Building PMF neatly in python

Question

Is there a library that would help me neatly build a sample probability mass function in python, for example:

Answer 1

Via the matplotlib.pyplot stem module

matplotlib.pyplot.stem (* args, ** kwargs)

from matplotlib.pyplot import stem stem(y, linefmt='b-', markerfmt='bo', basefmt='r-') stem(x, y, linefmt='b-', markerfmt='bo', basefmt='r-') 

or closer to metal

 #!/usr/bin/env python from pylab import * x = linspace(0.1, 2*pi, 10) markerline, stemlines, baseline = stem(x, cos(x), '-.') setp(markerline, 'markerfacecolor', 'b') setp(baseline, 'color','r', 'linewidth', 2) show() 

Here

Answer 2

I think it's neat enough

This is the code:

 from scipy import stats import matplotlib.pyplot as plt import numpy as np xk = np.arange(7) pk = (0.1, 0.2, 0.3, 0.1, 0.1, 0.0, 0.2) custm = stats.rv_discrete(name='custm', values=(xk, pk)) fig, ax = plt.subplots(1, 1) ax.plot(xk, custm.pmf(xk), 'ro', ms=8, mec='r') ax.vlines(xk, 0, custm.pmf(xk), colors='r', linestyles='-', lw=2) plt.title('Custom made discrete distribution(PMF)') plt.ylabel('Probability') plt.show() 

Ref, https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.rv_discrete.html