Dot-boxplots from DataFrames

For a more precise answer related to OP's question (with Pandas):

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

data = pd.DataFrame({ "A":np.random.normal(0.8,0.2,20),
                      "B":np.random.normal(0.8,0.1,20), 
                      "C":np.random.normal(0.9,0.1,20)} )

data.boxplot()

for i,d in enumerate(data):
    y = data[d]
    x = np.random.normal(i+1, 0.04, len(y))
    plt.plot(x, y, mfc = ["orange","blue","yellow"][i], mec='k', ms=7, marker="o", linestyle="None")

plt.hlines(1,0,4,linestyle="--")

---

Old version (more generic) :

With matplotlib :

import numpy as np
import matplotlib.pyplot as plt

a = np.random.normal(0,2,1000)
b = np.random.normal(-2,7,100)
data = [a,b]

plt.boxplot(data) # Or you can use the boxplot from Pandas

for i in [1,2]:
    y = data[i-1]
    x = np.random.normal(i, 0.02, len(y))
    plt.plot(x, y, 'r.', alpha=0.2)

Which gives that :

Inspired from this tutorial

Hope this helps !

This will be possible with seaborn version 0.6 (currently in the master branch on github) using the stripplot function. Here's an example:

import seaborn as sns
tips = sns.load_dataset("tips")
sns.boxplot(x="day", y="total_bill", data=tips)
sns.stripplot(x="day", y="total_bill", data=tips,
              size=4, jitter=True, edgecolor="gray")