Notes from the Kölner R meeting, 6 March 2015

[This article was first published on mages' blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

At last Friday’s Cologne R user group meeting we welcomed two Northerners from the left and right (or ‘right’ and ‘wrong’) side of the Rhine.

Using R in Excel via R.NET

Günter Faes and Matthias Spix

Download slides

Günter and Michael presented examples of a new R Excel plugin Calidris they developed using The plugin itself is written in C# and adds an R ribbon to Excel with pre-build functions.

In its current form the add-in is a proof of concept. It demonstrates in principal that functions based on R can be added to Excel. The version Günter and Michael demonstrated doesn’t have a reactive functionality yet, i.e. updating a cell will not update the output of an R function automatically at the moment. Feel free to get in touch with them if you would like to know more about their project. You find their contact details on the last slide of their presentation.

Text Mining with R

Cornelius Puschmann

Download slides

Cornelius gave an engaging high-level overview on text mining with R, covering:
  • From natural language processing (NLP) to text mining
  • Building corpora
  • Latent semantic analysis (LSA)
  • Topic models/Latent Dirichlet allocation (LDA)
  • Sentiment analysis
  • Misc useful packages
My key take-aways were: text mining is a fairly recent and very active research topic, there is a lot more in text mining then pretty word clouds, and a good domain knowledge is crucial as many techniques don’t provide clear answers and require the user to interpret to results.

A nice and illustrative example Cornelius presented at the end of his talk was the package gender by Linclon Mullen that uses historical US census data to predict the gender of people based on their first name. I have several colleagues with the name of ‘Leslie’ or ‘Lesley’. Thanks to gender I know now that my male colleagues are more likely to be spelled ‘Leslie’ than ‘Lesley’ and that a person with either name is more likely to be female.
library(gender) L1 <- gender("Leslie") L2 <- gender("Lesley") cbind(L1, L2) L1 L2 name "Leslie" "Lesley" proportion_male 0.2222 0.0995 proportion_female 0.7778 0.9005 gender "female" "female" year_min 1932 1932 year_max 2012 2012

Drinks and Networking

No Cologne R user group meeting would be complete without drinks and schnitzel at the Lux.
Photo: Günter Faes

Next Kölner R meeting

The next meeting will be scheduled soon. Please get in touch if you would like to present and share your experience, or indeed if you have a request for a topic you would like to hear more about. For more details see also our Meetup page. Thanks again to Bernd Weiß for hosting the event and Revolution Analytics for their sponsorship.

To leave a comment for the author, please follow the link and comment on their blog: mages' blog. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)