Hexagonal binning is a great alternative technique to visualize distributions when working with large sets of data
Hexagonal Binning is invented as another method to manage the problem of having a large amount of data that begins to overlap. This type of binning plots density, as opposed to points. Points are binned into gridded hexagons and distribution (the quantity of points per hexagon) is displayed using hexagons' area or color.
Having a maximum number of sides for a regular tessellation, allows the hexagon to be the most effective and compact division of 2D data space.
There are numerous reasons to use hexagons rather than squares for binning a 2D surface as a plane. One of the most apparent reasons is that hexagons are more similar to a circle than a square. This interprets in more effective data aggregation around the bin center.