library(coronavirusbrazil)
data("spatial_rj_neighborhoods")
head(spatial_rj_neighborhoods)
#> neighborhood cases Ordem deaths lat lon AP Extra_int1
#> 1 ABOLICAO 5 5 0 -22.88580 -43.29948 3.2 70
#> 2 ACARI 2 2 0 -22.82218 -43.34120 3.3 111
#> 3 AGUA SANTA 0 0 0 -22.91104 -43.31150 3.2 67
#> 4 ALTO DA BOA VISTA 3 3 0 -22.96063 -43.26083 2.2 34
#> 5 ANCHIETA 14 14 0 -22.82297 -43.39875 3.3 107
#> 6 ANDARAI 9 9 0 -22.92911 -43.25342 2.2 37
#> Extra_int2 Extra_txt ObjectId geoms log_cases log_deaths
#> 1 0 0 1 -43.29948, -22.88580 0.6989700 -Inf
#> 2 0 0 2 -43.34120, -22.82218 0.3010300 -Inf
#> 3 0 0 3 -43.31150, -22.91104 -Inf -Inf
#> 4 0 0 4 -43.26083, -22.96063 0.4771213 -Inf
#> 5 0 0 5 -43.39875, -22.82297 1.1461280 -Inf
#> 6 0 0 6 -43.25342, -22.92911 0.9542425 -Infmapview::mapview(spatial_rj_neighborhoods %>% dplyr::filter(lon < -30),
map = leaflet::leaflet() %>% leaflet::addTiles(),
zcol="cases", cex="cases",
layer.name="Casos",
label=paste0(spatial_rj_neighborhoods$neighborhood, ": ",
spatial_rj_neighborhoods$cases))