.. _statistics-histogram_demo_features:

statistics example code: histogram_demo_features.py
===================================================



.. plot:: /home/mdboom/Work/builds/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`)