e_scatter_3d(
  e,
  y,
  z,
  color,
  size,
  bind,
  coord_system = "cartesian3D",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  legend = FALSE,
  ...
)

e_scatter_3d_(
  e,
  y,
  z,
  color = NULL,
  size = NULL,
  bind = NULL,
  coord_system = "cartesian3D",
  name = NULL,
  rm_x = TRUE,
  rm_y = TRUE,
  legend = FALSE,
  ...
)

v <- LETTERS[1:10]
matrix <- data.frame(
  x = sample(v, 300, replace = TRUE),
  y = sample(v, 300, replace = TRUE),
  z = rnorm(300, 10, 1),
  color = rnorm(300, 10, 1),
  size = rnorm(300, 10, 1),
  stringsAsFactors = FALSE
) %>%
  dplyr::group_by(x, y) %>%
  dplyr::summarise(
    z = sum(z),
    color = sum(color),
    size = sum(size)
  ) %>%
  dplyr::ungroup()

matrix %>%
  e_charts(x) %>%
  e_scatter_3d(y, z, size, color) %>%
  e_visual_map(
    min = 1,
    max = 100,
    inRange = list(symbolSize = c(1, 30)),
    # scale size
    dimension = 3 # third dimension 0 = x, y = 1, z = 2, size = 3
  ) %>%
  e_visual_map(
    min = 1,
    max = 100,
    inRange = list(color = c("#bf444c", "#d88273", "#f6efa6")),
    # scale colors
    dimension = 4,
    # third dimension 0 = x, y = 1, z = 2, size = 3, color = 4
    bottom = 300 # padding to avoid visual maps overlap
  )

airports <- read.csv(
  paste0(
    "https://raw.githubusercontent.com/plotly/datasets/",
    "master/2011_february_us_airport_traffic.csv"
  )
)

airports %>%
  e_charts(long) %>%
  e_globe(
    globeOuterRadius = 100
  ) %>%
  e_scatter_3d(lat, cnt, coord_system = "globe", blendMode = "lighter") %>%
  e_visual_map(inRange = list(symbolSize = c(1, 10)))

# timeline
airports %>%
  group_by(state) %>%
  e_charts(long, timeline = TRUE) %>%
  e_globe(
    globeOuterRadius = 100
  ) %>%
  e_scatter_3d(lat, cnt, coord_system = "globe", blendMode = "lighter") %>%
  e_visual_map(inRange = list(symbolSize = c(1, 10)))