Ah, I was wondering why there was a large column in the middle of Australia. It actually lines up reasonably well with the only real population center there (Alice Springs), but at ~25k people, it seemed unlikely.
You might want to run a simplifying algorithm on the shapes first though, they're the official boundary coordinates so there's an absurd number of points on coastlines and the like, making point-in-polygon lookups very slow.
It has the stuff for doing your own geocoding as well. You can install it as a postgis extension and run geocoding SQL queries in postgres. It's an absolute joy.
Author here, sorry about the spikes where people do not actually live. A lot of users put only their country and not city, and I didn't want to throw that data away.
I probably should've checked the specificity of the location and only thrown out the data for large countries like Russia and China, or distributed it across all other data points in the country.
It would be nice if there were an easy way to hit the population center instead of geographic center of a nation in webgl-globe, at least. That big spike in the middle of Siberia puzzled me at first.
This also prompted me to add my location in github.
It would be interesting to see if there's a non-negligible difference to run this again in a few days, after everyone who gets word of it also adds in their location.
It would be very exciting to normalize the Github user numbers by the population in the area they map to.
Right now especially in Europe it seems to pretty much seems to map to population numbers of cities.
Is it really? If you look past Western Europe and North America it is definitely not. And even there you can see things, like that spike in Bay Area. Except for population size, there seem to be at least two more major factors at play: wealth and English proficiency. Even in Europe they are clearly visible: Oslo and Sofia are about the same population, Rome is at least three times more populated than Edinburgh. So, no, not really.
i thought the same when looking at the US, but then I noticed Los Angeles. L.A. is the 2nd largest city in the US, and the smaller spike, compared to its population, is consistent with what I've heard about the tech scene there.
It looks like this awesome visualization was done with Three.js, but I wanted to flag Ceasium[1] to anyone wanted to do 3D 'map stuff' in a browser. It has some great features, like built in support for CRS systems (hard), WMS/WMTS client. We got a lot done with it really fast.
Any thoughts what the European location that seems to be southwest of Berlin. Seems to be between Hannover and Leipzig, but there are no major cities there, and it's strange that its bigger than Berlin.
Well, it could be my coworkers here in Göttingen, but given that this lovely little town is about quite the middle of the country, I'm going with your post-edited hypothesis. Thanks for the hint, though, I was scratching my head about some of the other points I could not attribute to any city known to me.
I think that's it - there's a similar peak right in the middle of Australia with the nearest town being Alice Springs, but I highly doubt commits on the level of Brisbane come from there.
This is not the case. Examples: NYC vs SF and Madrid vs Berlin. Well, Madrid is bigger and more dense than most of the cities with more github users in this map.
If you're wondering why Andreessen Horowitz felt github was worth the 100M dollar investment, look no further than India and China. These massive populations are yet to be tapped for the most part leaving a great opportunity for future growth. For a company that has been profitable from the get-go, things are only going to get a lot better in the long run.
I know we're all guessing here, because I assume you don't work at Andreessen Horowitz, but I don't agree with the bet you're making. When it comes to online services, China has a tendency to adopt their own versions of services started elsewhere. For example, Google is dying hard in China [1]. The players in the social media scene are similarly unfamiliar to users outside of China, with Weibo leading (I'm lacking citation here).
If Github sees China as an opportunity, they'd better move quick, and look very deeply at what has allowed services like Baidu and Weibo to trounce American-born competitors in their market.
Hmm, would have been nice if the great lakes were still in place in North America...they're very useful landmarks for us frozen chosen in the American tundra (read: New York, Michigan, Wisconsin, Minnesota, South Ontario).
While it looks cool, it only takes you a second to realize that this is kind of a worthless visualization because to see the height of the bar you have to spin the globe so the line is parallel to the view plane. If you are looking straight down, you only get the color.
Remember, 3d isn't 3d, it's 3d projected on a 2d plane. And if this were real steroscopic 3d, then each of these datapoints would be like the 3d gimmics in movies like a spear right to your face.
That said I've got this bookmarked because I think at it's base it could be useful for other visualizations.
Here's a quick 2d visualization of the data using D3.js. The advantage of a 2d projection is you can see all parts of the globe at once and have quantitative encodings that aren't distorted by projection effects. In this case, color+radius encode the magnitude variable, but there is overlap of adjacent circles.
Low quality texture map with seams and bad filtering at the poles. Big perceptible delay on camera movements. WebGL doesn't make a subpar gfx demo cool.
No, it was the same for me. Seas are dark blue while landmasses are white near the poles, green in most other places and sandy yellow in deserts - light colours. It makes me expect lands to be light and seas to be dark, even on a stylised monochrome globe.
Good 3d visualization is tricky, this is a good example of a 3d fail.
The 3d here adds more trouble than goods. It makes it harder to see the whole set of data and it is also harder to compare.
Way more fun than redis. I actually like to sit in the channel and watch the data fly by (its color coded so its actually quite pretty). /connect irc.robscanlon.com /join #github or /join #wikipedia. You can create your own channel and stream your own data as well (it'll automatically create a url on my site for you with that wargame theme). I'm working on other themes that you can choose from.
And please don't bug the web-* bots that are hanging out in the rooms... they are the actual web servers and are a bit busy at the moment ;-)
Unfortunately I didn't have a chance to finish getting this completely working properly in FF. I assume that's the browser you were using (sorry about that).
Oh, no problem. It's a great web app. I just thought you probably accidentally reversed a couple of lines of code and would want to know about it. And, yes, I was using FF 24.
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[ 3.1 ms ] story [ 150 ms ] threadSame thing with China with a large spike in the middle of Gobi desert.
Same with Canada - apparently some lumberjacks code when it snows too hard and they can't get out!
I wonder if there is a similar column in the USA and where is it located.
India is surprisingly bare. Come on, you can do better than that.
P. S. Went to update my Location: in github.
http://i.imgur.com/cGuetKg.jpg
http://en.wikipedia.org/wiki/Geographic_center_of_the_contig...
[1]: https://s3.amazonaws.com/SocialHarvest/world.jpg
That has the administrative boundaries for every country.
The relevant project from the US government itself is here: https://www.census.gov/geo/maps-data/data/tiger.html
You might want to run a simplifying algorithm on the shapes first though, they're the official boundary coordinates so there's an absurd number of points on coastlines and the like, making point-in-polygon lookups very slow.
It has the stuff for doing your own geocoding as well. You can install it as a postgis extension and run geocoding SQL queries in postgres. It's an absolute joy.
I probably should've checked the specificity of the location and only thrown out the data for large countries like Russia and China, or distributed it across all other data points in the country.
Interesting project if you want to fork it!
It would be interesting to see if there's a non-negligible difference to run this again in a few days, after everyone who gets word of it also adds in their location.
I unconsciously expected the opposite.
It does correlate quite a bit to city population, although, the spike in what I presume to be Austin, relative to Dallas or Houston is quite telling.
[1]http://cesium.agi.com/
AWESOME job with this, it's both fascinating and well laid out!
EDIT: Could be people who just wrote "Germany".
I think that's it - there's a similar peak right in the middle of Australia with the nearest town being Alice Springs, but I highly doubt commits on the level of Brisbane come from there.
What would be interesting is to see where there are more Github users than you would expect by pure density of internet users.
Awesome job on the visualization btw.
If Github sees China as an opportunity, they'd better move quick, and look very deeply at what has allowed services like Baidu and Weibo to trounce American-born competitors in their market.
http://www.techinasia.com/china-baidu-qihoo-google-search-ma...
Remember, 3d isn't 3d, it's 3d projected on a 2d plane. And if this were real steroscopic 3d, then each of these datapoints would be like the 3d gimmics in movies like a spear right to your face.
That said I've got this bookmarked because I think at it's base it could be useful for other visualizations.
What is the third large spike on the East Coast? I assume the two more Northern spikes are Boston and New York.
http://bl.ocks.org/syntagmatic/6769077
Am I the only one who feel like it should be the reverse?
Personally I loved the 3D version. I found it interesting and fun.
http://streams.robscanlon.com/github
Its a work in progress!
And please don't bug the web-* bots that are hanging out in the rooms... they are the actual web servers and are a bit busy at the moment ;-)
http://www.youtube.com/watch?feature=player_detailpage&v=uCW...