Add the autohide argument to cols_nanoplot()

R/modify_columns.R

@@ -2252,6 +2252,16 @@ cols_add <- function(
 #'   *x*-axis data), which is useful in those cases where the nanoplot data
 #'   should be compared across rows.
 #'
+#' @param autohide *Automatically hide the `columns`/`columns_x_vals` column(s)*
+#'
+#'   `scalar<logical>` // *default:* `TRUE`
+#'
+#'   An option to automatically hide any columns specified in `columns` and also
+#'   `columns_x_vals` (if used). Any columns with their state changed to
+#'   'hidden' will behave the same as before, they just won't be displayed in
+#'   the finalized table. Should you want to have these 'input' columns be
+#'   viewable, set `autohide = FALSE`.
+#'
 #' @param columns_x_vals *Columns containing values for the optional x variable*
 #'
 #'   `<column-targeting expression>` // *default:* `NULL` (`optional`)
@@ -2428,7 +2438,7 @@ cols_add <- function(
 #'   gt(rowname_col = "test") |>
 #'   tab_header("Partial summary of daily tests performed on YF patient") |>
 #'   tab_stubhead(label = md("**Test**")) |>
-#'   cols_hide(columns = c(starts_with("norm"), starts_with("day"))) |>
+#'   cols_hide(columns = starts_with("norm")) |>
 #'   fmt_units(columns = units) |>
 #'   cols_nanoplot(
 #'     columns = starts_with("day"),
@@ -2472,6 +2482,7 @@ cols_add <- function(
 #'   cols_nanoplot(
 #'     columns = c(chicken, classic, supreme, veggie),
 #'     plot_type = "bar",
+#'     autohide = FALSE,
 #'     new_col_name = "pizzas_sold",
 #'     new_col_label = "Sales by Type",
 #'     options = nanoplot_options(
@@ -2512,12 +2523,14 @@ cols_add <- function(
 #'   cols_nanoplot(
 #'     columns = starts_with("population"),
 #'     reference_line = "median",
+#'     autohide = FALSE,
 #'     new_col_name = "population_plot",
 #'     new_col_label = md("*Change*")
 #'   ) |>
 #'   cols_nanoplot(
 #'     columns = starts_with("density"),
 #'     plot_type = "bar",
+#'     autohide = FALSE,
 #'     new_col_name = "density_plot",
 #'     new_col_label = md("*Change*")
 #'   ) |>
@@ -2585,7 +2598,6 @@ cols_add <- function(
 #'       data_bar_fill_color = "DarkOrange"
 #'     )
 #'   ) |>
-#'   cols_hide(columns = matches("0")) |>
 #'   tab_options(
 #'     table.width = px(400),
 #'     column_labels.hidden = TRUE
@@ -2637,7 +2649,6 @@ cols_add <- function(
 #'     title = md("Pizzas sold on **January 1, 2015**"),
 #'     subtitle = "Between the opening hours of 11:30 to 22:30"
 #'   ) |>
-#'   cols_hide(columns = c(date_time, sold)) |>
 #'   cols_nanoplot(
 #'     columns = sold,
 #'     columns_x_vals = date_time,
@@ -2695,7 +2706,7 @@ cols_add <- function(
 #'     plot_type = "boxplot",
 #'     options = nanoplot_options(y_val_fmt_fn = function(x) hms::as_hms(x))
 #'   ) |>
-#'   cols_hide(columns = c(time, is_weekend)) |>
+#'   cols_hide(columns = is_weekend) |>
 #'   cols_width(everything() ~ px(250)) |>
 #'   cols_align(align = "center", columns = nanoplots) |>
 #'   cols_align(align = "left", columns = date) |>
@@ -2733,6 +2744,7 @@ cols_nanoplot <- function(
     plot_height = "2em",
     missing_vals = c("gap", "zero", "remove"),
     autoscale = FALSE,
+    autohide = TRUE,
     columns_x_vals = NULL,
     reference_line = NULL,
     reference_area = NULL,
@@ -2986,6 +2998,24 @@ cols_nanoplot <- function(
       locations = cells_body(columns = validated_new_col_name)
     )
 
+  if (isTRUE(autohide)) {
+
+    data <-
+      cols_hide(
+        data = data,
+        columns = resolved_columns
+      )
+
+    if (length(resolved_columns_x) > 0) {
+
+      data <-
+        cols_hide(
+          data = data,
+          columns = resolved_columns_x
+        )
+    }
+  }
+
   data
 }