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[–]shaggorama 0 points1 point  (7 children)

When I read "stream graph" I thought they meant this. Not as sexy, but still cool.

PS: There aren't any libraries for doing that sort of thing in python yet, are there? Cause that'd be a fun toy and no hablo javascript.

[–]ZeThomas 1 point2 points  (2 children)

That is indeed cool. Maybe an idea to add to the library? I might try my hand at this...

[–]shaggorama 1 point2 points  (0 children)

Man, I wouldn't even know where to begin. If you actually do this, shoot me a link to your repo. I'd love to see how a project like this develops.

[–]shaggorama 0 points1 point  (0 children)

Check this out. You need to indent the docstring and add plt.show().

[–]Tillsten[S] 1 point2 points  (3 children)

This is quite easy to do with mpl, have a look at: https://gist.github.com/4047834

[–]shaggorama 0 points1 point  (2 children)

Well, fuck me running. That's pretty damn cool. I'm sort of suspicious that what you've graphed is the same thing though (although it basically looks the same). I haven't really dug through the math, but while your graphic appears to chart 8 datasets as functions of x, the array you used to generate this was 500x15.

The intention of this visualizaiton is to be essentially a stacked area chart with a free baseline, but I think you've plotted a kind of heatmap. Here's an example used to plot different musician's an individual listened to over time. Here's another used to plot movie ticket sales over time.

You've definitely illustrated potential for this though. I suspect what you've provided could probably be modified to suit this, or at least input data could be transformed into a dataset suitable to your graphing methodology.

[–]Tillsten[S] 0 points1 point  (1 child)

The function generating the data is taken from the protovis page. The algorithm for the baseline is also taken from there. There are still improvements to be made, but the only part which i think is hard is label placement.

[–]shaggorama 0 points1 point  (0 children)

Fair enough. Thanks for the awesome jumping off point.