Calculating a Gini Coefficients for a Number of Locales at Once in R

gini.R

# generate random data:
city <- c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J")
income <- sample(1:100000, 
  100, 
	replace = TRUE)
cities <- data.frame(city, income)

# graph our data:
library(ggplot2)
ggplot(cities,
	aes(income)) +
	stat_density(geom = "path",
		position = "identity") + 
	facet_wrap(~ city, ncol = 2)

library(reldist)
# gini coefficient for city A:
gini(cities[which(cities$city == "A"), ]$income)

# gini coefficients for all cities:
ginicities <- aggregate(income ~ city,
	data = cities,
	FUN = "gini")
names(ginisec) <- c("city", "gini")

ginisec

write.csv(ginicities, "gini.csv",
	row.names = FALSE)

aggregate(income ~ city,
	data = cities,
	FUN = "mean")

aggregate(income ~ city,
	data = cities,
	FUN = "median")

aggregate(income ~ city,
	data = cities,
	FUN = "length")

randomdata.csv