This document provides an introduction to using Matplotlib for data analysis and visualization. It outlines the presenter's background and experience with Python and Matplotlib. References to key Matplotlib documentation resources are given, including galleries of examples, API summaries, and tutorials. Different methods for importing and using Matplotlib are described, such as with Pylab, IPython, or different backends. The presentation concludes with demonstrations of Matplotlib examples using real stock market data.

1. A Utilitarian Introduction to
Matplotlib
20APR2013
Drew Arnett
a.arnett@ieee.org

2. whoami
• B.S. Electrical Engineering
• python user
– test control sw
– data analysis and processing
• utilitarian user of matplotlib

3. Presentation overview
Matplotlib.org doc is very good
… so mostly demo

4. References
• matplotlib.org +++ documentation
– gallery
– plotting commands summary
– examples
– navigation keyboard shortcuts
• Related:
– Numpy
– Scipy
– IPython
• Alternatives

5. References
• matplotlib.org +++ documentation
– gallery http://matplotlib.org/gallery.html
– plotting commands summary
http://matplotlib.org/api/pyplot_summary.html
– examples http://matplotlib.org/examples/index.html
– navigation keyboard shortcuts
http://matplotlib.org/users/navigation_toolbar.html
• Related:
– Numpy http://www.numpy.org/
– Scipy http://www.scipy.org/
– Ipython http://ipython.org/
• Alternatives

6. Usage
• Alternatives importing and use style
• Pylab
• Ipython
• Pythonic
• Backends
– Interactive
– Raster/vector
– GUI APIs

7. Demos
• Examples with S&P closing data (and another
example to show a two scales plot)
• Real world examples