Draft:Hexagonal binning plot
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Hexagonal binning plots (also referred to as hexbin plots) are a type of data visualization that represent the density of numerical data with two continuous variables.
The principle of hexagonal binning plots is to divide 2D space into hexagonal cells, count the number of observations in each cell, and encode this number as cell color[1].
Scientific papers referring to the concept of hexagonal binning plots (e.g. [2]) often reference Carr's paper on scatterplot matrix techniques for large N[3] as the first mention of hexagonal binning in the scientific literature. A technical report by the same author[4] justifies the use of hexagons. Among the merits of hexagons mentioned in this report is the fact that they have a "well defined number of neighbors" (6). This is in contrast to squares, which have 4 neighbors if one considers edges but 8 if one considers vertices.
They are seen as an alternative to scatter plots when the number of data points to display is large and would result in overlapping points and so-called overplotting [4][5].
See also
[edit]References
[edit]- ^ "Hexagonal binned plot". Matplotlib.org. Retrieved 26 February 2025.
- ^ Wilkinson, L.; Anand, A.; Grossman, R. (November 2006). "High-Dimensional Visual Analytics: Interactive Exploration Guided by Pairwise Views of Point Distributions". IEEE Transactions on Visualization and Computer Graphics. 12 (6): 1363–1372. doi:10.1109/TVCG.2006.94. ISSN 1941-0506. PMID 17073361.
- ^ Carr, D. B.; Littlefield, R. J.; Nicholson, W. L.; Littlefield, J. S. (1987-06-01). "Scatterplot Matrix Techniques for Large N". Journal of the American Statistical Association. 82 (398): 424–436. doi:10.1080/01621459.1987.10478445. ISSN 0162-1459.
- ^ a b Carr, D. B. (1990-04-01). Looking at large data sets using binned data plots (Report). Pacific Northwest National Lab. (PNNL), Richland, WA (United States). OSTI 6930282.
- ^ "Hexagonal binning". datavizproject.com. Retrieved 26 February 2025.