Before you get started with this article, I suggest you to read the article about Hexagonal Binning. In that article this method of data aggregation is shown and explained in detail. Two scatterplots, generated from two different datasets are compared, and so a class of specific datasets are highlighted. In fact, analyzing “sparse” datasets can be difficult, especially when we are looking for trends or clusters.
Scatterplots are a straightforward way to visualize the data distribution in a XY plane, especially when we are looking for trends or clusters. But when you have a dataset with a large number of points, many of these data points can overlap. This overalpping effect can make difficult to see any trends or clusters.
This article is an extension of the article Hexagonal Binning in which this method of data aggregation is shown. It starts showing how a dataset is represented in scatterplot and concludes showing it with a visual representation using hexagonal bins.
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