nice ggplot intro tutorial. Just run the commands, about 6 pages = flexible 1-3 hours of learning, depending how much reading you want to pair it with
by Ramon Saccilotto
Posts tagged with Hadley Wickham
![How to colour your heatmaps.
Top-left is not Tufte-compliant because primary colours occupy too much of the space (it’s distracting).
Top-left also uses colours that do not grade across our perceptual space. (Although hues do grade across wavelengths of light smoothly, we don’t perceive it that way.)
Topographical maps that use green, brown, and yellow likewise do not grade across perceptive colour space appropriately.
Top-right is fine but perhaps a little bland. A topographical map with a lot of hills and valleys would benefit more from this than one trying to show finer detail. (My intended application—overlaying two elliptical single-peaked utility functions—would have a hard time with such an approach.)
@hadley recommended this paper to me. I was asking how to select colours to represent level curves (isoclines / isoutility curves / etc) on a 2-D plot. (I.e., how to plot a ℝ²→ℝ¹ function effectively with colours other than greyscale+red.)
Big-money quote from Zeileis, Hornik, and Murrell:
It has been hypothesised that human vision evolved in three stages:
perception of light/dark contrasts;
yellow/blue contrasts (usually associated with our notion of warm/cold);
green/red contrasts (helpful for assessing the ripeness of fruit).
….. The subjective experience of [colour, however,] is less well understood.
Wikipedia pages to read:
RGB (old news)
HSV (old news)
CIELUV
HCL = Hue Chroma Lightness
Book to read:](http://24.media.tumblr.com/tumblr_lzhhr7JGSn1qc38e9o1_1280.png)
How to colour your heatmaps.
- Top-left is not Tufte-compliant because primary colours occupy too much of the space (it’s distracting).
- Top-left also uses colours that do not grade across our perceptual space. (Although hues do grade across wavelengths of light smoothly, we don’t perceive it that way.)
- Topographical maps that use green, brown, and yellow likewise do not grade across perceptive colour space appropriately.
- Top-right is fine but perhaps a little bland. A topographical map with a lot of hills and valleys would benefit more from this than one trying to show finer detail. (My intended application—overlaying two elliptical single-peaked utility functions—would have a hard time with such an approach.)
@hadley recommended this paper to me. I was asking how to select colours to represent level curves (isoclines / isoutility curves / etc) on a 2-D plot. (I.e., how to plot a ℝ²→ℝ¹ function effectively with colours other than greyscale+red.)
Big-money quote from Zeileis, Hornik, and Murrell:
It has been hypothesised that human vision evolved in three stages:
- perception of light/dark contrasts;
- yellow/blue contrasts (usually associated with our notion of warm/cold);
- green/red contrasts (helpful for assessing the ripeness of fruit).
….. The subjective experience of [colour, however,] is less well understood.
Wikipedia pages to read:
- RGB (old news)
- HSV (old news)
- CIELUV
- HCL = Hue Chroma Lightness
Book to read:
hi-res
My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]:
—Data is the most important thing, and the thing that you bring to the table.
—Geometric objects … what you actually see on the plot: points, lines, polygons, etc.
—Statistics transform the data in many useful ways. For example, binning and counting to create a histogram….
—Scales map values in the data space to values in an aesthetic space, whether it be colour, or size, or shape. Scales also provide an inverse mapping: a legend.
—A coordinate system describes how data coordinates are mapped to the plane of the graphic. It also provides axes and gridlines to make it possible to read the graph.
— A facetting, or conditioning, speci
