The Variable Tree

In the following blog post, I explore reader sentiment for the Epic Fantasy book series The Wheel of Time , as expressed in user-submitted ratings on Amazon and GoodReads. If you're a data scientist (or similar), you'll probably be interested in the data analysis which includes some interesting observations about the usefulness - or otherwise - of Amazon reviews. If you're a Epic Fantasy Series reader, you'll be interested in the outcome of my analysis: I've decided to go ahead and read all fourteen books. Note -   This is a spoiler free zone .  Updated 17th Sept: charts now more accurate, not quite as pretty * Recently, I was looking for a good book to read, and a friend recommended The Wheel of Time  series by Robert Jordan . But I'd heard from a few sources that the later volumes were harder going than the earlier volumes. Having struggled with later volumes of the Game of Thrones  series (sorry George ) I was wary of starting a mammoth fourteen vo

A friend recently told me about OpenFlights.org , a website that allows you to record, analyze, and share personal flight data. He showed me his dataset, which contained a record of every flight he'd taken over the past 10+ years. I was keen to investigate the dataset further, and my friend was happy to provide me with a copy so I could have a play (thank you Luigi!). The end result is the following collection of visualizations created in Gephi , with a little help from R . They show key transport hubs and routes for airports, countries, and continents that my friend has visited, and demonstrate some of the fun, insightful ways you can use such personal data. If you're interested in how the visualizations were created, check out the section at the end of this blog posting where I briefly describe the technologies required and steps involved. Note: OpenFlights.org is free to use, and supported by advertising and donations. You can join me in supporting OpenFlights.org v