The best part about writing a dissertation is finding clever ways to procrastinate. The motivation for this blog comes from one of the more creative ways I’ve found to keep myself from writing. I’ve posted about data mining in the past and this post follows up on those ideas using a topic that is relevant 
I was one of the 170 or so people at the Data Science hackathon in London over the weekend. As always this was well run by Carlos and his team who kept us fed, watered and connected to the Internet. One of the three challenges involved a dataset containing pairs of Twitter users, A and
When you woRk, you probably have a set of useful functions/packages you constantly use. For example, I often use the excellent quantmod package, and the nice multi.sapply function. You want your tools loaded when R session fires. In order to … Continue reading →
When work with large amounts of data that is structured in a tabular format, a common operation is to summarize that data in different ways using specific variables. In Microsoft Excel, pivot tables are a nice feature that is used for this purpose. Of course, R also has similar calculations that can be used to 
R is a piece of software, but it is also a community. Help community The most visible aspect of the R community is help. This is also the most useful to new users. The initial sense of cooperation with R was driven mainly by people helping each other. You don’t need to actively participate in
The post R...
Building on the previous posts (post 1 & post 2) I found there were 12 instances with the type of credit where there was a "Primary*" which means the lender borrowed twice in the same day, in the 2010 q4 data. It would seem simple enough in Excel, ...
The first post (found here) we downloaded the data and imported it to R using the gdata package. This post we will be changing the column names to make them more reasonable, and adding a quarter variable. The reason for changing the column names is bec...
With spring in the air, I thought it would be fun to do a series on (spring) cleaning data. The posts will follow my efforts to to download the data, import into R, cleaned it up, merge the different files, add columns of information created, and then ...
Last week I ran an introductory workshop on the analysis and visualisation of spatial data with R. The software has become established as one of the best around for statistics and it is becoming increasingly recognised as a tool for data visualisation (I wrote about this last year, also see here) and spatial analysis. Interest in R ...
I'm always worried about CRAN: a system maintained by FTP and emails from real humans (basically one of Uwe, Kurt or Prof Ripley). I'm worried for two reasons: the number of R packages is growing exponentially; time and time again I see frustrations ...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
