Adding a scatter of points to a boxplot using matplotlib

What you're looking for is a way to add jitter to the x-axis.

Something like this taken from here:

bp = titanic.boxplot(column='age', by='pclass', grid=False)for i in [1,2,3]:    y = titanic.age[titanic.pclass==i].dropna()    # Add some random "jitter" to the x-axis    x = np.random.normal(i, 0.04, size=len(y))    plot(x, y, 'r.', alpha=0.2)

Quoting the link:

One way to add additional information to a boxplot is to overlay the actual data; this is generally most suitable with small- or moderate-sized data series. When data are dense, a couple of tricks used above help the visualization:

1. reducing the alpha level to make the points partially transparent
2. adding random "jitter" along the x-axis to avoid overstriking

The code looks like this:

import pylab as Pimport numpy as np# Define data# Define numBoxesP.figure()bp = P.boxplot(data)for i in range(numBoxes):    y = data[i]    x = np.random.normal(1+i, 0.04, size=len(y))    P.plot(x, y, 'r.', alpha=0.2)P.show()

Expanding on Kyrubas's solution and using only matplotlib for the plotting part (sometimes I have difficulty formatting pandas plots with matplotlib).

from matplotlib import cmimport matplotlib.pyplot as pltimport pandas as pdimport numpy as np# initialize dataframen = 200ngroup = 3df = pd.DataFrame({'data': np.random.rand(n), 'group': map(np.floor, np.random.rand(n) * ngroup)})group = 'group'column = 'data'grouped = df.groupby(group)names, vals, xs = [], [] ,[]for i, (name, subdf) in enumerate(grouped):    names.append(name)    vals.append(subdf[column].tolist())    xs.append(np.random.normal(i+1, 0.04, subdf.shape[0]))plt.boxplot(vals, labels=names)ngroup = len(vals)clevels = np.linspace(0., 1., ngroup)for x, val, clevel in zip(xs, vals, clevels):    plt.scatter(x, val, c=cm.prism(clevel), alpha=0.4)

As a simpler, possibly newer option, you could use seaborn's swarmplot option.

import seaborn as snsimport matplotlib.pyplot as pltsns.set(style="whitegrid")tips = sns.load_dataset("tips")ax = sns.boxplot(x="day", y="total_bill", data=tips, showfliers = False)ax = sns.swarmplot(x="day", y="total_bill", data=tips, color=".25")plt.show()

Looking at the original question again (and having more experience myself), I think instead of sns.swarmplot, sns.stripplot would be more accurate.