Basic Data Plotting with Matplotlib Part 3: Histograms

Abstraction: Python matplotlib histogram creation and formatting tutorial with numpy

Key points:

• pyplot.hist() automatically selects bin ranges; default is 10 bins, increase with bins=20 argument
• Normalize to probability distribution with normed=True; area integrates to 1.0
• Cumulative distribution function via cumulative=True flag; custom bin edges passed as sequence
• histtype='step' removes filled bars; histtype='stepfilled' removes black inter-bin lines at high bin counts
• Overlapping distributions handled via alpha transparency (e.g. alpha=0.5 for second histogram)
• Uses numpy.random.normal to generate 1000 Gaussian-distributed sample points for demonstration

Connections: Matplotlib · Numpy · Data Visualization · Statistical Distribution

Source: http://bespokeblog.wordpress.com/2011/07/11/basic-data-plotting-with-matplotlib-part-3-histograms/