Create a map of Administrative Level 1 regions
Unlike ?admin1_choropleth, the regions here can span multiple countries.
admin1_region_choropleth( df, title = "", legend = "", num_colors = 7, zoom = NULL, reference_map = FALSE )
df |
A data.frame with a column named "region" and a column named "value". Elements in the "region" column must exactly match how regions are named in the "region" column in ?admin1.regions in the choroplethrAdmin1 package |
title |
An optional title for the map. |
legend |
An optional name for the legend. |
num_colors |
The number of colors on the map. A value of 1 will use a continuous scale. A value in [2, 9] will use that many colors. |
zoom |
An optional vector of regions to zoom in on. Elements of this vector must exactly match the names of regions as they appear in the "region" column of ?admin1.regions. |
reference_map |
If true, render the choropleth over a reference map from Google Maps. |
The map used comes from ?admin1.map in the choroplethrAdmin1 package. See ?get_admin_countries and ?get_admin_regions in the choroplethrAdmin1 package for help with the spelling of regions.
## Not run:
library(choroplethrAdmin1)
# map of continental us + southern canada
data("continental_us_states")
lower_canada = c("british columbia", "alberta", "saskatchewan", "manitoba", "ontario", "quebec")
regions = c(lower_canada, continental_us_states)
df = data.frame(region=regions, value=sample(1:length(regions)))
admin1_region_choropleth(df)
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