Mapping Capabilities in R

[This article was first published on Statistical Research » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

From time-to-time creating a basic map of the United States or other parts of the world to complement some statistical analysis is useful to emphasize a point. The maps package in R provide a good way to produce these these maps.  These maps axes are based on latitude and longitude so overlaying other information on these maps is quite simple.  Furthermore, it makes a nice addition to geo-spatial analysis.

This is a simple introductory example that is designed to show a couple of different examples.  First, it shows the USA lower 48 states database and how it can be used to create the state boundaries.  Second, the world database is used to add Alaska and Hawaii.  A nice feature is that the colors for each of the state boundaries can be easily changed to group states.   This (non-optimized) code shows a basic example on how to use the maps package to show the Election Day poll closing times for all 50 states and the District of Columbia.

m <- map("state", interior = FALSE, plot=FALSE)

m$my.colors <- 0
m$my.colors[m$names %in% c("virginia:main","georgia","vermont","kentucky","indiana","south carolina")] <- 2
m$my.colors[m$names %in% c("west virginia","north carolina:main","ohio")] <- 3
m$my.colors[m$names %in% c("tennessee","rhode island","oklahoma","new jersey","mississippi","massachusetts:main","illinois","maryland","maine","missouri","new hampshire","new jersey","pennsylvania","florida","connecticut","delaware","district of columbia","alabama")] <- 4
m$my.colors[m$names %in% c("arkansas")] <- 5
m$my.colors[m$names %in% c("arizona","colorado","kansas","louisiana","minnesota","michigan:north","michigan:south","nebraska","new york:main","new york:manhattan","new york:staten island","new york:long island","new mexico","north dakota","south dakota","texas","wyoming","wisconsin")] <- 6
m$my.colors[m$names %in% c("iowa","montana","nevada","utah")] <- 7
m$my.colors[m$names %in% c("california","idaho","oregon","washington:main")] <- 8 <- map("world", c("USA","hawaii"), xlim=c(-180,-65), ylim=c(19,72),interior = FALSE)
title("Election Day Poll Closing Times")

map("state", boundary = FALSE, col="grey", add = TRUE, fill=FALSE)
map("state", boundary = TRUE, col=m$my.colors, add = TRUE, fill=TRUE )
map("world", c("hawaii"), boundary = TRUE, col=8, add = TRUE, fill=TRUE )
map("world", c("USA:Alaska"), boundary = TRUE, col='orange', add = TRUE, fill=TRUE )
legend("topright", c('7:00pm','7:30pm','8:00pm','8:30pm','9:00pm','10:00pm','11:00pm','1:00am'),
pch=15, col=c(2,3,4,5,6,7,8,'orange'), title="Poll Closing Time (EST)", ncol=2, cex=1.2)

Because the maps are based on longitude and latitude this package can be extended beyond just county, state and country boundaries and can be used on techniques like kriging and co-kriging to develop model-based maps.

To leave a comment for the author, please follow the link and comment on their blog: Statistical Research » R. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)