Lesson 8. Creating interactive spatial maps in R using leaflet

Learning Objectives

After completing this tutorial, you will be able to:

  • Create an interactive leaflet map using R and rmarkdown.
  • Customize an interactive map with data-driven popups.

What you need

You will need a computer with internet access to complete this lesson.

# load packages
## Error in library(rjson): there is no package called 'rjson'

Interactive maps with Leaflet

Static maps are useful for creating figures for reports and presentation. Sometimes, however, we want to interact with our data. We can use the leaflet package for R to overlay our data on top of interactive maps. You can think about it like Google maps with your data overlaid on top!

What is leaflet?

Leaflet is an open-source JavaScript library that can be used to create mobile-friendly interactive maps.


  • Is designed with simplicity, performance and usability in mind,
  • Has a beautiful, easy to use, and well-documented API

The leaflet R package ‘wraps’ Leaflet functionality in an easy to use R package! Below, you can see some code that creates a basic web-map.

map <- leaflet() %>%
  addTiles() %>%  # use the default base map which is OpenStreetMap tiles
  addMarkers(lng=174.768, lat=-36.852,
             popup="The birthplace of R")

Create your own interactive map

Let’s create our own interactive map using the surface water data that we used in the previous lessons, using leaflet. To do this, we will follow the steps below:

  1. Request and get the data from the colorado.gov SODA API in R using fromJSON().
  2. Address column data types to ensure our quantitative data (number values) data are in fact numeric.
  3. Remove NA (missing data) values.

The code below is the same code that we used to process the surface water data in the previous lesson.

base_url <- "https://data.colorado.gov/resource/j5pc-4t32.json?"
full_url <- paste0(base_url, "station_status=Active",
water_data <- getURL(URLencode(full_url))
water_data_df <- fromJSON(water_data)
# remove the nested data frame
water_data_df <- flatten(water_data_df, recursive = TRUE)

# turn columns to numeric and remove NA values
water_data_df <- water_data_df %>%
  mutate_each_(funs(as.numeric), c( "amount", "location.latitude", "location.longitude")) %>%

Once our data are cleaned up, we can create our leaflet map. Notice that we are using pipes %>% to set the parameters for the leaflet map.

# create leaflet map
leaflet(water_data_df) %>%
  addTiles() %>%
  addCircleMarkers(lng=~location.longitude, lat=~location.latitude)

Data Tip: The code below provides an example of creating the same map without using pipes.

map <- leaflet(water_data_df)
map <- addTiles(map)
map <- addCircleMarkers(map, lng=~location.longitude, lat=~location.latitude)

Customize leaflet maps

We can customize our leaflet map too. Let’s do the following:

  1. Add custom data-driven popups to our map
  2. Adjust the point symbology
  3. Adjust the basemap. Let’s use a basemap from CartoDB called Positron.

Notice in the code below that we can specify the popup text using the popup= argument.

addMarkers(lng=~location.longitude, lat=~location.latitude, popup=~station_name)

We specify the basemap using the addProviderTiles() argument. In the example below, we use the CartoDB.Positron basemap:


leaflet(water_data_df) %>%
  addProviderTiles("CartoDB.Positron") %>%
  addMarkers(lng=~location.longitude, lat=~location.latitude, popup=~station_name)

Custom icons

We can specify a custom icon, too. Below, we are using an icon from the web.

Notice also that we are customizing the popup even more, adding BOTH the station name AND the discharge value.

paste0(station_name, "<br/>Discharge: ", amount)

We are using paste0() to do this. Remember that paste0() will paste together a series of text strings and object values.

# let's look at the output of our popup text before calling it in leaflet
# use head() to just look at the first 6 lines of the output
head(paste0(water_data_df$station_name, "<br/>Discharge: ", water_data_df$amount))
## [2] "PALMERTON DITCH<br/>Discharge: 12.65"                                 
## [3] "SWEDE DITCH<br/>Discharge: 6.77"                                      
## [4] "DRY CREEK CARRIER<br/>Discharge: 13.41"                               
## [5] "LEFT HAND CREEK NEAR BOULDER, CO.<br/>Discharge: 27"                  
## [6] "BOULDER CREEK NEAR ORODELL<br/>Discharge: 71"

The <br/> element in our popup above is HTML. This adds a line break to our popup so the Discharge text and value are on the second line - below the station name.

Let’s see what the custom icon and popup text looks like on our map.

# Specify custom icon
url = "http://tinyurl.com/jeybtwj"
water = makeIcon(url, url, 24, 24)

leaflet(water_data_df) %>%
  addProviderTiles("Stamen.Terrain") %>%
  addMarkers(lng=~location.longitude, lat=~location.latitude, icon=water,
                           "<br/>Discharge: ",

There is a lot more to learn about leaflet. Here, we’ve just scratched the surface.

Here we use addAwesomeMarkers() and adjust the color of each point on the map accordingly.

Here we use addCircleMarkers() and adjust the color accordingly.


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