Difference between revisions of "United States presidential election, 2012"

library(OpasnetUtils)
library(ggplot2)

###### Graph functions

fig <- function(data, candidate, log = TRUE) {
	out <- ggplot(data[data$Candidate == candidate , ], aes(x = Tally, y = Support)) +
		geom_point(shape=1) +    # Use hollow circles
		geom_smooth() +           # Add a loess smoothed fit curve with confidence region
		geom_smooth(method = lm) +
		opts(
			axis.text.x = theme_text(size = 20), 
			axis.text.y = theme_text(size = 20), 
			axis.title.x = theme_text(size = 20),
			axis.title.y = theme_text(size = 20, angle = 90), 
			legend.text = theme_text(size = 20),
			legend.title = theme_text(size = 20),
			title = paste("Smoothed regression of support of ", candidate, " along the size of precinct"),
			plot.title = theme_text(size=20)
		) + 
		scale_y_continuous("Candidate result in precinct, %") +
		if(log) {scale_x_log10("Vote tally in precinct") } else {scale_x_continuous("Vote tally in precinct") }

	return(out)
}

cumfig <- function(data, candidate) {
	out <- ggplot(data[data$Candidate == candidate , ], aes(x = Cumtally, y = Cumsupport)) +
		geom_point(shape = 1) +
		geom_smooth()
	return(out)
}

## OHIO ELECTION DATA NOV 2012

Fetch2(data.frame(Name = "election.ohio.2012", Key = "SSDDvuDfVDKOhlkO"))
colnames(election.ohio.2012@data)[colnames(election.ohio.2012@data) == "REGISTERED_VOTERS"] <- "Tally"

election.ohio.2012@data <- merge(
	election.ohio.2012@data, 
	as.data.frame(as.table(tapply(election.ohio.2012@data$Result, election.ohio.2012@data[c("County", "Election")], sum)))
) # Total votes for each county and election.


election.ohio.2012@data$Support <- election.ohio.2012@data$Result / election.ohio.2012@data$Freq


fig(election.ohio.2012@data, "Obama, Barack (D)") 
fig(election.ohio.2012@data, "Romney, Mitt (R)")


# OHIO PRESIDENTIAL PRIMARY ELECTION DATA

#data.oh <- opasnet.csv("c/c8/RepublicanPrimaryElection2012_8-StateCountyTotals.csv")
#head(data.oh)

# OKLAHOMA PRESIDENTIAL PRIMARY ELECTION DATA

data.ok <- opasnet.csv("6/6e/PrimaryElection2012OKresults_20120306.csv", sep = ",", header = TRUE)

data.ok <- data.ok[data.ok$Race_desc == "FOR PRESIDENT" & data.ok$Race_party == "REPUBLICAN" , ]
data.ok$Cand_desc <- data.ok$Cand_desc[ , drop = TRUE] # Drop unused levels of candidate names.

data.ok$Precinct <- as.factor(data.ok$Precinct) # Change precinct numbers to factors.

Totals <- as.data.frame(as.table(tapply(data.ok$Total_votes, data.ok["Precinct"], sum))) # Total votes for each precinct.
data.ok <- merge(data.ok, Totals)
data.ok$Support <- data.ok$Total_votes / data.ok$Freq

# Order precincts from smaller to larger and calculate candidate-specific cumulative sums.

data.ok <- data.ok[order(data.ok$Freq), ]
for(i in levels(data.ok$Cand_desc)) {
	data.ok$Cumvote[data.ok$Cand_desc == i] <- cumsum(data.ok$Total_vote[data.ok$Cand_desc == i])
	data.ok$Cumtally[data.ok$Cand_desc == i] <- cumsum(data.ok$Freq[data.ok$Cand_desc == i])
}

colnames(data.ok)[colnames(data.ok) == "Freq"] <- "Tally"
colnames(data.ok)[colnames(data.ok) == "Cand_desc"] <- "Candidate"


# Calculate cumulative support

data.ok$Cumsupport <- data.ok$Cumvote / data.ok$Cumtally

ggplot(data.ok, aes(x = Cumtally, y = Cumsupport, colour = Candidate)) +
		geom_line(size = 1.2) +
		opts(
			axis.text.x = theme_text(size = 20), 
			axis.text.y = theme_text(size = 20), 
			axis.title.x = theme_text(size = 20),
			axis.title.y = theme_text(size = 20, angle = 90), 
			legend.text = theme_text(size = 20),
			legend.title = theme_text(size = 20),
			title = "Cumulative support of candidates, Oklahoma Primary election, March 6th, 2012", 
			plot.title = theme_text(size=20)
		) + 
		scale_x_continuous("Cumulative vote tally") +
		scale_y_continuous("Candidate result, fraction", limits = c(0, 0.5))

fig(data.ok, "JON HUNTSMAN")
fig(data.ok, "MICHELE BACHMANN")
fig(data.ok, "MITT ROMNEY")
fig(data.ok, "MITT ROMNEY", log = FALSE)
fig(data.ok, "NEWT GINGRICH")
fig(data.ok, "NEWT GINGRICH", log = FALSE)
fig(data.ok, "OVER VOTES")
fig(data.ok, "RICK PERRY")
fig(data.ok, "RICK SANTORUM")
fig(data.ok, "RICK SANTORUM", log = FALSE)
fig(data.ok, "RON PAUL")
fig(data.ok, "UNDER VOTES")