon("toggle-off") phosphoricons::ph("toggle-left")
# shiny::icon("toggle-off")
} else if (identical(x,"datetime")) { } else if (identical(x,"datetime")) {
shiny::icon("calendar-days") phosphoricons::ph("calendar")
# shiny::icon("calendar-days")
} else if (identical(x,"id")) { } else if (identical(x,"id")) {
shiny::icon("id-card") phosphoricons::ph("identification-badge")
# shiny::icon("id-card")
} else { } else {
shiny::icon("table") phosphoricons::ph("table")
# shiny::icon("table")
} }
} }
} }

View file

@ -14,13 +14,25 @@ data_visuals_ui <- function(id, tab_title = "Plots", ...) {
list( list(
bslib::layout_sidebar( bslib::layout_sidebar(
sidebar = bslib::sidebar( sidebar = bslib::sidebar(
shiny::actionButton(
inputId = ns("act_plot"),
label = i18n$t("Plot"),
width = "100%",
icon = phosphoricons::ph("paint-brush", weight = "bold"),
# icon = shiny::icon("palette"),
disabled = FALSE
),
shiny::helpText(
i18n$t('Adjust plot input and settings below, then press "Plot".')
),
bslib::accordion( bslib::accordion(
id = "acc_plot", id = "acc_plot",
multiple = FALSE, multiple = FALSE,
bslib::accordion_panel( bslib::accordion_panel(
value = "acc_pan_plot", value = "acc_pan_plot",
title = "Create plot", title = i18n$t("Define plot"),
icon = bsicons::bs_icon("graph-up"), icon = phosphoricons::ph("chart-line"),
# icon = bsicons::bs_icon("graph-up"),
shiny::uiOutput(outputId = ns("primary")), shiny::uiOutput(outputId = ns("primary")),
shiny::helpText( shiny::helpText(
i18n$t( i18n$t(
@ -29,23 +41,22 @@ data_visuals_ui <- function(id, tab_title = "Plots", ...) {
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::uiOutput(outputId = ns("type")), shiny::uiOutput(outputId = ns("type")),
shiny::h5(i18n$t("Other variables")),
shiny::uiOutput(outputId = ns("secondary")), shiny::uiOutput(outputId = ns("secondary")),
shiny::uiOutput(outputId = ns("tertiary")), shiny::uiOutput(outputId = ns("tertiary"))
shiny::uiOutput(outputId = ns("color_palette")),
shiny::br(),
shiny::actionButton(
inputId = ns("act_plot"),
label = i18n$t("Plot"),
width = "100%",
icon = shiny::icon("palette"),
disabled = FALSE
), ),
shiny::helpText(i18n$t('Adjust settings, then press "Plot".')) bslib::accordion_panel(
value = "acc_pan_params",
title = i18n$t("Settings"),
icon = phosphoricons::ph("gear"),
shiny::uiOutput(outputId = ns("color_palette")),
shiny::uiOutput(outputId = ns("basic_parameters")),
), ),
bslib::accordion_panel( bslib::accordion_panel(
value = "acc_pan_download", value = "acc_pan_download",
title = "Download", title = "Download",
icon = bsicons::bs_icon("download"), icon = phosphoricons::ph("download-simple"),
# icon = bsicons::bs_icon("download"),
shinyWidgets::noUiSliderInput( shinyWidgets::noUiSliderInput(
inputId = ns("height_slide"), inputId = ns("height_slide"),
label = i18n$t("Plot height (mm)"), label = i18n$t("Plot height (mm)"),
@ -84,21 +95,22 @@ data_visuals_ui <- function(id, tab_title = "Plots", ...) {
shiny::downloadButton( shiny::downloadButton(
outputId = ns("download_plot"), outputId = ns("download_plot"),
label = i18n$t("Download plot"), label = i18n$t("Download plot"),
icon = shiny::icon("download") icon = phosphoricons::ph("arrow-fat-down")
# icon = shiny::icon("download")
) )
) )
), ),
shiny::p( shiny::p(
"We have collected a few notes on visualising data and details on the options included in FreesearchR:", "We have collected a few notes on visualising data and details on the options included in FreesearchR:",
shiny::tags$a( shiny::tags$a(
href = "https://agdamsbo.github.io/FreesearchR/articles/visuals.html", href = "https://freesearchr.github.io/FreesearchR-knowledge/app/visuals.html",
"View notes in new tab", "View notes in new tab",
target = "_blank", target = "_blank",
rel = "noopener noreferrer" rel = "noopener noreferrer"
) )
) )
), ),
shiny::plotOutput(ns("plot"), height = "70vh"), shiny::plotOutput(ns("plot"), height = "65vh"),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br(), shiny::tags$br(),
shiny::htmlOutput(outputId = ns("code_plot")) shiny::htmlOutput(outputId = ns("code_plot"))
@ -115,10 +127,7 @@ data_visuals_ui <- function(id, tab_title = "Plots", ...) {
#' @name data-plots #' @name data-plots
#' @returns shiny server module #' @returns shiny server module
#' @export #' @export
data_visuals_server <- function(id, data_visuals_server <- function(id, data, palettes = color_choices(), ...) {
data,
palettes,
...) {
shiny::moduleServer( shiny::moduleServer(
id = id, id = id,
module = function(input, output, session) { module = function(input, output, session) {
@ -170,94 +179,155 @@ data_visuals_server <- function(id,
plot_data <- data()[input$primary] plot_data <- data()[input$primary]
} }
plots <- possible_plots(data = plot_data) plots <- possible_plots(data = plot_data, source_list = available_plots())
plots_named <- get_plot_options(plots) |> plots_named <- get_input_params(plots) |>
lapply(\(.x) { lapply(\(.x) {
stats::setNames(.x$descr, .x$note) stats::setNames(.x$descr, .x$note)
}) })
# plots_named <- get_plot_options(plots) |>
# lapply(\(.x) {
# stats::setNames(.x$descr, .x$note)
# })
vectorSelectInput( vectorSelectInput(
inputId = ns("type"), inputId = ns("type"),
selected = NULL, selected = NULL,
label = shiny::h4(i18n$t("Plot type")), label = shiny::h5(i18n$t("Plot type")),
choices = Reduce(c, plots_named), choices = Reduce(c, plots_named),
multiple = FALSE multiple = FALSE
) )
}) })
rv$plot.params <- shiny::reactive({ rv$plot.params <- shiny::reactive({
get_plot_options(input$type) |> purrr::pluck(1) get_input_params(input$type) |> purrr::pluck(1)
# get_plot_options(input$type) |> purrr::pluck(1)
}) })
### Include two additional variable inputs
output$secondary <- shiny::renderUI({ output$secondary <- shiny::renderUI({
shiny::req(input$type) shiny::req(input$type)
cols <- c(rv$plot.params()[["secondary.extra"]], all_but(colnames( # Get the plot function name
subset_types(data(), rv$plot.params()[["secondary.type"]]) base_params <- rv$plot.params()[["base"]]
), input$primary))
columnSelectInput( filtered_params <- base_params[sapply(base_params, function(params) {
inputId = ns("secondary"), params$id %in% "secondary"
data = data, })][[1]]
selected = cols[1],
placeholder = i18n$t("Please select"), filtered_params$exclude <- input$primary
label = if (isTRUE(rv$plot.params()[["secondary.multi"]]))
i18n$t("Additional variables") create_input_element(
else input_id = "secondary",
i18n$t("Secondary variable"), ns = ns,
multiple = rv$plot.params()[["secondary.multi"]], params = append_list(data(), filtered_params, "data")
maxItems = rv$plot.params()[["secondary.max"]],
col_subset = cols,
none_label = i18n$t("No variable")
) )
}) })
output$tertiary <- shiny::renderUI({ output$tertiary <- shiny::renderUI({
shiny::req(input$type) shiny::req(input$type)
columnSelectInput( # Get the plot function name
inputId = ns("tertiary"), base_params <- rv$plot.params()[["base"]]
data = data,
placeholder = i18n$t("Please select"), filtered_params <- base_params[sapply(base_params, function(params) {
label = i18n$t("Grouping variable"), params$id %in% "tertiary"
multiple = FALSE, })][[1]]
col_subset = c(
"none", filtered_params$exclude <- c(input$primary, input$secondary)
all_but(
colnames(subset_types(data(), rv$plot.params()[["tertiary.type"]])), create_input_element(
input$primary, input_id = "tertiary",
input$secondary ns = ns,
) params = append_list(data(), filtered_params, "data")
),
none_label = i18n$t("No stratification")
) )
}) })
### Generating additional parameter inputs if any specified
output$basic_parameters <- renderUI({
req(input$type, rv$plot.params)
# Get the plot function name
base_params <- rv$plot.params()[["base"]]
filtered_params <- base_params[sapply(base_params, function(params) {
!params$id %in% c("secondary", "tertiary")
})]
# Create UI elements for base parameters
base_inputs <- lapply(filtered_params, function(params) {
input_id <- paste0("base_", params$id)
params$id <- NULL
if (params$type %in% "select_variables") {
params$data <- data()
}
create_input_element(params, ns, input_id)
})
tagList(base_inputs)
})
### Color option ### Color option
output$color_palette <- shiny::renderUI({ output$color_palette <- shiny::renderUI({
# shiny::req(input$type) # shiny::req(input$type)
colorSelectInput( colorSelectInput(
inputId = ns("color_palette"), inputId = ns("color_palette"),
label = i18n$t("Choose color palette"), label = i18n$t("Choose color palette"),
choices = palettes choices = palettes,
previews = 5
) )
}) })
shiny::observeEvent(input$act_plot, { shiny::observeEvent(input$act_plot, {
if (NROW(data()) > 0) { if (NROW(data()) > 0) {
tryCatch({ tryCatch({
# Get all input values with prefixes
base_inputs <- reactiveValuesToList(input)[grep("^base_", names(reactiveValuesToList(input)))]
# advanced_inputs <- reactiveValuesToList(input)[grep("^advanced_", names(reactiveValuesToList(input)))]
# Remove the prefix from names
names(base_inputs) <- gsub("^base_", "", names(base_inputs))
# names(advanced_inputs) <- gsub("^advanced_", "", names(advanced_inputs))
base_inputs <- c(base_inputs,
list(color.palette = input$color_palette))
# If any of the specified parameters are NULL/missing, the settings
# accordion/panel was never opened, and they can be ignored, as
# default settings will the be used.
if (any(sapply(base_inputs, is.null))) {
dynamic_params <- list()
} else {
dynamic_params <- base_inputs
}
# Build parameters for plotting function
parameters <- list( parameters <- list(
type = rv$plot.params()[["fun"]], type = rv$plot.params()[["fun"]],
pri = input$primary, pri = input$primary,
sec = input$secondary, sec = input$secondary,
ter = input$tertiary, ter = input$tertiary
color.palette = input$color_palette
) )
parameters <- modifyList(parameters, dynamic_params)
## If the dictionary holds additional arguments to pass to the ## If the dictionary holds additional arguments to pass to the
## plotting function, these are included ## plotting function, these are included
if (!is.null(rv$plot.params()[["fun.args"]])) { if (!is.null(rv$plot.params()[["fun.args"]])) {
parameters <- modifyList(parameters, rv$plot.params()[["fun.args"]]) default_params <- rv$plot.params()[["fun.args"]]
## Ensure not to overwrite user defined parameters are overwritten
## This allows to define default parameters.
##
## This will create a strange edge case, where the plot looks in
## one way, when plotted initially, but may change, when the settings
## accordion is opened. Problem for future me. Really mostly an edge case.
parameters <- modifyList(parameters, default_params[!names(default_params) %in% names(parameters)])
} }
shiny::withProgress(message = i18n$t("Drawing the plot. Hold tight for a moment.."), shiny::withProgress(message = i18n$t("Drawing the plot. Hold tight for a moment.."),
@ -293,7 +363,25 @@ data_visuals_server <- function(id,
if (!is.null(rv$plot)) { if (!is.null(rv$plot)) {
rv$plot rv$plot
} else { } else {
return(NULL) # Create a placeholder plot with instructions using ggplot2
ggplot2::ggplot() +
ggplot2::annotate(
"text",
x = 0.5,
y = 0.5,
label = i18n$t("Select variables and plot type,\nthen click 'Plot' to generate visualization"),
size = 5,
color = "gray50",
lineheight = 0.8
) +
ggplot2::xlim(0, 1) +
ggplot2::ylim(0, 1) +
ggplot2::theme_void() +
ggplot2::theme(
panel.background = ggplot2::element_rect(fill = "white"),
plot.background = ggplot2::element_rect(fill = "white")
)
# return(NULL)
} }
}) })
@ -337,492 +425,3 @@ data_visuals_server <- function(id,
} }
) )
} }
#' Select all from vector but
#'
#' @param data vector
#' @param ... exclude
#'
#' @returns vector
#' @export
#'
#' @examples
#' all_but(1:10, c(2, 3), 11, 5)
all_but <- function(data, ...) {
data[!data %in% c(...)]
}
#' Easily subset by data type function
#'
#' @param data data
#' @param types desired types
#' @param type.fun function to get type. Default is outcome_type
#'
#' @returns vector
#' @export
#'
#' @examples
#' default_parsing(mtcars) |> subset_types("ordinal")
#' default_parsing(mtcars) |> subset_types(c("dichotomous", "categorical"))
#' #' default_parsing(mtcars) |> subset_types("factor",class)
subset_types <- function(data, types, type.fun = data_type) {
data[sapply(data, type.fun) %in% types]
}
#' Implemented functions
#'
#' @description
#' Library of supported functions. The list name and "descr" element should be
#' unique for each element on list.
#'
#' - descr: Plot description
#'
#' - primary.type: Primary variable data type (continuous, dichotomous or ordinal)
#'
#' - secondary.type: Secondary variable data type (continuous, dichotomous or ordinal)
#'
#' - secondary.extra: "none" or NULL to have option to choose none.
#'
#' - tertiary.type: Tertiary variable data type (continuous, dichotomous or ordinal)
#'
#'
#' @returns list
#' @export
#'
#' @examples
#' supported_plots() |> str()
supported_plots <- function() {
list(
plot_bar_rel = list(
fun = "plot_bar",
fun.args = list(style = "fill"),
descr = i18n$t("Stacked relative barplot"),
note = i18n$t(
"Create relative stacked barplots to show the distribution of categorical levels"
),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
),
plot_bar_abs = list(
fun = "plot_bar",
fun.args = list(style = "dodge"),
descr = i18n$t("Side-by-side barplot"),
note = i18n$t(
"Create side-by-side barplot to show the distribution of categorical levels"
),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_hbars = list(
fun = "plot_hbars",
descr = i18n$t("Stacked horizontal bars"),
note = i18n$t(
"A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars"
),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_violin = list(
fun = "plot_violin",
descr = i18n$t("Violin plot"),
note = i18n$t(
"A modern alternative to the classic boxplot to visualise data distribution"
),
primary.type = c("datatime", "continuous"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
secondary.extra = "none",
tertiary.type = c("dichotomous", "categorical")
),
# plot_ridge = list(
# descr = "Ridge plot",
# note = "An alternative option to visualise data distribution",
# primary.type = "continuous",
# secondary.type = c("dichotomous" ,"categorical"),
# tertiary.type = c("dichotomous" ,"categorical"),
# secondary.extra = NULL
# ),
plot_sankey = list(
fun = "plot_sankey",
descr = i18n$t("Sankey plot"),
note = i18n$t("A way of visualising change between groups"),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
secondary.extra = NULL,
tertiary.type = c("dichotomous", "categorical")
),
plot_scatter = list(
fun = "plot_scatter",
descr = i18n$t("Scatter plot"),
note = i18n$t("A classic way of showing the association between to variables"),
primary.type = c("datatime", "continuous"),
secondary.type = c("datatime", "continuous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
),
plot_box = list(
fun = "plot_box",
descr = i18n$t("Box plot"),
note = i18n$t("A classic way to plot data distribution by groups"),
primary.type = c("datatime", "continuous"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_euler = list(
fun = "plot_euler",
descr = i18n$t("Euler diagram"),
note = i18n$t(
"Generate area-proportional Euler diagrams to display set relationships"
),
primary.type = c("dichotomous"),
secondary.type = c("dichotomous"),
secondary.multi = TRUE,
secondary.max = 4,
tertiary.type = c("dichotomous"),
secondary.extra = NULL
),
plot_euler = list(
fun = "plot_likert",
descr = i18n$t("Likert diagram"),
note = i18n$t(
"Plot survey results"
),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = TRUE,
secondary.extra = NULL,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
)
)
}
#' Get possible regression models
#'
#' @param data data
#'
#' @returns character vector
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' dplyr::pull("cyl") |>
#' possible_plots()
#'
#' mtcars |>
#' default_parsing() |>
#' dplyr::select("mpg") |>
#' possible_plots()
possible_plots <- function(data) {
# browser()
# data <- if (is.reactive(data)) data() else data
if (is.data.frame(data)) {
data <- data[[1]]
}
type <- data_type(data)
if (type == "unknown") {
out <- type
} else {
out <- supported_plots() |>
lapply(\(.x) {
if (type %in% .x$primary.type) {
.x$descr
}
}) |>
unlist()
}
unname(out)
}
#' Get the function options based on the selected function description
#'
#' @param data vector
#'
#' @returns list
#' @export
#'
#' @examples
#' ls <- mtcars |>
#' default_parsing() |>
#' dplyr::pull(mpg) |>
#' possible_plots() |>
#' (\(.x){
#' .x[[1]]
#' })() |>
#' get_plot_options()
get_plot_options <- function(data) {
descrs <- supported_plots() |>
lapply(\(.x) {
.x$descr
}) |>
unlist()
supported_plots() |>
(\(.x) {
.x[match(data, descrs)]
})()
}
#' Wrapper to create plot based on provided type
#'
#' @param data data.frame
#' @param pri primary variable
#' @param sec secondary variable
#' @param ter tertiary variable
#' @param type plot type (derived from possible_plots() and matches custom function)
#' @param color.palette choose color palette. See \code{\link{plot_colors}} for support.
#' @param ... ignored for now
#'
#' @name data-plots
#'
#' @returns ggplot2 object
#' @export
#'
#' @examples
#' create_plot(mtcars, "plot_violin", "mpg", "cyl") |> attributes()
create_plot <- function(data,
type,
pri,
sec,
ter = NULL,
color.palette = "viridis",
...) {
if (!is.null(sec)) {
if (!any(sec %in% names(data))) {
sec <- NULL
}
}
if (!is.null(ter)) {
if (!ter %in% names(data)) {
ter <- NULL
}
}
parameters <- list(
pri = pri,
sec = sec,
ter = ter,
color.palette = color.palette,
...
)
out <- do.call(type, modifyList(parameters, list(data = data)))
code <- rlang::call2(type, !!!parameters, .ns = "FreesearchR")
attr(out, "code") <- code
out
}
#' Print label, and if missing print variable name for plots
#'
#' @param data vector or data frame
#' @param var variable name. Optional.
#'
#' @returns character string
#' @export
#'
#' @examples
#' mtcars |> get_label(var = "mpg")
#' mtcars |> get_label()
#' mtcars$mpg |> get_label()
#' gtsummary::trial |> get_label(var = "trt")
#' gtsummary::trial$trt |> get_label()
#' 1:10 |> get_label()
get_label <- function(data, var = NULL) {
# data <- if (is.reactive(data)) data() else data
if (!is.null(var) & is.data.frame(data)) {
data <- data[[var]]
}
out <- REDCapCAST::get_attr(data = data, attr = "label")
if (is.na(out)) {
if (is.null(var)) {
out <- deparse(substitute(data))
} else {
if (is.symbol(var)) {
out <- gsub('\"', "", deparse(substitute(var)))
} else {
out <- var
}
}
}
out
}
#' Line breaking at given number of characters for nicely plotting labels
#'
#' @param data string
#' @param lineLength maximum line length
#' @param fixed flag to force split at exactly the value given in lineLength.
#' Default is FALSE, only splitting at spaces.
#'
#' @returns character string
#' @export
#'
#' @examples
#' "Lorem ipsum... you know the routine" |> line_break()
#' paste(sample(letters[1:10], 100, TRUE), collapse = "") |> line_break(force = TRUE)
line_break <- function(data,
lineLength = 20,
force = FALSE) {
if (isTRUE(force)) {
## This eats some letters when splitting a sentence... ??
gsub(paste0("(.{1,", lineLength, "})(\\s|[[:alnum:]])"),
"\\1\n",
data)
} else {
paste(strwrap(data, lineLength), collapse = "\n")
}
## https://stackoverflow.com/a/29847221
}
#' Wrapping
#'
#' @param data list of ggplot2 objects
#' @param tag_levels passed to patchwork::plot_annotation if given. Default is NULL
#' @param title panel title
#' @param guides passed to patchwork::wrap_plots()
#' @param axes passed to patchwork::wrap_plots()
#' @param axis_titles passed to patchwork::wrap_plots()
#' @param ... passed to patchwork::wrap_plots()
#'
#' @returns list of ggplot2 objects
#' @export
#'
wrap_plot_list <- function(data,
tag_levels = NULL,
title = NULL,
axis.font.family = NULL,
guides = "collect",
axes = "collect",
axis_titles = "collect",
...) {
if (ggplot2::is_ggplot(data[[1]])) {
if (length(data) > 1) {
out <- data |>
(\(.x) {
if (rlang::is_named(.x)) {
purrr::imap(.x, \(.y, .i) {
.y + ggplot2::ggtitle(.i)
})
} else {
.x
}
})() |>
align_axes() |>
patchwork::wrap_plots(guides = guides,
axes = axes,
axis_titles = axis_titles,
...)
if (!is.null(tag_levels)) {
out <- out + patchwork::plot_annotation(tag_levels = tag_levels)
}
if (!is.null(title)) {
out <- out +
patchwork::plot_annotation(
title = title,
theme = ggplot2::theme(plot.title = ggplot2::element_text(size = 25))
)
}
} else {
out <- data[[1]]
}
} else {
cli::cli_abort("Can only wrap lists of {.cls ggplot} objects")
}
if (!is.null(axis.font.family)) {
if (inherits(x = out, what = "patchwork")) {
out <- out &
ggplot2::theme(axis.text = ggplot2::element_text(family = axis.font.family))
} else {
out <- out +
ggplot2::theme(axis.text = ggplot2::element_text(family = axis.font.family))
}
}
out
}
#' Aligns axes between plots
#'
#' @param ... ggplot2 objects or list of ggplot2 objects
#'
#' @returns list of ggplot2 objects
#' @export
#'
align_axes <- function(...,
x.axis = TRUE,
y.axis = TRUE) {
# 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)) {
## Assumes list of ggplots
p <- list(...)
} else if (is.list(..1)) {
## Assumes list with list of ggplots
p <- ..1
} else {
cli::cli_abort("Can only align {.cls ggplot} objects or a list of them")
}
yr <- clean_common_axis(p, "y")
xr <- clean_common_axis(p, "x")
suppressWarnings({
purrr::map(p, \(.x) {
out <- .x
if (isTRUE(x.axis)) {
out <- out + ggplot2::xlim(xr)
}
if (isTRUE(y.axis)) {
out <- out + ggplot2::ylim(yr)
}
out
})
})
}
#' Extract and clean axis ranges
#'
#' @param p plot
#' @param axis axis. x or y.
#'
#' @returns vector
#' @export
#'
clean_common_axis <- function(p, axis) {
purrr::map(p, ~ ggplot2::layer_scales(.x)[[axis]]$get_limits()) |>
unlist() |>
(\(.x) {
if (is.numeric(.x)) {
range(.x)
} else {
as.character(.x)
}
})() |>
unique()
}

View file

@ -56,38 +56,25 @@
#' #'
#' @export #' @export
generate_colors <- function(n, palette = "viridis", ...) { generate_colors <- function(n, palette = "viridis", ...) {
if (!is.numeric(n) ||
length(n) != 1 || n < 1 || n != as.integer(n)) { # --- Input validation -------------------------------------------------------
if (!is.numeric(n) || length(n) != 1 || n < 1 || n %% 1 != 0) {
stop("`n` must be a single positive integer.") stop("`n` must be a single positive integer.")
} }
if (!is.function(palette) && (!is.character(palette) || length(palette) != 1)) {
stop("`palette` must be a single character string or a function.")
}
# Function passthrough — call directly with n and ... # --- Function passthrough ---------------------------------------------------
if (is.function(palette)) { if (is.function(palette)) {
return(palette(n, ...)) return(palette(n, ...))
} }
if (!is.character(palette) || length(palette) != 1) { # --- Named palette dispatch -------------------------------------------------
stop("`palette` must be a single character string or a function.")
}
if (!is.numeric(n) ||
length(n) != 1 || n < 1 || n != as.integer(n)) {
stop("`n` must be a single positive integer.")
}
if (!is.character(palette) || length(palette) != 1) {
stop("`palette` must be a single character string.")
}
palette_lower <- tolower(palette) palette_lower <- tolower(palette)
viridis_palettes <- c("viridis", viridis_palettes <- c("viridis", "magma", "plasma", "inferno",
"magma", "cividis", "mako", "rocket", "turbo")
"plasma",
"inferno",
"cividis",
"mako",
"rocket",
"turbo")
if (palette_lower %in% viridis_palettes) { if (palette_lower %in% viridis_palettes) {
viridisLite::viridis(n = n, option = palette_lower, ...) viridisLite::viridis(n = n, option = palette_lower, ...)
@ -107,25 +94,32 @@ generate_colors <- function(n, palette = "viridis", ...) {
} else if (palette_lower == "topo") { } else if (palette_lower == "topo") {
grDevices::topo.colors(n = n, ...) grDevices::topo.colors(n = n, ...)
} else if (palette %in% rownames(RColorBrewer::brewer.pal.info)) { } else {
max_n <- RColorBrewer::brewer.pal.info[palette, "maxcolors"] # Case-insensitive RColorBrewer lookup
fetch_n <- max(min(n, max_n), 3L) # clamp to [3, max_n] for brewer.pal() brewer_names <- rownames(RColorBrewer::brewer.pal.info)
base_colors <- RColorBrewer::brewer.pal(n = fetch_n, name = palette) brewer_match <- brewer_names[match(palette_lower, tolower(brewer_names))]
if (!is.na(brewer_match)) {
max_n <- RColorBrewer::brewer.pal.info[brewer_match, "maxcolors"]
fetch_n <- max(min(n, max_n), 3L)
base_colors <- RColorBrewer::brewer.pal(n = fetch_n, name = brewer_match)
grDevices::colorRampPalette(base_colors)(n) grDevices::colorRampPalette(base_colors)(n)
} else if (palette %in% grDevices::palette.pals()) { } else {
grDevices::colorRampPalette(palette.colors(palette = palette))(n) # Case-insensitive grDevices palette.pals() lookup
pal_names <- grDevices::palette.pals()
pal_match <- pal_names[match(palette_lower, tolower(pal_names))]
if (!is.na(pal_match)) {
grDevices::colorRampPalette(grDevices::palette.colors(palette = pal_match))(n)
} else if (palette %in% grDevices::hcl.pals()) { } else if (palette %in% grDevices::hcl.pals()) {
# Named HCL palettes (e.g. "Rocket", "Plasma") — distinct from viridisLite
grDevices::hcl.colors(n = n, palette = palette, ...) grDevices::hcl.colors(n = n, palette = palette, ...)
} else { } else {
message( warning(
paste0( "Unknown palette: '", palette, "'. Falling back to viridis.\n",
"Unknown palette: '",
palette,
"'. ",
"Falling back to default R colors.\n",
"Available options:\n", "Available options:\n",
" viridisLite : viridis, magma, plasma, inferno, cividis, mako, rocket, turbo\n", " viridisLite : viridis, magma, plasma, inferno, cividis, mako, rocket, turbo\n",
" grDevices : hcl, rainbow, heat, terrain, topo\n", " grDevices : hcl, rainbow, heat, terrain, topo\n",
@ -133,9 +127,9 @@ generate_colors <- function(n, palette = "viridis", ...) {
" grDevices : use grDevices::palette.pals() to see all options\n", " grDevices : use grDevices::palette.pals() to see all options\n",
" RColorBrewer : use RColorBrewer::brewer.pal.info to see all options" " RColorBrewer : use RColorBrewer::brewer.pal.info to see all options"
) )
)
viridisLite::viridis(n = n, option = "viridis") viridisLite::viridis(n = n, option = "viridis")
# grDevices::hcl.colors(n = n) }
}
} }
} }
@ -254,12 +248,12 @@ color_choices <- function() {
"Perceptual (blue-yellow)" = "viridis", "Perceptual (blue-yellow)" = "viridis",
"Perceptual (fire)" = "plasma", "Perceptual (fire)" = "plasma",
"Colour-blind friendly" = "Okabe-Ito", "Colour-blind friendly" = "Okabe-Ito",
"Qualitative (bold)" = "Dark 2", "Diverging (red-yellow-green)"= "RdYlGn",
"Qualitative (paired)" = "Paired",
"Sequential (blues)" = "Blues",
"Diverging (red-blue)" = "RdBu", "Diverging (red-blue)" = "RdBu",
"Tableau style" = "Tableau 10", "Sequential (blues)" = "Blues",
"Pastel" = "Pastel 1", "Qualitative (paired)" = "Paired",
"Rainbow" = "rainbow" "Qualitative (bold)" = "Dark 2",
"Rainbow" = "Spectral",
"Generic" = "Set1"
) )
} }

View file

@ -1 +1 @@
hosted_version <- function()'v26.3.6-260331' hosted_version <- function()'v26.6.1'

View file

@ -714,7 +714,7 @@ make_success_alert <- function(data,
i18n$t("Data ready to be imported!") i18n$t("Data ready to be imported!")
), ),
sprintf( sprintf(
i18n$t("Data has %s obs. of %s variables."), i18n$t("The data set has %s obs. in %s variables."),
nrow(data), nrow(data),
ncol(data) ncol(data)
), ),
@ -725,7 +725,7 @@ make_success_alert <- function(data,
i18n$t("Data successfully imported!") i18n$t("Data successfully imported!")
), ),
sprintf( sprintf(
i18n$t("Data has %s obs. of %s variables."), i18n$t("The data set has %s obs. in %s variables."),
nrow(data), nrow(data),
ncol(data) ncol(data)
), ),

View file

@ -37,20 +37,6 @@ landing_page_ui <- function(i18n) {
div( div(
class = "container my-5", class = "container my-5",
# Introduction text
# div(
# class = "row mb-5",
# div(
# class = "col-12 text-center",
# p(
# class = "lead",
# i18n$t("Start with FreesearchR for basic data evaluation and analysis."),
# i18n$t("When you need more advanced tools, you'll be better prepared to use R directly."),
# style = "font-size: 1.2rem; color: #555;"
# )
# )
# ),
# Core Features Section # Core Features Section
h2(i18n$t("Core Features"), class = "text-center mb-4", h2(i18n$t("Core Features"), class = "text-center mb-4",
style = "color: #1E4A8F; font-weight: 600;"), style = "color: #1E4A8F; font-weight: 600;"),
@ -68,7 +54,8 @@ landing_page_ui <- function(i18n) {
class = "card-body text-center p-4", class = "card-body text-center p-4",
div( div(
style = "font-size: 3rem; color: #1E4A8F; margin-bottom: 15px;", style = "font-size: 3rem; color: #1E4A8F; margin-bottom: 15px;",
fa("file-import") phosphoricons::ph("folder-simple-plus", weight = "bold")
# fa("file-import")
), ),
h4(i18n$t("Import Data"), class = "card-title", style = "color: #2D2D42; font-weight: 600;"), h4(i18n$t("Import Data"), class = "card-title", style = "color: #2D2D42; font-weight: 600;"),
p( p(
@ -89,7 +76,8 @@ landing_page_ui <- function(i18n) {
class = "card-body text-center p-4", class = "card-body text-center p-4",
div( div(
style = "font-size: 3rem; color: #1E4A8F; margin-bottom: 15px;", style = "font-size: 3rem; color: #1E4A8F; margin-bottom: 15px;",
fa("pen-to-square") phosphoricons::ph("note-pencil", weight = "bold")
# fa("pen-to-square")
), ),
h4(i18n$t("Data Management"), class = "card-title", style = "color: #2D2D42; font-weight: 600;"), h4(i18n$t("Data Management"), class = "card-title", style = "color: #2D2D42; font-weight: 600;"),
p( p(
@ -110,7 +98,8 @@ landing_page_ui <- function(i18n) {
class = "card-body text-center p-4", class = "card-body text-center p-4",
div( div(
style = "font-size: 3rem; color: #1E4A8F; margin-bottom: 15px;", style = "font-size: 3rem; color: #1E4A8F; margin-bottom: 15px;",
fa("magnifying-glass-chart") phosphoricons::ph("magnifying-glass", weight = "bold")
# fa("magnifying-glass-chart")
), ),
h4(i18n$t("Descriptive Statistics"), class = "card-title", style = "color: #2D2D42; font-weight: 600;"), h4(i18n$t("Descriptive Statistics"), class = "card-title", style = "color: #2D2D42; font-weight: 600;"),
p( p(
@ -135,7 +124,7 @@ landing_page_ui <- function(i18n) {
style = "border-left: 4px solid #8A4FFF;", style = "border-left: 4px solid #8A4FFF;",
div( div(
class = "card-body", class = "card-body",
h5(fa("chart-line"), " ", i18n$t("Data Visualization"), class = "card-title", style = "color: #2D2D42;"), h5(phosphoricons::ph("chart-line", weight = "bold"), " ", i18n$t("Data Visualization"), class = "card-title", style = "color: #2D2D42;"),
p(class = "card-text small", i18n$t("Create simple, clean plots for quick insights and overview")) p(class = "card-text small", i18n$t("Create simple, clean plots for quick insights and overview"))
) )
) )
@ -147,7 +136,7 @@ landing_page_ui <- function(i18n) {
style = "border-left: 4px solid #8A4FFF;", style = "border-left: 4px solid #8A4FFF;",
div( div(
class = "card-body", class = "card-body",
h5(fa("calculator"), " ", i18n$t("Regression Models"), class = "card-title", style = "color: #2D2D42;"), h5(phosphoricons::ph("calculator", weight = "bold"), " ", i18n$t("Regression Models"), class = "card-title", style = "color: #2D2D42;"),
p(class = "card-text small", i18n$t("Build simple regression models for advanced analysis")) p(class = "card-text small", i18n$t("Build simple regression models for advanced analysis"))
) )
) )
@ -164,7 +153,7 @@ landing_page_ui <- function(i18n) {
style = "background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%); border: none;", style = "background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%); border: none;",
div( div(
class = "card-body p-4", class = "card-body p-4",
h4(fa("download"), " ", i18n$t("Export & Learn"), class = "text-center mb-3", style = "color: #1E4A8F;"), h4(phosphoricons::ph("book-bookmark", weight = "bold"), " ", i18n$t("Export & Learn"), class = "text-center mb-3", style = "color: #1E4A8F;"),
div( div(
class = "row text-center", class = "row text-center",
div( div(

View file

@ -19,7 +19,8 @@ data_missings_ui <- function(id, ...) {
bslib::accordion_panel( bslib::accordion_panel(
value = "acc_pan_mis", value = "acc_pan_mis",
title = "Settings", title = "Settings",
icon = bsicons::bs_icon("gear"), icon = phosphoricons::ph("gear"),
# icon = bsicons::bs_icon("gear"),
shiny::conditionalPanel( shiny::conditionalPanel(
condition = "output.missings == true", condition = "output.missings == true",
shiny::uiOutput(ns("missings_method")), shiny::uiOutput(ns("missings_method")),
@ -36,14 +37,16 @@ data_missings_ui <- function(id, ...) {
inputId = ns("act_miss"), inputId = ns("act_miss"),
label = i18n$t("Evaluate"), label = i18n$t("Evaluate"),
width = "100%", width = "100%",
icon = shiny::icon("calculator"), icon = phosphoricons::ph("calculator",weight = "bold"),
# icon = shiny::icon("calculator"),
disabled = TRUE disabled = TRUE
) )
), ),
do.call(bslib::accordion_panel, c( do.call(bslib::accordion_panel, c(
list( list(
title = "Download", title = "Download",
icon = bsicons::bs_icon("file-earmark-arrow-down") icon = phosphoricons::ph("download-simple")
# icon = bsicons::bs_icon("file-earmark-arrow-down")
), ),
table_download_ui(id = ns("tbl_dwn"), title = NULL) table_download_ui(id = ns("tbl_dwn"), title = NULL)
)) ))

View file

@ -39,7 +39,8 @@ plot_download_ui <- regression_ui <- function(id, ...) {
shiny::downloadButton( shiny::downloadButton(
outputId = ns("download_plot"), outputId = ns("download_plot"),
label = "Download plot", label = "Download plot",
icon = shiny::icon("download") icon = phosphoricons::ph("arrow-fat-down")
# icon = shiny::icon("download")
) )
) )
} }

878
R/plot-helpers.R Normal file
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@ -0,0 +1,878 @@
#' Implemented functions
#'
#' @description
#' Library of supported functions. The list name and "descr" element should be
#' unique for each element on list.
#'
#' - fun: the plotting function
#'
#' - fun.args: default parameters for the plotting function
#'
#' - descr: Plot description
#'
#' - note: Short note/description of the function for displaying in ui and docs
#'
#' - primary.type: Primary variable data type (see [data_type])
#'
#' - base: holds a list of parameters for plot input fields generation
#' Secondary and tertiary variable input fields are mandatory.
#'
#'
#' @returns list
#' @export
#'
#' @examples
#' available_plots() |> str()
available_plots <- function() {
list(
plot_bar_rel = list(
fun = "plot_bar",
fun.args = list(style = "fill"),
descr = i18n$t("Stacked relative barplot"),
note = i18n$t(
"Create relative stacked barplots to show the distribution of categorical levels"
),
primary.type = c("dichotomous", "categorical"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
allow_none = FALSE,
# inputId = "sec",
label = i18n$t("Additional variable"),
multiple = FALSE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
),
plot_bar_abs = list(
fun = "plot_bar",
fun.args = list(style = "dodge"),
descr = i18n$t("Side-by-side barplot"),
note = i18n$t(
"Create side-by-side barplot to show the distribution of categorical levels"
),
primary.type = c("dichotomous", "categorical"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
allow_none = TRUE,
# inputId = "sec",
label = i18n$t("Secondary variable"),
multiple = FALSE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
),
plot_hbars = list(
fun = "plot_hbars",
descr = i18n$t("Stacked horizontal bars"),
note = i18n$t(
"A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars"
),
primary.type = c("dichotomous", "categorical"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
allow_none = TRUE,
# inputId = "sec",
label = i18n$t("Secondary variable"),
multiple = FALSE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
),
list(
id = "reverse",
type = "select_input",
label = i18n$t("Reverse colors"),
choices = c(yes = TRUE, no = FALSE)
)
),
advanced = list()
#########
),
plot_violin = list(
fun = "plot_violin",
descr = i18n$t("Violin plot"),
note = i18n$t(
"A modern alternative to the classic boxplot to visualise data distribution"
),
primary.type = c("datatime", "continuous"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
allow_none = TRUE,
# inputId = "sec",
label = i18n$t("Secondary variable"),
multiple = FALSE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
),
plot_sankey = list(
fun = "plot_sankey",
descr = i18n$t("Sankey plot"),
note = i18n$t("A way of visualising change between groups"),
primary.type = c("dichotomous", "categorical"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
allow_none = FALSE,
# inputId = "sec",
label = i18n$t("Secondary variable"),
multiple = FALSE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
),
plot_scatter = list(
fun = "plot_scatter",
descr = i18n$t("Scatter plot"),
note = i18n$t("A classic way of showing the association between to variables"),
primary.type = c("datatime", "continuous"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("datatime", "continuous", "categorical"),
allow_none = FALSE,
# inputId = "sec",
label = i18n$t("Secondary variable"),
multiple = FALSE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
),
plot_box = list(
fun = "plot_box",
descr = i18n$t("Box plot"),
note = i18n$t("A classic way to plot data distribution by groups"),
primary.type = c("datatime", "continuous"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
allow_none = TRUE,
# inputId = "sec",
label = i18n$t("Secondary variable"),
multiple = FALSE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
),
plot_euler = list(
fun = "plot_euler",
descr = i18n$t("Euler diagram"),
note = i18n$t(
"Generate area-proportional Euler diagrams to display set relationships"
),
primary.type = c("dichotomous"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous"),
allow_none = FALSE,
# inputId = "sec",
label = i18n$t("Secondary variable"),
multiple = TRUE,
maxItems = 4
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
),
plot_likert = list(
fun = "plot_likert",
descr = i18n$t("Likert diagram"),
note = i18n$t("Plot survey results"),
primary.type = c("dichotomous", "categorical"),
### Input definitions ###
base = list(
list(
id = "secondary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
allow_none = TRUE,
# inputId = "sec",
label = i18n$t("Additional variables"),
multiple = TRUE
),
list(
id = "tertiary",
type = "select_variables",
var_types = c("dichotomous", "categorical"),
# inputId = "sec",
label = i18n$t("Grouping variable"),
multiple = FALSE
)
),
advanced = list()
#########
)
)
}
# Helper function to create input elements dynamically
create_input_element <- function(params, ns, input_id) {
# Add the namespaced inputId to the arguments
params$inputId <- ns(input_id)
# Map input types to Shiny functions
input_function <- switch(
params$type,
"numeric_input" = shiny::numericInput,
"select_input" = shiny::selectInput,
"checkbox_input" = shiny::checkboxInput,
"slider_input" = shiny::sliderInput,
"text_input" = shiny::textInput,
"select_variables" = selectPlotVariables
)
params$type <- NULL
params$id <- NULL
# Call the function with all arguments
do.call(input_function, params)
}
#' Wrapper for columnSelectInput
#'
selectPlotVariables <- function(data,
exclude = NULL,
allow_none = TRUE,
var_types,
...) {
datar <- if (is.reactive(data)) {
data
} else {
reactive(data)
}
cols <- all_but(colnames(subset_types(datar(), var_types)), exclude)
if (isTRUE(allow_none)) {
cols <- c("none", cols)
}
params <- list(...)
params$none_label <- i18n$t("No variable")
params$col_subset <- cols
rlang::exec(columnSelectInput, !!!append_list(datar(), params, "data"))
}
#' Select all from vector but
#'
#' @param data vector
#' @param ... exclude
#'
#' @returns vector
#' @export
#'
#' @examples
#' all_but(1:10, c(2, 3), 11, 5)
all_but <- function(data, ...) {
data[!data %in% c(...)]
}
#' Easily subset by data type function
#'
#' @param data data
#' @param types desired types
#' @param type.fun function to get type. Default is outcome_type
#'
#' @returns vector
#' @export
#'
#' @examples
#' default_parsing(mtcars) |> subset_types("ordinal")
#' default_parsing(mtcars) |> subset_types(c("dichotomous", "categorical"))
#' #' default_parsing(mtcars) |> subset_types("factor",class)
subset_types <- function(data, types, type.fun = data_type) {
data[sapply(data, type.fun) %in% types]
}
#' Implemented functions
#'
#' @description
#' Library of supported functions. The list name and "descr" element should be
#' unique for each element on list.
#'
#' - descr: Plot description
#'
#' - primary.type: Primary variable data type (continuous, dichotomous or ordinal)
#'
#' - secondary.type: Secondary variable data type (continuous, dichotomous or ordinal)
#'
#' - secondary.extra: "none" or NULL to have option to choose none.
#'
#' - tertiary.type: Tertiary variable data type (continuous, dichotomous or ordinal)
#'
#'
#' @returns list
#' @export
#'
#' @examples
#' supported_plots() |> str()
supported_plots <- function() {
list(
plot_bar_rel = list(
fun = "plot_bar",
fun.args = list(style = "fill"),
descr = i18n$t("Stacked relative barplot"),
note = i18n$t(
"Create relative stacked barplots to show the distribution of categorical levels"
),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
),
plot_bar_abs = list(
fun = "plot_bar",
fun.args = list(style = "dodge"),
descr = i18n$t("Side-by-side barplot"),
note = i18n$t(
"Create side-by-side barplot to show the distribution of categorical levels"
),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_hbars = list(
fun = "plot_hbars",
descr = i18n$t("Stacked horizontal bars"),
note = i18n$t(
"A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars"
),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_violin = list(
fun = "plot_violin",
descr = i18n$t("Violin plot"),
note = i18n$t(
"A modern alternative to the classic boxplot to visualise data distribution"
),
primary.type = c("datatime", "continuous"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
secondary.extra = "none",
tertiary.type = c("dichotomous", "categorical")
),
# plot_ridge = list(
# descr = "Ridge plot",
# note = "An alternative option to visualise data distribution",
# primary.type = "continuous",
# secondary.type = c("dichotomous" ,"categorical"),
# tertiary.type = c("dichotomous" ,"categorical"),
# secondary.extra = NULL
# ),
plot_sankey = list(
fun = "plot_sankey",
descr = i18n$t("Sankey plot"),
note = i18n$t("A way of visualising change between groups"),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
secondary.extra = NULL,
tertiary.type = c("dichotomous", "categorical")
),
plot_scatter = list(
fun = "plot_scatter",
descr = i18n$t("Scatter plot"),
note = i18n$t("A classic way of showing the association between to variables"),
primary.type = c("datatime", "continuous"),
secondary.type = c("datatime", "continuous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
),
plot_box = list(
fun = "plot_box",
descr = i18n$t("Box plot"),
note = i18n$t("A classic way to plot data distribution by groups"),
primary.type = c("datatime", "continuous"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = FALSE,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = "none"
),
plot_euler = list(
fun = "plot_euler",
descr = i18n$t("Euler diagram"),
note = i18n$t(
"Generate area-proportional Euler diagrams to display set relationships"
),
primary.type = c("dichotomous"),
secondary.type = c("dichotomous"),
secondary.multi = TRUE,
secondary.max = 4,
tertiary.type = c("dichotomous"),
secondary.extra = NULL
),
plot_likert = list(
fun = "plot_likert",
descr = i18n$t("Likert diagram"),
note = i18n$t("Plot survey results"),
primary.type = c("dichotomous", "categorical"),
secondary.type = c("dichotomous", "categorical"),
secondary.multi = TRUE,
secondary.extra = NULL,
tertiary.type = c("dichotomous", "categorical"),
secondary.extra = NULL
)
)
}
#' Get possible regression models
#'
#' @param data data
#'
#' @returns character vector
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' dplyr::pull("cyl") |>
#' possible_plots()
#'
#' mtcars |>
#' default_parsing() |>
#' dplyr::select("mpg") |>
#' possible_plots()
possible_plots <- function(data, source_list = supported_plots()) {
# browser()
# data <- if (is.reactive(data)) data() else data
if (is.data.frame(data)) {
data <- data[[1]]
}
type <- data_type(data)
if (type == "unknown") {
out <- type
} else {
out <- source_list |>
lapply(\(.x) {
if (type %in% .x$primary.type) {
.x$descr
}
}) |>
unlist()
}
unname(out)
}
#' Get the function options based on the selected function description
#'
#' @param data vector
#'
#' @returns list
#' @export
#'
#' @examples
#' ls <- mtcars |>
#' default_parsing() |>
#' dplyr::pull(mpg) |>
#' possible_plots() |>
#' (\(.x){
#' .x[[1]]
#' })() |>
#' get_plot_options()
get_plot_options <- function(data) {
descrs <- supported_plots() |>
lapply(\(.x) {
.x$descr
}) |>
unlist()
supported_plots() |>
(\(.x) {
.x[match(data, descrs)]
})()
}
#' Get the function parameters based on the selected function description
#'
#' @param data vector
#'
#' @returns list
#' @export
#'
#' @examples
#' ls <- mtcars |>
#' default_parsing() |>
#' dplyr::pull(mpg) |>
#' possible_plots() |>
#' (\(.x){
#' .x[[1]]
#' })() |>
#' get_input_params()
get_input_params <- function(data) {
descr <- available_plots() |>
lapply(\(.x) {
.x$descr
}) |>
unlist()
available_plots() |>
(\(.x) {
.x[match(data, descr)]
})()
}
#' Wrapper to create plot based on provided type
#'
#' @param data data.frame
#' @param pri primary variable
#' @param sec secondary variable
#' @param ter tertiary variable
#' @param type plot type (derived from possible_plots() and matches custom function)
#' @param color.palette choose color palette. See \code{\link{plot_colors}} for support.
#' @param ... ignored for now
#'
#' @name data-plots
#'
#' @returns ggplot2 object
#' @export
#'
#' @examples
#' create_plot(mtcars, "plot_violin", "mpg", "cyl") |> attributes()
create_plot <- function(data,
type,
pri,
sec,
ter = NULL,
color.palette = "viridis",
...) {
if (!is.null(sec)) {
if (!any(sec %in% names(data))) {
sec <- NULL
}
}
if (!is.null(ter)) {
if (!ter %in% names(data)) {
ter <- NULL
}
}
parameters <- list(
pri = pri,
sec = sec,
ter = ter,
color.palette = color.palette,
...
)
out <- do.call(type, modifyList(parameters, list(data = data)))
code <- rlang::call2(type, !!!parameters, .ns = "FreesearchR")
attr(out, "code") <- code
out
}
#' Print label, and if missing print variable name for plots
#'
#' @param data vector or data frame
#' @param var variable name. Optional.
#'
#' @returns character string
#' @export
#'
#' @examples
#' mtcars |> get_label(var = "mpg")
#' mtcars |> get_label()
#' mtcars$mpg |> get_label()
#' gtsummary::trial |> get_label(var = "trt")
#' gtsummary::trial$trt |> get_label()
#' 1:10 |> get_label()
get_label <- function(data, var = NULL) {
# data <- if (is.reactive(data)) data() else data
if (!is.null(var) & is.data.frame(data)) {
data <- data[[var]]
}
out <- REDCapCAST::get_attr(data = data, attr = "label")
if (is.na(out)) {
if (is.null(var)) {
out <- deparse(substitute(data))
} else {
if (is.symbol(var)) {
out <- gsub('\"', "", deparse(substitute(var)))
} else {
out <- var
}
}
}
out
}
#' Line breaking at given number of characters for nicely plotting labels
#'
#' @param data string
#' @param lineLength maximum line length
#' @param fixed flag to force split at exactly the value given in lineLength.
#' Default is FALSE, only splitting at spaces.
#'
#' @returns character string
#' @export
#'
#' @examples
#' "Lorem ipsum... you know the routine" |> line_break()
#' paste(sample(letters[1:10], 100, TRUE), collapse = "") |> line_break(force = TRUE)
line_break <- function(data,
lineLength = 20,
force = FALSE) {
if (isTRUE(force)) {
## This eats some letters when splitting a sentence... ??
gsub(paste0("(.{1,", lineLength, "})(\\s|[[:alnum:]])"),
"\\1\n",
data)
} else {
paste(strwrap(data, lineLength), collapse = "\n")
}
## https://stackoverflow.com/a/29847221
}
#' Wrapping
#'
#' @param data list of ggplot2 objects
#' @param tag_levels passed to patchwork::plot_annotation if given. Default is NULL
#' @param title panel title
#' @param guides passed to patchwork::wrap_plots()
#' @param axes passed to patchwork::wrap_plots()
#' @param axis_titles passed to patchwork::wrap_plots()
#' @param ... passed to patchwork::wrap_plots()
#'
#' @returns list of ggplot2 objects
#' @export
#'
wrap_plot_list <- function(data,
tag_levels = NULL,
title = NULL,
axis.font.family = NULL,
guides = "collect",
axes = "collect",
axis_titles = "collect",
y.axis.percentage = FALSE,
...) {
if (ggplot2::is_ggplot(data[[1]])) {
if (length(data) > 1) {
out <- data |>
(\(.x) {
if (rlang::is_named(.x)) {
purrr::imap(.x, \(.y, .i) {
.y + ggplot2::ggtitle(.i)
})
} else {
.x
}
})() |>
align_axes(percentage = y.axis.percentage) |>
patchwork::wrap_plots(guides = guides,
axes = axes,
axis_titles = axis_titles,
...)
if (!is.null(tag_levels)) {
out <- out + patchwork::plot_annotation(tag_levels = tag_levels)
}
if (!is.null(title)) {
out <- out +
patchwork::plot_annotation(
title = title,
theme = ggplot2::theme(plot.title = ggplot2::element_text(size = 25))
)
}
} else {
out <- data[[1]]
}
} else {
cli::cli_abort("Can only wrap lists of {.cls ggplot} objects")
}
if (!is.null(axis.font.family)) {
if (inherits(x = out, what = "patchwork")) {
out <- out &
ggplot2::theme(axis.text = ggplot2::element_text(family = axis.font.family))
} else {
out <- out +
ggplot2::theme(axis.text = ggplot2::element_text(family = axis.font.family))
}
}
out
}
#' Aligns axes between plots
#'
#' @param ... ggplot2 objects or list of ggplot2 objects
#'
#' @returns list of ggplot2 objects
#' @export
#'
align_axes <- function(...,
x.axis = TRUE,
y.axis = TRUE,
percentage = FALSE) {
# 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)) {
## Assumes list of ggplots
p <- list(...)
} else if (is.list(..1)) {
## Assumes list with list of ggplots
p <- ..1
} else {
cli::cli_abort("Can only align {.cls ggplot} objects or a list of them")
}
yr <- clean_common_axis(p, "y")
xr <- clean_common_axis(p, "x")
suppressWarnings({
p_out <- purrr::map(p, \(.x) {
out <- .x
if (isTRUE(x.axis)) {
out <- out + ggplot2::xlim(xr)
}
if (isTRUE(y.axis)) {
out <- out + ggplot2::ylim(yr)
}
out
})
})
if (isTRUE(percentage)) {
lapply(p_out, \(.x) {
.x +
ggplot2::scale_y_continuous(labels = scales::percent)
})
} else {
p_out
}
}
#' Extract and clean axis ranges
#'
#' @param p plot
#' @param axis axis. x or y.
#'
#' @returns vector
#' @export
#'
clean_common_axis <- function(p, axis) {
purrr::map(p, ~ ggplot2::layer_scales(.x)[[axis]]$get_limits()) |>
unlist() |>
(\(.x) {
if (is.numeric(.x)) {
range(.x)
} else {
as.character(.x)
}
})() |>
unique()
}

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@ -1,5 +1,29 @@
plot_bar <- function(data, pri, sec, ter = NULL, style = c("stack", "dodge", "fill"), #' Title
color.palette = "viridis", max_level = 30, ...) { #'
#' @name data-plots
#'
#' @param style barplot style passed to geom_bar position argument.
#' One of c("stack", "dodge", "fill")
#'
#' @returns ggplot list object
#' @export
#'
#' @examples
#' mtcars |>
#' dplyr::mutate(cyl = factor(cyl), am = factor(am)) |>
#' plot_bar(pri = "cyl", sec = "am", style = "fill")
#'
#' mtcars |>
#' dplyr::mutate(dplyr::across(tidyselect::all_of(c("cyl","am","gear")),factor)) |>
#' plot_bar(pri = "cyl", sec = "gear", ter = "am", style = "stack",color.palette="turbo")
plot_bar <- function(data,
pri,
sec = NULL,
ter = NULL,
style = c("stack", "dodge", "fill"),
color.palette = "viridis",
max_level = 30,
...) {
style <- match.arg(style) style <- match.arg(style)
if (!is.null(ter)) { if (!is.null(ter)) {
@ -8,18 +32,21 @@ plot_bar <- function(data, pri, sec, ter = NULL, style = c("stack", "dodge", "fi
ds <- list(data) ds <- list(data)
} }
out <- lapply(ds, \(.ds){ out <- lapply(ds, \(.ds) {
plot_bar_single( plot_bar_single(
data = .ds, data = .ds,
pri = pri, pri = pri,
sec = sec, sec = sec,
style = style, style = style,
max_level = max_level, max_level = max_level,
color.palette = color.palette color.palette = color.palette,
...
) )
}) })
wrap_plot_list(out, title = glue::glue(i18n$t("Grouped by {get_label(data,ter)}")), ...) wrap_plot_list(out,
title = glue::glue(i18n$t("Grouped by {get_label(data,ter)}")),
y.axis.percentage = TRUE)
} }
@ -41,7 +68,11 @@ plot_bar <- function(data, pri, sec, ter = NULL, style = c("stack", "dodge", "fi
#' mtcars |> #' mtcars |>
#' dplyr::mutate(cyl = factor(cyl), am = factor(am)) |> #' dplyr::mutate(cyl = factor(cyl), am = factor(am)) |>
#' plot_bar_single(pri = "cyl", style = "stack",color.palette="turbo") #' plot_bar_single(pri = "cyl", style = "stack",color.palette="turbo")
plot_bar_single <- function(data, pri, sec = NULL, style = c("stack", "dodge", "fill"), max_level = 30, plot_bar_single <- function(data,
pri,
sec = NULL,
style = c("stack", "dodge", "fill"),
max_level = 30,
color.palette = "viridis") { color.palette = "viridis") {
style <- match.arg(style) style <- match.arg(style)
@ -51,16 +82,11 @@ plot_bar_single <- function(data, pri, sec = NULL, style = c("stack", "dodge", "
p_data <- as.data.frame(table(data[c(pri, sec)])) |> p_data <- as.data.frame(table(data[c(pri, sec)])) |>
dplyr::mutate(dplyr::across(tidyselect::any_of(c(pri, sec)), forcats::as_factor), dplyr::mutate(dplyr::across(tidyselect::any_of(c(pri, sec)), forcats::as_factor),
p = Freq / NROW(data) p = Freq / NROW(data))
)
if (nrow(p_data) > max_level) { if (nrow(p_data) > max_level) {
p_data <- sort_by( p_data <- sort_by(p_data, p_data[["Freq"]], decreasing = TRUE) |>
p_data,
p_data[["Freq"]],
decreasing = TRUE
) |>
head(max_level) head(max_level)
} }
@ -73,39 +99,31 @@ plot_bar_single <- function(data, pri, sec = NULL, style = c("stack", "dodge", "
fill <- pri fill <- pri
} }
p <- ggplot2::ggplot( p <- ggplot2::ggplot(p_data, ggplot2::aes(x = .data[[pri]], y = p, fill = .data[[fill]])) +
p_data,
ggplot2::aes(
x = .data[[pri]],
y = p,
fill = .data[[fill]]
)
) +
ggplot2::geom_bar(position = style, stat = "identity") + ggplot2::geom_bar(position = style, stat = "identity") +
ggplot2::scale_y_continuous(labels = scales::percent) + scale_fill_generate(palette = color.palette) +
scale_fill_generate(palette=color.palette) + ggplot2::xlab(get_label(data, pri)) +
ggplot2::ylab("Percentage") + ggplot2::guides(fill = ggplot2::guide_legend(title = get_label(data, fill)))
ggplot2::xlab(get_label(data,pri))+
ggplot2::guides(fill = ggplot2::guide_legend(title = get_label(data,fill)))
## To handle large number of levels and long level names ## To handle large number of levels and long level names
if (nrow(p_data) > 10 | any(nchar(as.character(p_data[[pri]])) > 6)) { if (nrow(p_data) > 10 |
any(nchar(as.character(p_data[[pri]])) > 6)) {
p <- p + p <- p +
# ggplot2::guides(fill = "none") + # ggplot2::guides(fill = "none") +
ggplot2::theme( ggplot2::theme(axis.text.x = ggplot2::element_text(
axis.text.x = ggplot2::element_text(
angle = 90, angle = 90,
vjust = 1, hjust = 1 vjust = 1,
))+ hjust = 1
ggplot2::theme( )) +
axis.text.x = ggplot2::element_text(vjust = 0.5) ggplot2::theme(axis.text.x = ggplot2::element_text(vjust = 0.5))
)
if (is.null(sec)){ if (is.null(sec)) {
p <- p + p <- p +
ggplot2::guides(fill = "none") ggplot2::guides(fill = "none")
} }
} }
p p +
ggplot2::scale_y_continuous(labels = scales::percent) +
ggplot2::ylab("Percentage")
} }

View file

@ -32,11 +32,11 @@ plot_box <- function(data, pri, sec, ter = NULL,color.palette="viridis",...) {
data = .ds, data = .ds,
pri = pri, pri = pri,
sec = sec, sec = sec,
color.palette=color.palette color.palette=color.palette, ...
) )
}) })
wrap_plot_list(out,title=glue::glue(i18n$t("Grouped by {get_label(data,ter)}")),...) wrap_plot_list(out,title=glue::glue(i18n$t("Grouped by {get_label(data,ter)}")))
} }

View file

@ -131,7 +131,7 @@ plot_euler <- function(data, pri, sec, ter = NULL, seed = 2103,color.palette="vi
#' D = sample(c(TRUE, FALSE, FALSE, FALSE), 50, TRUE) #' D = sample(c(TRUE, FALSE, FALSE, FALSE), 50, TRUE)
#' ) |> plot_euler_single() #' ) |> plot_euler_single()
#' mtcars[c("vs", "am")] |> plot_euler_single("magma") #' mtcars[c("vs", "am")] |> plot_euler_single("magma")
plot_euler_single <- function(data,color.palette="viridis") { plot_euler_single <- function(data,color.palette="viridis", ...) {
data |> data |>
ggeulerr(shape = "circle") + ggeulerr(shape = "circle") +

View file

@ -15,13 +15,15 @@ plot_hbars <- function(data,
pri, pri,
sec, sec,
ter = NULL, ter = NULL,
color.palette = "viridis") { color.palette = "viridis",
...) {
vertical_stacked_bars( vertical_stacked_bars(
data = data, data = data,
score = pri, score = pri,
group = sec, group = sec,
strata = ter, strata = ter,
color.palette = color.palette color.palette = color.palette,
...
) )
} }
@ -74,7 +76,7 @@ vertical_stacked_bars <- function(data,
colors <- generate_colors(n = nrow(df.table), palette = color.palette) colors <- generate_colors(n = nrow(df.table), palette = color.palette)
## Colors are reversed by default as that usually gives the best result ## Colors are reversed by default as that usually gives the best result
if (isTRUE(reverse)) { if (isTRUE(reverse) | reverse=="TRUE") {
colors <- rev(colors) colors <- rev(colors)
} }

View file

@ -15,7 +15,8 @@ plot_likert <- function(data,
pri, pri,
sec = NULL, sec = NULL,
ter = NULL, ter = NULL,
color.palette = "viridis") { color.palette = "viridis",
...) {
if (!is.null(ter)) { if (!is.null(ter)) {
ds <- split(data, data[ter]) ds <- split(data, data[ter])
} else { } else {

View file

@ -95,7 +95,8 @@ plot_sankey <- function(data,
default.color = "#2986cc", default.color = "#2986cc",
box.color = "#1E4B66", box.color = "#1E4B66",
na.color = "grey80", na.color = "grey80",
missing.level = "Missing") { missing.level = "Missing",
...) {
if (!is.null(ter)) { if (!is.null(ter)) {
ds <- split(data, data[ter]) ds <- split(data, data[ter])
} else { } else {

View file

@ -8,7 +8,7 @@
#' @examples #' @examples
#' mtcars |> plot_scatter(pri = "mpg", sec = "wt") #' mtcars |> plot_scatter(pri = "mpg", sec = "wt")
#' mtcars |> plot_scatter(pri = "mpg", sec = "wt",ter="carb") #' mtcars |> plot_scatter(pri = "mpg", sec = "wt",ter="carb")
plot_scatter <- function(data, pri, sec, ter = NULL, color.palette="viridis") { plot_scatter <- function(data, pri, sec, ter = NULL, color.palette="viridis", ...) {
if (is.null(ter)) { if (is.null(ter)) {
rempsyc::nice_scatter( rempsyc::nice_scatter(
data = data, data = data,

View file

@ -8,7 +8,7 @@
#' @examples #' @examples
#' mtcars |> plot_violin(pri = "mpg", sec = "cyl") #' mtcars |> plot_violin(pri = "mpg", sec = "cyl")
#' mtcars |> plot_violin(pri = "mpg", sec = "cyl", ter = "gear", color.palette="Blues") #' mtcars |> plot_violin(pri = "mpg", sec = "cyl", ter = "gear", color.palette="Blues")
plot_violin <- function(data, pri, sec, ter = NULL, color.palette="viridis") { plot_violin <- function(data, pri, sec, ter = NULL, color.palette="viridis", ...) {
if (!is.null(ter)) { if (!is.null(ter)) {
ds <- split(data, data[ter]) ds <- split(data, data[ter])
} else { } else {
@ -23,7 +23,8 @@ plot_violin <- function(data, pri, sec, ter = NULL, color.palette="viridis") {
group = sec, group = sec,
response = pri, response = pri,
xtitle = get_label(data, var = sec), xtitle = get_label(data, var = sec),
ytitle = get_label(data, var = pri) ytitle = get_label(data, var = pri),
...
)+ )+
scale_fill_generate(palette=color.palette) scale_fill_generate(palette=color.palette)
}) })

View file

@ -43,7 +43,8 @@ m_redcap_readUI <- function(id, title = TRUE, url = NULL) {
shiny::actionButton( shiny::actionButton(
inputId = ns("data_connect"), inputId = ns("data_connect"),
label = i18n$t("Connect"), label = i18n$t("Connect"),
icon = shiny::icon("link", lib = "glyphicon"), icon = phosphoricons::ph("link",weight = "bold"),
# icon = shiny::icon("link", lib = "glyphicon"),
width = "100%", width = "100%",
disabled = TRUE disabled = TRUE
), ),
@ -99,7 +100,8 @@ m_redcap_readUI <- function(id, title = TRUE, url = NULL) {
shinyWidgets::dropMenu( shinyWidgets::dropMenu(
shiny::actionButton( shiny::actionButton(
inputId = ns("dropdown_params"), inputId = ns("dropdown_params"),
label = shiny::icon("filter"), label = phosphoricons::ph("funnel",weight = "bold"),
# label = shiny::icon("filter"),
width = "50px" width = "50px"
), ),
filter_ui filter_ui
@ -118,7 +120,8 @@ m_redcap_readUI <- function(id, title = TRUE, url = NULL) {
shiny::actionButton( shiny::actionButton(
inputId = ns("data_import"), inputId = ns("data_import"),
label = i18n$t("Import"), label = i18n$t("Import"),
icon = shiny::icon("download", lib = "glyphicon"), icon = phosphoricons::ph("download-simple",weight = "bold"),
# icon = shiny::icon("download", lib = "glyphicon"),
width = "100%", width = "100%",
disabled = TRUE disabled = TRUE
), ),

View file

@ -57,7 +57,8 @@ regression_ui <- function(id, ...) {
bslib::accordion_panel( bslib::accordion_panel(
value = "acc_pan_reg", value = "acc_pan_reg",
title = i18n$t("Regression"), title = i18n$t("Regression"),
icon = bsicons::bs_icon("calculator"), icon = phosphoricons::ph("calculator"),
# icon = bsicons::bs_icon("calculator"),
shiny::uiOutput(outputId = ns("outcome_var")), shiny::uiOutput(outputId = ns("outcome_var")),
# shiny::selectInput( # shiny::selectInput(
# inputId = "design", # inputId = "design",
@ -91,7 +92,8 @@ regression_ui <- function(id, ...) {
bslib::input_task_button( bslib::input_task_button(
id = ns("load"), id = ns("load"),
label = i18n$t("Analyse"), label = i18n$t("Analyse"),
icon = bsicons::bs_icon("pencil"), icon = phosphoricons::ph("math-operations"),
# icon = bsicons::bs_icon("pencil"),
label_busy = i18n$t("Working..."), label_busy = i18n$t("Working..."),
icon_busy = fontawesome::fa_i("arrows-rotate", icon_busy = fontawesome::fa_i("arrows-rotate",
class = "fa-spin", class = "fa-spin",
@ -136,7 +138,8 @@ regression_ui <- function(id, ...) {
list( list(
value = "acc_pan_coef_plot", value = "acc_pan_coef_plot",
title = "Coefficients plot", title = "Coefficients plot",
icon = bsicons::bs_icon("bar-chart-steps"), icon = phosphoricons::ph("chart-bar-horizontal"),
# icon = bsicons::bs_icon("bar-chart-steps"),
shiny::tags$br(), shiny::tags$br(),
shiny::uiOutput(outputId = ns("plot_model")) shiny::uiOutput(outputId = ns("plot_model"))
), ),
@ -179,7 +182,8 @@ regression_ui <- function(id, ...) {
shiny::downloadButton( shiny::downloadButton(
outputId = ns("download_plot"), outputId = ns("download_plot"),
label = i18n$t("Download plot"), label = i18n$t("Download plot"),
icon = shiny::icon("download") icon = phosphoricons::ph("arrow-fat-down")
# icon = shiny::icon("download")
) )
) )
) )
@ -200,7 +204,8 @@ regression_ui <- function(id, ...) {
bslib::accordion_panel( bslib::accordion_panel(
value = "acc_pan_checks", value = "acc_pan_checks",
title = "Checks", title = "Checks",
icon = bsicons::bs_icon("clipboard-check"), icon = phosphoricons::ph("checks"),
# icon = bsicons::bs_icon("clipboard-check"),
shiny::uiOutput(outputId = ns("plot_checks")) shiny::uiOutput(outputId = ns("plot_checks"))
) )
) )

View file

@ -50,7 +50,7 @@ string_split_ui <- function(id) {
), ),
actionButton( actionButton(
inputId = ns("create"), inputId = ns("create"),
label = tagList(phosphoricons::ph("pencil"), i18n$t("Apply split")), label = tagList(phosphoricons::ph("pencil",weight = "bold"), i18n$t("Apply split")),
class = "btn-outline-primary float-end" class = "btn-outline-primary float-end"
), ),
tags$div(class = "clearfix") tags$div(class = "clearfix")

Binary file not shown.

View file

@ -37,7 +37,8 @@ table_download_server <- function(id, data, file_name = "table", ...) {
shiny::downloadButton( shiny::downloadButton(
outputId = ns("act_table"), outputId = ns("act_table"),
label = i18n$t("Download table"), label = i18n$t("Download table"),
icon = shiny::icon("download") icon = phosphoricons::ph("arrow-fat-down")
# icon = shiny::icon("download")
) )
} else { } else {
# Return NULL to show nothing # Return NULL to show nothing

View file

@ -15,7 +15,8 @@ ui_elements <- function(selection) {
"home" = bslib::nav_panel( "home" = bslib::nav_panel(
title = "FreesearchR", title = "FreesearchR",
# title = shiny::div(htmltools::img(src="FreesearchR-logo-white-nobg-h80.png")), # title = shiny::div(htmltools::img(src="FreesearchR-logo-white-nobg-h80.png")),
icon = shiny::icon("house"), icon = phosphoricons::ph("house", weight = "bold"),
# icon = shiny::icon("house"),
shiny::fluidRow( shiny::fluidRow(
# "The browser language is", # "The browser language is",
# textOutput("your_lang"), # textOutput("your_lang"),
@ -45,7 +46,8 @@ ui_elements <- function(selection) {
############################################################################## ##############################################################################
"import" = bslib::nav_panel( "import" = bslib::nav_panel(
title = i18n$t("Get started"), title = i18n$t("Get started"),
icon = shiny::icon("play"), icon = phosphoricons::ph("play", weight = "bold"),
# icon = shiny::icon("play"),
value = "nav_import", value = "nav_import",
shiny::fluidRow( shiny::fluidRow(
shiny::column(width = 2), shiny::column(width = 2),
@ -122,7 +124,8 @@ ui_elements <- function(selection) {
inputId = "modal_initial_view", inputId = "modal_initial_view",
label = i18n$t("Quick overview"), label = i18n$t("Quick overview"),
width = "100%", width = "100%",
icon = shiny::icon("binoculars"), icon = phosphoricons::ph("binoculars",weight = "bold"),
# icon = shiny::icon("binoculars"),
disabled = FALSE disabled = FALSE
), ),
shiny::br(), shiny::br(),
@ -166,7 +169,8 @@ ui_elements <- function(selection) {
inputId = "act_start", inputId = "act_start",
label = i18n$t("Let's begin!"), label = i18n$t("Let's begin!"),
width = "100%", width = "100%",
icon = shiny::icon("play"), icon = phosphoricons::ph("play",weight = "bold"),
# icon = shiny::icon("play"),
disabled = TRUE disabled = TRUE
), ),
shiny::br(), shiny::br(),
@ -185,11 +189,13 @@ ui_elements <- function(selection) {
############################################################################## ##############################################################################
"prepare" = bslib::nav_menu( "prepare" = bslib::nav_menu(
title = i18n$t("Prepare"), title = i18n$t("Prepare"),
icon = shiny::icon("pen-to-square"), icon = phosphoricons::ph("note-pencil", weight = "bold"),
# icon = shiny::icon("pen-to-square"),
value = "nav_prepare", value = "nav_prepare",
bslib::nav_panel( bslib::nav_panel(
title = i18n$t("Overview and filter"), title = i18n$t("Overview and filter"),
icon = shiny::icon("eye"), icon = phosphoricons::ph("eye"),
# icon = shiny::icon("eye"),
value = "nav_prepare_overview", value = "nav_prepare_overview",
tags$h3(i18n$t("Overview and filtering")), tags$h3(i18n$t("Overview and filtering")),
fluidRow( fluidRow(
@ -241,7 +247,7 @@ ui_elements <- function(selection) {
"Read more on how ", "Read more on how ",
tags$a( tags$a(
"data types", "data types",
href = "https://agdamsbo.github.io/FreesearchR/articles/data-types.html", href = "https://freesearchr.github.io/FreesearchR-knowledge/app/data_types.html",
target = "_blank", target = "_blank",
rel = "noopener noreferrer" rel = "noopener noreferrer"
), ),
@ -264,7 +270,8 @@ ui_elements <- function(selection) {
), ),
bslib::nav_panel( bslib::nav_panel(
title = i18n$t("Edit and create data"), title = i18n$t("Edit and create data"),
icon = shiny::icon("file-pen"), icon = phosphoricons::ph("pencil-line"),
# icon = shiny::icon("file-pen"),
tags$h3(i18n$t("Subset, rename and convert variables")), tags$h3(i18n$t("Subset, rename and convert variables")),
fluidRow(shiny::column( fluidRow(shiny::column(
width = 9, shiny::tags$p( width = 9, shiny::tags$p(
@ -293,13 +300,13 @@ ui_elements <- function(selection) {
width = 3, width = 3,
shiny::actionButton( shiny::actionButton(
inputId = "modal_update", inputId = "modal_update",
label = i18n$t("Modify factor levels"), label = i18n$t("Modify factor"),
width = "100%" width = "100%"
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::helpText( shiny::helpText(i18n$t(
i18n$t("Reorder or rename the levels of factor/categorical variables.") "Modify the levels of factor/categorical variables."
), )),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br() shiny::tags$br()
), ),
@ -312,9 +319,7 @@ ui_elements <- function(selection) {
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::helpText( shiny::helpText(
i18n$t( i18n$t("Create factor/categorical variable from other variables.")
"Create factor/categorical variable from a continous variable (number/date/time)."
)
), ),
shiny::tags$br(), shiny::tags$br(),
shiny::tags$br() shiny::tags$br()
@ -391,14 +396,16 @@ ui_elements <- function(selection) {
"describe" = "describe" =
bslib::nav_menu( bslib::nav_menu(
title = i18n$t("Evaluate"), title = i18n$t("Evaluate"),
icon = shiny::icon("magnifying-glass-chart"), icon = phosphoricons::ph("magnifying-glass", weight = "bold"),
# icon = shiny::icon("magnifying-glass-chart"),
value = "nav_describe", value = "nav_describe",
# id = "navdescribe", # id = "navdescribe",
# bslib::navset_bar( # bslib::navset_bar(
# title = "", # title = "",
bslib::nav_panel( bslib::nav_panel(
title = i18n$t("Characteristics"), title = i18n$t("Characteristics"),
icon = bsicons::bs_icon("table"), icon = phosphoricons::ph("table"),
# icon = bsicons::bs_icon("table"),
bslib::layout_sidebar( bslib::layout_sidebar(
sidebar = bslib::sidebar( sidebar = bslib::sidebar(
shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE), shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE),
@ -410,7 +417,8 @@ ui_elements <- function(selection) {
open = TRUE, open = TRUE,
value = "acc_pan_chars", value = "acc_pan_chars",
title = "Settings", title = "Settings",
icon = bsicons::bs_icon("table"), icon = phosphoricons::ph("table"),
# icon = bsicons::bs_icon("table"),
# vectorSelectInput( # vectorSelectInput(
# inputId = "baseline_theme", # inputId = "baseline_theme",
# selected = "none", # selected = "none",
@ -452,7 +460,8 @@ ui_elements <- function(selection) {
inputId = "act_eval", inputId = "act_eval",
label = i18n$t("Evaluate"), label = i18n$t("Evaluate"),
width = "100%", width = "100%",
icon = shiny::icon("calculator"), icon = phosphoricons::ph("calculator",weight = "bold"),
# icon = shiny::icon("calculator"),
disabled = TRUE disabled = TRUE
), ),
shiny::helpText(i18n$t( shiny::helpText(i18n$t(
@ -466,7 +475,8 @@ ui_elements <- function(selection) {
), ),
bslib::nav_panel( bslib::nav_panel(
title = i18n$t("Correlations"), title = i18n$t("Correlations"),
icon = bsicons::bs_icon("bounding-box"), icon = phosphoricons::ph("graph"),
# icon = bsicons::bs_icon("bounding-box"),
bslib::layout_sidebar( bslib::layout_sidebar(
sidebar = bslib::sidebar( sidebar = bslib::sidebar(
# shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE), # shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE),
@ -507,7 +517,8 @@ ui_elements <- function(selection) {
do.call(bslib::nav_panel, c( do.call(bslib::nav_panel, c(
list( list(
title = i18n$t("Missings"), title = i18n$t("Missings"),
icon = bsicons::bs_icon("x-circle") icon = phosphoricons::ph("placeholder")
# icon = bsicons::bs_icon("x-circle")
), ),
data_missings_ui(id = "missingness", validation_ui("validation_mcar")) data_missings_ui(id = "missingness", validation_ui("validation_mcar"))
)) ))
@ -522,7 +533,8 @@ ui_elements <- function(selection) {
c( c(
list( list(
title = i18n$t("Visuals"), title = i18n$t("Visuals"),
icon = shiny::icon("chart-line"), icon = phosphoricons::ph("chart-line", weight = "bold"),
# icon = shiny::icon("chart-line"),
value = "nav_visuals" value = "nav_visuals"
), ),
data_visuals_ui("visuals") data_visuals_ui("visuals")
@ -543,7 +555,8 @@ ui_elements <- function(selection) {
"analyze" = "analyze" =
bslib::nav_panel( bslib::nav_panel(
title = i18n$t("Regression"), title = i18n$t("Regression"),
icon = shiny::icon("calculator"), icon = phosphoricons::ph("calculator", weight = "bold"),
# icon = shiny::icon("calculator"),
value = "nav_analyses", value = "nav_analyses",
do.call(bslib::navset_card_tab, regression_ui("regression")) do.call(bslib::navset_card_tab, regression_ui("regression"))
), ),
@ -555,7 +568,8 @@ ui_elements <- function(selection) {
"download" = "download" =
bslib::nav_panel( bslib::nav_panel(
title = i18n$t("Download"), title = i18n$t("Download"),
icon = shiny::icon("download"), icon = phosphoricons::ph("download-simple", weight = "bold"),
# icon = shiny::icon("download"),
value = "nav_download", value = "nav_download",
shiny::fluidRow( shiny::fluidRow(
shiny::column(width = 2), shiny::column(width = 2),
@ -591,7 +605,8 @@ ui_elements <- function(selection) {
shiny::downloadButton( shiny::downloadButton(
outputId = "report", outputId = "report",
label = "Download report", label = "Download report",
icon = shiny::icon("download") icon = phosphoricons::ph("arrow-fat-down")
# icon = shiny::icon("download")
), ),
shiny::br() shiny::br()
# shiny::helpText("If choosing to output to MS Word, please note, that when opening the document, two errors will pop-up. Choose to repair and choose not to update references. The issue is being worked on. You can always choose LibreOffice instead."), # shiny::helpText("If choosing to output to MS Word, please note, that when opening the document, two errors will pop-up. Choose to repair and choose not to update references. The issue is being worked on. You can always choose LibreOffice instead."),
@ -621,7 +636,8 @@ ui_elements <- function(selection) {
shiny::downloadButton( shiny::downloadButton(
outputId = "data_modified", outputId = "data_modified",
label = "Download data", label = "Download data",
icon = shiny::icon("download") icon = phosphoricons::ph("arrow-fat-down")
# icon = shiny::icon("download")
) )
) )
), ),
@ -678,7 +694,7 @@ ui_elements <- function(selection) {
"docs" = bslib::nav_item( "docs" = bslib::nav_item(
# shiny::img(shiny::icon("book")), # shiny::img(shiny::icon("book")),
shiny::tags$a( shiny::tags$a(
href = "https://agdamsbo.github.io/FreesearchR/", href = "https://freesearchr.github.io/FreesearchR-knowledge/",
"Docs", "Docs",
shiny::icon("arrow-up-right-from-square"), shiny::icon("arrow-up-right-from-square"),
target = "_blank", target = "_blank",

View file

@ -44,7 +44,7 @@ update_factor_ui <- function(id) {
actionButton( actionButton(
disabled = TRUE, disabled = TRUE,
inputId = ns("drop_levels"), inputId = ns("drop_levels"),
label = tagList(phosphoricons::ph("sort-ascending"), i18n$t("Drop empty")), label = tagList(phosphoricons::ph("trash",weight = "bold"), i18n$t("Drop empty")),
class = "btn-outline-primary mb-3", class = "btn-outline-primary mb-3",
width = "100%" width = "100%"
) )
@ -55,7 +55,7 @@ update_factor_ui <- function(id) {
actionButton( actionButton(
inputId = ns("sort_levels"), inputId = ns("sort_levels"),
label = tagList( label = tagList(
phosphoricons::ph("sort-ascending"), phosphoricons::ph("sort-ascending",weight = "bold"),
i18n$t("Sort by levels") i18n$t("Sort by levels")
), ),
class = "btn-outline-primary mb-3", class = "btn-outline-primary mb-3",
@ -68,7 +68,7 @@ update_factor_ui <- function(id) {
actionButton( actionButton(
inputId = ns("sort_occurrences"), inputId = ns("sort_occurrences"),
label = tagList( label = tagList(
phosphoricons::ph("sort-ascending"), phosphoricons::ph("sort-ascending",weight = "bold"),
i18n$t("Sort by count") i18n$t("Sort by count")
), ),
class = "btn-outline-primary mb-3", class = "btn-outline-primary mb-3",
@ -92,7 +92,7 @@ update_factor_ui <- function(id) {
actionButton( actionButton(
inputId = ns("create"), inputId = ns("create"),
label = tagList( label = tagList(
phosphoricons::ph("arrow-clockwise"), phosphoricons::ph("arrow-clockwise",weight = "bold"),
i18n$t("Update factor variable") i18n$t("Update factor variable")
), ),
class = "btn-outline-primary" class = "btn-outline-primary"

View file

@ -30,7 +30,7 @@ update_variables_ui <- function(id, title = "") {
placement = "bottom-end", placement = "bottom-end",
shiny::actionButton( shiny::actionButton(
inputId = ns("settings"), inputId = ns("settings"),
label = phosphoricons::ph("gear"), label = phosphoricons::ph("gear",weight = "bold"),
class = "pull-right float-right" class = "pull-right float-right"
), ),
shinyWidgets::textInputIcon( shinyWidgets::textInputIcon(
@ -75,7 +75,7 @@ update_variables_ui <- function(id, title = "") {
shiny::actionButton( shiny::actionButton(
inputId = ns("validate"), inputId = ns("validate"),
label = htmltools::tagList( label = htmltools::tagList(
phosphoricons::ph("arrow-circle-right", title = i18n$t("Apply changes")), phosphoricons::ph("arrow-circle-right", title = i18n$t("Apply changes"),weight = "bold"),
i18n$t("Apply changes") i18n$t("Apply changes")
), ),
width = "100%" width = "100%"

View file

@ -2,20 +2,20 @@
-------------------------------- R environment --------------------------------- -------------------------------- R environment ---------------------------------
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
|setting |value | |setting |value |
|:-----------|:------------------------------------------| |:-----------|:--------------------------------------------------------------------------------------------------|
|version |R version 4.5.2 (2025-10-31) | |version |R version 4.5.2 (2025-10-31) |
|os |macOS Tahoe 26.4 | |os |macOS Tahoe 26.5 |
|system |aarch64, darwin20 | |system |aarch64, darwin20 |
|ui |RStudio | |ui |RStudio |
|language |(EN) | |language |(EN) |
|collate |en_US.UTF-8 | |collate |en_US.UTF-8 |
|ctype |en_US.UTF-8 | |ctype |en_US.UTF-8 |
|tz |Europe/Copenhagen | |tz |Europe/Copenhagen |
|date |2026-03-31 | |date |2026-06-01 |
|rstudio |2026.01.1+403 Apple Blossom (desktop) | |rstudio |2026.04.0+526 Globemaster Allium (desktop) |
|pandoc |3.6.4 @ /opt/homebrew/bin/ (via rmarkdown) | |pandoc |3.8.3 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/aarch64/ (via rmarkdown) |
|quarto |1.7.30 @ /usr/local/bin/quarto | |quarto |1.9.37 @ /usr/local/bin/quarto |
|FreesearchR |26.3.6.260331 | |FreesearchR |26.6.1.260601 |
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
@ -26,6 +26,8 @@
|apexcharter |0.4.5 |2026-01-07 |CRAN (R 4.5.2) | |apexcharter |0.4.5 |2026-01-07 |CRAN (R 4.5.2) |
|askpass |1.2.1 |2024-10-04 |CRAN (R 4.5.0) | |askpass |1.2.1 |2024-10-04 |CRAN (R 4.5.0) |
|assertthat |0.2.1 |2019-03-21 |CRAN (R 4.5.0) | |assertthat |0.2.1 |2019-03-21 |CRAN (R 4.5.0) |
|attachment |0.4.5 |2025-03-14 |CRAN (R 4.5.0) |
|attempt |0.3.1 |2020-05-03 |CRAN (R 4.5.0) |
|backports |1.5.0 |2024-05-23 |CRAN (R 4.5.0) | |backports |1.5.0 |2024-05-23 |CRAN (R 4.5.0) |
|base64enc |0.1-6 |2026-02-02 |CRAN (R 4.5.2) | |base64enc |0.1-6 |2026-02-02 |CRAN (R 4.5.2) |
|bayestestR |0.17.0 |2025-08-29 |CRAN (R 4.5.0) | |bayestestR |0.17.0 |2025-08-29 |CRAN (R 4.5.0) |
@ -44,6 +46,7 @@
|cardx |0.3.2 |2026-02-05 |CRAN (R 4.5.2) | |cardx |0.3.2 |2026-02-05 |CRAN (R 4.5.2) |
|caTools |1.18.3 |2024-09-04 |CRAN (R 4.5.0) | |caTools |1.18.3 |2024-09-04 |CRAN (R 4.5.0) |
|cellranger |1.1.0 |2016-07-27 |CRAN (R 4.5.0) | |cellranger |1.1.0 |2016-07-27 |CRAN (R 4.5.0) |
|cffr |1.2.1 |2026-01-12 |CRAN (R 4.5.2) |
|checkmate |2.3.4 |2026-02-03 |CRAN (R 4.5.2) | |checkmate |2.3.4 |2026-02-03 |CRAN (R 4.5.2) |
|class |7.3-23 |2025-01-01 |CRAN (R 4.5.0) | |class |7.3-23 |2025-01-01 |CRAN (R 4.5.0) |
|classInt |0.4-11 |2025-01-08 |CRAN (R 4.5.0) | |classInt |0.4-11 |2025-01-08 |CRAN (R 4.5.0) |
@ -53,7 +56,6 @@
|colorspace |2.1-2 |2025-09-22 |CRAN (R 4.5.0) | |colorspace |2.1-2 |2025-09-22 |CRAN (R 4.5.0) |
|commonmark |2.0.0 |2025-07-07 |CRAN (R 4.5.0) | |commonmark |2.0.0 |2025-07-07 |CRAN (R 4.5.0) |
|crayon |1.5.3 |2024-06-20 |CRAN (R 4.5.0) | |crayon |1.5.3 |2024-06-20 |CRAN (R 4.5.0) |
|curl |7.0.0 |2025-08-19 |CRAN (R 4.5.0) |
|data.table |1.18.2.1 |2026-01-27 |CRAN (R 4.5.2) | |data.table |1.18.2.1 |2026-01-27 |CRAN (R 4.5.2) |
|datamods |1.5.3 |2024-10-02 |CRAN (R 4.5.0) | |datamods |1.5.3 |2024-10-02 |CRAN (R 4.5.0) |
|datawizard |1.3.0 |2025-10-11 |CRAN (R 4.5.0) | |datawizard |1.3.0 |2025-10-11 |CRAN (R 4.5.0) |
@ -62,6 +64,7 @@
|devtools |2.4.6 |2025-10-03 |CRAN (R 4.5.0) | |devtools |2.4.6 |2025-10-03 |CRAN (R 4.5.0) |
|DHARMa |0.4.7 |2024-10-18 |CRAN (R 4.5.0) | |DHARMa |0.4.7 |2024-10-18 |CRAN (R 4.5.0) |
|digest |0.6.39 |2025-11-19 |CRAN (R 4.5.2) | |digest |0.6.39 |2025-11-19 |CRAN (R 4.5.2) |
|dockerfiler |0.2.5 |2025-05-07 |CRAN (R 4.5.0) |
|doParallel |1.0.17 |2022-02-07 |CRAN (R 4.5.0) | |doParallel |1.0.17 |2022-02-07 |CRAN (R 4.5.0) |
|dplyr |1.2.0 |2026-02-03 |CRAN (R 4.5.2) | |dplyr |1.2.0 |2026-02-03 |CRAN (R 4.5.2) |
|DT |0.34.0 |2025-09-02 |CRAN (R 4.5.0) | |DT |0.34.0 |2025-09-02 |CRAN (R 4.5.0) |
@ -84,7 +87,7 @@
|foreach |1.5.2 |2022-02-02 |CRAN (R 4.5.0) | |foreach |1.5.2 |2022-02-02 |CRAN (R 4.5.0) |
|foreign |0.8-91 |2026-01-29 |CRAN (R 4.5.2) | |foreign |0.8-91 |2026-01-29 |CRAN (R 4.5.2) |
|Formula |1.2-5 |2023-02-24 |CRAN (R 4.5.0) | |Formula |1.2-5 |2023-02-24 |CRAN (R 4.5.0) |
|FreesearchR |26.3.6 |NA |NA | |FreesearchR |26.6.1 |NA |NA |
|fs |1.6.7 |2026-03-06 |CRAN (R 4.5.2) | |fs |1.6.7 |2026-03-06 |CRAN (R 4.5.2) |
|gdtools |0.5.0 |2026-02-09 |CRAN (R 4.5.2) | |gdtools |0.5.0 |2026-02-09 |CRAN (R 4.5.2) |
|generics |0.1.4 |2025-05-09 |CRAN (R 4.5.0) | |generics |0.1.4 |2025-05-09 |CRAN (R 4.5.0) |
@ -94,7 +97,7 @@
|ggplot2 |4.0.2 |2026-02-03 |CRAN (R 4.5.2) | |ggplot2 |4.0.2 |2026-02-03 |CRAN (R 4.5.2) |
|ggridges |0.5.7 |2025-08-27 |CRAN (R 4.5.0) | |ggridges |0.5.7 |2025-08-27 |CRAN (R 4.5.0) |
|ggstats |0.13.0 |2026-03-06 |CRAN (R 4.5.2) | |ggstats |0.13.0 |2026-03-06 |CRAN (R 4.5.2) |
|glue |1.8.0 |2024-09-30 |CRAN (R 4.5.0) | |glue |1.8.0 |2024-09-30 |CRAN (R 4.5.2) |
|gridExtra |2.3 |2017-09-09 |CRAN (R 4.5.0) | |gridExtra |2.3 |2017-09-09 |CRAN (R 4.5.0) |
|gt |1.3.0 |2026-01-22 |CRAN (R 4.5.2) | |gt |1.3.0 |2026-01-22 |CRAN (R 4.5.2) |
|gtable |0.3.6 |2024-10-25 |CRAN (R 4.5.0) | |gtable |0.3.6 |2024-10-25 |CRAN (R 4.5.0) |
@ -107,7 +110,6 @@
|htmltools |0.5.9 |2025-12-04 |CRAN (R 4.5.2) | |htmltools |0.5.9 |2025-12-04 |CRAN (R 4.5.2) |
|htmlwidgets |1.6.4 |2023-12-06 |CRAN (R 4.5.0) | |htmlwidgets |1.6.4 |2023-12-06 |CRAN (R 4.5.0) |
|httpuv |1.6.16 |2025-04-16 |CRAN (R 4.5.0) | |httpuv |1.6.16 |2025-04-16 |CRAN (R 4.5.0) |
|httr |1.4.8 |2026-02-13 |CRAN (R 4.5.2) |
|IDEAFilter |0.2.1 |2025-07-29 |CRAN (R 4.5.0) | |IDEAFilter |0.2.1 |2025-07-29 |CRAN (R 4.5.0) |
|insight |1.4.6 |2026-02-04 |CRAN (R 4.5.2) | |insight |1.4.6 |2026-02-04 |CRAN (R 4.5.2) |
|iterators |1.0.14 |2022-02-05 |CRAN (R 4.5.0) | |iterators |1.0.14 |2022-02-05 |CRAN (R 4.5.0) |
@ -117,7 +119,6 @@
|keyring |1.4.1 |2025-06-15 |CRAN (R 4.5.0) | |keyring |1.4.1 |2025-06-15 |CRAN (R 4.5.0) |
|knitr |1.51 |2025-12-20 |CRAN (R 4.5.2) | |knitr |1.51 |2025-12-20 |CRAN (R 4.5.2) |
|labeling |0.4.3 |2023-08-29 |CRAN (R 4.5.0) | |labeling |0.4.3 |2023-08-29 |CRAN (R 4.5.0) |
|labelled |2.16.0 |2025-10-22 |CRAN (R 4.5.0) |
|later |1.4.8 |2026-03-05 |CRAN (R 4.5.2) | |later |1.4.8 |2026-03-05 |CRAN (R 4.5.2) |
|lattice |0.22-7 |2025-04-02 |CRAN (R 4.5.2) | |lattice |0.22-7 |2025-04-02 |CRAN (R 4.5.2) |
|lifecycle |1.0.5 |2026-01-08 |CRAN (R 4.5.2) | |lifecycle |1.0.5 |2026-01-08 |CRAN (R 4.5.2) |
@ -127,6 +128,7 @@
|MASS |7.3-65 |2025-02-28 |CRAN (R 4.5.0) | |MASS |7.3-65 |2025-02-28 |CRAN (R 4.5.0) |
|Matrix |1.7-4 |2025-08-28 |CRAN (R 4.5.0) | |Matrix |1.7-4 |2025-08-28 |CRAN (R 4.5.0) |
|memoise |2.0.1 |2021-11-26 |CRAN (R 4.5.0) | |memoise |2.0.1 |2021-11-26 |CRAN (R 4.5.0) |
|mgcv |1.9-4 |2025-11-07 |CRAN (R 4.5.0) |
|mime |0.13 |2025-03-17 |CRAN (R 4.5.0) | |mime |0.13 |2025-03-17 |CRAN (R 4.5.0) |
|minqa |1.2.8 |2024-08-17 |CRAN (R 4.5.0) | |minqa |1.2.8 |2024-08-17 |CRAN (R 4.5.0) |
|mvtnorm |1.3-2 |2024-11-04 |CRAN (R 4.5.2) | |mvtnorm |1.3-2 |2024-11-04 |CRAN (R 4.5.2) |
@ -139,6 +141,7 @@
|openssl |2.3.5 |2026-02-26 |CRAN (R 4.5.2) | |openssl |2.3.5 |2026-02-26 |CRAN (R 4.5.2) |
|openxlsx2 |1.25 |2026-03-07 |CRAN (R 4.5.2) | |openxlsx2 |1.25 |2026-03-07 |CRAN (R 4.5.2) |
|otel |0.2.0 |2025-08-29 |CRAN (R 4.5.0) | |otel |0.2.0 |2025-08-29 |CRAN (R 4.5.0) |
|pak |0.9.2 |2025-12-22 |CRAN (R 4.5.2) |
|parameters |0.28.3 |2025-11-25 |CRAN (R 4.5.2) | |parameters |0.28.3 |2025-11-25 |CRAN (R 4.5.2) |
|patchwork |1.3.2 |2025-08-25 |CRAN (R 4.5.0) | |patchwork |1.3.2 |2025-08-25 |CRAN (R 4.5.0) |
|pbmcapply |1.5.1 |2022-04-28 |CRAN (R 4.5.0) | |pbmcapply |1.5.1 |2022-04-28 |CRAN (R 4.5.0) |
@ -150,7 +153,7 @@
|pkgload |1.5.0 |2026-02-03 |CRAN (R 4.5.2) | |pkgload |1.5.0 |2026-02-03 |CRAN (R 4.5.2) |
|plyr |1.8.9 |2023-10-02 |CRAN (R 4.5.0) | |plyr |1.8.9 |2023-10-02 |CRAN (R 4.5.0) |
|polyclip |1.10-7 |2024-07-23 |CRAN (R 4.5.0) | |polyclip |1.10-7 |2024-07-23 |CRAN (R 4.5.0) |
|polyglotr |1.7.1 |NA |NA | |polylabelr |1.0.0 |2026-01-19 |CRAN (R 4.5.2) |
|pracma |2.4.6 |2025-10-22 |CRAN (R 4.5.0) | |pracma |2.4.6 |2025-10-22 |CRAN (R 4.5.0) |
|processx |3.8.6 |2025-02-21 |CRAN (R 4.5.0) | |processx |3.8.6 |2025-02-21 |CRAN (R 4.5.0) |
|promises |1.5.0 |2025-11-01 |CRAN (R 4.5.0) | |promises |1.5.0 |2025-11-01 |CRAN (R 4.5.0) |
@ -188,15 +191,14 @@
|rprojroot |2.1.1 |2025-08-26 |CRAN (R 4.5.0) | |rprojroot |2.1.1 |2025-08-26 |CRAN (R 4.5.0) |
|rsconnect |1.7.0 |2025-12-06 |CRAN (R 4.5.2) | |rsconnect |1.7.0 |2025-12-06 |CRAN (R 4.5.2) |
|rstudioapi |0.18.0 |2026-01-16 |CRAN (R 4.5.2) | |rstudioapi |0.18.0 |2026-01-16 |CRAN (R 4.5.2) |
|rvest |1.0.5 |NA |NA |
|S7 |0.2.1 |2025-11-14 |CRAN (R 4.5.2) | |S7 |0.2.1 |2025-11-14 |CRAN (R 4.5.2) |
|sass |0.4.10 |2025-04-11 |CRAN (R 4.5.0) | |sass |0.4.10 |2025-04-11 |CRAN (R 4.5.0) |
|scales |1.4.0 |2025-04-24 |CRAN (R 4.5.0) | |scales |1.4.0 |2025-04-24 |CRAN (R 4.5.0) |
|see |0.13.0 |2026-01-30 |CRAN (R 4.5.2) | |see |0.13.0 |2026-01-30 |CRAN (R 4.5.2) |
|selectr |0.5-1 |NA |NA |
|sessioninfo |1.2.3 |2025-02-05 |CRAN (R 4.5.0) | |sessioninfo |1.2.3 |2025-02-05 |CRAN (R 4.5.0) |
|shiny |1.13.0 |2026-02-20 |CRAN (R 4.5.2) | |shiny |1.13.0 |2026-02-20 |CRAN (R 4.5.2) |
|shiny.i18n |0.3.0 |2023-01-16 |CRAN (R 4.5.0) | |shiny.i18n |0.3.0 |2023-01-16 |CRAN (R 4.5.0) |
|shiny2docker |0.0.3 |2025-06-28 |CRAN (R 4.5.0) |
|shinybusy |0.3.3 |2024-03-09 |CRAN (R 4.5.0) | |shinybusy |0.3.3 |2024-03-09 |CRAN (R 4.5.0) |
|shinyjs |2.1.1 |2026-01-15 |CRAN (R 4.5.2) | |shinyjs |2.1.1 |2026-01-15 |CRAN (R 4.5.2) |
|shinyTime |1.0.3 |2022-08-19 |CRAN (R 4.5.0) | |shinyTime |1.0.3 |2022-08-19 |CRAN (R 4.5.0) |
@ -214,13 +216,10 @@
|tidyselect |1.2.1 |2024-03-11 |CRAN (R 4.5.0) | |tidyselect |1.2.1 |2024-03-11 |CRAN (R 4.5.0) |
|timechange |0.4.0 |2026-01-29 |CRAN (R 4.5.2) | |timechange |0.4.0 |2026-01-29 |CRAN (R 4.5.2) |
|toastui |0.4.0 |2025-04-03 |CRAN (R 4.5.0) | |toastui |0.4.0 |2025-04-03 |CRAN (R 4.5.0) |
|triebeard |0.4.1 |NA |NA |
|tweenr |2.0.3 |2024-02-26 |CRAN (R 4.5.0) | |tweenr |2.0.3 |2024-02-26 |CRAN (R 4.5.0) |
|twosamples |2.0.1 |2023-06-23 |CRAN (R 4.5.0) | |twosamples |2.0.1 |2023-06-23 |CRAN (R 4.5.0) |
|tzdb |0.5.0 |2025-03-15 |CRAN (R 4.5.0) | |tzdb |0.5.0 |2025-03-15 |CRAN (R 4.5.0) |
|urltools |1.7.3.1 |NA |NA |
|usethis |3.2.1 |2025-09-06 |CRAN (R 4.5.0) | |usethis |3.2.1 |2025-09-06 |CRAN (R 4.5.0) |
|utf8 |1.2.6 |2025-06-08 |CRAN (R 4.5.0) |
|uuid |1.2-2 |2026-01-23 |CRAN (R 4.5.2) | |uuid |1.2-2 |2026-01-23 |CRAN (R 4.5.2) |
|vctrs |0.7.1 |2026-01-23 |CRAN (R 4.5.2) | |vctrs |0.7.1 |2026-01-23 |CRAN (R 4.5.2) |
|viridis |0.6.5 |2024-01-29 |CRAN (R 4.5.0) | |viridis |0.6.5 |2024-01-29 |CRAN (R 4.5.0) |
@ -232,4 +231,5 @@
|xml2 |1.5.2 |2026-01-17 |CRAN (R 4.5.2) | |xml2 |1.5.2 |2026-01-17 |CRAN (R 4.5.2) |
|xtable |1.8-8 |2026-02-22 |CRAN (R 4.5.2) | |xtable |1.8-8 |2026-02-22 |CRAN (R 4.5.2) |
|yaml |2.3.12 |2025-12-10 |CRAN (R 4.5.2) | |yaml |2.3.12 |2025-12-10 |CRAN (R 4.5.2) |
|yesno |0.1.3 |2024-07-26 |CRAN (R 4.5.0) |
|zip |2.3.3 |2025-05-13 |CRAN (R 4.5.0) | |zip |2.3.3 |2025-05-13 |CRAN (R 4.5.0) |

File diff suppressed because it is too large Load diff

View file

@ -89,7 +89,6 @@
"and","og" "and","og"
"from each pair","fra hvert par" "from each pair","fra hvert par"
"Plot","Tegn" "Plot","Tegn"
"Adjust settings, then press ""Plot"".","Juster indstillingerne og tryk så ""Tegn""."
"Plot height (mm)","Højde af grafik (mm)" "Plot height (mm)","Højde af grafik (mm)"
"Plot width (mm)","Bredde af grafik (mm)" "Plot width (mm)","Bredde af grafik (mm)"
"File format","File format" "File format","File format"
@ -97,12 +96,7 @@
"Select variable","Vælg variabel" "Select variable","Vælg variabel"
"Response variable","Svarvariable" "Response variable","Svarvariable"
"Plot type","Type af grafik" "Plot type","Type af grafik"
"Please select","Vælg"
"Additional variables","Yderligere variabler"
"Secondary variable","Sekundær variabel"
"No variable","Ingen variabel" "No variable","Ingen variabel"
"Grouping variable","Variabel til gruppering"
"No stratification","Ingen stratificering"
"Drawing the plot. Hold tight for a moment..","Tegner grafikken. Spænd selen.." "Drawing the plot. Hold tight for a moment..","Tegner grafikken. Spænd selen.."
"#Plotting\n","#Tegner\n" "#Plotting\n","#Tegner\n"
"Stacked horizontal bars","Stablede horisontale søjler" "Stacked horizontal bars","Stablede horisontale søjler"
@ -260,7 +254,6 @@
"FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR er tilgængelig på flere sprog. For at få hjælp med oversættelser, kontakt os venligst på info@freesearchr.org" "FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR er tilgængelig på flere sprog. For at få hjælp med oversættelser, kontakt os venligst på info@freesearchr.org"
"Home","Hjem" "Home","Hjem"
"Start with FreesearchR for basic data evaluation and analysis.","Start med FreesearchR til grundlæggende dataevaluering og -analyse." "Start with FreesearchR for basic data evaluation and analysis.","Start med FreesearchR til grundlæggende dataevaluering og -analyse."
"When you need more advanced tools, you'll be better prepared to use R directly.","Når du har brug for mere avancerede værktøjer, vil du være bedre forberedt på at bruge R direkte."
"(Read more)","(Læs mere)" "(Read more)","(Læs mere)"
"Run the FreesearchR app locally when working with sensitive data.","Kør FreesearchR-appen lokalt, når du arbejder med følsomme data." "Run the FreesearchR app locally when working with sensitive data.","Kør FreesearchR-appen lokalt, når du arbejder med følsomme data."
"Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Indlæs data fra regneark, REDCap-servere, eller prøv med eksempeldata. Flere kilder understøttes for maksimal fleksibilitet." "Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Indlæs data fra regneark, REDCap-servere, eller prøv med eksempeldata. Flere kilder understøttes for maksimal fleksibilitet."
@ -271,14 +264,11 @@
"When you need more advanced tools, you'll be prepared to use R directly.","Når du har brug for mere avancerede værktøjer, vil du være forberedt på at bruge R direkte." "When you need more advanced tools, you'll be prepared to use R directly.","Når du har brug for mere avancerede værktøjer, vil du være forberedt på at bruge R direkte."
"The app contains a selelct number of features and will guide you through key analyses.","Appen indeholder udvalgte funktioner, og guider dig gennem de vigtigste analyser." "The app contains a selelct number of features and will guide you through key analyses.","Appen indeholder udvalgte funktioner, og guider dig gennem de vigtigste analyser."
"Sort by Levels","Sorter efter niveauer" "Sort by Levels","Sorter efter niveauer"
"Modify factor levels","Ændr kategoriske niveauer"
"Reorder or rename the levels of factor/categorical variables.","Ændr navn eller rækkefølge på kategorisk variabel."
"Maximum number of observations:","Maximale antal observationer:" "Maximum number of observations:","Maximale antal observationer:"
"setting to 0 includes all","angiv 0 for at inkludere alle" "setting to 0 includes all","angiv 0 for at inkludere alle"
"Select a dataset from your environment or sample dataset from a package.","Vælg et datasæt fra din kørende session eller vælg træningsdata." "Select a dataset from your environment or sample dataset from a package.","Vælg et datasæt fra din kørende session eller vælg træningsdata."
"Select a sample dataset from a package.","Vælg et træningsdatasæt." "Select a sample dataset from a package.","Vælg et træningsdatasæt."
"Data ready to be imported!","Data er klar til at blive importeret!" "Data ready to be imported!","Data er klar til at blive importeret!"
"Data has %s obs. of %s variables.","Data har %s obs. på %s variabler."
"Data successfully imported!","Data successfully imported!" "Data successfully imported!","Data successfully imported!"
"Click to see data","Klik for at se data" "Click to see data","Klik for at se data"
"No data present.","Ingen data tilstede." "No data present.","Ingen data tilstede."
@ -314,10 +304,23 @@
"Sample data","Sample data" "Sample data","Sample data"
"Settings","Settings" "Settings","Settings"
"Create new factor","Create new factor" "Create new factor","Create new factor"
"Choose color palette","Choose color palette"
"Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')" "Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')"
"Drop empty","Drop empty" "Drop empty","Drop empty"
"Choose variable:","Choose variable:" "Choose variable:","Choose variable:"
"An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter." "An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter."
"An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter." "An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter."
"Likert diagram","Likert diagram" "Likert diagram","Likert diagram"
"Modify factor","Modify factor"
"Create factor/categorical variable from other variables.","Create factor/categorical variable from other variables."
"The data set has %s obs. in %s variables.","The data set has %s obs. in %s variables."
"Adjust plot input and settings below, then press ""Plot"".","Adjust plot input and settings below, then press ""Plot""."
"Define plot","Define plot"
"Choose color palette","Choose color palette"
"Additional variable","Additional variable"
"Grouping variable","Grouping variable"
"Secondary variable","Secondary variable"
"Reverse colors","Reverse colors"
"Plot survey results","Plot survey results"
"Additional variables","Additional variables"
"Other variables","Other variables"
"Select variables and plot type,\nthen click 'Plot' to generate visualization","Select variables and plot type,\nthen click 'Plot' to generate visualization"

1 en da
89 and og
90 from each pair fra hvert par
91 Plot Tegn
Adjust settings, then press "Plot". Juster indstillingerne og tryk så "Tegn".
92 Plot height (mm) Højde af grafik (mm)
93 Plot width (mm) Bredde af grafik (mm)
94 File format File format
96 Select variable Vælg variabel
97 Response variable Svarvariable
98 Plot type Type af grafik
Please select Vælg
Additional variables Yderligere variabler
Secondary variable Sekundær variabel
99 No variable Ingen variabel
Grouping variable Variabel til gruppering
No stratification Ingen stratificering
100 Drawing the plot. Hold tight for a moment.. Tegner grafikken. Spænd selen..
101 #Plotting\n #Tegner\n
102 Stacked horizontal bars Stablede horisontale søjler
254 FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org FreesearchR er tilgængelig på flere sprog. For at få hjælp med oversættelser, kontakt os venligst på info@freesearchr.org
255 Home Hjem
256 Start with FreesearchR for basic data evaluation and analysis. Start med FreesearchR til grundlæggende dataevaluering og -analyse.
When you need more advanced tools, you'll be better prepared to use R directly. Når du har brug for mere avancerede værktøjer, vil du være bedre forberedt på at bruge R direkte.
257 (Read more) (Læs mere)
258 Run the FreesearchR app locally when working with sensitive data. Kør FreesearchR-appen lokalt, når du arbejder med følsomme data.
259 Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility. Indlæs data fra regneark, REDCap-servere, eller prøv med eksempeldata. Flere kilder understøttes for maksimal fleksibilitet.
264 When you need more advanced tools, you'll be prepared to use R directly. Når du har brug for mere avancerede værktøjer, vil du være forberedt på at bruge R direkte.
265 The app contains a selelct number of features and will guide you through key analyses. Appen indeholder udvalgte funktioner, og guider dig gennem de vigtigste analyser.
266 Sort by Levels Sorter efter niveauer
Modify factor levels Ændr kategoriske niveauer
Reorder or rename the levels of factor/categorical variables. Ændr navn eller rækkefølge på kategorisk variabel.
267 Maximum number of observations: Maximale antal observationer:
268 setting to 0 includes all angiv 0 for at inkludere alle
269 Select a dataset from your environment or sample dataset from a package. Vælg et datasæt fra din kørende session eller vælg træningsdata.
270 Select a sample dataset from a package. Vælg et træningsdatasæt.
271 Data ready to be imported! Data er klar til at blive importeret!
Data has %s obs. of %s variables. Data har %s obs. på %s variabler.
272 Data successfully imported! Data successfully imported!
273 Click to see data Klik for at se data
274 No data present. Ingen data tilstede.
304 Sample data Sample data
305 Settings Settings
306 Create new factor Create new factor
Choose color palette Choose color palette
307 Optional filter logic (e.g., ⁠[gender] = 'female') Optional filter logic (e.g., ⁠[gender] = 'female')
308 Drop empty Drop empty
309 Choose variable: Choose variable:
310 An empty data set was imported. Please review data filter. An empty data set was imported. Please review data filter.
311 An error was encountered exporting data. Please review data filter. An error was encountered exporting data. Please review data filter.
312 Likert diagram Likert diagram
313 Modify factor Modify factor
314 Create factor/categorical variable from other variables. Create factor/categorical variable from other variables.
315 The data set has %s obs. in %s variables. The data set has %s obs. in %s variables.
316 Adjust plot input and settings below, then press "Plot". Adjust plot input and settings below, then press "Plot".
317 Define plot Define plot
318 Choose color palette Choose color palette
319 Additional variable Additional variable
320 Grouping variable Grouping variable
321 Secondary variable Secondary variable
322 Reverse colors Reverse colors
323 Plot survey results Plot survey results
324 Additional variables Additional variables
325 Other variables Other variables
326 Select variables and plot type,\nthen click 'Plot' to generate visualization Select variables and plot type,\nthen click 'Plot' to generate visualization

View file

@ -89,7 +89,6 @@
"and","na" "and","na"
"from each pair","kutoka kwa kila jozi" "from each pair","kutoka kwa kila jozi"
"Plot","Kipande cha habari" "Plot","Kipande cha habari"
"Adjust settings, then press ""Plot"".","Rekebisha mipangilio, kisha bonyeza ""Plot""."
"Plot height (mm)","Urefu wa kiwanja (mm)" "Plot height (mm)","Urefu wa kiwanja (mm)"
"Plot width (mm)","Upana wa kiwanja (mm)" "Plot width (mm)","Upana wa kiwanja (mm)"
"File format","Umbizo la faili" "File format","Umbizo la faili"
@ -97,12 +96,7 @@
"Select variable","Chagua kigezo" "Select variable","Chagua kigezo"
"Response variable","Kigezo cha majibu" "Response variable","Kigezo cha majibu"
"Plot type","Aina ya kiwanja" "Plot type","Aina ya kiwanja"
"Please select","Tafadhali chagua"
"Additional variables","Vigezo vya ziada"
"Secondary variable","Kigezo cha pili"
"No variable","Hakuna kigezo" "No variable","Hakuna kigezo"
"Grouping variable","Kigezo cha kuweka katika makundi"
"No stratification","Hakuna matabaka"
"Drawing the plot. Hold tight for a moment..","Kuchora njama. Shikilia kwa muda.." "Drawing the plot. Hold tight for a moment..","Kuchora njama. Shikilia kwa muda.."
"#Plotting\n","#Upangaji\n" "#Plotting\n","#Upangaji\n"
"Stacked horizontal bars","Pau za mlalo zilizopangwa kwa mpangilio" "Stacked horizontal bars","Pau za mlalo zilizopangwa kwa mpangilio"
@ -260,7 +254,6 @@
"FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR inapatikana katika lugha nyingi. Ili kukusaidia na tafsiri, tafadhali wasiliana nasi kwa info@freesearchr.org." "FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR inapatikana katika lugha nyingi. Ili kukusaidia na tafsiri, tafadhali wasiliana nasi kwa info@freesearchr.org."
"Home","Nyumbani" "Home","Nyumbani"
"Start with FreesearchR for basic data evaluation and analysis.","Anza na FreesearchR kwa tathmini na uchambuzi wa data ya msingi." "Start with FreesearchR for basic data evaluation and analysis.","Anza na FreesearchR kwa tathmini na uchambuzi wa data ya msingi."
"When you need more advanced tools, you'll be better prepared to use R directly.","Unapohitaji zana za hali ya juu zaidi, utakuwa tayari zaidi kutumia R moja kwa moja."
"(Read more)","(Soma zaidi)" "(Read more)","(Soma zaidi)"
"Run the FreesearchR app locally when working with sensitive data.","Endesha programu ya FreesearchR ndani ya eneo lako unapofanya kazi na data nyeti." "Run the FreesearchR app locally when working with sensitive data.","Endesha programu ya FreesearchR ndani ya eneo lako unapofanya kazi na data nyeti."
"Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Pakia data kutoka kwa lahajedwali, seva za REDCap, au jaribu na data ya sampuli. Vyanzo vingi vinaungwa mkono kwa unyumbufu wa hali ya juu." "Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Pakia data kutoka kwa lahajedwali, seva za REDCap, au jaribu na data ya sampuli. Vyanzo vingi vinaungwa mkono kwa unyumbufu wa hali ya juu."
@ -271,14 +264,11 @@
"When you need more advanced tools, you'll be prepared to use R directly.","Unapohitaji zana za hali ya juu zaidi, utakuwa tayari kutumia R moja kwa moja." "When you need more advanced tools, you'll be prepared to use R directly.","Unapohitaji zana za hali ya juu zaidi, utakuwa tayari kutumia R moja kwa moja."
"The app contains a selelct number of features and will guide you through key analyses.","The app contains a selelct number of features and will guide you through key analyses." "The app contains a selelct number of features and will guide you through key analyses.","The app contains a selelct number of features and will guide you through key analyses."
"Sort by Levels","Sort by Levels" "Sort by Levels","Sort by Levels"
"Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Maximum number of observations:","Maximum number of observations:" "Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all" "setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package." "Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package." "Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!" "Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!" "Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data" "Click to see data","Click to see data"
"No data present.","No data present." "No data present.","No data present."
@ -314,10 +304,23 @@
"Sample data","Sample data" "Sample data","Sample data"
"Settings","Settings" "Settings","Settings"
"Create new factor","Create new factor" "Create new factor","Create new factor"
"Choose color palette","Choose color palette"
"Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')" "Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')"
"Drop empty","Drop empty" "Drop empty","Drop empty"
"Choose variable:","Choose variable:" "Choose variable:","Choose variable:"
"An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter." "An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter."
"An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter." "An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter."
"Likert diagram","Likert diagram" "Likert diagram","Likert diagram"
"Modify factor","Modify factor"
"Create factor/categorical variable from other variables.","Create factor/categorical variable from other variables."
"The data set has %s obs. in %s variables.","The data set has %s obs. in %s variables."
"Adjust plot input and settings below, then press ""Plot"".","Adjust plot input and settings below, then press ""Plot""."
"Define plot","Define plot"
"Choose color palette","Choose color palette"
"Additional variable","Additional variable"
"Grouping variable","Grouping variable"
"Secondary variable","Secondary variable"
"Reverse colors","Reverse colors"
"Plot survey results","Plot survey results"
"Additional variables","Additional variables"
"Other variables","Other variables"
"Select variables and plot type,\nthen click 'Plot' to generate visualization","Select variables and plot type,\nthen click 'Plot' to generate visualization"

1 en sw
89 and na
90 from each pair kutoka kwa kila jozi
91 Plot Kipande cha habari
Adjust settings, then press "Plot". Rekebisha mipangilio, kisha bonyeza "Plot".
92 Plot height (mm) Urefu wa kiwanja (mm)
93 Plot width (mm) Upana wa kiwanja (mm)
94 File format Umbizo la faili
96 Select variable Chagua kigezo
97 Response variable Kigezo cha majibu
98 Plot type Aina ya kiwanja
Please select Tafadhali chagua
Additional variables Vigezo vya ziada
Secondary variable Kigezo cha pili
99 No variable Hakuna kigezo
Grouping variable Kigezo cha kuweka katika makundi
No stratification Hakuna matabaka
100 Drawing the plot. Hold tight for a moment.. Kuchora njama. Shikilia kwa muda..
101 #Plotting\n #Upangaji\n
102 Stacked horizontal bars Pau za mlalo zilizopangwa kwa mpangilio
254 FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org FreesearchR inapatikana katika lugha nyingi. Ili kukusaidia na tafsiri, tafadhali wasiliana nasi kwa info@freesearchr.org.
255 Home Nyumbani
256 Start with FreesearchR for basic data evaluation and analysis. Anza na FreesearchR kwa tathmini na uchambuzi wa data ya msingi.
When you need more advanced tools, you'll be better prepared to use R directly. Unapohitaji zana za hali ya juu zaidi, utakuwa tayari zaidi kutumia R moja kwa moja.
257 (Read more) (Soma zaidi)
258 Run the FreesearchR app locally when working with sensitive data. Endesha programu ya FreesearchR ndani ya eneo lako unapofanya kazi na data nyeti.
259 Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility. Pakia data kutoka kwa lahajedwali, seva za REDCap, au jaribu na data ya sampuli. Vyanzo vingi vinaungwa mkono kwa unyumbufu wa hali ya juu.
264 When you need more advanced tools, you'll be prepared to use R directly. Unapohitaji zana za hali ya juu zaidi, utakuwa tayari kutumia R moja kwa moja.
265 The app contains a selelct number of features and will guide you through key analyses. The app contains a selelct number of features and will guide you through key analyses.
266 Sort by Levels Sort by Levels
Modify factor levels Modify factor levels
Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
267 Maximum number of observations: Maximum number of observations:
268 setting to 0 includes all setting to 0 includes all
269 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
270 Select a sample dataset from a package. Select a sample dataset from a package.
271 Data ready to be imported! Data ready to be imported!
Data has %s obs. of %s variables. Data has %s obs. of %s variables.
272 Data successfully imported! Data successfully imported!
273 Click to see data Click to see data
274 No data present. No data present.
304 Sample data Sample data
305 Settings Settings
306 Create new factor Create new factor
Choose color palette Choose color palette
307 Optional filter logic (e.g., ⁠[gender] = 'female') Optional filter logic (e.g., ⁠[gender] = 'female')
308 Drop empty Drop empty
309 Choose variable: Choose variable:
310 An empty data set was imported. Please review data filter. An empty data set was imported. Please review data filter.
311 An error was encountered exporting data. Please review data filter. An error was encountered exporting data. Please review data filter.
312 Likert diagram Likert diagram
313 Modify factor Modify factor
314 Create factor/categorical variable from other variables. Create factor/categorical variable from other variables.
315 The data set has %s obs. in %s variables. The data set has %s obs. in %s variables.
316 Adjust plot input and settings below, then press "Plot". Adjust plot input and settings below, then press "Plot".
317 Define plot Define plot
318 Choose color palette Choose color palette
319 Additional variable Additional variable
320 Grouping variable Grouping variable
321 Secondary variable Secondary variable
322 Reverse colors Reverse colors
323 Plot survey results Plot survey results
324 Additional variables Additional variables
325 Other variables Other variables
326 Select variables and plot type,\nthen click 'Plot' to generate visualization Select variables and plot type,\nthen click 'Plot' to generate visualization

View file

@ -22,7 +22,7 @@ visuals_demo_app <- function() {
) )
) )
server <- function(input, output, session) { server <- function(input, output, session) {
pl <- data_visuals_server("visuals", data = shiny::reactive(default_parsing(mtcars))) pl <- data_visuals_server("visuals", data = shiny::reactive(default_parsing(mtcars)),palettes = color_choices())
} }
shiny::shinyApp(ui, server) shiny::shinyApp(ui, server)
} }

File diff suppressed because it is too large Load diff

View file

@ -89,7 +89,6 @@
"and","og" "and","og"
"from each pair","fra hvert par" "from each pair","fra hvert par"
"Plot","Tegn" "Plot","Tegn"
"Adjust settings, then press ""Plot"".","Juster indstillingerne og tryk så ""Tegn""."
"Plot height (mm)","Højde af grafik (mm)" "Plot height (mm)","Højde af grafik (mm)"
"Plot width (mm)","Bredde af grafik (mm)" "Plot width (mm)","Bredde af grafik (mm)"
"File format","File format" "File format","File format"
@ -97,12 +96,7 @@
"Select variable","Vælg variabel" "Select variable","Vælg variabel"
"Response variable","Svarvariable" "Response variable","Svarvariable"
"Plot type","Type af grafik" "Plot type","Type af grafik"
"Please select","Vælg"
"Additional variables","Yderligere variabler"
"Secondary variable","Sekundær variabel"
"No variable","Ingen variabel" "No variable","Ingen variabel"
"Grouping variable","Variabel til gruppering"
"No stratification","Ingen stratificering"
"Drawing the plot. Hold tight for a moment..","Tegner grafikken. Spænd selen.." "Drawing the plot. Hold tight for a moment..","Tegner grafikken. Spænd selen.."
"#Plotting\n","#Tegner\n" "#Plotting\n","#Tegner\n"
"Stacked horizontal bars","Stablede horisontale søjler" "Stacked horizontal bars","Stablede horisontale søjler"
@ -260,7 +254,6 @@
"FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR er tilgængelig på flere sprog. For at få hjælp med oversættelser, kontakt os venligst på info@freesearchr.org" "FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR er tilgængelig på flere sprog. For at få hjælp med oversættelser, kontakt os venligst på info@freesearchr.org"
"Home","Hjem" "Home","Hjem"
"Start with FreesearchR for basic data evaluation and analysis.","Start med FreesearchR til grundlæggende dataevaluering og -analyse." "Start with FreesearchR for basic data evaluation and analysis.","Start med FreesearchR til grundlæggende dataevaluering og -analyse."
"When you need more advanced tools, you'll be better prepared to use R directly.","Når du har brug for mere avancerede værktøjer, vil du være bedre forberedt på at bruge R direkte."
"(Read more)","(Læs mere)" "(Read more)","(Læs mere)"
"Run the FreesearchR app locally when working with sensitive data.","Kør FreesearchR-appen lokalt, når du arbejder med følsomme data." "Run the FreesearchR app locally when working with sensitive data.","Kør FreesearchR-appen lokalt, når du arbejder med følsomme data."
"Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Indlæs data fra regneark, REDCap-servere, eller prøv med eksempeldata. Flere kilder understøttes for maksimal fleksibilitet." "Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Indlæs data fra regneark, REDCap-servere, eller prøv med eksempeldata. Flere kilder understøttes for maksimal fleksibilitet."
@ -271,14 +264,11 @@
"When you need more advanced tools, you'll be prepared to use R directly.","Når du har brug for mere avancerede værktøjer, vil du være forberedt på at bruge R direkte." "When you need more advanced tools, you'll be prepared to use R directly.","Når du har brug for mere avancerede værktøjer, vil du være forberedt på at bruge R direkte."
"The app contains a selelct number of features and will guide you through key analyses.","Appen indeholder udvalgte funktioner, og guider dig gennem de vigtigste analyser." "The app contains a selelct number of features and will guide you through key analyses.","Appen indeholder udvalgte funktioner, og guider dig gennem de vigtigste analyser."
"Sort by Levels","Sorter efter niveauer" "Sort by Levels","Sorter efter niveauer"
"Modify factor levels","Ændr kategoriske niveauer"
"Reorder or rename the levels of factor/categorical variables.","Ændr navn eller rækkefølge på kategorisk variabel."
"Maximum number of observations:","Maximale antal observationer:" "Maximum number of observations:","Maximale antal observationer:"
"setting to 0 includes all","angiv 0 for at inkludere alle" "setting to 0 includes all","angiv 0 for at inkludere alle"
"Select a dataset from your environment or sample dataset from a package.","Vælg et datasæt fra din kørende session eller vælg træningsdata." "Select a dataset from your environment or sample dataset from a package.","Vælg et datasæt fra din kørende session eller vælg træningsdata."
"Select a sample dataset from a package.","Vælg et træningsdatasæt." "Select a sample dataset from a package.","Vælg et træningsdatasæt."
"Data ready to be imported!","Data er klar til at blive importeret!" "Data ready to be imported!","Data er klar til at blive importeret!"
"Data has %s obs. of %s variables.","Data har %s obs. på %s variabler."
"Data successfully imported!","Data successfully imported!" "Data successfully imported!","Data successfully imported!"
"Click to see data","Klik for at se data" "Click to see data","Klik for at se data"
"No data present.","Ingen data tilstede." "No data present.","Ingen data tilstede."
@ -314,10 +304,23 @@
"Sample data","Sample data" "Sample data","Sample data"
"Settings","Settings" "Settings","Settings"
"Create new factor","Create new factor" "Create new factor","Create new factor"
"Choose color palette","Choose color palette"
"Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')" "Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')"
"Drop empty","Drop empty" "Drop empty","Drop empty"
"Choose variable:","Choose variable:" "Choose variable:","Choose variable:"
"An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter." "An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter."
"An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter." "An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter."
"Likert diagram","Likert diagram" "Likert diagram","Likert diagram"
"Modify factor","Modify factor"
"Create factor/categorical variable from other variables.","Create factor/categorical variable from other variables."
"The data set has %s obs. in %s variables.","The data set has %s obs. in %s variables."
"Adjust plot input and settings below, then press ""Plot"".","Adjust plot input and settings below, then press ""Plot""."
"Define plot","Define plot"
"Choose color palette","Choose color palette"
"Additional variable","Additional variable"
"Grouping variable","Grouping variable"
"Secondary variable","Secondary variable"
"Reverse colors","Reverse colors"
"Plot survey results","Plot survey results"
"Additional variables","Additional variables"
"Other variables","Other variables"
"Select variables and plot type,\nthen click 'Plot' to generate visualization","Select variables and plot type,\nthen click 'Plot' to generate visualization"

1 en da
89 and og
90 from each pair fra hvert par
91 Plot Tegn
Adjust settings, then press "Plot". Juster indstillingerne og tryk så "Tegn".
92 Plot height (mm) Højde af grafik (mm)
93 Plot width (mm) Bredde af grafik (mm)
94 File format File format
96 Select variable Vælg variabel
97 Response variable Svarvariable
98 Plot type Type af grafik
Please select Vælg
Additional variables Yderligere variabler
Secondary variable Sekundær variabel
99 No variable Ingen variabel
Grouping variable Variabel til gruppering
No stratification Ingen stratificering
100 Drawing the plot. Hold tight for a moment.. Tegner grafikken. Spænd selen..
101 #Plotting\n #Tegner\n
102 Stacked horizontal bars Stablede horisontale søjler
254 FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org FreesearchR er tilgængelig på flere sprog. For at få hjælp med oversættelser, kontakt os venligst på info@freesearchr.org
255 Home Hjem
256 Start with FreesearchR for basic data evaluation and analysis. Start med FreesearchR til grundlæggende dataevaluering og -analyse.
When you need more advanced tools, you'll be better prepared to use R directly. Når du har brug for mere avancerede værktøjer, vil du være bedre forberedt på at bruge R direkte.
257 (Read more) (Læs mere)
258 Run the FreesearchR app locally when working with sensitive data. Kør FreesearchR-appen lokalt, når du arbejder med følsomme data.
259 Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility. Indlæs data fra regneark, REDCap-servere, eller prøv med eksempeldata. Flere kilder understøttes for maksimal fleksibilitet.
264 When you need more advanced tools, you'll be prepared to use R directly. Når du har brug for mere avancerede værktøjer, vil du være forberedt på at bruge R direkte.
265 The app contains a selelct number of features and will guide you through key analyses. Appen indeholder udvalgte funktioner, og guider dig gennem de vigtigste analyser.
266 Sort by Levels Sorter efter niveauer
Modify factor levels Ændr kategoriske niveauer
Reorder or rename the levels of factor/categorical variables. Ændr navn eller rækkefølge på kategorisk variabel.
267 Maximum number of observations: Maximale antal observationer:
268 setting to 0 includes all angiv 0 for at inkludere alle
269 Select a dataset from your environment or sample dataset from a package. Vælg et datasæt fra din kørende session eller vælg træningsdata.
270 Select a sample dataset from a package. Vælg et træningsdatasæt.
271 Data ready to be imported! Data er klar til at blive importeret!
Data has %s obs. of %s variables. Data har %s obs. på %s variabler.
272 Data successfully imported! Data successfully imported!
273 Click to see data Klik for at se data
274 No data present. Ingen data tilstede.
304 Sample data Sample data
305 Settings Settings
306 Create new factor Create new factor
Choose color palette Choose color palette
307 Optional filter logic (e.g., ⁠[gender] = 'female') Optional filter logic (e.g., ⁠[gender] = 'female')
308 Drop empty Drop empty
309 Choose variable: Choose variable:
310 An empty data set was imported. Please review data filter. An empty data set was imported. Please review data filter.
311 An error was encountered exporting data. Please review data filter. An error was encountered exporting data. Please review data filter.
312 Likert diagram Likert diagram
313 Modify factor Modify factor
314 Create factor/categorical variable from other variables. Create factor/categorical variable from other variables.
315 The data set has %s obs. in %s variables. The data set has %s obs. in %s variables.
316 Adjust plot input and settings below, then press "Plot". Adjust plot input and settings below, then press "Plot".
317 Define plot Define plot
318 Choose color palette Choose color palette
319 Additional variable Additional variable
320 Grouping variable Grouping variable
321 Secondary variable Secondary variable
322 Reverse colors Reverse colors
323 Plot survey results Plot survey results
324 Additional variables Additional variables
325 Other variables Other variables
326 Select variables and plot type,\nthen click 'Plot' to generate visualization Select variables and plot type,\nthen click 'Plot' to generate visualization

View file

@ -89,7 +89,6 @@
"and","na" "and","na"
"from each pair","kutoka kwa kila jozi" "from each pair","kutoka kwa kila jozi"
"Plot","Kipande cha habari" "Plot","Kipande cha habari"
"Adjust settings, then press ""Plot"".","Rekebisha mipangilio, kisha bonyeza ""Plot""."
"Plot height (mm)","Urefu wa kiwanja (mm)" "Plot height (mm)","Urefu wa kiwanja (mm)"
"Plot width (mm)","Upana wa kiwanja (mm)" "Plot width (mm)","Upana wa kiwanja (mm)"
"File format","Umbizo la faili" "File format","Umbizo la faili"
@ -97,12 +96,7 @@
"Select variable","Chagua kigezo" "Select variable","Chagua kigezo"
"Response variable","Kigezo cha majibu" "Response variable","Kigezo cha majibu"
"Plot type","Aina ya kiwanja" "Plot type","Aina ya kiwanja"
"Please select","Tafadhali chagua"
"Additional variables","Vigezo vya ziada"
"Secondary variable","Kigezo cha pili"
"No variable","Hakuna kigezo" "No variable","Hakuna kigezo"
"Grouping variable","Kigezo cha kuweka katika makundi"
"No stratification","Hakuna matabaka"
"Drawing the plot. Hold tight for a moment..","Kuchora njama. Shikilia kwa muda.." "Drawing the plot. Hold tight for a moment..","Kuchora njama. Shikilia kwa muda.."
"#Plotting\n","#Upangaji\n" "#Plotting\n","#Upangaji\n"
"Stacked horizontal bars","Pau za mlalo zilizopangwa kwa mpangilio" "Stacked horizontal bars","Pau za mlalo zilizopangwa kwa mpangilio"
@ -260,7 +254,6 @@
"FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR inapatikana katika lugha nyingi. Ili kukusaidia na tafsiri, tafadhali wasiliana nasi kwa info@freesearchr.org." "FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org","FreesearchR inapatikana katika lugha nyingi. Ili kukusaidia na tafsiri, tafadhali wasiliana nasi kwa info@freesearchr.org."
"Home","Nyumbani" "Home","Nyumbani"
"Start with FreesearchR for basic data evaluation and analysis.","Anza na FreesearchR kwa tathmini na uchambuzi wa data ya msingi." "Start with FreesearchR for basic data evaluation and analysis.","Anza na FreesearchR kwa tathmini na uchambuzi wa data ya msingi."
"When you need more advanced tools, you'll be better prepared to use R directly.","Unapohitaji zana za hali ya juu zaidi, utakuwa tayari zaidi kutumia R moja kwa moja."
"(Read more)","(Soma zaidi)" "(Read more)","(Soma zaidi)"
"Run the FreesearchR app locally when working with sensitive data.","Endesha programu ya FreesearchR ndani ya eneo lako unapofanya kazi na data nyeti." "Run the FreesearchR app locally when working with sensitive data.","Endesha programu ya FreesearchR ndani ya eneo lako unapofanya kazi na data nyeti."
"Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Pakia data kutoka kwa lahajedwali, seva za REDCap, au jaribu na data ya sampuli. Vyanzo vingi vinaungwa mkono kwa unyumbufu wa hali ya juu." "Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.","Pakia data kutoka kwa lahajedwali, seva za REDCap, au jaribu na data ya sampuli. Vyanzo vingi vinaungwa mkono kwa unyumbufu wa hali ya juu."
@ -271,14 +264,11 @@
"When you need more advanced tools, you'll be prepared to use R directly.","Unapohitaji zana za hali ya juu zaidi, utakuwa tayari kutumia R moja kwa moja." "When you need more advanced tools, you'll be prepared to use R directly.","Unapohitaji zana za hali ya juu zaidi, utakuwa tayari kutumia R moja kwa moja."
"The app contains a selelct number of features and will guide you through key analyses.","The app contains a selelct number of features and will guide you through key analyses." "The app contains a selelct number of features and will guide you through key analyses.","The app contains a selelct number of features and will guide you through key analyses."
"Sort by Levels","Sort by Levels" "Sort by Levels","Sort by Levels"
"Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Maximum number of observations:","Maximum number of observations:" "Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all" "setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package." "Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package." "Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!" "Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!" "Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data" "Click to see data","Click to see data"
"No data present.","No data present." "No data present.","No data present."
@ -314,10 +304,23 @@
"Sample data","Sample data" "Sample data","Sample data"
"Settings","Settings" "Settings","Settings"
"Create new factor","Create new factor" "Create new factor","Create new factor"
"Choose color palette","Choose color palette"
"Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')" "Optional filter logic (e.g., [gender] = 'female')","Optional filter logic (e.g., [gender] = 'female')"
"Drop empty","Drop empty" "Drop empty","Drop empty"
"Choose variable:","Choose variable:" "Choose variable:","Choose variable:"
"An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter." "An empty data set was imported. Please review data filter.","An empty data set was imported. Please review data filter."
"An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter." "An error was encountered exporting data. Please review data filter.","An error was encountered exporting data. Please review data filter."
"Likert diagram","Likert diagram" "Likert diagram","Likert diagram"
"Modify factor","Modify factor"
"Create factor/categorical variable from other variables.","Create factor/categorical variable from other variables."
"The data set has %s obs. in %s variables.","The data set has %s obs. in %s variables."
"Adjust plot input and settings below, then press ""Plot"".","Adjust plot input and settings below, then press ""Plot""."
"Define plot","Define plot"
"Choose color palette","Choose color palette"
"Additional variable","Additional variable"
"Grouping variable","Grouping variable"
"Secondary variable","Secondary variable"
"Reverse colors","Reverse colors"
"Plot survey results","Plot survey results"
"Additional variables","Additional variables"
"Other variables","Other variables"
"Select variables and plot type,\nthen click 'Plot' to generate visualization","Select variables and plot type,\nthen click 'Plot' to generate visualization"

1 en sw
89 and na
90 from each pair kutoka kwa kila jozi
91 Plot Kipande cha habari
Adjust settings, then press "Plot". Rekebisha mipangilio, kisha bonyeza "Plot".
92 Plot height (mm) Urefu wa kiwanja (mm)
93 Plot width (mm) Upana wa kiwanja (mm)
94 File format Umbizo la faili
96 Select variable Chagua kigezo
97 Response variable Kigezo cha majibu
98 Plot type Aina ya kiwanja
Please select Tafadhali chagua
Additional variables Vigezo vya ziada
Secondary variable Kigezo cha pili
99 No variable Hakuna kigezo
Grouping variable Kigezo cha kuweka katika makundi
No stratification Hakuna matabaka
100 Drawing the plot. Hold tight for a moment.. Kuchora njama. Shikilia kwa muda..
101 #Plotting\n #Upangaji\n
102 Stacked horizontal bars Pau za mlalo zilizopangwa kwa mpangilio
254 FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org FreesearchR inapatikana katika lugha nyingi. Ili kukusaidia na tafsiri, tafadhali wasiliana nasi kwa info@freesearchr.org.
255 Home Nyumbani
256 Start with FreesearchR for basic data evaluation and analysis. Anza na FreesearchR kwa tathmini na uchambuzi wa data ya msingi.
When you need more advanced tools, you'll be better prepared to use R directly. Unapohitaji zana za hali ya juu zaidi, utakuwa tayari zaidi kutumia R moja kwa moja.
257 (Read more) (Soma zaidi)
258 Run the FreesearchR app locally when working with sensitive data. Endesha programu ya FreesearchR ndani ya eneo lako unapofanya kazi na data nyeti.
259 Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility. Pakia data kutoka kwa lahajedwali, seva za REDCap, au jaribu na data ya sampuli. Vyanzo vingi vinaungwa mkono kwa unyumbufu wa hali ya juu.
264 When you need more advanced tools, you'll be prepared to use R directly. Unapohitaji zana za hali ya juu zaidi, utakuwa tayari kutumia R moja kwa moja.
265 The app contains a selelct number of features and will guide you through key analyses. The app contains a selelct number of features and will guide you through key analyses.
266 Sort by Levels Sort by Levels
Modify factor levels Modify factor levels
Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
267 Maximum number of observations: Maximum number of observations:
268 setting to 0 includes all setting to 0 includes all
269 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
270 Select a sample dataset from a package. Select a sample dataset from a package.
271 Data ready to be imported! Data ready to be imported!
Data has %s obs. of %s variables. Data has %s obs. of %s variables.
272 Data successfully imported! Data successfully imported!
273 Click to see data Click to see data
274 No data present. No data present.
304 Sample data Sample data
305 Settings Settings
306 Create new factor Create new factor
Choose color palette Choose color palette
307 Optional filter logic (e.g., ⁠[gender] = 'female') Optional filter logic (e.g., ⁠[gender] = 'female')
308 Drop empty Drop empty
309 Choose variable: Choose variable:
310 An empty data set was imported. Please review data filter. An empty data set was imported. Please review data filter.
311 An error was encountered exporting data. Please review data filter. An error was encountered exporting data. Please review data filter.
312 Likert diagram Likert diagram
313 Modify factor Modify factor
314 Create factor/categorical variable from other variables. Create factor/categorical variable from other variables.
315 The data set has %s obs. in %s variables. The data set has %s obs. in %s variables.
316 Adjust plot input and settings below, then press "Plot". Adjust plot input and settings below, then press "Plot".
317 Define plot Define plot
318 Choose color palette Choose color palette
319 Additional variable Additional variable
320 Grouping variable Grouping variable
321 Secondary variable Secondary variable
322 Reverse colors Reverse colors
323 Plot survey results Plot survey results
324 Additional variables Additional variables
325 Other variables Other variables
326 Select variables and plot type,\nthen click 'Plot' to generate visualization Select variables and plot type,\nthen click 'Plot' to generate visualization

View file

@ -1,10 +1,10 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{align_axes} \name{align_axes}
\alias{align_axes} \alias{align_axes}
\title{Aligns axes between plots} \title{Aligns axes between plots}
\usage{ \usage{
align_axes(..., x.axis = TRUE, y.axis = TRUE) align_axes(..., x.axis = TRUE, y.axis = TRUE, percentage = FALSE)
} }
\arguments{ \arguments{
\item{...}{ggplot2 objects or list of ggplot2 objects} \item{...}{ggplot2 objects or list of ggplot2 objects}

View file

@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{all_but} \name{all_but}
\alias{all_but} \alias{all_but}
\title{Select all from vector but} \title{Select all from vector but}

27
man/available_plots.Rd Normal file
View file

@ -0,0 +1,27 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot-helpers.R
\name{available_plots}
\alias{available_plots}
\title{Implemented functions}
\usage{
available_plots()
}
\value{
list
}
\description{
Library of supported functions. The list name and "descr" element should be
unique for each element on list.
\itemize{
\item fun: the plotting function
\item fun.args: default parameters for the plotting function
\item descr: Plot description
\item note: Short note/description of the function for displaying in ui and docs
\item primary.type: Primary variable data type (see \link{data_type})
\item base: holds a list of parameters for plot input fields generation
Secondary and tertiary variable input fields are mandatory.
}
}
\examples{
available_plots() |> str()
}

View file

@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{clean_common_axis} \name{clean_common_axis}
\alias{clean_common_axis} \alias{clean_common_axis}
\title{Extract and clean axis ranges} \title{Extract and clean axis ranges}

View file

@ -1,12 +1,13 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R, R/plot_bar.R, R/plot_box.R, % Please edit documentation in R/data_plots.R, R/plot-helpers.R, R/plot_bar.R,
% R/plot_hbar.R, R/plot_likert.R, R/plot_ridge.R, R/plot_sankey.R, % R/plot_box.R, R/plot_hbar.R, R/plot_likert.R, R/plot_ridge.R,
% R/plot_scatter.R, R/plot_violin.R % R/plot_sankey.R, R/plot_scatter.R, R/plot_violin.R
\name{data-plots} \name{data-plots}
\alias{data-plots} \alias{data-plots}
\alias{data_visuals_ui} \alias{data_visuals_ui}
\alias{data_visuals_server} \alias{data_visuals_server}
\alias{create_plot} \alias{create_plot}
\alias{plot_bar}
\alias{plot_bar_single} \alias{plot_bar_single}
\alias{plot_box} \alias{plot_box}
\alias{plot_box_single} \alias{plot_box_single}
@ -21,10 +22,21 @@
\usage{ \usage{
data_visuals_ui(id, tab_title = "Plots", ...) data_visuals_ui(id, tab_title = "Plots", ...)
data_visuals_server(id, data, palettes, ...) data_visuals_server(id, data, palettes = color_choices(), ...)
create_plot(data, type, pri, sec, ter = NULL, color.palette = "viridis", ...) create_plot(data, type, pri, sec, ter = NULL, color.palette = "viridis", ...)
plot_bar(
data,
pri,
sec = NULL,
ter = NULL,
style = c("stack", "dodge", "fill"),
color.palette = "viridis",
max_level = 30,
...
)
plot_bar_single( plot_bar_single(
data, data,
pri, pri,
@ -38,9 +50,9 @@ plot_box(data, pri, sec, ter = NULL, color.palette = "viridis", ...)
plot_box_single(data, pri, sec = NULL, seed = 2103, color.palette = "viridis") plot_box_single(data, pri, sec = NULL, seed = 2103, color.palette = "viridis")
plot_hbars(data, pri, sec, ter = NULL, color.palette = "viridis") plot_hbars(data, pri, sec, ter = NULL, color.palette = "viridis", ...)
plot_likert(data, pri, sec = NULL, ter = NULL, color.palette = "viridis") plot_likert(data, pri, sec = NULL, ter = NULL, color.palette = "viridis", ...)
plot_ridge(data, x, y, z = NULL, color.palette = "viridis", ...) plot_ridge(data, x, y, z = NULL, color.palette = "viridis", ...)
@ -57,12 +69,13 @@ plot_sankey(
default.color = "#2986cc", default.color = "#2986cc",
box.color = "#1E4B66", box.color = "#1E4B66",
na.color = "grey80", na.color = "grey80",
missing.level = "Missing" missing.level = "Missing",
...
) )
plot_scatter(data, pri, sec, ter = NULL, color.palette = "viridis") plot_scatter(data, pri, sec, ter = NULL, color.palette = "viridis", ...)
plot_violin(data, pri, sec, ter = NULL, color.palette = "viridis") plot_violin(data, pri, sec, ter = NULL, color.palette = "viridis", ...)
} }
\arguments{ \arguments{
\item{id}{Module id. (Use 'ns("id")')} \item{id}{Module id. (Use 'ns("id")')}
@ -91,6 +104,8 @@ shiny server module
ggplot2 object ggplot2 object
ggplot list object
ggplot object ggplot object
ggplot2 object ggplot2 object
@ -116,6 +131,8 @@ Data correlations evaluation module
Wrapper to create plot based on provided type Wrapper to create plot based on provided type
Title
Single vertical barplot Single vertical barplot
Beautiful box plot(s) Beautiful box plot(s)
@ -138,6 +155,13 @@ Beautiful violin plot
} }
\examples{ \examples{
create_plot(mtcars, "plot_violin", "mpg", "cyl") |> attributes() create_plot(mtcars, "plot_violin", "mpg", "cyl") |> attributes()
mtcars |>
dplyr::mutate(cyl = factor(cyl), am = factor(am)) |>
plot_bar(pri = "cyl", sec = "am", style = "fill")
mtcars |>
dplyr::mutate(dplyr::across(tidyselect::all_of(c("cyl","am","gear")),factor)) |>
plot_bar(pri = "cyl", sec = "gear", ter = "am", style = "stack",color.palette="turbo")
mtcars |> mtcars |>
dplyr::mutate(cyl = factor(cyl), am = factor(am)) |> dplyr::mutate(cyl = factor(cyl), am = factor(am)) |>
plot_bar_single(pri = "cyl", sec = "am", style = "fill") plot_bar_single(pri = "cyl", sec = "am", style = "fill")

27
man/get_input_params.Rd Normal file
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@ -0,0 +1,27 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot-helpers.R
\name{get_input_params}
\alias{get_input_params}
\title{Get the function parameters based on the selected function description}
\usage{
get_input_params(data)
}
\arguments{
\item{data}{vector}
}
\value{
list
}
\description{
Get the function parameters based on the selected function description
}
\examples{
ls <- mtcars |>
default_parsing() |>
dplyr::pull(mpg) |>
possible_plots() |>
(\(.x){
.x[[1]]
})() |>
get_input_params()
}

View file

@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{get_label} \name{get_label}
\alias{get_label} \alias{get_label}
\title{Print label, and if missing print variable name for plots} \title{Print label, and if missing print variable name for plots}

View file

@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{get_plot_options} \name{get_plot_options}
\alias{get_plot_options} \alias{get_plot_options}
\title{Get the function options based on the selected function description} \title{Get the function options based on the selected function description}

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@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{line_break} \name{line_break}
\alias{line_break} \alias{line_break}
\title{Line breaking at given number of characters for nicely plotting labels} \title{Line breaking at given number of characters for nicely plotting labels}

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@ -4,7 +4,7 @@
\alias{plot_euler_single} \alias{plot_euler_single}
\title{Easily plot single euler diagrams} \title{Easily plot single euler diagrams}
\usage{ \usage{
plot_euler_single(data, color.palette = "viridis") plot_euler_single(data, color.palette = "viridis", ...)
} }
\value{ \value{
ggplot2 object ggplot2 object

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@ -1,10 +1,10 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{possible_plots} \name{possible_plots}
\alias{possible_plots} \alias{possible_plots}
\title{Get possible regression models} \title{Get possible regression models}
\usage{ \usage{
possible_plots(data) possible_plots(data, source_list = supported_plots())
} }
\arguments{ \arguments{
\item{data}{data} \item{data}{data}

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@ -0,0 +1,11 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot-helpers.R
\name{selectPlotVariables}
\alias{selectPlotVariables}
\title{Wrapper for columnSelectInput}
\usage{
selectPlotVariables(data, exclude = NULL, allow_none = TRUE, var_types, ...)
}
\description{
Wrapper for columnSelectInput
}

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@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{subset_types} \name{subset_types}
\alias{subset_types} \alias{subset_types}
\title{Easily subset by data type function} \title{Easily subset by data type function}

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@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{supported_plots} \name{supported_plots}
\alias{supported_plots} \alias{supported_plots}
\title{Implemented functions} \title{Implemented functions}

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@ -1,5 +1,5 @@
% Generated by roxygen2: do not edit by hand % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_plots.R % Please edit documentation in R/plot-helpers.R
\name{wrap_plot_list} \name{wrap_plot_list}
\alias{wrap_plot_list} \alias{wrap_plot_list}
\title{Wrapping} \title{Wrapping}
@ -12,6 +12,7 @@ wrap_plot_list(
guides = "collect", guides = "collect",
axes = "collect", axes = "collect",
axis_titles = "collect", axis_titles = "collect",
y.axis.percentage = FALSE,
... ...
) )
} }