Blog Archives

My Personal Intro to F1 Race Statistics

January 10, 2013
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My Personal Intro to F1 Race Statistics

One of the many things I keep avoiding is statistics. I’ve never really been convinced about the 5% significance level thing; as far as I can tell, hardly anything that’s interesting normally distributes; all the counting that’s involved just confuses me; and I never really got to grips with confidently combining probabilities. I find a

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WordPress Stats in R

January 9, 2013
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WordPress Stats in R

A trackback from Martin Hawksey’s recent post on Analysing WordPress post velocity and momentum stats with Google Sheets (Spreadsheet), which demonstrates how to pull WordPress stats into a Google Spreadsheet and generates charts and reports therein, reminded me of the WordPress stats API. So here’s a quick function for pulling WordPress reports into R. (Code

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NHS Winter Situation Reports: Shiny Viewer v2

December 18, 2012
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NHS Winter Situation Reports: Shiny Viewer v2

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

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Mapping Primary Care Trust (PCT) Data, Part 1

December 7, 2012
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Mapping Primary Care Trust (PCT) Data, Part 1

The launch or official opening or whatever it was of the Open Data Institute this week provided another chance to grab a snapshot of notable folk in the community, as for example demonstrated by people commonly followed by users of the #ODIlaunch hashtag on Twitter. The PR campaign also resulted in the appearance of some

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More Shiny Goodness – Tinkering With the Ergast Motor Racing Data API

December 4, 2012
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More Shiny Goodness – Tinkering With the Ergast Motor Racing Data API

I had a bit of a play with Shiny over the weekend, using the Ergast Motor Racing Data API and the magical Shiny library for R, that makes building interactive, browser based applications around R a breeze. As this is just a quick heads-up/review post, I’ll largely limit myself to a few screenshots. When I

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Quick Shiny Demo – Exploring NHS Winter Sit Rep Data

November 28, 2012
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Quick Shiny Demo – Exploring NHS Winter Sit Rep Data

Having spent a chink of the weekend and a piece of yesterday trying to pull NHS Winter sitrep data into some sort of shape in Scraperwiki, (described, in part, here: When Machine Readable Data Still Causes “Issues” – Wrangling Dates…), I couldn’t but help myself last night and had a quick go at using RStudio’s

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Interactive Scenarios With Shiny – The Race to the F1 2012 Drivers’ Championship

November 18, 2012
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Interactive Scenarios With Shiny – The Race to the F1 2012 Drivers’ Championship

In Paths to the F1 2012 Championship Based on How They Might Finish in the US Grand Prix I posted a quick hack to calculate the finishing positions that would determine the F1 2012 Drivers’ Championship in today’s United States Grand Prix, leaving a tease dangling around the possibility of working out what combinations would

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The Race to the F1 2012 Drivers’ Championship – Initial Sketches

November 16, 2012
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The Race to the F1 2012 Drivers’ Championship – Initial Sketches

In part inspired by the chart described in The electoral map sans the map, I thought I’d start mulling over a quick sketch showing the race to the 2012 Formula One Drivers’ Championship. The chart needs to show tension somehow, so in this first really quick and simple rough sketch, you really do have to

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its the Gramma an punctuashun wot its’ about, Rgiht?

October 4, 2012
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its the Gramma an punctuashun wot its’ about, Rgiht?

This is another of those confluence style posts, where a handful of things I’ve read in quick succession seem to phase lock in my mind: (brought to mind in part via @downes a week or so ago: How to Synch 32 Metronomes) The first was a post by Alan Levine on Making Text Work, which

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Merging Data Sets Based on Partially Matched Data Elements

September 26, 2012
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Merging Data Sets Based on Partially Matched Data Elements

A tweet from @coneee yesterday about merging two datasets using columns of data that don’t quite match got me wondering about a possible R recipe for handling partial matching. The data in question related to country names in a datafile that needed fusing with country names in a listing of ISO country codes. The original

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