Comments have gone both ways, with Ware being dubbed (in a somewhat derogatory way) the "Britain capital of porn", while some people have highlighted the better "performance", shall we say, of Ware viewers (who, ahem, lasted on line nearly 2 minutes longer than the average viewer).
The data (or at least an excerpt) are available from The Guardian website and so I have very, very quickly played around with them. In particular, I think that it's kind of weird that the analysis focussed just on the maximum value; so I had a quick look at the entire distribution.
Interestingly, it appears that not just Ware, but basically all of the British towns in the dataset are above the world average; some are even very close to the porn capital! So do the same comments made for Ware apply to the whole of the UK?
After downloading the data to a file "PornUse.csv", you can easily recreate the graph with this very simple R code:
boxplot(time_seconds~Region,main="Time spent online viewing porn (in secs)",ylab="Time (seconds)")
abline(h=536,lwd=2,lty=2)
ord <- order(time_seconds,decreasing=TRUE)
for (i in 1:3) {
text(1,time_seconds[ord[i]],Town[ord[i]],cex=.6,pos=4)
}
ord2 <- order(time_seconds,decreasing=FALSE)
text(4,time_seconds[ord2[4]],Town[ord2[4]],cex=.6,pos=4)
for (i in 1:3) {
text(1,time_seconds[ord2[i]],Town[ord2[i]],cex=.6,pos=4)
}
ord <- order(time_seconds,decreasing=TRUE)
for (i in 1:3) {
text(1,time_seconds[ord[i]],Town[ord[i]],cex=.6,pos=4)
}
ord2 <- order(time_seconds,decreasing=FALSE)
text(4,time_seconds[ord2[4]],Town[ord2[4]],cex=.6,pos=4)
for (i in 1:3) {
text(1,time_seconds[ord2[i]],Town[ord2[i]],cex=.6,pos=4)
}
Hah, "lasted" -- brilliant choice of words, Gianluca!
ReplyDeleteCarefully searched! ;-)
ReplyDeleteI don't have any knowledge of R code but to me the letter R does really suite the post.
ReplyDeleteHadn't thought of that, Picchio $-$ but you do have a point! :-)
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ReplyDeleteWow, thank you very much for sharing this, pretty similar to what was posted on http://www.sextingusers.com/
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