Matching continuous data to the United States map, and Wisconsin county map

plot_map.R

library('ggplot2')
library('maps')

# Plot the United State map with AQL data

head(state_aql)
#         name      AQL      state
# 1    Alabama 34.83090    alabama
# 2     Alaska 21.12207     alaska
# 3    Arizona 28.49161    arizona
# 4   Arkansas 34.61867   arkansas
# 5 California 32.34555 california
# 6   Colorado 26.22654   colorado

states_map = map_data("state")
p1 = ggplot(state_aql, aes(map_id = state)) +
        geom_map(aes(fill = AQL), map = states_map) +
        expand_limits(x = states_map$long, y = states_map$lat) +
        scale_fill_gradient(low = "#ff7b75", high = "#5b0300", space = "Lab") +
        labs(title = "American Air Quality in 2016")
p1

# Plot the Wisconsin County map with AQL data

# Since there is no full county data, add a column to the county_map and give
# unknown data as `NA`

print(county_aql)
#          name      AQL     county  subregion
# 1     Ashland 22.39474    ashland    ashland
# 2       Brown 32.77049      brown      brown
# 3        Dane 36.56000       dane       dane
# 4       Dodge 34.44000      dodge      dodge
# 5  Eau Claire 33.00000 eau claire eau claire
# 6      Forest 19.94118     forest     forest
# 7       Grant 32.43182      grant      grant
# 8     Kenosha 33.70588    kenosha    kenosha
# 9   La Crosse 29.81818  la crosse  la crosse
# 10  Milwaukee 37.14054  milwaukee  milwaukee
# 11  Outagamie 31.35000  outagamie  outagamie
# 12    Ozaukee 36.62500    ozaukee    ozaukee
# 13       Sauk 35.94872       sauk       sauk
# 14     Taylor 29.24000     taylor     taylor
# 15      Vilas 22.72727      vilas      vilas
# 16   Waukesha 35.58824   waukesha   waukesha

# Load county_map data
county_map = map_data('county', region = 'Wisconsin')

# Build a list
county_list = as.list(query4$AQL)
names(county_list) = query4$subregion

# Given unknow data NA
values = c()
for (sub in county_map$subregion){
    if (sub %in% names(county_list)){
        values[length(values) + 1] = county_list[[sub]]
    } else {
        values[length(values) + 1] = NA
    }
}
county_map$aql = values

head(county_map)

# long	lat	group	order	region	subregion	aql
# -89.78249	43.64219	1	1	wisconsin	adams	NA
# -89.77676	43.66511	1	2	wisconsin	adams	NA
# -89.79395	43.67657	1	3	wisconsin	adams	NA
# -89.81686	43.68803	1	4	wisconsin	adams	NA
# -89.83405	43.71668	1	5	wisconsin	adams	NA
# -89.83405	43.75679	1	6	wisconsin	adams	NA

p2 = ggplot(county_map, aes(x = long, y = lat, group = group)) +
        geom_polygon(colour = "grey", aes(fill = aql)) +
        scale_fill_gradient(low = "#ff7b75", high = "#5b0300", space = "Lab", na.value="white") +
        labs(title = "AQL in 16 counties of Wisconsin in 2016") +
        coord_map() 
p2