Here is not only the requested elderberry chart, but also the
R script that generated it.
If theymos updates the data you'll be able to generate the same charts yourself (after changing the pastebin url in the script).
### reddit/r/Bitcoin stats
require(RJSONIO)
require(reshape)
require(ggplot2)
### change "pasteBinUrl" if theymos updates data
###
pasteBinUrl <- "http://pastebin.com/6kbMAAR3"
###
### functions
date.func <- function(x) ISOdate(1970,1,1)+ x$Unixtime
### download data
uniqueID <- gregexpr("[1-9]", pasteBinUrl)[[1]]
reddit <- fromJSON(paste("http://pastebin.com/download.php?i=", substr(pasteBinUrl, uniqueID[1], uniqueID[2]), sep=''))
### format data sets for plotting
r.month <- data.frame(do.call(rbind, reddit$month))
r.day <- data.frame(do.call(rbind, reddit$day))
r.hour <- data.frame(do.call(rbind, reddit$hour))
colnames(r.month) <- c("Unixtime", paste(c("Uniques per", "Pageviews per"),"month"))
colnames(r.day) <- c("Unixtime", paste(c("Uniques per", "Pageviews per", "Subscriptions per"),"day"))
colnames(r.hour) <- c("Unixtime", paste(c("Uniques per", "Pageviews per"), "hour"))
#r.day$"Cumulative subscriptions" <- rev(c(cumsum(r.day$Subscriptions)))
r.day$Date <- date.func(r.day); r.month$Date <- date.func(r.month); r.hour$Date <- date.func(r.hour)
plot.df <- rbind(
melt(r.month[, 2:4], id="Date"),
melt(r.day[, 2:5], id="Date"),
melt(r.hour[, 2:4], id="Date")
)
#### the chart
reddit.plot <- ggplot(plot.df, aes(Date, value)) +
geom_line() +
facet_wrap(~variable, scales="free", ncol=1) +
ggtitle("r/Bitcoin statistics from theymos' data") + xlab("") + ylab("")
png(paste('reddit', Sys.Date(), '.png',sep=''),height=960*4,width=960*16/9*4/5,res=220)
reddit.plot
dev.off()
#### the end
. 
