Data Art: London mapped in R

By Data Tricks, 17 October 2017

Last month we published a tutorial on creating a unique map of London in R using the ggplot2 package. We’ve been playing around with colours to produce this rather patriotic and artistic looking alternative map. See below for the full code. Be sure to read our tutorial which has links to the postcode data CSVs.

Full code:

filenames <- c("e.csv", "n.csv", "nw.csv", "se.csv", "sw.csv", "w.csv", "wc.csv", "ec.csv")
postcodes <-,lapply(filenames,read.csv,header=FALSE))
postcodes <- postcodes[-which(postcodes$V3 == 0),]

diagonal1white <- data.frame(V3=c(514709:548505), Diagonal1white=seq(from=195461, to=169935, length.out=33797))
diagonal1red <- data.frame(V3=c(514709:548505), Diagonal1red=seq(from=195461, to=169935, length.out=33797))
diagonal2white <- data.frame(V3=c(514709:548505), Diagonal2white=seq(from=169935, to=195461, length.out=33797))
diagonal2red <- data.frame(V3=c(514709:548505), Diagonal2red=seq(from=169935, to=195461, length.out=33797))
postcodes <- join_all(list(postcodes,diagonal1white,diagonal1red,diagonal2white,diagonal2red), by="V3", type="full")

#Blue background
postcodes$Colour <- "Blue"
postcodes$Colour <- ifelse(abs(postcodes$V4 - postcodes$Diagonal1white)<2500, "White", postcodes$Colour)
postcodes$Colour <- ifelse((postcodes$V3>531607 & (postcodes$V4 - postcodes$Diagonal1red)<1500 & (postcodes$V4 - postcodes$Diagonal1red>-500)), "Red", postcodes$Colour)
postcodes$Colour <- ifelse((postcodes$V3<531607 & (postcodes$V4 - postcodes$Diagonal1red)<500 & (postcodes$V4 - postcodes$Diagonal1red>-1500)), "Red", postcodes$Colour)
postcodes$Colour <- ifelse(abs(postcodes$V4 - postcodes$Diagonal2white)<2500, "White", postcodes$Colour)
postcodes$Colour <- ifelse((postcodes$V3>531607 & (postcodes$V4 - postcodes$Diagonal2red)<1500 & (postcodes$V4 - postcodes$Diagonal2red>-500)), "Red", postcodes$Colour)
postcodes$Colour <- ifelse((postcodes$V3<531607 & (postcodes$V4 - postcodes$Diagonal2red)<500 & (postcodes$V4 - postcodes$Diagonal2red>-1500)), "Red", postcodes$Colour)
postcodes$Colour <- ifelse(abs(postcodes$V3 - 531607)<2500, "White",postcodes$Colour)
postcodes$Colour <- ifelse(abs(postcodes$V4 - 182698)<3000, "White",postcodes$Colour)
postcodes$Colour <- ifelse(abs(postcodes$V3 - 531607)<1500, "Red",postcodes$Colour)
postcodes$Colour <- ifelse(abs(postcodes$V4 - 182698)<2000, "Red",postcodes$Colour)

gg <- ggplot()
gg <- gg + geom_point(data=postcodes[which(postcodes$Colour == "White"),], aes(V3,V4), colour="#ffffff", size=0.2, alpha=0.3)
gg <- gg + geom_point(data=postcodes[which(postcodes$Colour == "Red"),], aes(V3,V4), colour="#c80000", size=0.2, alpha=0.3)
gg <- gg + geom_point(data=postcodes[which(postcodes$Colour == "Blue"),], aes(V3,V4), colour="#0000ff", size=0.2, alpha=0.3)
gg <- gg + coord_fixed(1)
gg <- gg + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())
gg <- gg + theme(axis.title.x=element_blank(), axis.text.x=element_blank(), axis.ticks.x=element_blank())
gg <- gg + theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank())
gg <- gg + theme(panel.background = element_rect(fill = 'grey'))

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