A 2D density plot or  2D histogram is an extension of the well known histogram. It shows the distribution of values in a data set across the range of two quantitative variables. It is really

useful to avoid over plotting in a scatterplot. If you have too many dots, the 2D density plot counts the number of observations within a particular area of the 2D space. This specific area can be

a square or a hexagon (hexbin). You can also estimate a 2D kernel density estimation and represent it with contours.


Note that this online course has a chapter dedicated to 2D arrays visualization.


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  • From overlapping scatterplot to 2D density

    Contour plot

    2D Histogram


    2D Density

    Marginal plots

    If you have a huge amount of dots on your graphic, it is advised to represent the marginal distribution of both the X and Y variables. This is easy to do using the jointplot() function of the Seaborn library.