Well, if you're still interested I made a quick example model:
Given this generic example boxplot:
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style("whitegrid")
tips = sns.load_dataset("tips")
plt.figure(figsize=(20,8))
box = sns.boxplot(x="total_bill",y="day", orient='h', data=tips)
From which I look for min, median and max
values:
df1 = tips.groupby('day')['total_bill'].agg(Min='min', Median='median', Max='max')
df1
Do the same for quartiles and/or percentiles
day |
Min |
Median |
Max |
Thur |
7.51 |
16.2 |
43.11 |
Fri |
5.75 |
15.38 |
40.17 |
Sat |
3.07 |
18.24 |
50.81 |
Sun |
7.25 |
19.63 |
48.17 |
Then iterating over new values to make annotations:
for i in range(len(df1.Min)):
box.annotate(str(df1.Min[i]), xy=(df1.Min[i]-0.1,i), ha='right')
for i in range(len(df1.Median)):
box.annotate(str(df1.Median[i]), xy=(df1.Median[i]-0.1,i), ha='right')
for i in range(len(df1.Max)):
box.annotate(str(df1.Max[i]), xy=(df1.Max[i]+0.1,i), ha='left')

Note:
From there you can fully customize size, color, font, vertical/horizontal alignement and so on... :)