Seaborn uses inter-quartile range to detect the outliers. What you need to do is to reproduce the same function in the column you want to drop the outliers. It's quite easy to do in Pandas.
If we assume that your dataframe is called
df and the column you want to filter based
Q1 = df['AVG'].quantile(0.25) Q3 = df['AVG'].quantile(0.75) IQR = Q3 - Q1 #IQR is interquartile range. filter = (df['AVG'] >= Q1 - 1.5 * IQR) & (df['AVG'] <= Q3 + 1.5 *IQR) df.loc[filter]
If you need to remove outliers and you need it to work with grouped data, without extra complications, just add
showfliers argument as False in the function call. It's inherited from matplotlib.
You can simply turn showfliers = False in seaborn.