Create a choropleth of US Counties

The map used is county.map in the choroplethrMaps package. See country.regions in the choroplethrMaps package for an object which can help you coerce your regions into the required format.

county_choropleth(df, title = "", legend = "", num_colors = 7,
  state_zoom = NULL, county_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 county.map.
title	An optional title for the map.
legend	An optional name for the legend.
num_colors	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.
state_zoom	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.
county_zoom	An optional vector of counties to zoom in on. Elements of this vector must exactly match the names of counties as they appear in the "region" column of ?county.regions.
reference_map	If true, render the choropleth over a reference map from Google Maps.

Examples

# default parameters
data(df_pop_county)
county_choropleth(df_pop_county,
                  title  = "US 2012 County Population Estimates",
                  legend = "Population")

# zoom in on california and add a reference map
county_choropleth(df_pop_county,
                  title         = "California County Population Estimates",
                  legend        = "Population",
                  state_zoom    = "california",
                  reference_map = TRUE)
#> Error: Google now requires an API key.
#>        See ?register_google for details.

# continuous scale 
data(df_pop_county)
county_choropleth(df_pop_county,
                 title      = "US 2012 County Population Estimates",
                 legend     = "Population",
                 num_colors = 1,
                 state_zoom = c("california", "oregon", "washington"))

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following object is masked from ‘package:testthat’:
#> 
#>     matches
#> The following object is masked from ‘package:acs’:
#> 
#>     combine
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(choroplethrMaps)
data(county.regions)

# show the population of the 5 counties (boroughs) that make up New York City
nyc_county_names = c("kings", "bronx", "new york", "queens", "richmond")
nyc_county_fips = county.regions %>%
  filter(state.name == "new york" & county.name %in% nyc_county_names) %>%
  select(region)
county_choropleth(df_pop_county,
                  title        = "Population of Counties in New York City",
                  legend       = "Population",
                  num_colors   = 1,
                  county_zoom = nyc_county_fips$region)