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If you have some R code to include in a document, especially a Web-based document like a blog post, the new “Pretty R” feature on inside-R.org can help you make it look its best. Given some raw R code, it will create a HTML version of the code, adding syntax highlighting elements and links. Functions, strings, comments and literals are all color-coded to make reading easier, and function names are linked to the corresponding R help pages in the Language Reference from inside-R.org.

For example, the Freakonometrics blog had an excellent post the other day on using time series methods to forecast pageviews reported on Google Analytics. (It's a great blog if you haven't checked it out before. I also like it because it gives me a chance to brush up on my French. But I digress.) The author, Arthur Charpentier, did include the R code, but I found it a little hard to read. Here's a screenshot:

I cut-and-pasted the code into the Pretty R tool (after removing the > and + prompts, which I recommend as good practice for posting R code — it makes it easier for others to paste it into a script), and then just pasted the resulting HTML into this blog post. Here's the result:

```base=read.table("http://perso.univ-rennes1.fr/arthur.charpentier/million2.csv",
X2=cumsum(base\$nombre)
X=X1+X2
kt=which(D==as.Date("01/06/2010","%d/%m/%Y"))
D0=as.Date("08/11/2008","%d/%m/%Y")
D=D0+1:length(X1)
P=rep(NA,(length(X)-kt)+1)
for(h in 0:(length(X)-kt)){
model  <- arima(X[1:(kt+h)],c(7 ,   # partie AR
1,                # partie I
7),method="CSS")  # partie MA
forecast <- predict(model,200)
u=max(D[1:kt+h])+1:300
k=which(u==as.Date("01/01/2011","%d/%m/%Y"))
(P[h+1]=1-pnorm(1000000,forecast\$pred[k],forecast\$se[k]))
}```

The Pretty R tool is open to everyone, you don't need to set up an account to use it. I hope it's useful to all R authors and bloggers.

inside-R.org: Pretty R Syntax Highlighter