I'm plotting ACS data (counts of low-income children) for each county across the entire U.S. I don't have any markers, just a county shapefile and a value for each county in a popup.

Unsurprisingly this is too large for browsers to handle. I've seen some similar questions here that deal with clustering, but since I have nothing to cluster I'm starting a new question.

I've tried breaking it up into 4 regional maps, but even those are too much.

Is there some way to lower the footprint, but still have all the county specific data?

I'm using R to generate the map, so R-specific responses are helpful but not necessary.

1 Answer 1


The solution is found in r package rmapshaper.

Apply the function rmapshaper::ms_simplify() to the result of tigris::geo_join() (the merged Large SpatialPolygonsDataFrame that is the combination of shapefile and data for each geography).

For my initial merge file that was 685 MB, the result was 17.6 MB. Voila!

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