Python II: Data Analysis and Visualization
==========================================


Expectations
------------

* Previous Python experience *required*. Focus is on using Python as a tool,
  not on learning the language.

* Python is not the solution to all your problems. (I.e., this seminar is
  informational rather than evangelical in nature. Draw your own conclusions.)

* Python is not a magical gift box; it is a programming language. At least
  some work will be required to reach your goals.

* Consider me to be a tour guide rather than an expert.

   * Will highlight capabilities of various packages, but have very little
     experience with most of them.


Useful Resources
----------------

* Stack Overflow: http://stackoverflow.com  (Someone has probably already asked
  your question and received an answer or a dozen answers. If not, you can ask
  questions here too.)

* Python 2 Reference: http://docs.python.org/2

* Python 3 Reference: http://docs.python.org/3

* IPython Notebook Gallery: http://nbviewer.ipython.org/

* IPython Reference: `a collection of IPython tutorials
  <https://github.com/ipython/ipython/tree/master/examples/notebooks#a-collection-of-notebooks-for-using-ipython-effectively>`_


IPython
-------

* Copy and paste of example output.

* Pop-up help.

* Tab completions.

* Automatic pretty-printing.

* Persistent history.

* Logging sessions.

* Demo mode.

* Loading Python files.

* Pylab

   * vs SAGE

NumPy
-----

* NumPy arrays vs Python lists.

* Creation of arrays.

   * ``array``

   * ``arange``

   * ``linspace``

   * ``zeros``, ``ones``

* Reshaping arrays.

* ``eye``

* Element-wise operations.

* Simple linear algebra.

* Simple stats.

.. note::
   If you were in the morning session, then you want to ``np.resize`` to resize
   a NumPy array and not ``np.reshape`` as I accidentally wrote. Sorry for the
   problem.

SciPy
-----

matplotlib
----------

pandas
------

StatsModels
-----------

NetworkX
--------

NLTK
----

scikits
-------

* scikit-learn

* scikit-image

SymPy
-----

* Running ``isympy``.

* Using SymPy from within an IPython GUI.

   * Example.

StarCluster
-----------

Miscellany
----------

* mpi4py

* IPython parallelism

* Cython

* Numba

* PyCUDA

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