7 Mapping with `leaflet`

7.1 Overview

leaflet is an R package for building interactive maps. It is especially useful when your data include locations, coordinates, regions, or boundaries and you want viewers to explore the map directly.

leaflet(data = ...) %>%
  addTiles() %>%
  add*()

data: dataset
leaflet(): initializes the map
addTiles(): adds a basemap
add*(): adds markers, circles, polygons, or other layers
%>%: builds the map step by step

7.2 Basic Map

library(leaflet)

leaflet() %>%
  addTiles()

7.3 Add a Single Marker

leaflet() %>%
  addTiles() %>%
  addMarkers(
    lng = -96.7970,
    lat = 32.7767,
    popup = "Dallas, Texas"
  )

7.4 Map Data from a Dataset

leaflet(quakes) %>%
  addTiles() %>%
  addMarkers(
    lng = ~long,
    lat = ~lat
  )

7.5 Markers vs Circle Markers

Key Distinction

addMarkers() places standard map pins
addCircleMarkers() draws scalable points on the map

For most data visualization tasks, addCircleMarkers() is preferred.

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat
  )

7.6 Encode Size with Magnitude

Key Idea

Marker size is one of the most effective ways to encode magnitude in a map.

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat,
    radius = ~mag
  )

7.6.1 Scaling Marker Size

Raw values are often too small or too large. Scale them for readability:

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat,
    radius = ~mag * 2,   # simple scaling
    fillOpacity = 0.7
  )

You can also normalize:

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat,
    radius = ~sqrt(mag) * 3,
    fillOpacity = 0.7
  )

7.7 Add Rich Popups and Labels

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat,
    radius = ~mag * 2,
    popup = ~paste(
      "Magnitude:", mag,
      "<br>Depth:", depth
    )
  )

7.8 Use Color Intentionally

Color Best Practices

Use color to encode a meaningful variable
Ensure contrast with the basemap
Avoid too many categories

pal <- colorNumeric(
  palette = "viridis",
  domain = quakes$mag
)

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat,
    radius = ~mag * 2,
    color = ~pal(mag),
    fillOpacity = 0.7
  )

7.9 Add a Legend

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat,
    radius = ~mag * 2,
    color = ~pal(mag),
    fillOpacity = 0.7
  ) %>%
  addLegend(
    "bottomright",
    pal = pal,
    values = ~mag,
    title = "Magnitude"
  )

7.10 Adjust the View

leaflet() %>%
  addTiles() %>%
  setView(lng = -96.7970, lat = 32.7767, zoom = 10)

7.11 Change the Basemap

leaflet() %>%
  addProviderTiles(providers$CartoDB.Positron)

7.12 Interactivity

Why Use leaflet?

Users can: - zoom and pan - click for details - explore spatial patterns

7.13 Workflow

Recommended Approach

Start with a basemap
Add points
Encode magnitude with size
Add color and labels
Refine view and legend

7.14 Summary

Use radius to encode magnitude
Scale size for readability
Combine size + color for clarity
Use popups to avoid clutter

7.15 Exercise

leaflet(quakes) %>%
  addTiles() %>%
  addCircleMarkers(
    lng = ~long,
    lat = ~lat
  )

Modify: - Scale radius by mag - Add color by mag - Add a popup