Waterfall missing

R/plotly_build.R

@@ -226,7 +226,9 @@ plotly_build.plotly <- function(p, registerFrames = TRUE) {
       # 3. The grouping from (2) and any groups detected via dplyr::groups()
       #    are combined into a single grouping variable, .plotlyGroupIndex
       builtData <- arrange_safe(builtData, ".plotlyTraceIndex")
-      isComplete <- complete.cases(builtData[names(builtData) %in% c("x", "y", "z")])
+      # Missing values have special meaning for waterfall
+      vars <- if (trace$type != "waterfall") c("x", "y", "z")
+      isComplete <- complete.cases(builtData[names(builtData) %in% vars])
       # warn about missing values if groups aren't relevant for this trace type
       if (any(!isComplete) && !has_group(trace)) {
         warning("Ignoring ", sum(!isComplete), " observations", call. = FALSE)

tests/testthat/test-plotly-waterfall.R

@@ -11,4 +11,20 @@ test_that("Simple waterfall works", {
   expect_doppelganger_built(p, "waterfall-simple")
 })
 
+test_that("Waterfall missing values are retained", {
+  y <- c("Sales", "Consulting", "Maintenance", "Other revenue", "Net revenue", "Purchases", "Material expenses", "Personnel expenses", "Other expenses", "Operating profit", "Investment income", "Financial income", "Profit before tax", "Income tax (15%)", "Profit after tax")
+
+  d <- data.frame(
+    measure = c("relative", "relative", "relative", "relative", "total", "relative", "relative", "relative", "relative", "total", "relative", "relative", "total", "relative", "total"),
+    y = factor(y, levels = y),
+    x = c(375, 128, 78, 27, NA, -327, -12, -78, -12, NA, 32, 89, NA, -45, NA)
+  )
+
+  p <- plot_ly(d, measure = ~measure, y = ~y, x = ~x) %>%
+    add_trace(type = "waterfall", orientation = "h") %>%
+    layout(yaxis = list(autorange = "reversed"))
+
+  expect_doppelganger_built(p, "waterfall-missing-values")
+})
+