# Matplotlib Sample Histogram

Python code used to generate the image (taken from here):

import matplotlib import numpy as np import matplotlib.pyplot as plt np.random.seed(19680801) # example data mu = 100 # mean of distribution sigma = 15 # standard deviation of distribution x = mu + sigma * np.random.randn(437) num_bins = 50 fig, ax = plt.subplots() # the histogram of the data n, bins, patches = ax.hist(x, num_bins, density=1) # add a 'best fit' line y = ((1 / (np.sqrt(2 * np.pi) * sigma)) * np.exp(-0.5 * (1 / sigma * (bins - mu))**2)) ax.plot(bins, y, '--') ax.set_xlabel('Smarts') ax.set_ylabel('Probability density') ax.set_title(r'Histogram of IQ: $\mu=100$, $\sigma=15$') # Tweak spacing to prevent clipping of ylabel fig.tight_layout() plt.savefig('histogram.png', dpi=400)