US Maps Including Alaska and Hawaii

Obtain United States map data frames of varying region types (e.g. county, state). The map data frames include Alaska and Hawaii conveniently placed to the bottom left, as they appear in most maps of the US. Convenience functions for plotting choropleths and working with FIPS codes are also provided.

See code to generate these images below

Purpose

Typically in R it is difficult to create nice US choropleths that include Alaska and Hawaii. The functions presented here attempt to elegantly solve this problem by manually moving these states to a new location and providing a fortified data frame for mapping and visualization. This allows the user to easily add data to color the map.

Shape Files

The shape files that we use to plot the maps in R are located in the data-raw folder. For more information refer to the US Census Bureau. Maps at both the state and county levels are included for convenience (zip code maps may be included in the future).

Installation

To install from CRAN (recommended), run the following code in an R console:

install.packages("usmap")

To install the package from this repository, run the following code in an R console:

# install.package("devtools")
devtools::install_github("pdil/usmap")

Installing using devtools::install_github will provide the most recent developer build of usmap.

To begin using usmap, simply import the package using the library command:

library(usmap)

To read the package vignettes, which explain helpful uses of the package, use vignette:

vignette(package = "usmap")
vignette("introduction", package = "usmap")
vignette("mapping", package = "usmap")

You can also read the vignettes online at the following links:

• Introduction
• Mapping the US

Features

• Obtain map with certain region breakdown

state_map <- us_map(regions = "states")
county_map <- us_map(regions = "counties")

• Include only certain states

new_england_states <- c("Connecticut", "Maine", "Massachusetts", "New Hampshire", "Rhode Island", "Vermont")
new_england_map <- us_map(regions = "states", include = new_england_states)

• Look up FIPS codes for states and counties

fips("New Jersey")
#> "34"
 
fips("NJ", county = "Mercer")
#> "34021"

• Retrieve states or counties with FIPS codes

fips_info(c("34", "35"))
#>         full abbr fips
#> 1 New Jersey   NJ   34 
#> 2 New Mexico   NM   35
 
fips_info(c("34021", "35021"))
#>         full abbr         county  fips
#> 1 New Jersey   NJ  Mercer County 34021
#> 2 New Mexico   NM Harding County 35021

• Color map with data

plot_usmap(data = statepop, values = "pop_2015", lines = "red") + 
  scale_fill_continuous(name = "Population (2015)", label = scales::comma) + 
  theme(legend.position = "right")

Code for maps shown above

library(usmap)
library(ggplot2)
 
# States map
plot_usmap(data = statepop, values = "pop_2015") + 
  scale_fill_continuous(low = "white", high = "red", guide = FALSE) +
  scale_x_continuous(expand = c(0, 0)) + scale_y_continuous(expand = c(0, 0))
 
# Counties map
plot_usmap(data = countypop, values = "pop_2015") + 
  scale_fill_continuous(low = "white", high = "red", guide = FALSE) +
  scale_x_continuous(expand = c(0, 0)) + scale_y_continuous(expand = c(0, 0))

Acknowledgements

The code used to generate the map files was based on this blog post by Bob Rudis:
Moving The Earth (well, Alaska & Hawaii) With R