Example gallery

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Example gallery

This gallery shows several ways to use DonutMap. All locations, category values, and links are simulated for demonstration. They are not observed data.

Shared data

The examples use a small synthetic network of locations in eastern Canada. The background layer is a simple sf polygon created inside the vignette, so the gallery does not depend on an external map download.

locations <- data.frame(
  place = c("Hub A", "Hub B", "Hub C", "Hub D", "Hub E", "Hub F"),
  lon = c(-73.6, -72.9, -71.4, -70.8, -69.4, -67.8),
  lat = c(45.5, 46.2, 46.8, 47.7, 48.5, 49.2)
)

categories <- c("Local", "Regional", "Remote")

donut_data <- merge(
  locations,
  data.frame(category = categories),
  by = NULL
)

donut_data$value <- c(
  42, 32, 18,
  28, 64, 22,
  30, 54, 40,
  26, 45, 58,
  20, 38, 72,
  16, 30, 88
)

donut_data$category <- factor(donut_data$category, levels = categories)

flows <- data.frame(
  from = c(
    "Hub A", "Hub A", "Hub B", "Hub B", "Hub C",
    "Hub C", "Hub D", "Hub E", "Hub F"
  ),
  to = c(
    "Hub B", "Hub C", "Hub C", "Hub D", "Hub D",
    "Hub E", "Hub E", "Hub F", "Hub C"
  ),
  volume = c(120, 85, 95, 60, 130, 75, 90, 50, 70),
  corridor = c(
    "Local", "Regional", "Local", "Remote", "Regional",
    "Remote", "Local", "Remote", "Regional"
  )
)

category_colours <- c(
  Local = "#1b9e77",
  Regional = "#7570b3",
  Remote = "#d95f02"
)

background <- sf::st_as_sfc(
  sf::st_bbox(
    c(xmin = -74.5, ymin = 44.8, xmax = -66.8, ymax = 50.0),
    crs = sf::st_crs(4326)
  )
)

study_area <- sf::st_sf(
  area = "Simulated study area",
  geometry = background
)

1. Static donuts without links

Use donut_map() without flows when the goal is to compare compositions at locations.

donut_map(
  donut_data,
  place,
  category,
  value,
  lon = lon,
  lat = lat,
  map = study_area,
  crs = 3347,
  radius_range = c(18000, 52000),
  colours = category_colours
) +
  labs(
    title = "Compositions only",
    fill = "Category"
  ) +
  theme(legend.position = "right")

2. Static map with curved coloured links

Supplying flows, from, to, and flow_value draws links between donuts. The flow_group and flow_colours arguments colour the links and arrows by a categorical flow variable.

donut_map(
  donut_data,
  place,
  category,
  value,
  lon = lon,
  lat = lat,
  map = study_area,
  crs = 3347,
  radius_range = c(18000, 52000),
  colours = category_colours,
  flows = flows,
  from = from,
  to = to,
  flow_value = volume,
  flow_group = corridor,
  flow_colours = category_colours,
  flow_curvature = 0.25,
  flow_linewidth_range = c(0.3, 2.4),
  flow_arrow = TRUE
) +
  labs(
    title = "Curved links coloured by corridor",
    fill = "Donut category",
    linewidth = "Volume"
  ) +
  theme(legend.position = "right")

3. Straight links

Use flow_curvature = 0 for direct straight links. This is often useful for small networks where curved trajectories would add visual clutter.

donut_map(
  donut_data,
  place,
  category,
  value,
  lon = lon,
  lat = lat,
  map = study_area,
  crs = 3347,
  radius_range = c(18000, 52000),
  colours = category_colours,
  flows = flows,
  from = from,
  to = to,
  flow_value = volume,
  flow_group = corridor,
  flow_colours = category_colours,
  flow_curvature = 0,
  flow_linewidth_range = c(0.3, 2.4),
  flow_arrow = TRUE
) +
  labs(
    title = "Straight links",
    fill = "Donut category",
    linewidth = "Volume"
  ) +
  theme(legend.position = "right")

4. Interactive map with filtered links

donut_leaflet() creates a clickable leaflet widget. The flow_min argument keeps only larger flows, which can make dense networks easier to read.

donut_leaflet(
  donut_data,
  place,
  category,
  value,
  lon = lon,
  lat = lat,
  map = study_area,
  radius_range = c(18000, 52000),
  colours = category_colours,
  flows = flows,
  from = from,
  to = to,
  flow_value = volume,
  flow_group = corridor,
  flow_colours = category_colours,
  flow_min = 80,
  flow_weight_range = c(1, 7),
  flow_curvature = 0.25,
  flow_arrow = TRUE,
  flow_arrow_size = 35000,
  flow_opacity = 0.8
)

5. Geometry-first workflow

For more customized maps, compute the sf layers first and then plot or transform them yourself.

donut_layer <- donut_polygons(
  donut_data,
  place,
  category,
  value,
  lon = lon,
  lat = lat,
  crs = 3347,
  radius_range = c(18000, 52000)
)

flow_layer <- flow_lines(
  flows,
  donut_data,
  from,
  to,
  volume,
  place,
  group = corridor,
  lon = lon,
  lat = lat,
  crs = 3347,
  flow_curvature = -0.18,
  flow_n = 50
)

ggplot() +
  geom_sf(
    data = flow_layer,
    aes(linewidth = value, colour = group),
    alpha = 0.7
  ) +
  geom_sf(data = donut_layer, aes(fill = category), colour = "white") +
  scale_colour_manual(values = category_colours) +
  scale_fill_manual(values = category_colours) +
  coord_sf(datum = NA) +
  labs(
    title = "Custom map from sf layers",
    colour = "Flow group",
    fill = "Donut category",
    linewidth = "Volume"
  ) +
  theme_minimal()

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.