diff --git a/R/plot-helpers.R b/R/plot-helpers.R
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+#' 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 = 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_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()
+}