I've a dataset with locations and their frequencies (sum of counts)

I want the leaflet cluster to display the frequencies as pointers instead of the count of occurrences.

city            state   latitude    longitude   Count

San Juan        PR      18.410462   -66.060533  5
Honolulu        HI      21.2782     -157.82199  8
Boca Raton      FL      26.391346   -80.21824   17
Key Biscayne    FL      25.700966   -80.16195   2

I use the function

leaflet(df) %>% addTiles() %>% addMarkers(
  clusterOptions = markerClusterOptions(),

to display the map, but it displays the count of each location pointer as one, regardless of the frequency. How do I customize the code so that it displays the frequencies instead of counts in pointers ?

This is how I want my end result as


1 Answer 1


One possible answer is expand your data.frame by the column Count. Doing this, you will have n number of points (based on Count) for every location.

Try the reproducible example below:

# Load libraries

# Load data
df <- data.frame('city' = c("San Juan", "Honolulu", "Boca Raton", "Key Biscayne"),
                 'state' = c("PR", "HI", "FL", "FL"),
                 'latitude' = c(18.410462, 21.2782, 26.391346, 25.700966),
                 'longitude' = c(-66.060533, -157.82199, -80.21824, -80.16195),
                 'Count' = c(5, 8, 17, 2))

# Expand dataframe
df.expanded <- df[rep(row.names(df), df$Count),]

# Leaflet map of df
leaflet(df.expanded) %>% addTiles() %>% 
  addMarkers(clusterOptions = markerClusterOptions())


Notice that in the figure there are 19 points in yellow because "Boca Raton" (Count = 17) and "Key Biscayne" (Count = 2) are collapsed at that level of zoom.

  • 1
    Hi This could be a possible workaround but I'm afraid that it would drastically increase the processing time and memory in my case as I have over 8 million entries.
    – Dee V
    May 21, 2017 at 21:15

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