Fix #2305: geom_boxplot outlier.shape=NA now hides outlier points

The geom2trace.GeomBoxplot function now checks for:
- outliers = FALSE parameter
- outlier.shape = NA (via params$outlier_gp$shape in newer ggplot2)

When either condition is true, boxpoints is set to FALSE in the plotly
trace to hide outlier points.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: cpsievert

R/layers2traces.R

@@ -872,6 +872,12 @@ geom2trace.GeomBoxplot <- function(data, params, p) {
   # marker styling must inherit from GeomPoint$default_aes
   # https://github.com/hadley/ggplot2/blob/ab42c2ca81458b0cf78e3ba47ed5db21f4d0fc30/NEWS#L73-L7
   point_defaults <- GeomPoint$use_defaults(NULL)
+
+  # Determine if outliers should be hidden
+  # Hide outliers if: outliers = FALSE, or outlier.shape = NA (via outlier_gp$shape)
+  hide_outliers <- isFALSE(params$outliers) ||
+    isTRUE(is.na(params$outlier_gp$shape))
+
   compact(list(
     x = data[["x"]],
     y = data[["y"]],
@@ -885,6 +891,8 @@ geom2trace.GeomBoxplot <- function(data, params, p) {
       aes2plotly(data, params, "fill"),
       aes2plotly(data, params, "alpha")
     ),
+    # Control whether outlier points are shown
+    boxpoints = if (hide_outliers) FALSE else "outliers",
     # markers/points
     marker = list(
       opacity = point_defaults$alpha,

tests/testthat/test-ggplot-boxplot.R

@@ -83,3 +83,29 @@ test_that("correct # of unique fillcolors", {
   fills <- sapply(L$data, "[[", "fillcolor")
   expect_equivalent(length(unique(fills)), length(unique(dat$col)))
 })
+
+test_that("outlier.shape = NA hides outlier points (#2305)", {
+  # With outlier.shape = NA, plotly should not show outlier points
+  p <- ggplot(iris, aes(Species, Sepal.Length)) + geom_boxplot(outlier.shape = NA)
+  L <- plotly_build(ggplotly(p))$x
+  expect_equal(L$data[[1]]$type, "box")
+  # boxpoints should be FALSE or "false" to hide outliers
+  expect_true(isFALSE(L$data[[1]]$boxpoints) || identical(L$data[[1]]$boxpoints, "false"))
+
+  # With default (no outlier.shape specified), outliers should show
+  p_default <- ggplot(iris, aes(Species, Sepal.Length)) + geom_boxplot()
+  L_default <- plotly_build(ggplotly(p_default))$x
+  # Default should either be NULL (plotly default shows outliers) or "outliers"/"suspectedoutliers"
+  expect_true(
+    is.null(L_default$data[[1]]$boxpoints) ||
+    L_default$data[[1]]$boxpoints %in% c("outliers", "suspectedoutliers", TRUE)
+  )
+})
+
+test_that("outliers = FALSE hides outlier points", {
+  # ggplot2 also supports outliers = FALSE parameter
+  p <- ggplot(iris, aes(Species, Sepal.Length)) + geom_boxplot(outliers = FALSE)
+  L <- plotly_build(ggplotly(p))$x
+  expect_equal(L$data[[1]]$type, "box")
+  expect_true(isFALSE(L$data[[1]]$boxpoints) || identical(L$data[[1]]$boxpoints, "false"))
+})