Dynamically Displaying Interactive Maps in Quarto with Leaflet and JSON Data
Quarto is a powerful tool for creating reproducible and shareable documents. One of its strengths is its ability to seamlessly integrate R code and visualizations. In this article, we'll explore how to leverage this integration to create dynamic Leaflet maps within Quarto documents, loading map data from JSON files.
The Challenge:
Imagine you have a dataset containing geographical locations stored in a JSON file. You want to visualize this data on an interactive map within your Quarto document, but you don't want to hardcode the data directly into your R code. This is where the combination of Leaflet and JSON data loading comes into play.
Scenario:
Let's say we have a JSON file named locations.json containing coordinates and information about various points of interest:
[
{ "name": "Central Park", "lat": 40.7829, "lon": -73.9654 },
{ "name": "Times Square", "lat": 40.7589, "lon": -73.9851 },
{ "name": "Empire State Building", "lat": 40.7484, "lon": -73.9857 }
]
We want to display these locations on a Leaflet map within our Quarto document.
Original Code (without JSON loading):
```{r}
library(leaflet)
# Hardcoded data
locations <- data.frame(
name = c("Central Park", "Times Square", "Empire State Building"),
lat = c(40.7829, 40.7589, 40.7484),
lon = c(-73.9654, -73.9851, -73.9857)
)
leaflet() %>%
addTiles() %>%
addMarkers(data = locations, lng = ~lon, lat = ~lat, popup = ~name)
This code works, but it requires us to manually update the locations data frame every time we have new data. This is inefficient and error-prone.
Solution: Dynamically Load Data from JSON
To make our map dynamic and avoid manual data updates, we can use the jsonlite package to read our JSON data and then integrate it into our Leaflet map.
```{r}
library(leaflet)
library(jsonlite)
# Load JSON data
locations_data <- fromJSON("locations.json")
# Convert to data frame
locations <- data.frame(
name = locations_data$name,
lat = locations_data$lat,
lon = locations_data$lon
)
# Create Leaflet map
leaflet() %>%
addTiles() %>%
addMarkers(data = locations, lng = ~lon, lat = ~lat, popup = ~name)
Explanation:
- Load JSON data: We use the
fromJSONfunction from thejsonlitepackage to read the contents of thelocations.jsonfile. - Convert to data frame: The
fromJSONfunction returns a list. We convert this list to a data frame for easier handling by Leaflet. - Create Leaflet map: We use the familiar Leaflet syntax to create a map, adding markers for each location from our
locationsdata frame.
Benefits of Using JSON:
- Data Separation: JSON files allow us to store map data independently from our R code, making the code cleaner and more readable.
- Flexibility: We can easily update the map data by modifying the JSON file without altering the R code.
- Scalability: This approach scales well, allowing us to handle large datasets without overloading our R code.
Additional Enhancements:
- Marker Customization: Use
iconOptionswithinaddMarkersto customize the appearance of your markers. - Popup Content: Modify the
popupparameter to display more information about each location in the popups. - Clustering: For many markers, use
addMarkerswith theclusterOptionsparameter to create marker clusters for better visualization.
Conclusion:
By using JSON files and the jsonlite package, we can dynamically load map data into our Quarto documents, making our Leaflet maps more flexible and scalable. This approach allows us to easily update our map data without modifying the R code, keeping our documents clean and reproducible.
Resources:
- Leaflet Documentation: Learn more about Leaflet's extensive capabilities.
- jsonlite Package Documentation: Explore how to work with JSON data in R.
- Quarto Documentation: Discover the full potential of Quarto for reproducible and interactive documents.
