python: plotting a histogram with a function line on top

Question

I\'m trying to do a little bit of distribution plotting and fitting in Python using SciPy for stats and matplotlib for the plotting. I\'m having good luck with some things like

Answer 1

Expanding on Malik's answer, and trying to stick with vanilla NumPy, SciPy and Matplotlib. I've pulled in Seaborn, but it's only used to provide nicer defaults and small visual tweaks:

import numpy as np
import scipy.stats as sps
import matplotlib.pyplot as plt

import seaborn as sns
sns.set(style='ticks')

# parameterise our distributions
d1 = sps.norm(0, 10)
d2 = sps.norm(60, 15)

# sample values from above distributions
y1 = d1.rvs(300)
y2 = d2.rvs(200)
# combine mixture
ys = np.concatenate([y1, y2])

# create new figure with size given explicitly
plt.figure(figsize=(10, 6))

# add histogram showing individual components
plt.hist([y1, y2], 31, histtype='barstacked', density=True, alpha=0.4, edgecolor='none')

# get X limits and fix them
mn, mx = plt.xlim()
plt.xlim(mn, mx)

# add our distributions to figure
x = np.linspace(mn, mx, 301)
plt.plot(x, d1.pdf(x) * (len(y1) / len(ys)), color='C0', ls='--', label='d1')
plt.plot(x, d2.pdf(x) * (len(y2) / len(ys)), color='C1', ls='--', label='d2')

# estimate Kernel Density and plot
kde = sps.gaussian_kde(ys)
plt.plot(x, kde.pdf(x), label='KDE')

# finish up
plt.legend()
plt.ylabel('Probability density')
sns.despine()

gives us the following plot:

I've tried to stick with a minimal feature set while producing relatively nice output, notably using SciPy to estimate the KDE is very easy.