Graphing SOPA Shirt Distributions

gistfile1.r

#Sopa data munging:
sopa.d <- read.csv("~/Downloads/Kickstarter Backer Report - $15 reward - Jan 15 6pm.csv")
sopa.i <- read.csv("~/Downloads/Kickstarter Backer Report - $30 reward - Jan 15 6pm.csv")

#International survey didn't have the pickup question so fake a column:
sopa.i$Choices.2 <- sopa.i$Choices.1
sopa.i$Choices.1 <- "No"
sopa <- rbind(sopa.d, sopa.i)

# Rename Levels:
levels(sopa$Choices.2) <- c(NA, "Grey", "White", "White")

#Rename columns:
colnames(sopa) <- c(head(colnames(sopa),-3), "shirt_size", "pickup", "color")

#Reorder sizes levels:
sopa$shirt_size <- factor(sopa$shirt_size, levels = c("", "S", "M", "L", "XL", "XXL"))

#Data.frame should look like this:
#           City    State Postal.Code Country shirt_size pickup color   i8n
#1      Brooklyn       NY       11201     USA         XL    Yes  Grey FALSE
#2           xxx      xxx          xx     USA          M    Yes White FALSE
#3 mountain view       ca       94117     USA          M     No  Grey FALSE
#4      New York       NY  10002-2412     USA         XL    Yes  Grey FALSE
#5      Brooklyn       NY       11215     USA          L    Yes  Grey FALSE
#6      New york New York       10013     USA         XL    Yes  Grey FALSE

qplot(data = droplevels(subset(sopa, shirt_size != "")), x = shirt_size, fill = color, color = I("black"), position = "dodge") +
	scale_fill_manual("Color", breaks = c("Grey", "White"), values = c("grey", "White")) + 
	scale_x_discrete("Shirt Size", breaks = c("", "L", "M", "S", "XL", "XXL"), labels = c("No response", "L", "M", "S", "XL", "XXL")) + 
	scale_y_continuous("Backers")