11

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 `AVG`

, then

```
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]
```

3

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.

```
showfliers=False
```

0

You can simply turn showfliers = False in seaborn.

KeyError: 'AVG' – Leos313 – 2020-10-15T09:13:03.200

1Probably you don’t have that column. The OP had a column called AVG – Tasos – 2020-10-15T15:07:55.890

right, I do not! Now, I know what to look for! Thank you – Leos313 – 2020-10-15T15:16:09.350