Scraping and plotting InTrade data

price_and_volume.R

# Scraping and plotting InTrade data
doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ggplot2", "lubridate")
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Fin the "contractId" of the contract in which you're interested
# Let's try Barack Obama to win the third Presidential debate:
# http://www.intrade.com/v4/markets/contract/?contractId=766623
contractID <- 766623  # second debate is 766621

# InTrade makes it easy to get their contract data:
URL <- paste0("http://data.intrade.com/graphing/jsp/downloadTaS.jsp?contractId=",
              contractID,
              "&timezone=US/Eastern")
timeAndSales <- read.csv(URL, as.is = T)
head(timeAndSales)

# Use lubridate to convert characters to POSIXlt date/times:
timeAndSales$Time <- parse_date_time(timeAndSales$Date.and.time,
                                        "b d, Y I:M p")
# Narrow window of interest
startCutoff <- ymd_hms("2012-10-22 20:00:00")  # So
endCutoff <- ymd_hms("2012-10-22 23:30:00")    # easy!
timeAndSales <- with(timeAndSales, timeAndSales[Time > startCutoff & Time < endCutoff, ])

zp1 <- ggplot(data = timeAndSales)  #    \/ as.numeric seems necessary to avoid an error
zp1 <- zp1 + geom_vline(aes(xintercept = as.numeric(Time), alpha = Volume),
                        lwd = 2, colour = gray(1/3))
zp1 <- zp1 + geom_smooth(aes(x = Time, y = Price))
zp1 <- zp1 + geom_line(aes(x = Time, y = Price),
                       colour = "firebrick")
zp1 <- zp1 + scale_x_datetime()
zp1 <- zp1 + theme_bw()
zp1 <- zp1 + scale_y_continuous(limits = c(0, 100), expand = c(0, 0))
zp1 <- zp1 + ggtitle("InTrade Price for\n\"Barack Obama to win the third Presidential debate\"")
print(zp1)