In case you missed them, here are some articles from March of particular interest to R users. Facebook used R to analyze profile photo changes to create a map of same-sex marriage support in the USA. Joe Rickert contrasts random sampling with fitting models directly to large data sets. A presentation by Carlos Somohano summarizes the history, skills and...
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A quick introduction to ggplot2
My friend Jonah asked me to guest lecture in his R seminar aimed at grad students and postdocs in Integrative Biology. I gave Jonah a bunch of topics ranging from reproducible research with R to data manipulation. The consensus was data visualization so I put together a 2 hour talk/hands on presentation for ggplot2 beginners.
R and social media
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...
Behind the NCAA Visualizer: Python, R and JavaScript
Rodrigo Zamith's NCAA Tournament Visualizer is a great example of an interactive data visualization. If you want to create something similar, Rodrigo has shared detailed behind-the-scenes information on how it was created. He used a mix of tools: Python was used to scrape team statistics fromt the NCAA website R was used to prepare the data for analysis, and...
Changing figure options mid-chunk (in a loop) using the pander package.
I wrote already about changing figure options mid-chunk in reproducible research. This can be important e.g. if you are looping through a dataset to produce a graphic for each variable but the figure width or height need to depend on properties of the variables, e.g. if you are producing histograms and want the figures to
Starting Analysis and Visualisation of Spatial Data with R
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 ...
Dirichlet Process, Infinite Mixture Models, and Clustering
The Dirichlet process provides a very interesting approach to understand group assignments and models for clustering effects. Often time we encounter the k-means approach. However, it is necessary to have a fixed number of clusters. Often we encounter situations where we don’t know how many fixed clusters we need. Suppose we’re trying to identify
Sync
I am listening to the audiobook Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Lifeby Steven Strogatz which I got from Audible. Obviously a mathematical book is not ideal to listen to, but lacking illustrations I can ma...
Worry about correctness and repeatability, not p-values
In data science work you often run into cryptic sentences like the following: Age adjusted death rates per 10,000 person years across incremental thirds of muscular strength were 38.9, 25.9, and 26.6 for all causes; 12.1, 7.6, and 6.6 for cardiovascular disease; and 6.1, 4.9, and 4.2 for cancer (all P < 0.01 for linear
Estimated Follower Accession Charts for Twitter
Just over a year or so ago, Mat Morrison/@mediaczar introduced me to a visualisation he’d been working on (How should Page Admins deal with Flame Wars?) that I started to refer to as an accession chart (Visualising Activity Around a Twitter Hashtag or Search Term Using R). The idea is that we provide each entrant 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
