# Plotting spatial neighbors in ggmap

June 15, 2015
By

(This article was first published on Maxwell B. Joseph, and kindly contributed to R-bloggers)

The R package spdep has great utilities to define spatial neighbors (e.g. `dnearneigh`, `knearneigh`, with a nice vignette to boot), but the plotting functionality is aimed at base graphics.
If you’re hoping to plot spatial neighborhoods as line segments in ggplot2, or ggmap, you’ll need the neighborhood data to be stored in a data frame.
So, to save others some trouble, I thought I’d share a little function that converts a spatial neighbors object (of class `nb`) to a data frame.
This function is largely an alteration of the existing plotting function for base graphics, plot.nb.

``````library(spdep)
data(nc.sids)

# function converts nb object to a data.frame
nb_to_df <- function(nb, coords){
x <- coords[, 1]
y <- coords[, 2]
n <- length(nb)

cardnb <- card(nb)
i <- rep(1:n, cardnb)
j <- unlist(nb)
return(data.frame(x=x[i], xend=x[j],
y=y[i], yend=y[j]))
}

# create distance-based neighbors
sids_nb <- dnearneigh(sidscents, d1=0, d2=80, longlat=T)
nb_df <- nb_to_df(sids_nb, sidscents)

# create data frame of coordinates
coord_df <- data.frame(sidscents)
names(coord_df) <- c("lon", "lat")

# plot results with ggmap
library(ggmap)
basemap <- get_map("North Carolina", zoom=6)

ggmap(basemap) +
geom_segment(aes(x=x, xend=xend, y=y, yend=yend),
data=nb_df) +
geom_point(aes(x=lon, y=lat), data=coord_df) +
ylab("Latitude") +
xlab("Longitude")`````` R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...