HighChart County Choropleth Map of County Poverty, 2015

2 min read

The following code downloads county-level poverty data in 2015 from the American Community Survey (ACS) via an API using the acs package. I then create an interactive Highchart map using the package highcharter.

Download ACS Poverty data via an API

library(tibble)
library(dplyr)
library(tidyr)
library(fst)
library(highcharter)
library("viridisLite")
library(acs)

api.key.install(key = "07e1aef2e1de18c0bd4ad888c8bd1295aa7400f9")
all_counties = acs::geo.make(state = "*", county = "*")
all_tracts = acs::geo.make(state = c(state.abb, "DC"), county = "*", tract = "*")


pov_total_2015 = acs::acs.fetch(endyear = 2015, span = 5, geography = all_counties, 
    table.number = "B17001", case.sensitive = F, dataset = "acs", key = "07e1aef2e1de18c0bd4ad888c8bd1295aa7400f9")

df = tibble::as_tibble(pov_total_2015@estimate) %>% dplyr::bind_cols(fips = paste0(as.character(pov_total_2015@geography$state), 
    as.character(pov_total_2015@geography$county))) %>% dplyr::mutate(Poverty = 100 * 
    B17001_002/B17001_001) %>% dplyr::select(fips, Poverty)

Creating a HighChart Map

pov <- df$Poverty
minVal = min(pov, na.rm = T)
maxVal = max(pov, na.rm = T)
val95 = quantile(pov, 0.95, na.rm = T)
val05 = quantile(pov, 0.05, na.rm = T)
valBins = 5
value_binned = round(maxVal/(valBins + 1))

dclass <- data_frame(from = seq(minVal, maxVal - value_binned, by = value_binned), 
    to = seq(from[2], maxVal, by = value_binned), color = substring(viridis(length(from), 
        option = "C"), 0, 7))
dclass <- list_parse(dclass)


hc <- hcmap("https://code.highcharts.com/mapdata/countries/us/us-all-all.js", 
    data = df, value = "Poverty", joinBy = c("fips", "fips"), name = "Poverty", 
    dataLabels = list(enabled = FALSE, format = "{point.name}"), borderColor = "#FAFAFA", 
    borderWidth = 0.1, tooltip = list(headerFormat = "Poverty-", valueDecimals = 2, 
        valueSuffix = "%")) %>% hc_title(text = "Percentage Living Below Poverty Level in 2015 (ACS)") %>% 
    hc_subtitle(text = "johnbradford.github.io") %>% hc_mapNavigation(enabled = TRUE) %>% 
    hc_colorAxis(dataClasses = dclass)

Once the chart is created, it has to be saved using the htmlwidgets package. I saved it to a folder on my github page using the following code, and then use an iframe html tag to display it.

library(htmlwidgets)
htmlwidgets::saveWidget(hc, file = "us_poverty_map.html")