• Leaflet is one of the most popular open-source JavaScript libraries for interactive maps. It’s used by websites ranging from The New York Times and The Washington Post to GitHub and Flickr, as well as GIS specialists like OpenStreetMap, Mapbox, and CartoDB.

• The Leaflet R package makes it easy to integrate and control Leaflet maps in R.

To install this R package, run this command at your R prompt:

install.packages("leaflet")
# to install the development version from Github, run
# devtools::install_github("rstudio/leaflet")

Once installed, you can use this package at the R console, within R Markdown documents, and within Shiny applications.

You create a Leaflet map with these basic steps:

1. Create a map widget by calling leaflet().
2. Add layers (i.e., features) to the map by using layer functions (e.g. addTiles, addMarkers, addPolygons) to modify the map widget.
3. Repeat step 2 as desired.
4. Print the map widget to display it.

Here’s a basic example:

library(leaflet) 
my_map <- leaflet(width="100%", height=300) %>%
  addTiles() %>% # Add default OpenStreetMap map tiles
  addMarkers(lat=29.5850369, lng=-98.6182212,   popup="Campbell's Office")
my_map #Print the map

Recall the magrittr pipe operator (%>%), without it, we’d have to write:

my_map <- leaflet()
my_map <- addTiles(my_map)
my_map <- addMarkers(my_map, lat=29.5850369, lng=-98.6182212, popup="Campbell's Office")
my_map

#Or worse
my_map<-addMarkers(addTiles(leaflet()), lat=29.5850369, lng=-98.6182212, popup="Campbell's Office")

Point data for markers can come from a variety of sources:

• SpatialPoints or SpatialPointsDataFrame objects (from the sp package)
• POINT, sfc_POINT, and sf objects (from the sf package); only X and Y dimensions will be considered
• Two-column numeric matrices (first column is longitude, second is latitude)
• Data frame with latitude and logitude columns. You can explicitly tell the marker function which columns contain the coordinate data (e.g. addMarkers(lng = ~Longitude, lat = ~Latitude)), or let the function look for columns named lat/latitude and lon/lng/long/longitude (case insensitive).
• Simply provide numeric vectors as lng and lat arguments

Note that MULTIPOINT objects from sf are not supported at this time.

Markers are added using the addMarkers or the addAwesomeMarkers functions. Their default appearance is a dropped pin.

data(quakes)

# Show first 20 rows from the `quakes` dataset
leaflet(data = quakes[1:20,],width="100%", height=300) %>% addTiles() %>%
  addMarkers(~long, ~lat, popup = ~as.character(mag), label = ~as.character(mag))

The blue markers that leaflet comes packaged with may not be enough depending on what you’re mapping. Thankfully you can make your own markers from .png files.

roadrunnerIcon <- makeIcon( 
  iconUrl = "http://a3.espncdn.com/combiner/i?img=%2Fi%2Fteamlogos%2Fncaa%2F500%2F2636.png", 
  iconWidth = 31*215/230, iconHeight = 31, 
  iconAnchorX = 31*215/230/2, iconAnchorY = 16 
) 

roadrunnerLatLong <- data.frame( 
lat = c(29.5850369, 29.5823632, 29.424606), 
lng = c(-98.6182212, -98.621411, -98.5045881)) 

When adding multiple markers to a map, you may want to add popups for each marker. You can specify a string of plain text for each popup, or you can provide HTML which will be rendered inside of each popup.

roadrunnerSites<-c("<a href='http://www.business.utsa.edu/mss/index.aspx'>Mgmt Sci & Stat</a>",
"<a href='https://en.wikipedia.org/wiki/Convocation_Center_(University_of_Texas_at_San_Antonio)'>UTSA Convocation Center</a>",
"<a href='http://txsdc.utsa.edu/'>Texas Demographic Center</a>")

roadrunnerLatLong %>% 
  leaflet(width="100%", height=350) %>% 
  addTiles() %>% 
  addMarkers(icon = roadrunnerIcon, popup = roadrunnerSites)

Sometimes you might have so many points on a map that it doesn’t make sense to plot every marker. In these situations leaflet allows you to plot clusters of markers using addMarkers(clusterOptions = markerClusterOptions()). When you zoom in to each cluster, the clusters will separate until you can see the individual markers.

leaflet(quakes,width="100%",heigh=350) %>% addTiles() %>% addMarkers(
  clusterOptions = markerClusterOptions()
)

## Assuming "long" and "lat" are longitude and latitude, respectively

Instead of adding markers or clusters you can easily add circle markers using addCircleMarkers().

# Some fake pirate data
df <- sp::SpatialPointsDataFrame(
  cbind(
    (runif(20) - .5) * 10 - 90.620130,  # lng
    (runif(20) - .5) * 3.8 + 25.638077  # lat
  ),
  data.frame(type = factor(
    ifelse(runif(20) > 0.75, "pirate", "ship"),
    c("ship", "pirate")
  ))
)

leaflet(df,width="100%",height=200) %>% addTiles() %>% addCircleMarkers()

Circles are added using addCircles().

tx.cities<-data.frame(name=c("Austin","Corpus Christi","Dallas","El Paso","Fort Worth","Galveston","Houston","Lubbock","San Angelo","San Antonio","Tyler"), pop=c(815974,305382,1200699,651685,746547,47820,2114761,230622,93644,1333953,97237), lat=c(30.307182,27.754252,32.794176,31.84836,32.779542,29.18326,29.780472,33.566479,31.438912,29.472403,32.314954),lng=c(-97.755996,-97.173385,-96.765503,-106.426979,-97.346335,-94.969755,-95.386342,-101.886677,-100.45185,-98.525142,-95.304631)) 

tx.cities %>% 
  leaflet(width="100%",height=350) %>% 
  addTiles() %>% 
  addCircles(weight = 1, radius = sqrt(tx.cities$pop) * 30)

## Assuming "lng" and "lat" are longitude and latitude, respectively

You can add rectangles on leaflet maps as well:

leaflet(width="100%",height=400) %>% 
    addTiles() %>% 
    addRectangles(lat1 = 29.15, lng1 = -98.8, 
                  lat2 = 30.5, lng2 = -97.5)

Adding a legend can be useful if you have markers on your map with different colors:

suppressPackageStartupMessages(library(rgdal))

# From http://data.okfn.org/data/datasets/geo-boundaries-world-110m
countries <- readOGR("https://raw.githubusercontent.com/datasets/geo-boundaries-world-110m/master/countries.geojson")

map <- leaflet(countries) %>% addTiles()

pal <- colorNumeric(
  palette = "YlGnBu",
  domain = countries$gdp_md_est
)
map %>%
  addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 1,
    color = ~pal(gdp_md_est)
  ) %>%
  addLegend("bottomright", pal = pal, values = ~gdp_md_est,
    title = "Est. GDP (2010)",
    labFormat = labelFormat(prefix = "$"),
    opacity = 1
  )

## OGR data source with driver: GeoJSON 
## Source: "https://raw.githubusercontent.com/datasets/geo-boundaries-world-110m/master/countries.geojson", layer: "countries"
## with 177 features
## It has 63 fields

For more details about the leaflet package for R visit http://rstudio.github.io/leaflet/.