Grid-based choropleth layer — viz

The gridchoro function builds a choropleth map based on a spatial grid aggregation. It first generates a grid from the input spatial data frame, aggregates values within each cell, and maps them using a color classification.

Usage

viz_gridchoro(
  map,
  data = NULL,
  var,
  grid = "square",
  step = 15,
  level = 1,
  ratio_factor = 1,
  coords = "geo",
  missing = "white",
  fixmax = NULL,
  legend = TRUE,
  leg_type = "vertical",
  leg_pos = c(10, 10),
  ...
)

Arguments

map: A geoviz map created with viz_create.
data: A spatial dataframe Use data to enable iteration over features.
var: character or character vector. Variable(s) used for aggregation. If two variables are provided, a ratio is computed.
grid: character. Optional. Type of grid used for aggregation (default "square"). One of: "square", "dot", "diamond", "hexbin", "hex", "triangle", "arbitrary", "random", "h3", "h3geo", "hexgeo", "hexbingeo", "square_sph".
step: numeric. Optional. Grid resolution (default 15).
level: numeric. Optional. Subdivision level for hierarchical grids (default 1).
ratio_factor: numeric. Optional. Multiplication factor applied to ratio values (default 1).
coords: character. Optional. Coordinate system (default "geo"). One of: "geo", "svg".
missing: character. Optional. Fill color for missing values (default "white").
fixmax: numeric. Optional. Maximum value for color scaling. Useful for map comparability.
legend: logical. Optional. Whether to display legend (default TRUE).
leg_type: character. Optional. Legend type (default "vertical"). One of: "horizontal", "vertical".
leg_pos: numeric vector. Optional. Legend position (default c(10, 10)).
...: Additional parameters passed to choropleth rendering (same as viz_choro). With the leg_ prefix, you can configure the legend. For example: leg_title, leg_subtitle, leg_note, etc.

Examples

library(sf)
world <- st_read(
  system.file("gpkg/world.gpkg", package = "geoviz"),
  quiet = TRUE
)
cities <- st_read(
  system.file("gpkg/cities.gpkg", package = "geoviz"),
  quiet = TRUE
)

viz_create(projection = "EqualEarth") |>
viz_path(datum = world, fill = "#f1f3f5") |>
viz_gridchoro(data = cities, var = "population") |>
viz_render()