R code for the Dataviz MOOC exercise, week 1.

IIDVIZs01.R

library(ggplot2)

top10 <- structure(list(Country = structure(c(10L, 2L, 9L, 3L, 6L, 7L, 
8L, 4L, 5L, 1L), .Label = c("Brazil", "China", "France", "Germany", 
"India", "Japan", "Russia", "Saudi Arabia", "UK", "USA"), class = "factor"), 
    Budget = c(739.3, 89.8, 62.7, 58.8, 58.4, 52.7, 46.2, 44.2, 
    37.3, 36.6)), .Names = c("Country", "Budget"), class = "data.frame", row.names = c(NA, 
-10L))
top10$Country <- factor(top10$Country, levels=c(as.character(rev(top10$Country)))) 
png(filename="fig1.png",600,600,res=72)
ggplot(top10, aes(x=Country, y=Budget)) + geom_bar(stat="identity", fill="darkgrey") + coord_flip() + labs(title = "The overwhelming US military domination:\nTop 10 Defence Budgets in 2011") + theme_tufte() + theme(plot.title = element_text(lineheight=1, face="bold", hjust=0),axis.text = element_text(size=12), axis.title = element_text(size=12)) + xlab("") + ylab("Budget (in US$bn)") + geom_text(aes(label = Budget),hjust=1.1, family="serif")
dev.off()

top10relative <- structure(list(Country = structure(c(8L, 7L, 4L, 10L, 9L, 5L, 
1L, 3L, 6L, 2L), .Label = c("Algeria", "Armenia", "Iraq", "Israel", 
"Jordan", "Myanmar", "Oman", "Saudi Arabia", "USA", "Yemen"), class = "factor"), 
    Budget = c(8.26, 6.42, 5.99, 5.5, 4.91, 4.82, 4.47, 4.46, 
    4.42, 3.77)), .Names = c("Country", "Budget"), class = "data.frame", row.names = c(NA, 
-10L))
top10relative$Country <- factor(top10relative$Country,levels=rev(as.character(top10relative$Country)))
png(filename="fig2.png",600,600,res=72)
ggplot(top10relative, aes(x=Country, y=Budget)) + geom_bar(stat="identity", fill="darkgrey") + coord_flip() + labs(title = "The strongest defence efforts:\nTop 10 Defence Budgets in 2011, as a % of GDP") + theme_tufte() + theme(plot.title = element_text(lineheight=1, face="bold", hjust=0),axis.text = element_text(size=12), axis.title = element_text(size=12)) + xlab("") + ylab("Budget (as a % of GDP)") + geom_text(aes(label = Budget),hjust=1.1, family="serif")
dev.off()

regions <- structure(list(Country = structure(c(16L, 15L, 3L, 4L, 7L, 8L, 
2L, 6L, 5L, 9L, 12L, 13L, 11L, 1L, 10L, 14L), .Label = c("Brazil", 
"China", "France", "Germany", "India", "Japan", "NATO Europe", 
"Non NATO Europe", "Other Asia and Australasia", "Other Latin America and the Carribean", 
"Other Middle East and North Africa", "Russia", "Saudi Arabia", 
"Sub-Saharan Africa", "UK", "USA"), class = "factor"), Continent = structure(c(5L, 
2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 6L, 4L, 4L, 3L, 3L, 7L), .Label = c("Asia", 
"Europe", "Latin America and the Carribean", "Middle East and North Africa", 
"North America", "Russia", "Sub-Saharan Africa"), class = "factor"), 
    Share = c(45.7, 3.9, 3.6, 2.7, 7.8, 1.6, 5.5, 3.6, 2.3, 7, 
    3.3, 2.9, 5, 2.3, 1.8, 1)), .Names = c("Country", "Continent", 
"Share"), class = "data.frame", row.names = c(NA, -16L))
regions$Country <- factor(regions$Country, levels=rev(as.character(regions$Country)))
regions$Continent <- factor(regions$Continent, levels = unique(as.character(regions$Continent)))
library(plyr)
regions$coord <- ddply(regions, .(Continent), summarize, (cumsum(Share) + cumsum(Share)-Share)/2)[,2]
regions$Continent <- factor(regions$Continent, levels = rev(c("Sub-Saharan Africa","Russia", "Latin America and the Carribean", "Middle East and North Africa", "Asia","Europe", "North America")))
levels(regions$Continent) <- rev(c("Sub-Saharan Africa","Russia", "Latin America and\nthe Carribean", "Middle East and\n North Africa", "Asia","Europe", "North America")) 
levels(regions$Country)[c(1,2,4,7,11)] <- c("Sub-Saharan\nAfrica", "Other Latin America\nand the Caribbean", "Other Middle East\nand North Africa", "Other Asia and\nAustralasia", "Non Nato\nEurope")
library(scales)
png(filename="fig3.png",1000,600,res=72)
ggplot(regions, aes(x=Continent, y=Share, fill=Country)) + geom_bar(stat="identity")  + labs(title = "The West dominates the World's Defence Spendings: \nPlanned Global Defence Expenditures by Region and Country as % of global spendings, 2011") + theme_tufte() + theme(plot.title = element_text(lineheight=1, face="bold", hjust=0,size=18),axis.text = element_text(size=12), legend.position="none") + xlab("") + ylab("") + geom_text(aes(y=coord,label = Country),vjust=0.5) + scale_y_continuous(labels=function(x) return(paste(x, " %", sep="")))
dev.off()