Question

I am trying to plot some information that shows full population and then a subset of that population by location on a map. I’ve seen data visualizations that use concentric circles or 3-d inverted cones to convey this. I just can’t figure out how to do it in ggplot / ggmap

Here’s a free hand version in Paint that shows a rough idea of what I’m looking to do:

Here’s a rough piece of data for an example:

> dput(df1)
structure(list(zip = c("00210", "00653", "00952", "02571", "04211", 
"05286", "06478", "07839", "10090", "11559"), city = c("Portsmouth", 
"Guanica", "Sabana Seca", "Wareham", "Auburn", "Craftsbury", 
"Oxford", "Greendell", "New York", "Lawrence"), state = c("NH", 
"PR", "PR", "MA", "ME", "VT", "CT", "NJ", "NY", "NY"), latitude = c(43.005895, 
17.992112, 18.429218, 41.751554, 44.197009, 44.627698, 41.428163, 
41.12831, 40.780751, 40.61579), longitude = c(-71.013202, -66.90097, 
-66.18014, -70.71059, -70.239485, -72.434398, -73.12729, -74.678956, 
-73.977182, -73.73126), timezone = c(-5L, -4L, -4L, -5L, -5L, 
-5L, -5L, -5L, -5L, -5L), dst = c(TRUE, FALSE, FALSE, TRUE, TRUE, 
TRUE, TRUE, TRUE, TRUE, TRUE), totalPop = c(43177, 37224, 37168, 
15492, 1614, 88802, 2587, 80043, 78580, 87461), subPop = c(42705, 
36926, 27556, 10827, 774, 39060, 1542, 21304, 53438, 2896)), .Names = c("zip", 
"city", "state", "latitude", "longitude", "timezone", "dst", 
"totalPop", "subPop"), row.names = c(1L, 50L, 200L, 900L, 1500L, 
2000L, 2500L, 3000L, 3500L, 4000L), class = "data.frame")

Any suggestions?

Answer 1

The basic idea is to use separate geoms for the two populations, making sure the smaller one is plotted after the larger one, so its layer is on top:

library(ggplot2) # using version 0.9.2.1
library(maps)

# load us map data
all_states <- map_data("state")

# start a ggplot. it won't plot til we type p
p <- ggplot()  

# add U.S. states outlines to ggplot
p <- p + geom_polygon(data=all_states, aes(x=long, y=lat, group = group),
     colour="grey", fill="white" )

# add total Population
p <- p + geom_point(data=df1, aes(x=longitude, y=latitude, size = totalPop), 
     colour="#b5e521")

# add sub Population as separate layer with smaller points at same long,lat
p <- p + geom_point(data=df1, aes(x=longitude, y=latitude, size = subPop), 
     colour="#00a3e8")

# change name of legend to generic word "Population"
p <- p + guides(size=guide_legend(title="Population"))

# display plot
p 

From the map, it is clear your data include non-contiguous-US locations, in which case you may want different underlying map data. get_map() from ggmap package provides a couple options:

require(ggmap)
require(mapproj)
map <- get_map(location = 'united states', zoom = 3, maptype = "terrain", 
       source = "google")
p <- ggmap(map)

After which you add the total and sub Population geom_point() layers and display it as before.