Jeroen Ooms released a new version of his (amazing) online ggplot2 web interface:

yeroon.net/ggplot2 is a web interface for Hadley Wickham’s R package ggplot2. It is used as a tool for rapid prototyping, exploratory graphical analysis and education of statistics and R. The interface is written completely in javascript, therefore there is no need to install anything on the client side: a standard browser will do.

The new version has a lot of cool new features, like advanced data import, integration with Google docs, converting variables from numeric to factor to dates and vice versa, and a lot of new geom’s. Some of which you can watch in his new video demo of the application:

The application is on:
http://www.yeroon.net/ggplot2/

p.s: other posts about this (including videos explaining how some of this was done) can be views on the category page: R and the web

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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:
http://69.164.204.238:2904/
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:
http://gitorious.org/r-node

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:

How does R-Node works

(Credit: The following text is based on this forum thread)

R-node, uses protovis for drawing graphs. Protovis is a visualization toolkit written in JavaScript using the canvas element. Using simple graphical marks, like boxes and dots, one can construct custom views to present or explore data.

Besides Protovis, R-node also uses jquery and ExtJS core on the front-end.

Most R commands are passed back to the server and their results returned to the client. Some, such as the graph commands, are parsed and the arguments used in javascript re-implementations of the R commands (e.g. the R command ‘plot’ has a protovis equivalent).

The server side is R+Rserve, and to connect the browser client to the R server Jamie used a nodejs based application server.

Projects utilised in this include:

• Protovis – http://vis.stanford.edu/protovis/
• Nodejs – http://nodejs.org/
• R – http://www.r-project.org/
• Rserve – http://www.rforge.net/Rserve/doc.html
• Shjs – http://shjs.sourceforge.net/

I would love to read your thoughts about this in the comments.

Today Jeroen announced a new version (0.11) of his web interface to ggplot2. See it here:
http://www.yeroon.net/ggplot2/

As Jeroen wrote:

New features include 1D geom’s (histogram, density, freqpoly), syntax mode (by clicking the tiny arrow at the bottom), and some additional facet options. And some minor improvements and fixes, most notably for Internet Explorer.
The data upload has not been improved yet, I am working on that. For now, it supports .csv, .sav (spss), and tab delimited data. Please make sure your filename has the appropriate extension and every column has a header in your data. If you export a dataframe from R, use:
write.csv(mydf, ”mydf.csv” , row.names=F). If you upload an spss
datafile, none of this should be a concern.
Supported browsers are IE6-8, FF, Safari, and Chrome, but a recent browser is highly recommended. As always, feedback is more than welcome.

Here is a little demo video that shows how to use the new features:

The datafile from the demo is available at http://www.yeroon.net/ggplot2/myMovies.csv.

I wish the best to Jeroen, and hope to see many more such uses in the future.