Publications by Tony Hirst
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 get a chance, I’ll try to do a bit mo...
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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 open data related use cas...
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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 spreadsheet (with daily reports for Monday to...
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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 repo...
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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 lot...
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The Basics of Betting as a Way of Keeping Score…
Another preparatory step before I start learning about stats in the context of Formula One… There are a couple of things I’m hoping to achieve when I actually start the journey: 1) finding ways of using stats to help to pull out patterns and events that are interesting from a storytelling or news perspective; 2) seeing if I can come up with a...
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Getting Started with F1 Betting Data
As part of my “learn about Formula One Stats” journey, one of the things I wanted to explore was how F1 betting odds change over the course of a race weekend, along with how well they predict race weekend outcomes. Courtesy of @flutterF1, I managed to get a peek of some betting data from one of the race weekends last year year. In this prelim...
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F1Stats – Visually Comparing Qualifying and Grid Positions with Race Classification
[If this isn’t your thing, the posts in this thread will be moving to a new blog soon, rather than taking over OUseful.info…] Following the roundabout tour of F1Stats – A Prequel to Getting Started With Rank Correlations, here’s a walk through of my attempt to replicate the first part of A Tale of Two Motorsports: A Graphical-Statistical ...
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Using SPARQL Query Libraries to Generate Simple Linked Data API Wrappers
A handful of open Linked Data have appeared through my feeds in the last couple of days, including (via RBloggers) SPARQL with R in less than 5 minutes, which shows how to query US data.gov Linked Data and then Leigh Dodds’ Brief Review of the Land Registry Linked Data. I was going to post a couple of of examples merging those two posts – sho...
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F1Stats – Correlations Between Qualifying, Grid and Race Classification
Following directly on from F1Stats – Visually Comparing Qualifying and Grid Positions with Race Classification, and continuing in my attempt to replicate some of the methodology and results used in A Tale of Two Motorsports: A Graphical-Statistical Analysis of How Practice, Qualifying, and Past SuccessRelate to Finish Position in NASCAR and For...
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