Jeroen Ooms’s latest APP #rstats #appiness

Jeroen Ooms, famed inventor of Open CPU and advanced Web Apps, just released a new app.


A new   OpenCPU app allows you to knit and markdown in the browser. It has a unique  code editor which automatically updates the output after 3 seconds of inactivity. It uses the Ace web editor with mode-r.js (thanks to RStudio ).

the source package lives in the opencpu app repo on github. You can try it out on the public cloud server

#install the package
install_github("markdownapp", "opencpu")

#open it in opencpu

The app uses the knitr R package and a few lines of javascript to call

Potential Economic Consequences to Western Strike on Assad/Syria


  1. Oil goes up.
  2. Rupee goes down
  3. Bonds go up
  4. Stocks go down
  5. Dollar under some pressure

Medium Term

  1. Oil stays >100
  2. Canadian Oil pipeline better likelihood
  3. Russian wrangles or does not some energy deal/benefit
  4. Economic GDP in West inches up
  5. Clear message sent to other nations with WMD including Iran and North Korea
  6. US Distraction encourages spin off ripple effects from other smaller nations
  7. Terrorism or Al Quaeda in Syria comes back

(based on a question asked)

Click Image for Better Look

Screenshot from 2013-08-27 22:23:13

OpenCPU: Cloud Based Analytics comes to age

After 3 years in development, the latest project from Jeroen Ooms is now ready.
Screenshot from 2013-08-26 19:38:03
Check it out-yourself
OpenCPU is a software framework for embedded statistical computation and reproducible research. The server exposes a web API interfacing R, Latex and Pandoc. This API is used for example to integrate statistical functionality into systems, share and execute scripts or reports on centralized servers, and build R based “apps”. The OpenCPU server can run either as a single-user server inside the interactive R session (for local use and development), or as a cloud server that builds on Linux and rApache.
An OpenCPU app is an R package which includes some web page(s) that call the R functions in the package using the OpenCPU API. This makes a convenient way to develop, package and ship standalone R web applications.
Security is enforced using AppArmor. AppArmor is a security module for the linux kernel and enforces mandatory access control policies on a by-process basis. These policies can easily be customized by modifying the AppArmor profiles that ship with the OpenCPU cloud server.
Both the OpenCPU single-user server and OpenCPU cloud server have been tested to work with RStudio 0.98 and above.
See also the appendix in the server manual on this topic.
Absolutely. OpenCPU is released under the Apache2 License.

Websites for Artists

Here is some work I have been doing on a non-profit basis for painters and artists. Most of them are very creative , but especially the smaller artists need help with making a showcase website for their art. This is also a much more professional option than Tumblr for Websites.

  1. Create a account for the artist
  2. Encourage the artist to take the 18$/per year for custom domain name
  3. Exmplain how you login to with the username and password you created in step1
  4. Bulk Upload their high quality images in the Dashboard > Media > Add New
  5. Chose a theme like because it showcases art work from several posts on the front page
  6. Create a different post  for each painting. At bottom right of the post- set Featured Image. Insert Art work from Add Media button on top> from Media Gallery
  7. Change the About Page by WordPress to add contact details of gallery and information about artist so customers can buy the art
  8. Publish the Website for that painter

Some Websites I have created in less than hour each for artists, for free , are below





Screenshot from 2013-09-26 18:04:48

Screenshot from 2013-09-26 18:04:34

ps- It ‘s also a great way to help your local art community and meet interesting people 🙂

pps- If you dont really like WordPress also check out Wix at

The Excellent V 2.0 of R Commander #rstats

Just a few  clicks with the new version of R Commander and Beautiful Markdown Code. (using KMggplot plugin for R Commander). kmggplot1

ggplot AND markdown made easy!!


Now how cool is that! Update your R Commander Package today . Now on CRAN!

This should especially be useful to people blogging! (note I cleaned up some warnings!)




Iris for Big Data #rstats #bigdata

Quote of the Day-

it is impossible to be a data scientist without knowing iris 

#Anonymous #Quotes


Revolution Analytics has been nice enough to provide both datasets and code for analyzing Big Data in R.

Site was updated so here are the new links


while the Datasets collection is still elementary, as a R Instructor I find this list extremely useful. However I wish they look at some other repositories and make .xdf and “tidy” csv versions. A little bit of RODBC usage should help, and so will some descriptions. Maybe they should partner with Quandl, DataMarket, or Infochimps on this initiative than do it alone.


Overall there can be a R package (like a Big Data version of the famous datasets package in R)

But a nice and very useful effort

Revolution R Datasets

More code-

Also a recent project made by a student of mine on Revolution Datasets and using their blog posts.

Note how much more better the above project is than use the mini and super clean datasets within R (like Boston)


Hat TIP- R’s very own Mr Smith
For more on IRIS


The Wonderful ggmap package for spatial analysis in R #rstats

I really like two functions in ggmap package. One is geocode that converts any text charachter into basically a google maps query and returns the longitude and latitude for it.

geocode("Saddledome Calgary")
> geocode("Calgary")
Information from URL :
Google Maps API Terms of Service :
        lon      lat
1 -114.0581 51.04532
> geocode("Saddledome Calgary")
Information from URL :
Google Maps API Terms of Service :
        lon      lat
1 -114.0513 51.03811



the other is qmap that makes a map out of the text query. We can change the level of detail using the zoom option.

One of the options that I like is of course watercolor using parameter maptype.

qmap("Saddledome Calgary")
qmap("Saddledome Calgary",zoom=15)
qmap("Saddledome Calgary",zoom=15,maptype="watercolor")


Other useful options for spatial analysis are get_map and ggmap which get and plot the map for a query. In between of course you can add the layers for your data.

This is a relatively recent package and you can test it out how it makes spatial analysis even more easy for beginners.

See the package site ,these slides , or this article on the R Journal.