Seaborn is a graphic library built on top of Matplotlib. It allows to make your charts prettier, and facilitates some of the common data visualisation needs (like mapping a color to a variable or using faceting). This page gives

general tips concerning this awesome library. Visit individual chart sections if you need a specific type of plot. The Seaborn documentation is also very well done and help going further. Most of the customisations that work

for Matplotlib work for Seaborn, so do not hesitate to visit the Matplotlib page of the gallery. Last but not least, note that loading seaborn before a matplotlib plot allows you to benefit from its well looking style!

If you are a newbie in dataviz and seaborn, I suggest to follow this datacamp online course. The third part is dedicated to seaborn.


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  • Seaborn style on top of matplotlib

    If you know how to make a chart with matplotlib, just load the seaborn library and your chart will look way better:

    Seaborn themes

    Manage colors

    Since Seaborn is built on top of matplotlib, most of the customization available on Matplotlib work on seaborn as well. This is especially true for axis, annotation and margin:

    Manage axis



    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.


    Random examples using seaborn