choroplethr (version 3.7.0)

county_choropleth: Create a choropleth of US Counties

Description

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.

Usage

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

if (FALSE) {
# 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)

# 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)
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)
}