Scagnostics Explained

Scagnostics (scatterplot diagnostics) is a series of measures that characterize certain properties of a point cloud in a scatter plot. The term and idea was coined by John Tukey and Paul Tukey, though they didn't publish it; later it was elaborated by Wilkinson, Anand, and Grossman. The following nine dimensions are considered:^{[1] [2]}

1. For the outliers in the data:
   1. outlying
2. For the density of data points:
   1. skewed
   2. clumpy
   3. sparse
   4. striated
3. For the shape of the point cloud:
   1. convex
   2. skinny
   3. stringy
4. For trends in the data:
   1. monotony

External links

• Python library pyscagnostics
• R package scagnostics

Notes and References

1. Wilkinson . Leland . Scagnostics . 23 April 2008 . 25 March 2022 . en.
2. Wilkinson . Leland . Anand . Anushka . Grossman . Robert . Graph-theoretic scagnostics . In Proc. 2005 IEEE Symp. On Information Visualization (INFOVIS . 2005 . 157–164 . 10.1.1.329.1315 .