.. _statistics-histogram_demo_features: statistics example code: histogram_demo_features.py =================================================== .. plot:: /home/tcaswell/other_source/matplotlib/doc/mpl_examples/statistics/histogram_demo_features.py :: """ Demo of the histogram (hist) function with a few features. In addition to the basic histogram, this demo shows a few optional features: * Setting the number of data bins * The normed flag, which normalizes bin heights so that the integral of the histogram is 1. The resulting histogram is a probability density. * Setting the face color of the bars * Setting the opacity (alpha value). """ import numpy as np import matplotlib.mlab as mlab import matplotlib.pyplot as plt # example data mu = 100 # mean of distribution sigma = 15 # standard deviation of distribution x = mu + sigma * np.random.randn(10000) num_bins = 50 # the histogram of the data n, bins, patches = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5) # add a 'best fit' line y = mlab.normpdf(bins, mu, sigma) plt.plot(bins, y, 'r--') plt.xlabel('Smarts') plt.ylabel('Probability') plt.title(r'Histogram of IQ: $\mu=100$, $\sigma=15$') # Tweak spacing to prevent clipping of ylabel plt.subplots_adjust(left=0.15) plt.show() Keywords: python, matplotlib, pylab, example, codex (see :ref:how-to-search-examples)