Making a population density map from tabulated (.txt) data in R?

Question

I have California population density data from from the U.S. Census in an Excel file.

The spatial information is provided in ZIP Code Tabulation Areas (ZCTAs). How do I plot a population density map with that data using R?

This is what I have been doing:

dataset

library(maptools)
library(RColorBrewer)
library(classInt)
library(maps)

## set the working directory.
setwd("../Downloads")

## load the file
pop <- read.table("mre.txt", header=TRUE, row.names=1, sep=",")

#select color palette and the number colors (levels of income) to represent on the map
colors <- brewer.pal(9, "YlOrRd")

#set breaks for the 9 colors 
brks<<-classIntervals(pop$POP10, n=9, style="quantile")
brks<- brks$brks

#plot the map
plot(pop, col=colors[findInterval(pop$POP10, brks,all.inside=TRUE)], axes=F)

I also tried this other way:

CaliforniaZTACs<-readShapePoly("[tl_2010_06_zcta510.shp][2]")
plot(CaliforniaZTACs)
CaliforniaZTACs

but could not associate a population density value from my dataset to the location ID of the tl_2010-06-zcta510.shp file.

Answer 1

The more populated area seems to be the regions of San Francisco and Los Angeles, right?

library(ggplot2)

pop <- read.table("mre.txt", header=TRUE, row.names=1, sep=",")
pop <- data.frame(pop)

ggplot(data=pop,aes(x=LONG,y=LAT)) + geom_point(data=pop, aes(size=POP10)) + theme_bw()

You can also add a Google Maps (or OpenStreetMap) image as background with R get_map function and plot it with ggmap package + your data.

library(ggmap)

x <- get_map(location="California", zoom=6, maptype="terrain")

ggmap(x, extent="normal") + geom_point(data=pop, aes(x=LONG,y=LAT,size=POP10)) + theme_bw()