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feat: new cut option to simplify factors to only the top N levels

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Andreas Gammelgaard Damsbo 2025-10-21 21:30:07 +03:00
commit 0c2b061708
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12 changed files with 337 additions and 236 deletions
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17
R/plot_sankey.R
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@ -83,7 +83,7 @@ str_remove_last <- function(data, pattern = "\n") {
#' mtcars |>
#' default_parsing() |>
#' plot_sankey("cyl", "gear", "vs", color.group = "pri")
plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors = NULL) {
plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors = NULL,missing.level="Missing") {
if (!is.null(ter)) {
ds <- split(data, data[ter])
} else {
@ -91,7 +91,7 @@ plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors
}
out <- lapply(ds, \(.ds){
plot_sankey_single(.ds, pri = pri, sec = sec, color.group = color.group, colors = colors)
plot_sankey_single(.ds, pri = pri, sec = sec, color.group = color.group, colors = colors,missing.level=missing.level)
})
patchwork::wrap_plots(out)
@ -120,14 +120,21 @@ plot_sankey <- function(data, pri, sec, ter = NULL, color.group = "pri", colors
#' mtcars |>
#' default_parsing() |>
#' plot_sankey_single("cyl", "vs", color.group = "pri")
plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), colors = NULL, ...) {
#' stRoke::trial |>
#' default_parsing() |>
#' plot_sankey_single("diabetes", "hypertension")
plot_sankey_single <- function(data, pri, sec, color.group = c("pri", "sec"), colors = NULL,missing.level="Missing", ...) {
color.group <- match.arg(color.group)
browser()
data_orig <- data
data[c(pri, sec)] <- data[c(pri, sec)] |>
dplyr::mutate(dplyr::across(dplyr::where(is.factor), forcats::fct_drop))
dplyr::mutate(
# dplyr::across(dplyr::where(is.logical), as.factor),
dplyr::across(dplyr::where(is.factor), forcats::fct_drop)#,
# dplyr::across(dplyr::where(is.factor), \(.x){forcats::fct_na_value_to_level(.x,missing.level)})
)
# browser()
data <- data |> sankey_ready(pri = pri, sec = sec, ...)