James Cheshire

R Code

Load the libraries we need

library("ggplot2")
library("ggthemes")
library("rworldmap")
library("classInt")
library("gridExtra")
library("grid")
library("cowplot")

load data – this is the processed file from http://www.nature.com/articles/sdata201634 I offer no guarantees about whether I ran the script correctly etc! I’d encourage you to take the data direct from the authors.

#City data
cities<- read.csv("alldata.csv")
#for some reason the coords were loaded as factors so I've created two new numeric fields here
cities$X<-as.numeric(as.vector(cities$Longitude))
cities$Y<-as.numeric(as.vector(cities$Latitude))
#World map base from rworldmap
world <- fortify(getMap(resolution="low"))

Take a look at the data

head(cities)

Create the base map

base<- ggplot() + geom_map(data=world, map=world, aes(x=long,y=lat, map_id=id, group=group),fill="#CCCCCC") +theme_map()

Now plot the cities on top – with circles scaled by city size. Here I am using the mollweide projection. This script loops through the data and checks for updates from one year to the next. It then plots the cities as proportional circles for each year and saves out an image for each 100 years of data. If you are just interested in the maps themselves and have your own point data then most of the below can be ignored.
Set the breaks for the size of the circles

size_breaks<-c(10000,50000,100000,500000,1000000,5000000,10000000)

#Here I'm looping through the data each year to select the years required and comparing/ updating the values for each city.
count<-1
for (i in unique(cities$year))
{
if (count==1)
{
  Data<-cities[which(cities$year==i),]
}else{
  New_Data<-cities[which(cities$year==i),]
  #replace old rows
  Data2<-merge(Data, New_Data, by.x="X", by.y="X", all=T)
  New_Vals<-Data2[!is.na(Data2$pop.y),c("City.y","X","Y.y","pop.y")]
  names(New_Vals)<-c("City","X","Y","pop")
  Old_Vals<-Data2[is.na(Data2$pop.y),c("City.x","X","Y.x","pop.x")]
  names(Old_Vals)<-c("City","X","Y","pop")
  Data<-rbind(New_Vals,Old_Vals)
  Data<- aggregate(Data$pop, by=list(Data$City,Data$X, Data$Y), FUN="mean")
  names(Data)<-c("City","X","Y","pop")
}
#This statement sorts out the BC/ AC in the title that we'll use for the plot.
if(i<0)
{
title <- paste0("Cities in the Year ",sqrt(i^2)," BC")
}else{
  title <- paste0("Cities in the Year ",i," AD")
}
#There's lots going on here with the myriad of different ggplot2 parameters. I've broken each chunk up line by line to help make it a little clearer.
Map<-base+
  geom_point(data=Data, aes(x=X, y=Y, size=pop), colour="#9933CC",alpha=0.3, pch=20)+
  scale_size(breaks=size_breaks,range=c(2,14), limits=c(min(cities$pop), max(cities$pop)),labels=c("10K","50k","100K","500k","1M","5M","10M+"))+
  coord_map("mollweide", ylim=c(-55,80),xlim=c(-180,180))+
  theme(legend.position="bottom",legend.direction="horizontal",legend.justification="center",legend.title=element_blank(),plot.title = element_text(hjust = 0.5,face='bold',family = "Helvetica"))+ggtitle(title)+guides(size=guide_legend(nrow=1))
#I only want to plot map every 100 years
if(i%%100==0)
{
png(paste0("outputs/",i,"_moll.png"), width=30,height=20, units="cm", res=150)
print(Map)
dev.off()
}
count<-count+1
}

Just to make things a little more interesting I wanted to try a plot of two hemispheres (covering most, but not all) of the globe. I’ve also added the key in between them. This depends on the plot_grid() functionality as well as a few extra steps you’ll spot that we didn’t need above.

count<-1
for (i in unique(cities$year))
{
if (count==1)
{
  Data<-cities[which(cities$year==i),]
}else{
  New_Data<-cities[which(cities$year==i),]
  #replace old rows
  Data2<-merge(Data, New_Data, by.x="X", by.y="X", all=T)
  New_Vals<-Data2[!is.na(Data2$pop.y),c("City.y","X","Y.y","pop.y")]
  names(New_Vals)<-c("City","X","Y","pop")
  Old_Vals<-Data2[is.na(Data2$pop.y),c("City.x","X","Y.x","pop.x")]
  names(Old_Vals)<-c("City","X","Y","pop")
  Data<-rbind(New_Vals,Old_Vals)
  Data<- aggregate(Data$pop, by=list(Data$City,Data$X, Data$Y), FUN="mean")
  names(Data)<-c("City","X","Y","pop")
}
#Create a map for each hemisphere - to help with the positioning I needed to use the `plot.margin` options in the `theme()` settings.
map1<-base+geom_point(data=Data, aes(x=X, y=Y, size=pop), colour="#9933CC",alpha=0.3, pch=20)+scale_size(breaks=size_breaks,range=c(2,16), limits=c(min(cities$pop), max(cities$pop)))+coord_map("ortho", orientation = c(10, 60, 0),ylim=c(-55,70))+ theme(legend.position="none",plot.margin = unit(c(0.5,0.5,-0.1,0.5), "cm"))
map2<- base+geom_point(data=Data, aes(x=X, y=Y, size=pop), colour="#9933CC",alpha=0.3, pch=20)+scale_size(breaks=size_breaks,range=c(2,16),limits=c(min(cities$pop), max(cities$pop)))+coord_map("ortho", orientation = c(10, -90, 0),ylim=c(-55,70))+ theme(legend.position="none", plot.margin = unit(c(0.5,0.5,0,0.5), "cm"))
#create dummy plot that we will use the legend from - basically I just want to create something that has a legend (they've been switched off for the maps above)
dummy<-ggplot()+geom_point(aes(1:7,1,size=size_breaks),colour="#9933CC", alpha=0.3, pch=20)+scale_size(breaks=size_breaks,range=c(2,16),labels=c("10K","50k","100K","500k","1M","5M","10M+"),limits=c(min(cities$pop), max(cities$pop)))+theme(legend.position="bottom",legend.direction="vertical",legend.title=element_blank())+guides(size=guide_legend(nrow=1,byrow=TRUE))
Legend <- get_legend(dummy)
#This statement sorts out the BC/ AC in the title.
if(i<0)
{
title <- ggdraw() + draw_label(paste0("Cities in the Year ",sqrt(i^2)," BC"), fontface='bold',fontfamily = "Helvetica")
}else{
  title <- ggdraw() + draw_label(paste0("Cities in the Year ",i," AD"), fontface='bold',fontfamily = "Helvetica")
}
#I only want to plot map every 100 years
if(i%%100==0)
{
png(paste0("outputs/",i,".png"), width=20,height=30, units="cm", res=150)
#This is where the elements of the plot are combined
print(plot_grid(title,map1, Legend,map2, ncol=1,rel_heights = c(.1,1, .1,1)))
dev.off()
}
count<-count+1
}