Notes from the Kölner R meeting, 6 March 2015

March 10, 2015
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(This article was first published on mages' blog, and kindly contributed to R-bloggers)

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

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Günter and Michael presented examples of a new R Excel plugin Calidris they developed using R.net. 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

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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.

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