How to remove outliers from Seaborn boxplot charts

In this article, I am going to show you how to remove outliers from Seaborn boxplots. First, I am going to plot a boxplot without modifications. Then, I will remove all of the outliers. In the end, I am going to restore outliers, but this time I am going to make them less prominent.

Boxplot with outliers

Let’s start with plotting the data I already have.

1
2
3
import seaborn as sb

sb.boxplot(x = 'Value', data = with_merged)

Subscribe to the newsletter and join the free email course.

Boxplot without outliers

To remove the outliers from the chart, I have to specify the “showfliers” parameter and set it to false.

1
sb.boxplot(x = 'Value', data = with_merged, showfliers = False)

Change the outliers style

In the next example, I am going to change the size of the outliers markers to make them less distracting for people who look at the chart.

1
sb.boxplot(x = 'Value', data = with_merged, flierprops = dict(markerfacecolor = '0.50', markersize = 2))

Remember to share on social media!
If you like this text, please share it on Facebook/Twitter/LinkedIn/Reddit or other social media.

If you want to contact me, send me a message on LinkedIn or Twitter.

Would you like to have a call and talk? Please schedule a meeting using this link.


Bartosz Mikulski
Bartosz Mikulski * data/machine learning engineer * conference speaker * co-founder of Software Craft Poznan & Poznan Scala User Group

Subscribe to the newsletter and get access to my free email course on building trustworthy data pipelines.

Do you want to work with me at riskmethods?

REMOTE position (available in Poland or Germany)