How to extract other data of outlier that is specified with that outlier in box plot in python?

Question

this is the my pandas data frame:

Datetime	SN NO.	Values	data1	data2	data3	data4	data5	data6
2020-09-29T14:59:13.4461479+02:00	701	24.511	3.556	3.557	3.555	3.551	3.559	3.555
2020-09-29T15:48:04.6368679+02:00	702	24.516	3.554	3.555	3.555	3.556	3.552	3.557
2020-09-29T15:51:46.2555875+02:00	703	24.517	3.553	3.556	3.551	3.553	3.558	3.554
2020-10-01T12:51:59.2687665+02:00	704	24.519	3.552	3.557	3.556	3.559	3.557	3.557
2021-02-01T19:27:09.0472459+02:00	705	24.511	3.551	3.558	3.558	3.550	3.551	3.552
.	.	.	.	.	.	.	.	.

boxplot = df.reset_index().boxplot(column=['Values'], by = "Datetime", return_type=None)
from matplotlib.cbook import boxplot_stats
outliers = [y for stat in boxplot_stats(df['Values']) for y in stat['fliers']]
print(outliers)
boxplot.plot()
plt.show()

[sorry for inconvenience this picture was deleted]

as shown in the box plot, there is some outlier but I want to extract other data which is included in the row with that specific values. (by example: one outlier is 24.519 from the data frame but I also need other data such as SN no. and data1, data2, data3, and so on for specific values. what is the best way to do it?

Answer 1

To get a DF with all the outliers:

df_outliers = df.loc[df['Values'].isin(outlier_values), :]

To get only one row:

df_outliers = df.loc[df['Values'].eq(single_value), :]

If you have multiple rows with the same Value it will find all of them.

To keep only some columns from the original df:

cols = ['data1', 'data2']
df_outliers = df.loc[df['Values'].isin(outlier_values), cols]