The map used is state.map in the package choroplethrMaps. See state.regions in the choroplethrMaps package for a data.frame that can help you coerce your regions into the required format.

state_choropleth(df, title = "", legend = "", num_colors = 7,
zoom = NULL, reference_map = FALSE)

## Arguments

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 state.map. An optional title for the map. An optional name for the legend. The number of colors to use on the map. A value of 0 uses a divergent scale (useful for visualizing negative and positive numbers), A value of 1 uses a continuous scale (useful for visualizing outliers), and a value in [2, 9] will use that many quantiles. An optional vector of states to zoom in on. Elements of this vector must exactly match the names of states as they appear in the "region" column of ?state.regions. If true, render the choropleth over a reference map from Google Maps.

## Examples

# default parameters
data(df_pop_state)
state_choropleth(df_pop_state,
title  = "US 2012 State Population Estimates",
legend = "Population")
# choropleth over reference map of continental usa
data(continental_us_states)
state_choropleth(df_pop_state,
title         = "US 2012 State Population Estimates",
legend        = "Population",
zoom          = continental_us_states,
reference_map = TRUE)#> Error: Google now requires an API key.
df_pop_state$str = "" for (i in 1:nrow(df_pop_state)) { if (df_pop_state[i,"value"] < 1000000) { df_pop_state[i,"str"] = "< 1M" } else { df_pop_state[i,"str"] = "> 1M" } } df_pop_state$value = df_pop_state\$str