Using Red R- R with a Visual Interface

For people complaining about the GUI on R, here is the ah Enterprise Version of R called Red R.

It is available at the website at


You can read more there or just go through the short video created by them at

Basically it is a click and point method of using R with the ability to store schemas and thus very good for repeatable operations as well.

Not bad for epic software, huh?

A Software Called Rattle

One of my favorite software GUI’s- here is a paper talking of it, it was published in R Journal and describes Dr Graham William’s work in it. If you are software user or creator it is worth a dekko in terms of adding analytical extensions for your platform of business.

Interview Hadley Wickham R Project Data Visualization Guru

Here is an interview with the genius behind many of the R Project’s Graphical Packages- Dr Hadley Wickham.

Ajay– Describe your pivotal moments in your career in science from a high school science student leading up till here as a professor.

Hadley– After high school I went to medical school. After three years and a degree I realised that I really didn’t want to be a doctor so I went back to two topics that I had enjoyed in high school: programming and statistics. I really loved the practice of statistics, digging in to data and figuring out what was going on, but didn’t find the theoretical study of computer science so interesting. That spurred me to get my MSc in Statistics and then to apply to graduate school in the US.

The next pivotal moment occurred when I accepted a PhD offer from Iowa State. I applied to ISU because I was interested in multivariate data and visualisation and heard that the department had a focus on those two topics, through the presence of Di Cook and Heike Hofmann. I couldn’t have made a better choice – Di and Heike were fantastic major professors and I loved the combination of data analysis, software development and teaching that they practiced. That in turn lead to my decision to look for a job in academia.

Ajay– You have created almost ten R Packages as per your website Do you think there is a potential for a commercial version for a data visualization R software? What are your views on the current commercial R packages?

Hadley– I think there’s a lot of opportunity for the development of user-friendly data visualisation tools based on R. These would be great for novices and casual users, wrapping up the complexities of the command-line into an approachable GUI – see Jeroen Oom’s for an example.

Developing these tools is not something that is part of my research endeavors. I’m a strong believer in the power of computational thinking and the advantages that programming (instead of pointing and clicking) brings. Creating visualizations with code makes reproducibility, automation and communication much easier – all of which are important for good science.

Commercial packages fill a hole in the R ecosystem. They make R more palatable to enterprise customers with guaranteed support, and they can offer a way to funnel some of that money back into the R ecosystem. I am optimistic about the future of these endeavors.

Ajay– Clearly with your interest in graphics, you seem to favor visual solutions. Do you also feel that R Project could benefit from better R GUIs or GUIs for specific packages?

Hadley– See above – while GUIs are useful for novices and casual users, they are not a good fit for the demands of science. In my opinion, what R needs more are better tutorials and documentation so that people don’t need to use GUIs. I’m very excited about the new dynamic html help system – I think it has huge potential for making R easier to use.

Compared to other programming languages, R currently lacks good online (free) introductions for new users. I think this is because many R developers are academics and the incentives aren’t there to make freely available documentation. Personally, I would love to make (e.g.) the ggplot2 book available openly available under a creative common license, but I would receive no academic credit for doing so.

Ajay– Describe the top 3-5 principles which you have explained in your book, ggplot2: Elegant graphics for data analysis). What are other important topics that you cover in the book?

Hadley– The ggplot2 book gives you the theory to understand the construction of almost any statistical graphic. With this theory in hand, you are much better equipped to create visualisations that are tailored to the exact problem you face, rather than having to rely on a canned set of pre-made graphics.

The book is divided into sections based on the components of this theory, called the layered grammar of graphics, which is based on Lee Wilkinson’s excellent “The Grammar of Graphics”. It’s quite possible to use ggplot2 without understanding these components, but the better you understand, the better your ability to critique and improve your graphics.

Ajay– What are the five best tutorials that you would recommend for students learning data visualization in R? As a data visualization person do you feel that R could do with more video tutorials?

Hadley– If you want to learn about ggplot2, I’d highly recommend the following two resources:

* The Learning R blog,
* The ggplot2 mailing list,

For general data management and manipulation (often needed before you can visualise data) and visualisation using base graphics, Quick-R ( is very useful.

Local useR groups can be an excellent if you live nearby. Lately, the bay area ( and the New York ( useR groups have had some excellent speakers on visualisation, and they often post slides and videos online.

Ajay– What are your personal hobbies? How important are work-life balance and serendipity for creative, scientific and academic people?

Hadley– When I’m not working, I enjoy reading and cooking. I find it’s important to take regular breaks from my research and software development work. When I come back I’m usually bursting with new ideas. Two resources that have helped shape my views on creativity and productivity are Elizabeth’s Gilbert TED talk on nurturing creativity ( and
“The Creative Habit: Learn It and Use It for Life”, by Twyla Twarp ( I highly recommend both of them.

Dr Wickham’s impressive biography can be best seen at

Fast R Graphics

So you don’t know R  because you were always working on office projects and did not have time to learn. The R list looked down on you and told you to read the documentation first. And then you needed to create some fast R graphics and some R code.

Help is here-

Download R from,install it

open it-go to packages> set CRAN Mirror > to your country from drop down

type following in the R GUI near the ‘ >’ prompt-

“install.packages(“rattle”, dependencies=TRUE)”

so it should loook like

>install.packages(“rattle”, dependencies=TRUE)

Wait 15 minutes while downloads happen

Then packages>load package>rattle

Type rattle() at the command prompt

Now – in the new window called Rattle

load data from a .csv file using the browse options

click execute

Go straight to Explore-and click on distibutions.

Note you can also download rattle from , these guys are the best.

Here are the graphs


But what about the code (note some variable names disguised).The code may be intimidating to a novice R user but it is auto generated , its like jumping straight to SAS Enterprise without learning SAS Editor-

Go to the last tab -log and

see the auto generated code.


Choosing GUI for R :Simplify

While trolling through R literature, came across some good GUI ‘s for R. I am currently experimenting with two of them .

Out of these I can recommend R Commander 

Not only is the GUI quite neat and clean, the interface actually prints out R code for you. so its a great help if you are learning R and want to learn and do projects at the same time. I imported a dataset of 200,000 rows and while it did take 3-5 secs longer than SAS or SPSS would have taken —Its very very good for a free STATS package. The graphics are also quite good , and I currently evaluating the modeling and scoring capabilities as well .

The second GUI is Rattle. 

It is slightly less easy to install than R Commander which automatically downloads the dependencies in terms of packages and its also bigger (nearly 15 mb) for a dependency named RGtk2.

Coming up , a side by side comparison of these two GUI’s in terms of modeling and a search for additional GUIs.

Speaking of search, there  is a FireFox Add on for searching R specific material.

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