"I Want Hue" – Colors for Data Scientists (opens in new tab)

Here are Color Brewer palettes in CSS and JSON: https://github.com/mbostock/d3/tree/master/lib/colorbrewer

I appreciate this. For a deficiency that affects so many men, I'm always dismayed by the lack if awareness.

I don't see Latour as a particularly bad choice for bridging those worlds. One of his main points is paying close empirical attention to both how scientists actually work, and how non-human things work. Unlike a lot of humanities theorists of science, he actually went into laboratories and wrote down what seem like pretty honest accounts of what he found there. He's fairly controversial among pure social constructionists partly as a result. For example, he had a dispute with David Bloor some years ago [1] over Latour's insistence on including nonhuman objects in his explanation of how science works (rather than treating science as a purely social process). More recently, he's been attacking the tendency, born of the legacy of critical theory, to treat intellectual activity as a series of de-maskings of something the scholar will always find to be "naive" [2].

I mean, the last thing we should want, as scientists, is to have blind faith in a quasi-religious, idealized view of how science works, rather than empirically investigating how it actually works. Plus he seems pretty interested lately in tying in some philosophical ideas with quantitative network-analysis methods: http://www.bruno-latour.fr/sites/default/files/123-WHOLE-PAR...

[1] Bloor's attack on Latour, http://reclus.files.wordpress.com/2009/03/bloor-anti-latour...., and a reply, http://www.melissa.ens-cachan.fr/IMG/pdf/latour_-_reponse_a_...

[2] http://www.pathguy.com/Latour.pdf

This makes me think of a "degree, in fashion, from France" http://www.youtube.com/watch?v=EZFOab0Ar4M #portal2

I'm no color expert but I'm pretty sure color distance in RGB space is a pretty poor metric compared to other color models (at least some of them). Looking at an RGB color cube I see big splashes of near-identical colors while the entire spectrum of oranges is hard to even find.

But, doing it this way can result in oversaturated colors that compete for attention.

This will sound snarky, but there's just too much that's wrong with this comment to let it stand. For people reading this: please don't do any the above.

Go here for good color scales and spare yourself the risk of getting it all wrong: http://colorbrewer2.org

If you're going to not use colorbrewer, please, either know what you're doing (and if you're reading this comment, you don't) you either stick with black and white, or you at least use orange and blue (orange and blue is a combination that's safe with most common types of color-blindness, and also tends to separate well in black-and-white conversions).

Just as importantly: don't try to guess what colors look like for colorblind people, either (and don't do it in RGB space like the original post suggested either! RGB is a device-centric coordinate system; please use something like Lab or Luv). The rightest, simplest way to simulate different types of color blindness is to use define 2D affine subspaces of Lab space, like here: http://www.inf.ufrgs.br/%7Eoliveira/pubs_files/CVD_Mass_Spri... (figure 2, in page 3)

Unless you're staying on a computer your 'pure colors' aren't really pure.

And pure green (0,255,0) is really unpleasant.

Hmm...the linked page worked for me on several tries for 16, 20, and 22 colors, even restricting the luminance somewhat.

I used the protovis categorical colors (http://mbostock.github.com/protovis/docs/color.html, see at the bottom of the page) when I needed a 20-color map recently.

Check out http://colorbrewer2.org/