The fine author Joe Cheng of RStudio Shiny suggested in this Google Groups message to use htmlOutput rather than the ugly hack in my last post R Shiny svg with no d3. As I should have known, it works great and eliminates all the useless javascrip...

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The fine author Joe Cheng of RStudio Shiny suggested in this Google Groups message to use htmlOutput rather than the ugly hack in my last post R Shiny svg with no d3. As I should have known, it works great and eliminates all the useless javascrip...

Today’s Gist could actually end up being very useful to a number of you. It’s something of a trumped-up example, but it illustrates in very simple code how to do three interesting things: Gather Tweets by search term (which we’ve done before), and look up user info for each of the users returned by that search. Convert textual user...

Reproducible Research in High-Throughput Biology: A Case Study Paolo Sonego, Bioinformatician at CBM Scrl (view code and case study on github) Metabolomics: an interpreting tool to understand kidney graft recipients grouping and their recovery trajectory Marco Calderisi, Chemometrician at Kode … Continue reading →

Given a random list of words, can you find which has the lowest or highest numerical value when we apply a basic number:letter cipher? A while back I asked David how he would solve this problem: http://projecteuler.net/problem=42 Today’s post shows how to take a vector of words, parse them into each of the individual letters comprising the word, and...

We’ve had some requests for ideas about how to make prettier network graphs, so here is one example, using the sna package for plotting, and the igraph package to calculate PageRank. The help file for gplot is pretty self-explanatory, but Melissa Clarkson has produced the most thorough and impressive guide for any R...

Having got my NHS Winter sitrep data scraper into shape (I think!), and dabbled with a quick Shiny demo using the R/Shiny library, I thought I’d tidy it up a little over the weekend and long the way learn a few new presentation tricks. To quickly recap the data availability, the NHS publish a weekly

We’re happy to announce the availability of Stan and RStan versions 1.1.0, which are general tools for performing model-based Bayesian inference using the no-U-turn sampler, an adaptive form of Hamiltonian Monte Carlo. Information on downloading and installing and using them is available as always from Stan Home Page: http://mc-stan.org/ Let us know if you have The post Stan...