Following today’s announcement, by Ian Fellows, regarding the release of the new version of Deducer (0.4) offering a strong support for ggplot2 using a GUI plot builder, Ian also sent an e-mail where he shows how to create a rose plot using the new ggplot2 GUI included in the latest version of Deducer. After the template is made, the plot can be generated with 4 clicks of the mouse.
Here is a video tutorial (Ian published) to show how this can be used:
Ian fellows, a hard working contributer to the R community (and a cool guy), has announced today the release of Deducer (0.4) to CRAN (scheduled to update in the next day or so). This major update also includes the release of a new plug-in package (DeducerExtras), containing additional dialogs and functionality.
Following is the e-mail he sent out with all the details and demo videos.
For your convenience (and with Ian’s permission), I am reposting his proposal here. You are welcome to send him feedback by e-mailing him (at: firstname.lastname@example.org), or by leaving a comment here (and I will direct him to your comment).
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 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://220.127.116.11:2904/ 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")
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.
One of the exciting new frontiers for R programming is of creating website interfaces to R code. At the forefront of this domain is a young and (very) bright man called Jeroen Ooms, whom I had the pleasure of meeting at useR 2009 (press the link to see his presentation).
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: