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I would like to know what algorithm is used to determine the 'outliers' in a boxplot distribution in Seaborn.

On their website seaborn.boxplot they simple state:

The box shows the quartiles of the dataset while the whiskers extend to show the rest of the distribution, except for points that are determined to be “outliers” using a method that is a function of the inter-quartile range.

I would really like to know what method they use. I've created boxplots from a dataframe and I seem to have a lot of 'outliers'.

Thanks

Answers

If you read further on the page you linked (or ctrl-f for "outlier"), you will see:

whis : float, optional
    Proportion of the IQR past the low and high quartiles to extend the plot whiskers.
    Points outside this range will be identified as outliers.