Plot municipal levels of support for Italian parties

plot_comuni.R

## Load libraries
library(sp)
library(RColorBrewer)
library(car)
library(stringdist)

## Read in the shapefile
shape <- readOGR("../shapefiles/",layer="Comuni_11")
shape$NOME <- iconv(shape$NOME, "latin1", "UTF8")
shape$NOME.lc <- tolower(shape$NOME)

shape$Regione <- tolower(car:::recode(shape$COD_REG,
	"'1'='Piemonte';
	'11'='Marche';
	'2'='Valle d\\'Aosta';
	'12'='Lazio';
	'3'='Lombardia';
	'13'='Abruzzo';
	'4'='Trentino-Alto Adige';
	'14'='Molise';
	'5'='Veneto';
	'15'='Campania';
	'6'='Friuli-Venezia Giulia';
	'16'='Puglia';
	'7'='Liguria';
	'17'='Basilicata';
	'8'='Emilia Romagna';
	'18'='Calabria';
	'9'='Toscana';
	'19'='Sicilia';
	'10'='Umbria';
	'20'='Sardegna'"))



## Load the election results
dat <- read.csv("2013_camera_wide.csv",header=T)

## Turn raw numbers into percentages
party.cols <- 4:19
dat[,party.cols] <- dat[,party.cols] / rowSums(dat[,party.cols])

## Tidy up names of municipalities
dat$Comune <- tolower(gsub("Comune di ","",dat$Comune))
## Remove German language alternates
dat$Comune <- gsub("/.*","",dat$Comune)
## Create region variable
dat$Regione <- tolower(gsub(" \\d","",dat$Circoscrizione))

## Strategy, within each region, create matrix of names by names
## pick result with smallest string distance
matchlists <- vector("list",length(unique(dat$Regione)))
unique.regions <- unique(dat$Regione)
for (i in 1:length(unique.regions)) {
	b <- shape$NOME.lc [which(shape$Regione == unique.regions[i])]
	a <- dat$Comune [which(dat$Regione == unique.regions[i])]
	matchlists[[i]] <- stringdistmatrix(a,b)
	rownames(matchlists[[i]]) <- a
	colnames(matchlists[[i]]) <- b
}
## Taking each matrix in turn
## move down the rows (data names)
## and work out which shapefile name it corresponds to 
matchvector <- vector("list",length(unique(dat$Regione)))
for (i in 1:length(unique.regions)) {
	matchvector[[i]] <- data.frame(Regione = unique.regions[i],
		dataName = rownames(matchlists[[i]]),
		shapeName = apply(matchlists[[i]],1,function(x)colnames(matchlists[[i]])[which.min(x)]),
		distance = apply(matchlists[[i]],1,min))
}

matchlist <- do.call("rbind",matchvector)
## There's a tiny problem with one entry
matchlist$shapeName [which(matchlist$dataName=="gravedona ed uniti")] <- NA

## Now merge
dat <- merge(dat,matchlist,
	by.x=c("Regione","Comune"),
	by.y=c("Regione","dataName"),
	all.x=T,all.y=F)

## Merge again, using region and shapefile name as keys
ita <- merge(shape,dat,
	by.x=c("Regione","NOME.lc"),
	by.y=c("Regione","shapeName"),
	all.x=T,all.y=F,sort=FALSE)

## ensure same order as shapefile
shape$sortname <- paste0(shape$Regione,shape$NOME.lc)
ita$sortname <- paste0(ita$Regione,ita$NOME.lc)
my.order <- match(shape$sortname,ita$sortname)
ita <- ita[my.order,]
table(ita$sortname==shape$sortname)

## Set up the information for the plots
party.cols <- 14:28
names(ita)[party.cols]
party.palettes <- recode(names(ita)[party.cols],
	"'Centro.Democratico'='OrRd';
	'Fare.per.Fermare.il.Declino'='Greys';
	'Fratelli.d.Italia'='PuBu';
	'Futuro.e.libertà..Fli.'='GnBu';
	'Grande.Sud...Mpa'='PuBuGn';
	'Il.Popolo.della.libertà..Pdl.'='Blues';
	'La.Destra'='Greys';
	'Lega.Nord'='Greens';
	'MoVimento.5.Stelle...beppegrillo.it'='Purples';
	'Partito.Democratico..Pd.'='Reds';
	'Rivoluzione.Civile'='Oranges';
	'Scelta.Civica.con.Monti.per.l.Italia'='YlGnBu';
	'Sinistra.ecologia.e.libertà..Sel.'='OrRd';
	'Südtiroler.Volkspartei..Svp.'='YlGn';
	'Unione.di.centro..Udc.'='Blues'"
)


## Iterate over parties

for (the.party in party.cols) {
	party.name <- names(ita)[the.party]
	party.name <- gsub("\\."," ",party.name)
	my.breaks <- quantile(ita[,the.party],probs=seq(0,1,by=1/9),na.rm=T)
	## For parties with concentrated support, take only non-zero elements
	if (any(duplicated(my.breaks))) {
		tmp <- ita[,the.party]
		tmp <- tmp[tmp>0]
		my.breaks <- quantile(tmp,probs=seq(0,1,by=1/9),na.rm=T)
	}
	ita$cutcolors <- cut(as.numeric(ita[,the.party]), my.breaks,na.rm=T)
	shape$cutcolors <- ita$cutcolors

	myPalette <- brewer.pal(9, party.palettes[which(party.cols==the.party)])

	## Print
	outfile <- paste0("graphics/",party.name,"_map.pdf")
	outfile <- gsub(" ","_",outfile)
	plot.title <- paste0(party.name," vote share by comune")
	pdf(file=outfile,width=21.0/2.54,height=29.7/2.54,paper="a4")
	print(spplot(shape, "cutcolors", col="transparent", col.regions=myPalette, main=plot.title))
	dev.off()

}