Comparing Sparklines

2019-05-31

Sparklines are curious things. They’re supposed to show a trend, and a trend only. They’re supposed to show when something (like stocks) increase and decrease, where the peaks and the valleys are. But sparklines are not supposed to be comparable with each other.

So when you’re seeing two sparklines with the same height, the ebbs and flows of the first one could play out between 0 and 10 (e.g. US-Dollar), while the other sparkline’s peak is at 10,000.

But that’s odd, no? Doesn’t that invite people to make totally false assumptions?

I like sparklines a lot, but I’m apt to violate this particular rule and make them cross-comparable unless I know people will never care about comparisons between elements. One way to get around the “what if the range is big?” problem is to plot sparkline heights as logs so that 1000 is a bit bigger than 100, which is a bit bigger than 10. The argument I make for doing that is you still see size differences and sparkline comparisons are imprecise to begin with, so magnitudes are more important than exact values.

Visualizing with Heatmaps in R

2019-06-17

Anisa Dhana shows how you can create a quick heatmap plot in R: To give your own colors use the scale_fill_gradientn function.ggplot(dat, aes(Age, Race)) + geom_raster(aes(fill = BMI)) + scale_fill_gradientn(colours=c("white", "red")) This is a quick example using ggplot2 but there are other heatmap libraries available too.

The Power of Hexagonal Binning

2019-06-10

Capri Granville explains hexagonal binning to us and gives a few examples: The reason for using hexagons is that it is still pretty simple, and when you rotate the chart by 60 degrees (or a multiple of 60 degrees) you still get the same visualization.  For squares, rotations of 60 degrees don’t work, only multiples […]

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May 2019
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