leaflet {leaflet} | R Documentation

## 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.

Options for Map creation

creates a custom CRS Refer to https://kartena.github.io/Proj4Leaflet/api/ for details.

### Usage

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

    leafletOptions(minZoom = NULL, maxZoom = NULL, crs = leafletCRS(),
      worldCopyJump = 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 matrices, data frames, spatial objects from the sp package (`SpatialPoints`, `SpatialPointsDataFrame`, `Polygon`, `Polygons`, `SpatialPolygons`, `SpatialPolygonsDataFrame`, `Line`, `Lines`, `SpatialLines`, and `SpatialLinesDataFrame`), and spatial data frames from the sf package.
`width` | the width of the map
`height` | the height of the map
`padding` | the padding of the map
`options` | the map options
`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.
`...` | other options.
`crsClass` | One of L.CRS.EPSG3857, L.CRS.EPSG4326, L.CRS.EPSG3395, L.CRS.Simple, L.Proj.CRS, L.Proj.CRS.TMS
`code` | CRS identifier
`proj4def` | Proj4 string
`projectedBounds` | Only when crsClass = 'L.Proj.CRS.TMS'
`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` | Tile size, in pixels, to use in this CRS (Default 256) Only needed when crsClass = 'L.Proj.CRS.TMS'

### 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.

http://leafletjs.com/reference.html#map-options for details.

### 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)
    ))

    m %>% addMarkers(
      c(-71.0382679, -122.1217866), c(42.3489054, 47.6763144), icon = list(
        iconUrl = 'http://www.rstudio.com/wp-content/uploads/2014/03/blue-125.png'
      ), popup = c('RStudio @ Boston', 'RStudio @ Seattle')
    )

    # 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('http://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png',
      attribution = paste(
        '&copy; <a href="http://openstreetmap.org">OpenStreetMap</a> contributors',
        '&copy; <a href="http://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)

[Package leaflet version 1.1.0 Index]