addClusterCharts

Clusters markers on a Leaflet map and visualizes them using customizable charts, such as pie or bar charts, showing counts by category. When using the "custom" type, a pie chart is rendered with aggregated data, employing methods like sum, min, max, mean, or median.

Usage

addClusterCharts(
  map,
  layerId = NULL,
  group = NULL,
  type = c("pie", "bar", "horizontal", "custom"),
  aggregation = c("sum", "min", "max", "mean", "median"),
  valueField = NULL,
  options = clusterchartOptions(),
  icon = NULL,
  html = NULL,
  popup = NULL,
  popupOptions = NULL,
  label = NULL,
  labelOptions = NULL,
  clusterOptions = NULL,
  clusterId = NULL,
  categoryField,
  categoryMap,
  popupFields = NULL,
  popupLabels = NULL,
  markerOptions = NULL,
  legendOptions = list(title = "", position = "topright"),
  data = getMapData(map)
)

Arguments

map: a map widget object created from leaflet()
layerId: the layer id
group: the name of the group the newly created layers should belong to (for clearGroup and addLayersControl purposes). Human-friendly group names are permitted–they need not be short, identifier-style names. Any number of layers and even different types of layers (e.g. markers and polygons) can share the same group name.
type: The type of chart to use for clusters: "pie", "bar", "horizontal", or "custom".
aggregation: Aggregation method for "custom" charts (e.g., sum, min, max, mean, median).
valueField: Column name with values to aggregate for "custom" charts.
options: Additional options for cluster charts (see clusterchartOptions).
icon: An icon or set of icons to include, created with makeIcon or iconList.
html: The column name containing the HTML content to include in the markers.
popup: The column name used to retrieve feature properties for the popup.
popupOptions: A Vector of popupOptions to provide popups
label: a character vector of the HTML content for the labels
labelOptions: A Vector of labelOptions to provide label options for each label. Default NULL
clusterOptions: if not NULL, markers will be clustered using Leaflet.markercluster; you can use markerClusterOptions() to specify marker cluster options
clusterId: the id for the marker cluster layer
categoryField: Column name for categorizing charts.
categoryMap: A data.frame mapping categories to chart properties (e.g., label, color, icons, stroke).
popupFields: A string or vector of strings indicating the column names to include in popups.
popupLabels: A string or vector of strings indicating the labels for the popup fields.
markerOptions: Additional options for markers (see markerOptions::markerOptions()).
legendOptions: A list of options for the legend, including the title and position.
data: the data object from which the argument values are derived; by default, it is the data object provided to leaflet() initially, but can be overridden

Details

The `clusterCharts` use Leaflet's `L.DivIcon`, allowing you to fully customize the styling of individual markers and clusters using CSS. Each individual marker within a cluster is assigned the CSS class `clustermarker`, while the entire cluster is assigned the class `clustermarker-cluster`. You can modify the appearance of these elements by targeting these classes in your custom CSS.

Examples

# Example usage:
library(sf)
#> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE
library(leaflet)
library(leaflet.extras2)

data <- sf::st_as_sf(breweries91)
categories <- c("Schwer", "Mäßig", "Leicht", "kein Schaden")
data$category <- sample(categories, size = nrow(data), replace = TRUE)

## Pie Chart
leaflet() %>%
  addProviderTiles("CartoDB.Positron") %>%
  leaflet::addLayersControl(overlayGroups = "clustermarkers") %>%
  addClusterCharts(
    data = data,
    categoryField = "category",
    categoryMap = data.frame(
      labels = categories,
      colors = c("#F88", "#FA0", "#FF3", "#BFB"),
      strokes = "gray"
    ),
    group = "clustermarkers",
    popupFields = c("brewery", "address", "zipcode", "category"),
    popupLabels = c("Brauerei", "Adresse", "PLZ", "Art"),
    label = "brewery"
  )


## Bar Chart
leaflet() %>%
  addProviderTiles("CartoDB.Positron") %>%
  leaflet::addLayersControl(overlayGroups = "clustermarkers") %>%
  addClusterCharts(
    data = data,
    type = "bar",
    categoryField = "category",
    categoryMap = data.frame(
      labels = categories,
      colors = c("#F88", "#FA0", "#FF3", "#BFB"),
      strokes = "gray"
    ),
    group = "clustermarkers",
    popupFields = c("brewery", "address", "zipcode", "category"),
    popupLabels = c("Brauerei", "Adresse", "PLZ", "Art"),
    label = "brewery"
  )


## Custom Pie Chart with "mean" aggregation on column "value"
data <- sf::st_as_sf(breweries91)
categories <- c("Schwer", "Mäßig", "Leicht", "kein Schaden")
data$category <- sample(categories, size = nrow(data), replace = TRUE)
data$value <- round(runif(nrow(data), 0, 100), 0)

leaflet() %>%
  addProviderTiles("CartoDB.Positron") %>%
  leaflet::addLayersControl(overlayGroups = "clustermarkers") %>%
  addClusterCharts(
    data = data,
    type = "custom",
    valueField = "value",
    aggregation = "mean",
    categoryField = "category",
    categoryMap = data.frame(
      labels = categories,
      colors = c("#F88", "#FA0", "#FF3", "#BFB"),
      strokes = "gray"
    ),
    options = clusterchartOptions(rmax = 50, digits = 0, innerRadius = 20),
    group = "clustermarkers",
    popupFields = c("brewery", "address", "zipcode", "category", "value"),
    popupLabels = c("Brauerei", "Adresse", "PLZ", "Art", "Value"),
    label = "brewery"
  )


## For Shiny examples, please run:
# runApp(system.file("examples/clusterCharts_app.R", package = "leaflet.extras2"))
# runApp(system.file("examples/clustercharts_sum.R", package = "leaflet.extras2"))

Usage

Arguments

Details

See also

Examples