leaflet: Create a Leaflet map widget

In rstudio/leaflet: Create Interactive Web Maps with the JavaScript 'Leaflet' Library

Create a Leaflet map widget

Description

This function creates a Leaflet map widget using htmlwidgets. The widget can be rendered on HTML pages generated from R Markdown, Shiny, or other applications.

Usage

leaflet(
  data = NULL,
  width = NULL,
  height = NULL,
  padding = 0,
  options = leafletOptions(),
  elementId = NULL,
  sizingPolicy = leafletSizingPolicy(padding = padding)
)

leafletOptions(
  minZoom = NULL,
  maxZoom = NULL,
  crs = leafletCRS(),
  worldCopyJump = NULL,
  preferCanvas = NULL,
  ...
)

leafletCRS(
  crsClass = "L.CRS.EPSG3857",
  code = NULL,
  proj4def = NULL,
  projectedBounds = NULL,
  origin = NULL,
  transformation = NULL,
  scales = NULL,
  resolutions = NULL,
  bounds = NULL,
  tileSize = NULL
)

Arguments

data	a data object. Currently supported objects are matrix, data frame, spatial data from the sf package, SpatVector from the terra package, and the Spatial* objects from the sp package that represent points, lines, or polygons.
width	the width of the map
height	the height of the map
padding	the padding of the map
options	the map options
elementId	Use an explicit element ID for the widget (rather than an automatically generated one).
sizingPolicy	htmlwidgets sizing policy object. Defaults to leafletSizingPolicy()
minZoom	Minimum zoom level of the map. Overrides any minZoom set on map layers.
maxZoom	Maximum zoom level of the map. This overrides any maxZoom set on map layers.
crs	Coordinate Reference System to use. Don't change this if you're not sure what it means.
worldCopyJump	With this option enabled, the map tracks when you pan to another "copy" of the world and seamlessly jumps to the original one so that all overlays like markers and vector layers are still visible.
preferCanvas	Whether leaflet.js Paths should be rendered on a Canvas renderer.
...	other options used for leaflet.js map creation.
crsClass	One of L.CRS.EPSG3857, L.CRS.EPSG4326, L.CRS.EPSG3395, L.CRS.Simple, L.Proj.CRS
code	CRS identifier
proj4def	Proj4 string
projectedBounds	DEPRECATED! Use the bounds argument.
origin	Origin in projected coordinates, if set overrides transformation option.
transformation	to use when transforming projected coordinates into pixel coordinates
scales	Scale factors (pixels per projection unit, for example pixels/meter) for zoom levels; specify either scales or resolutions, not both
resolutions	factors (projection units per pixel, for example meters/pixel) for zoom levels; specify either scales or resolutions, not both
bounds	Bounds of the CRS, in projected coordinates; if defined, Proj4Leaflet will use this in the getSize method, otherwise defaulting to Leaflet's default CRS size
tileSize	DEPRECATED! Specify the tilesize in the tileOptions() argument.

Details

The data argument is only needed if you are going to reference variables in this object later in map layers. For example, data can be a data frame containing columns latitude and longtitude, then we may add a circle layer to the map by leaflet(data) %>% addCircles(lat = ~latitude, lng = ~longtitude), where the variables in the formulae will be evaluated in the data.

Value

A HTML widget object, on which we can add graphics layers using ⁠%>%⁠ (see examples).

Functions

• leafletOptions(): Options for map creation

• leafletCRS(): class to create a custom CRS

See Also

leafletCRS() for creating a custom CRS.

See https://web.archive.org/web/20220702182250/https://leafletjs.com/reference-1.3.4.html#map-option for details and more options.

Examples

# !formatR
library(leaflet)
m <- leaflet() %>% addTiles()
m  # a map with the default OSM tile layer


# set bounds
m %>% fitBounds(0, 40, 10, 50)

# move the center to Snedecor Hall
m <- m %>% setView(-93.65, 42.0285, zoom = 17)
m

# popup
m %>% addPopups(-93.65, 42.0285, "Here is the <b>Department of Statistics</b>, ISU")
rand_lng <- function(n = 10) rnorm(n, -93.65, .01)
rand_lat <- function(n = 10) rnorm(n, 42.0285, .01)

# use automatic bounds derived from lng/lat data
m <- m %>% clearBounds()

# popup
m %>% addPopups(rand_lng(), rand_lat(), "Random popups")

# marker
m %>% addMarkers(rand_lng(), rand_lat())
m %>% addMarkers(
  rand_lng(), rand_lat(), popup = paste("A random letter", sample(LETTERS, 10))
)

Rlogo <- file.path(R.home("doc"), "html", "logo.jpg")
m %>% addMarkers(
  174.7690922, -36.8523071, icon = list(
    iconUrl = Rlogo, iconSize = c(100, 76)
  ), popup = "R was born here!"
)

m %>% addMarkers(rnorm(30, 175), rnorm(30, -37), icon = list(
  iconUrl = Rlogo, iconSize = c(25, 19)
))

# circle (units in metres)
m %>% addCircles(rand_lng(50), rand_lat(50), radius = runif(50, 50, 150))

# circle marker (units in pixels)
m %>% addCircleMarkers(rand_lng(50), rand_lat(50), color = "#ff0000")
m %>% addCircleMarkers(rand_lng(100), rand_lat(100), radius = runif(100, 5, 15))

# rectangle
m %>% addRectangles(
  rand_lng(), rand_lat(), rand_lng(), rand_lat(),
  color = "red", fill = FALSE, dashArray = "5,5", weight = 3
)

# polyline
m %>% addPolylines(rand_lng(50), rand_lat(50))

# polygon
m %>% addPolygons(rand_lng(), rand_lat(), layerId = "foo")

# geoJSON
seattle_geojson <- list(
  type = "Feature",
  geometry = list(
    type = "MultiPolygon",
    coordinates = list(list(list(
      c(-122.36075812146,  47.6759920119894),
      c(-122.360781646764, 47.6668890126755),
      c(-122.360782108665,  47.6614990696722),
      c(-122.366199035722, 47.6614990696722),
      c(-122.366199035722,  47.6592874248973),
      c(-122.364582509469, 47.6576254522105),
      c(-122.363887331445,  47.6569107302038),
      c(-122.360865528129, 47.6538418253251),
      c(-122.360866157644,  47.6535254473167),
      c(-122.360866581103, 47.6533126275176),
      c(-122.362526540691,  47.6541872926348),
      c(-122.364442114483, 47.6551892850798),
      c(-122.366077719797,  47.6560733960606),
      c(-122.368818463838, 47.6579742346694),
      c(-122.370115159943,  47.6588730808334),
      c(-122.372295967029, 47.6604350102328),
      c(-122.37381369088,  47.660582362063),
      c(-122.375522972109, 47.6606413027949),
      c(-122.376079703095,  47.6608793094619),
      c(-122.376206315662, 47.6609242364243),
      c(-122.377610811371,  47.6606160735197),
      c(-122.379857378879, 47.6610306942278),
      c(-122.382454873022,  47.6627496239169),
      c(-122.385357955057, 47.6638573778241),
      c(-122.386007328104,  47.6640865692306),
      c(-122.387186331506, 47.6654326177161),
      c(-122.387802656231,  47.6661492860294),
      c(-122.388108244121, 47.6664548739202),
      c(-122.389177800763,  47.6663784774359),
      c(-122.390582858689, 47.6665072251861),
      c(-122.390793942299,  47.6659699214511),
      c(-122.391507906234, 47.6659200946229),
      c(-122.392883050767,  47.6664166747017),
      c(-122.392847210144, 47.6678696739431),
      c(-122.392904778401,  47.6709016021624),
      c(-122.39296705153, 47.6732047491624),
      c(-122.393000803496,  47.6759322346303),
      c(-122.37666945305, 47.6759896300663),
      c(-122.376486363943,  47.6759891899754),
      c(-122.366078869215, 47.6759641734893),
      c(-122.36075812146,  47.6759920119894)
    )))
  ),
  properties = list(
    name = "Ballard",
    population = 48000,
    # You can inline styles if you want
    style = list(
      fillColor = "yellow",
      weight = 2,
      color = "#000000"
    )
  ),
  id = "ballard"
)
m %>% setView(-122.36075812146, 47.6759920119894, zoom = 13) %>% addGeoJSON(seattle_geojson)


# use the Dark Matter layer from CartoDB
leaflet() %>% addTiles("https://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png",
  attribution = paste(
    "&copy; <a href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors",
    "&copy; <a href=\"https://cartodb.com/attributions\">CartoDB</a>"
  )
) %>% setView(-122.36, 47.67, zoom = 10)

# provide a data frame to leaflet()
categories <- LETTERS[1:10]
df <- data.frame(
  lat = rand_lat(100), lng = rand_lng(100), size = runif(100, 5, 20),
  category = factor(sample(categories, 100, replace = TRUE), levels = categories),
  value = rnorm(100)
)
m <- leaflet(df) %>% addTiles()
m %>% addCircleMarkers(~lng, ~lat, radius = ~size)
m %>% addCircleMarkers(~lng, ~lat, radius = runif(100, 4, 10), color = c("red"))

# Discrete colors using the "RdYlBu" colorbrewer palette, mapped to categories
RdYlBu <- colorFactor("RdYlBu", domain = categories)
m %>% addCircleMarkers(~lng, ~lat, radius = ~size,
  color = ~RdYlBu(category), fillOpacity = 0.5)

# Continuous colors using the "Greens" colorbrewer palette, mapped to value
greens <- colorNumeric("Greens", domain = NULL)
m %>% addCircleMarkers(~lng, ~lat, radius = ~size,
  color = ~greens(value), fillOpacity = 0.5)

rstudio/leaflet documentation built on Aug. 8, 2024, 11:06 a.m.