The present and future of the R blogosphere (~7 minute video from useR2011)

This is (roughly) the lightning talk I gave in useR2011. If you are a reader of then this talk is not likely to tell you anything new. However, if you have a friend, college or student who is a new useRs of R, this talk will offer him a decent introduction to what the R blogosphere is all about.

The talk is a call for people of the R community to participate more in reading, writing and interacting with blogs.

I was encouraged to record this talk per the request of Chel Hee Lee, so it may be used in the recent useR conference in Korea (2011)

The talk (briefly) goes through:

  1. The widespread influence of the R blogosphere
  2. What R bloggers write about
  3. How to encourage a blogger you enjoy reading to keep writing
  4. How to start your own R blog (just go to
  5. Basic tips about writing a blog
  6. One advice about marketing your R blog (add it to
  7. And two thoughts about the future of R blogging (more bloggers and readers, and more interactive online visualization)

My apologies for any of the glitches in my English. For more talks about R, you can visit the R user groups blog. I hope more speakers from useR 2011 will consider uploading their talks online.

R-bloggers in 2010: Top 14 R posts, site statistics and invitation for sponsors

A year ago (on December 9th 2009), I wrote about founding, an (unofficial) online R journal written by bloggers who agreed to contribute their R articles to the site.

In this post I wish to celebrate R-bloggers’ first birthday by sharing with you:

  1. Links to the top 14 posts of 2010
  2. Reflections about the origin of R-bloggers
  3. Statistics on “how well” R-bloggers did this year
  4. Links to other related projects
  5. An invitation for sponsors/supporters to help keep the site alive

Continue reading R-bloggers in 2010: Top 14 R posts, site statistics and invitation for sponsors

WP-CodeBox: A better R syntax highlighter plugin for WordPress

Today I was informed of (what I believe is) a better the best WordPress plugin for R syntax highlighting called WP-CodeBox.  This plugin doesn’t require any hacks to make it work (as opposed to the WP-Syntax plugin, which I wrote about in the past).  WP-CodeBox can be downloaded and installed on a WordPress by searching for it in the “Add New” section in the plugins menu.

WP-CodeBox provides some nice features (some AJAX based) to the display of the code in the post:

  1. The code box in the post can now be folded (top right of the code box) so the code can be hidden so to not clutter the post (if the code is too long)
  2. The code box is added with another button  (top left of the code box) which allows the reader to see the code in a new window – so to easily enable a copy paste of the code.
  3. The options of the plugin allows automatic row numbering of the code, control over “tab” length and some other features.

p.s: Lastly, my thanks goes to guangchuang yu who’s comment on my original post, and he’s post on wp-codebox and R, has introduced me to this better plugin.

p.p.s: in case you blog on, there is also a solution for R syntax highlighting for bloggers.

R syntax highlighting for bloggers on

Good news for R bloggers who are using to host their blog.

This week, the good people running (special thanks goes to Yoav Farhi), have added the ability for all the users of the platform to be able to highlight their R code inside posts.

Basically you’ll need to wrap the code in your post like this:

[sourcecode language="r"]
test.function = function(r) {
    return(pi * r^2)

(Which will then look like this:
r syntax highlighted code example

Further details (and other supported languages) can be read about on this support page.

This new feature was possible thanks to the work of Yihui Xie (who create the famous cool animation package for R), who created a R syntax brush for the syntaxhighlighter WordPress plugin (the plugin used by for sytnax highlighting) . And thanks should also go to Andrew Redd, the creator of NppToR (which connects between notepad++ to R). He both made some good suggestions, and was game to take on the brush creation in case there would be problems, which thankfully so far there aren’t any)

p.s: If you are a users (e.g: have a self hosted WordPress blog) and want to enable R syntax highlighting for your blog, I would recommend the use of the WP-Syntax plugin (enhanced with GeSHi version which can be downloaded here.

Syncing files across computers using DropBox


In the past few months I have been using DropBox for syncing my work files between my home and work computer. It has saved me from numerous mistakes and from sending the files to myself via e-mail.

Recently I found this service highly useful for sharing files with 4 other people with whom I am working on a data analysis project. Being so happy with it (and also by gaining more storage space by inviting friends to use it), I thought of sharing my experience here with other R users that might benefit from this cool (free) service.

What is Dropbox?

Dropbox is a Software/Web2.0 file hosting service which enable users to synchronize files and folders between computers across the internet.
This is done by installing a software and then picking a “shared folder” on your computer. From that moment on, that folder will be synced with any computer you choose to install the software on (for example, your home/work computer, your laptop – and so on)

DropBox also enables users to share some of their folders with other DropBox users. This seamless integration of the service with your OS file system (Windows, Mac or Linux) is what’s making this service so comfortable, by allowing me to work with co-workers and have the same “project tree” of folders, all of which are always synced.

You could also share a file “online”, by getting a link to it which you could share with others. So for example, you could write an R code, share it online, and call to it later with source(). This is the easiest way I know of how to do this.

Dropbox is a “cloud computing” Web2.0 file hosting service offering both free and paid services. The free version (which I use) offers 2GB of “shared storage” (unless you invite other users, in which case you get some extended storage space. Which is one of my motivations in writing this post).

Dropbox has other non-trivial uses allowing one to:

The service’s major competitors are, Sugarsync and Mozy, non of which I have had the chance of trying.

How to start?

Simply go to:
Sign up, install the software, use the new shared folder, and let me know if it helped you :)

How to get Extra space?

You can:

  • Earn another 750MB of space by connecting your dropbox to your twitter/facebook account and sending a status update about them. To get this bonus, head over to “Get extra space free!” page.
  • Refer a friend to open a dropbox account (every friend joining earns you another 250MB of space). This bonus is bounded by a total of 8GB of added space (after that, you won’t be allowed any more extra space)
  • Upgrade – pay 10$ a month and get extra 50GB

R-Node: a web front-end to R with Protovis

Update (April 6 – 2010) : R-Node now has it’s own a website, with a dedicated google group (you can join it here)

* * * *

The integration of R into online web services is (for me) one of the more exciting prospects in R’s future. That is way I was very excited coming across Jamie Love’s recent creation: R-Node.

What is R-Node

R-Node is a (open source) web front-end to R (the statistical analysis package).

Using this front-end, you can from any web browser connect to an R instance running on a remote (or local) server, and interact with it, sending commands and receiving the responses. In particular, graphing commands such as plot() and hist() will execute in the browser, drawing the graph as an SVG image.

You can see a live demonstration of this interface by visiting:
And using the following user/password login info:
User: pvdemouser
Password: svL35NmPwMnt
(This link was originally posted here)

Here are some screenshots:

In the second screenshot you see the results of the R command ‘plot(x, y)’ (with the reimplementation of plot doing the actual plotting), and in the fourth screenshot you see a similar plot command along with a subsequent best fit line (data points calculated with ‘lowess()’) drawn in.

Once in, you can try out R by typing something like:

x < - rnorm(100)
plot(x, main="Random numbers")
l <- lowess(x)
lines (l$y)

The plot and lines commands will bring up a graph – you can escape out of it, download the graph as a SVG file, and change the graph type (e.g. do: plot (x, type=”o”) ).
Many R commands will work, though only the hist(), plot() and lines() work for graphing.
Please don’t type the R command q() – it will quit the server, stopping it working for everyone! Also, as everyone shares the same session for now, using more unique variable name than ‘x’ and ‘l’ will help you.

Currently there is only limited error checking but the code continues to be improved and developed. You can download it from:

How do you may imagine yourself using something like this? Feel invited to share with me and everyone else in the comments.

Here are some of the more technical details of R-Node:
Continue reading R-Node: a web front-end to R with Protovis

Google spreadsheets + google forms + R = Easily collecting and importing data for analysis

Someone on the R mailing list (link) asked: how can you easily (daily) collect data from many people into a spreadsheet and then analyse it using R.

The answer people gave to it where on various ways of using excel.  But excel files (at least for now),  are not “on the cloud”.  A better answer might be to create a google form that will update a google spreadsheet that will then be read by R.

If my last sentence wasn’t clear to you, then this post is for you.

Continue reading Google spreadsheets + google forms + R = Easily collecting and importing data for analysis