In pdil/usmap: US Maps Including Alaska and Hawaii

knitr::opts_chunk$set(
  collapse = TRUE,
  dpi = 300,
  comment = "#>",
  fig.align = "center",
  fig.path = "man/figures/README-",
  fig.width = 15,
  dev.args = list(bg = "transparent")
)

🗺 usmap

library(usmap)
library(ggplot2)

# City population county map (West Region) ####
citypop_t <- usmap_transform(citypop)
citypop_t_west <- citypop_t[(citypop_t$abbr %in% .west_region) & (citypop_t$abbr != "AK") & (citypop_t$abbr != "HI"), ]

west_county_citypop_map <-
  plot_usmap("counties", include = .west_region, exclude = c("AK", "HI"), color = "blue", fill = "lightblue") +
  geom_sf(data = citypop_t_west, aes(size = city_pop), color = "red", alpha = 0.7) +
  scale_size_continuous(range = c(2, 15), guide = "none") +
  ggrepel::geom_label_repel(
    data = citypop_t_west,
    aes(label = most_populous_city, geometry = geometry),
    size = 5, alpha = 0.8,
    label.r = unit(0.5, "lines"), label.size = 0.5,
    segment.color = "red", segment.size = 1,
    stat = "sf_coordinates", seed = 1002,
    max.overlaps = 20
  )

# Population by state with labels ####
state_pop_map_labeled <-
  plot_usmap(data = statepop, values = "pop_2022", labels = TRUE) +
  scale_fill_continuous(low = "white", high = "red", guide = "none")

# Blank county map (Alaska) ####
ak_county_map <-
  plot_usmap("counties", include = "AK", color = "red", fill = "#fffdcf")

# Poverty by county (South) ####
south_pov_map <-
  plot_usmap("counties", data = countypov, values = "pct_pov_2021",
             include = .south_region, color = "white", size = 0) +
  scale_fill_continuous(low = "darkgreen", high = "yellow", guide = "none")

# Poverty percentage by county ####
county_pov_map <-
  plot_usmap(data = countypov, values = "pct_pov_2021", size = 0.2) +
  scale_fill_continuous(low = "blue", high = "yellow", guide = "none")

# Rivers map ####
rivers_t <- usmap_transform(usrivers)

rivers_map <- plot_usmap("counties", color = "gray80") +
  geom_sf(data = rivers_t, aes(linewidth = Shape_Length), color = "blue") +
  scale_linewidth_continuous(range = c(0.3, 1.5), guide = "none")

# Combine plots ####
cowplot::plot_grid(
  west_county_citypop_map,
  state_pop_map_labeled,
  ak_county_map,
  south_pov_map,
  county_pov_map,
  rivers_map,
  nrow = 2
)

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 simple features (sf) object for mapping and visualization. This allows the user to easily add spatial data or features to the US map.

Shape Files

The shape files that we use to plot the maps in R are located in the usmapdata package. These are generated from the US Census Bureau cartographic boundary files. Maps at both the state and county levels are included for convenience.

Update History

| Date | usmap version | Shape File Year | Link | |------------------|:----------------:|:----------------:|:----------------:| | January 20, 2024 | 0.7.0 | 2022 | 🔗 | | February 27, 2022 | 0.6.0 | 2020 | 🔗 | | June 3, 2018 | 0.3.0 | 2017 | 🔗 | | January 29, 2017 | 0.1.0 | 2015 | 🔗 |

Installation

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

install.packages("usmap")

Developer Build

⚠️ The developer build may be unstable and not function correctly, use with caution.

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

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

This method will provide the most recent developer build of usmap.

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

library(usmap)

Documentation

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

vignette(package = "usmap")
vignette("usmap1", package = "usmap") # 1. Introduction
vignette("usmap2", package = "usmap") # 2. Mapping the US
vignette("usmap3", package = "usmap") # 3. Advanced Mapping

For further help with this package, open an issue or ask a question on Stack Overflow with the usmap tag.

Features

Map Plots

• Plot US maps

states <- plot_usmap("states")
counties <- plot_usmap("counties")

cowplot::plot_grid(states, counties, nrow = 1)

• Display only certain states, counties, or regions

library(ggplot2)

mt <- plot_usmap("states", include = .mountain, labels = TRUE)

fl <- plot_usmap("counties", data = countypov, values = "pct_pov_2021", include = "FL") +
  scale_fill_continuous(low = "green", high = "red", guide = "none")

ne <- plot_usmap("counties", data = countypop, values = "pop_2022", include = .new_england) +
  scale_fill_continuous(low = "blue", high = "yellow", guide = "none")

cowplot::plot_grid(mt, fl, ne, nrow = 1)

• Transform and add spatial data to map

library(ggplot2)

# Transform included `usrivers` data set
rivers_transformed <- usmap_transform(usrivers)

river_map <- plot_usmap("counties", color = "gray80") +
  geom_sf(data = rivers_transformed, aes(linewidth = Shape_Length), color = "blue") +
  scale_linewidth_continuous(range = c(0.3, 1.5), guide = "none")

# Transform included `earthquakes` data set
eq_transformed <- usmap_transform(earthquakes)

earthquake_map <- plot_usmap() +
  geom_sf(data = eq_transformed, aes(size = mag), color = "red", alpha = 0.25) +
  scale_size_continuous(guide = "none")

cowplot::plot_grid(river_map, earthquake_map, nrow = 1)

Map Data

• Obtain map data with certain region breakdown

us_map(regions = "states")

us_map(regions = "counties")

FIPS Codes

• Look up FIPS codes for states and counties

fips("New Jersey")

fips(c("AZ", "CA", "New Hampshire"))

fips("NJ", county = "Mercer")

fips("NJ", county = c("Bergen", "Hudson", "Mercer"))

• Retrieve states or counties with FIPS codes

fips_info(c("34", "35"))

fips_info(c("34021", "35021"))

• Add FIPS codes to data frame

library(dplyr)

data <- data.frame(
  state = c("NJ", "NJ", "NJ", "PA"),
  county = c("Bergen", "Hudson", "Mercer", "Allegheny")
)

data %>% rowwise %>% mutate(fips = fips(state, county))

Additional Information

Citation Information

The images generated by usmap are not under any copyright restrictions and may be used and distributed freely in any publication or otherwise.

The underlying shapefiles used to generate the map data are derived from the US Census Bureau's TIGER/Line Shapefiles which are not copyrighted but do suggest citation. See section 1.2 of this document.

If you wish to cite usmap in a publication (appreciated but never required!), you may do so in the following way:

citation("usmap")

Coordinate System

usmap uses the US National Atlas Equal Area coordinate system:

sf::st_crs(9311)

r sf::st_crs(9311)

This coordinate reference system (CRS) can also be obtained with usmap::usmap_crs().

Acknowledgments

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

pdil/usmap documentation built on April 3, 2024, 3:58 p.m.