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.
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:
My wife is a big lover of dance (especially Dance In Israel), and while reading through the NYtimes article: “To Impress, Tufts Prospects Turn to YouTube“, she found me a pearl: A woman performing interpretive dances for math/statistical plots. That includes small dance for: scatter plots, boxplots, barplots and a few others. Enjoy:
Duncan Murdoch just posted a youtube video presenting an animation clip of a 3d rgl object.
Duncan even went further and wrote an explanation on how he made the video:
here are the steps I used: 1. Design a shape to be displayed, and then play with the animation functions to make it change over time. Use play3d to do it live in R, movie3d to write the individual frames of the movie to .png files. 2. Use the ffmpeg package (not an R package, a separate project at http://ffmpeg.org) to convert the .png files to an .mp4 file. The individual frames totalled about 1 GB; the compressed movie is about 45 MB. 3. Upload to Youtube. I’m not a musician, so I had to use one of their licensed background tracks, I couldn’t write my own. I spent a lot of time picking one and then adjusting the timing of the video to compensate. Each render/upload cycle at full resolution took about an hour and a half. It’s a lot faster to render in a smaller window with fewer frames per second, but it’s still tedious. It’s easier to synchronize if you actually have a copy of the music locally, but Youtube doesn’t let you download their music. So the timing isn’t perfect, but it’s good enough for me!
I’ve been doodling some chart in R/ggplot using geom_text() to generate a labelled scatterplot. The chart actually builds up several layers using different datasets, so it’s not obvious how to set the ranges cleanly: I know the lower bound I want for the y-axis (y=0), but I want to let the upper bound float. There’s […]
Following the very positive feedback that Andreas and I have received from delegates of the first R in Insurance conference in July of this year, we are planning to repeat the event next year. We have already reserved a bigger auditorium. The second conference on R in Insurance will be held on Monday 14 July 2014 at Cass Business School in London, UK. This o […]
R can do a lot of really amazing things, but to use just about any of R's many features you need to first import your data and get it into the appropriate shape. For R beginners, this "data wrangling" task can be daunting. Fortunately, ComputerWorld's Sharon Machlis has created an in-depth tutorial for many data preparation tasks, which i […]
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After my last post I have recurringly received two questions: (a) is it worthwhile to analyze GNU R speed in simulations and (b) how would simulation speed compare between GNU R and Python. In this post I want to address the former question and next ti...
We’re pleased to announce two upcoming in-person training opportunities: Advanced R programming. SF, Dec 16-17. Learn the most important topics from advanced R programming in person. One day one, you’ll learn about metaprograming, functional programming and object oriented programming in R, as well general best practices for programming. Taught by Hadley Wic […]
P-values seem to be the bane of a statistician’s existence. I’ve seen situations where entire narratives are written without p-values and only provide the effects. It can also be used as a data reduction tool but ultimately it reduces the world into a binary system: yes/no, accept/reject. Not only that but the binary threshold is […]