Romain Francois, Professional R Enthusiast

I'm trying to make improvements to the R Graph Gallery, I'm looking for suggestions from users of the website.

I've started a question on the website's facebook page. Please take a few seconds to vote to existing improvements possibilities and perhaps offer some of your own ideas.

The purpose of Rcpp modules has always been to make it easy to expose C++ functions and classes to R. Up to now, Rcpp modules did not have a way to declare inheritance between C++ classes. This is now fixed in the development version, and the next version of Rcpp will have a simple mechanism to declare inheritance.

Consider this simple example, we have a base class Shape with two virtual methods (area and contains) and two classes Circle and Rectangle) each deriving from Shape and representing a specific shape.

The classes might look like this:

And we can expose these classes to R using the following module declarative code:

It is worth noticing that:

• The area and contains methods are exposed as part of the base Shape class
• Classes Rectangle and Circle simply declare that they derive from Shape using the derives notation.

R code that uses these classes looks like this:

So, let's crawl some data out of facebook using R. Don't get too excited though, this is just a weekend whatif project. Anyway, so for example, I want to download some photos where I'm tagged.

First, we need an access token from facebook. I don't know how to get this programmatically, so let's get one manually, log on to facebook and then go to the Graph API Explorer

Grab the access token and save it into a variable in R

access_token <- "************..."

Now we need to study the graph api to figure out the url we need to build to do what we want to do, e.g. here we want "me/photos". I've wrapped this into an R function:

And then we can use it:

That's it, I told you it was not that exciting, but it was still worth playing with ...

Blogroll:

• Mining Facebook Data: Most "Liked" Status and Friendship Network.
• Download your Facebook photos using R

The Google Open Source Programs Office sponsored me to create the new int64 package that has been released to CRAN a few days ago. The package has been mentionned in an article in the open source blog from Google.

The package defines classes int64 and uint64 that represent signed and unsigned 64 bit integer vectors. The package also allows conversion of several types (integer, numeric, character, logical) to 64 bit integer vectors, arithmetic operations as well as other standard group generic functions, and reading 64 bit integer vectors as a data.frame column using int64 or uint64 as the colClasses argument.

The package has a vignette that details its features, several examples are given in the usual help files. Once again, I've used RUnit for quality insurance about the package code

int64 has been developped so that 64 bit integer vectors are represented using only R data structures, i.e data is not represented as external pointers to some C++ object. Instead, each 64 bit integer is represented as a couple of regular 32 bit integers, each of them carrying half the bits of the underlying 64 bit integer. This was a choice by design so that 64 bit integer vectors can be serialized and used as data frame columns.

The package contains C++ headers that third party packages can used (via LinkingTo: int64) to use the C++ internals. This allows creation and manipulation of the objects in C++. The internals will be documented in another vignette for package developpers who wish to use the internals. For the moment, the main entry point is the C++ template class LongVector.

I'm particularly proud that Google trusted me to sponsor the development of int64. The next versions of packages Rcpp and RProtoBuf take advantage of the facilities of int64, e.g. Rcpp gains wrapping of C++ containers of 64 bit integers as R objects of classes int64 and uint64 and RProtoBuf improves handling of 64 bit integers in protobuf messages. More on this later

I played around with reverse dependencies of Rcpp. At the moment, 44 packages depend on Rcpp and the number goes up to 53 when counting recusive reverse dependencies.

I've used graphviz for the representation of the directed graph

Here is the code I've used to generate the dot file:

The R Bloggers website, maintained by Tal Galili, aggregates blogs (including mine) from many people of the R community.

Tal and I have been wondering about how to tight R Bloggers with the gallery, supporting each other's website. To that extent, I've made a quick and dirty widget, using the jquery cycle plugin that is now on the right sidebar of R bloggers, inside the related sites box.

The widget first chooses 20 items from the gallery at random, and then cycles through them.

This is an initial design made specifically for R Bloggers, but it is quite likely that I will improve on this and make the widget more generic so that other website can use it to advertise for the gallery.

I've added a PayPal button into the graph, just in case people want to help the development of the website

Following up on yesterday's post about facebook like box, I've added some more social things into the gallery. The main page gains a google plus "plus one" button, and each graph page now has a +1 button, a facebook like button, and a facebook comment box

You can now find me in google+, and still on facebook

The Journal of Statistical Software published our Rcpp article