In my previous post, I discussed how to use OpenStreetMaps (and standard plotting functions of R) to visualize John Snow’s dataset. But it is also possible to use Google Maps (and ggplot2 types of graphs).

library(ggmap)
get_london <- get_map(c(-.137,51.513), zoom=17)
london <- ggmap(get_london)

Again, the tricky part comes from the fact that the coordinate representation system, here, is not the same as the one used on Robin Wilson’s blog.

> library(maptools)
> setwd("/cholera/")
> deaths <- readShapePoints("Cholera_Deaths")
> head(deaths@coords)
coords.x1 coords.x2
0  529308.7  181031.4
1  529312.2  181025.2
2  529314.4  181020.3
3  529317.4  181014.3
4  529320.7  181007.9
5  529336.7  181006.0
> X <- deaths@coords

or, use d X_deaths.RData. So now, we have to change it

df_deaths <- data.frame(X)
library(sp)
library(rgdal)
coordinates(df_deaths)=~coords.x1+coords.x2
proj4string(df_deaths)=CRS("+init=epsg:27700") 
df_deaths = spTransform(df_deaths,CRS("+proj=longlat +datum=WGS84"))

Here, we have the same coordinate system as the one used in Google Maps. Now, we can add a layer, with the points,

london + geom_point(aes(x=coords.x1, y=coords.x2),data=data.frame(df_deaths@coords),col="red")

Again, it is possible to add the density, as an additional layer,

london + geom_point(aes(x=coords.x1, y=coords.x2), 
data=data.frame(df_deaths@coords),col="red")+
geom_density2d(data = data.frame(df_deaths@coords), 
aes(x = coords.x1, y=coords.x2), size = 0.3) + 
stat_density2d(data = data.frame(df_deaths@coords), 
aes(x = coords.x1, y=coords.x2,fill = ..level.., alpha = ..level..),size = 0.01, bins = 16, geom = "polygon") + scale_fill_gradient(low = "green", high = "red",guide = FALSE) + 
scale_alpha(range = c(0, 0.3), guide = FALSE)