How To Plot A Hanging Rootogram In Python?

Inspired by this question, how do you make the same kind of plot in python? This plot aims at having a nice visual representation of how your distribution is off of the expected di

Solution 1:

The idea is to just move each bar of the histogram plot where the top of the bar is at the expected value:

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab

fig, ax = plt.subplots(1, 2)
mu = 10
sig = 0.3
my_data = np.random.normal(mu, sig, 200)
x = np.linspace(9, 11, 100)

# I plot the data twice, one for the histogram only for comparison,# and one for the rootogram.# The trick will be to modify the histogram to make it hang to# the expected distribution curve:for a in ax:
    a.hist(my_data, normed=True)
    a.plot(x, mlab.normpdf(x, mu, sig))
    a.set_ylim(-0.2)
    a.set_xlim(9, 11)
    a.hlines(0, 9, 11, linestyle="--")

for rectangle in ax[1].patches:

    # expected value in the middle of the bar
    exp = mlab.normpdf(rectangle.get_x() + rectangle.get_width()/2., mu, sig)

    # difference to the expected value
    diff = exp - rectangle.get_height()
    rectangle.set_y(diff)

    ax[1].plot(rectangle.get_x() + rectangle.get_width()/2., exp, "ro")

ax[0].set_title("histogram")
ax[1].set_title("hanging rootogram")
plt.tight_layout()

Which gives:

HTH