This chart communicates the same insights as a contour plot. What is interesting is the choice of hexagonal buckets (rather than squares) to aggregate data. In fact, any tessellation<\/a> would work, in particular Voronoi tessellations<\/a>.<\/p>\n 3-D Voronoi tessellation\u00a0<\/em><\/p>\n 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.\u00a0 For squares, rotations of 60 degrees don’t work, only multiples of 90 degrees work. Is it possible to find a tessellation such that smaller rotations, say 45 or 30 degrees, leave the chart unchanged? The answer is no. Octogonal tessellations<\/a> don’t really exist, so the hexagon is an optimum.\u00a0<\/p>\n Hexagonal binning plots (source: here<\/a>)<\/em><\/p>\n Implementation in R<\/strong><\/p>\n The three plots described here (Voronoi diagram, hexagonal binning and contour plots) are available in the ggplot2 package.<\/p>\n Applications<\/strong><\/p>\n Voronoi diagrams can be used for nearest neighbor clustering or density estimation, the density estimate attached to a point being proportional to the inverse of the area of the Voronoi polygon containing it.<\/p>\n<\/p>\n Example of contour map (source: here<\/a>)<\/em><\/p>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<\/a><\/p>\n
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