Dataisbeautiful dataisbeautiful

Lego set price as a function of the number of included pieces [OC]

Lego set price as a function of the number of included pieces [OC]

This makes me feel better about my childhood. I always thought Lego was just trying to lure you in with the cheaper small sets and the gouging you with the larger sets but this seems pretty reasonable.

"Notable Deaths" according to wikipedia [OC]

"Notable Deaths" according to wikipedia [OC]

in one column, green means higher number, while in the other, green means lower number. This is really confusing.

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Subway stations renamed after their most popular Instagram hashtag [OC]

Subway stations renamed after their most popular Instagram hashtag [OC]

We rename underground stations after the Instagram hashtag which is most popular around them. So you get a pretty good picture of how the city is photographed and what is going on where – especially for travelling, shopping, drinks and food. For more cities: https://tagsandthecity.net

Data source:

We grabbed geo-tagged photographs from 2014 from Instagram via it’s API (please note: we can no longer do that since Instagram restricted API access in July 2016). We only use data from 2014 because Instagram started clustering geo tags around 2014/2015, so precise localisation was no longer possible.

Technicalities:

For each city we chose the hundred most popular stations (popular on Instagram). The stations got their name mainly automatically, but with a bit of editorial choice. We calculate the most significant hashtag which is used around each station (largest deviation from average frequency of respective hashtag across all stations), usually within 300 meters. But if this hashtag is just the station’s or the neighborhood’s name we went for the next one. When a hashtag refered to an event which is not repeated each year at the same place, we skipped it too. We only counted one photograph from each account and a hashtag had to have a minimum frequency of 100.

People involved:

Map design: Jug Cerović http://jugcerovic.com

Tech: David Goldwich

Editorial stuff: Tin Fischer http://herrfischer.net

Software used:

Mainly Spatialite and QGIS.

Wine Consumption per Capita in the US [OC]

Wine Consumption per Capita in the US [OC]
Wine Consumption per Capita in the US [OC]

For the curious yet lazy

The 1985 diethylene glycol wine scandal was an incident in which several Austrian wineries illegally adulterated their wines using the toxic substance diethylene glycol (a primary ingredient in some brands of antifreeze) to make the wines appear sweeter and more full-bodied in the style of late harvest wines.[1] Many of these Austrian wines were exported to Germany, some of them in bulk to be bottled at large-scale German bottling facilities. At these facilities, some Austrian wines were illegally blended into German wines by the importers, resulting in diethylene glycol ending up in some bulk-bottled German wines as well.[2]

source

via me being curious and procrastinating.

Two years of running, all at once [OC]

Two years of running, all at once [OC]

My man.

If it weren't for you, I'd still be staring at a grayscale map trying to figure out where the running routes were

Try one of these subthreads