Building Machine Learning Systems with Python - Richert, Coelho

You will also find the book NumPy Beginner's Guide - Second Edition, Ivan Idris,
Packt Publishing very valuable. Additional tutorial style guides are at http://
scipy-lectures.github.com; you may also visit the official SciPy tutorial at
http://docs.scipy.org/doc/scipy/reference/tutorial.
In this book, we will use NumPy Version 1.6.2 and SciPy Version 0.11.0.
Chapter 1
Learning NumPy
So let us import NumPy and play a bit with it. For that, we need to start the Python
interactive shell.
>>> import numpy
>>> numpy.version.full_version
1.6.2
As we do not want to pollute our namespace, we certainly should not do the following:
>>> from numpy import *
The numpy.array array will potentially shadow the array package that is included
in standard Python. Instead, we will use the following convenient shortcut:
>>> import numpy as np
>>> a = np.array([0,1,2,3,4,5])
>>> a
array([0, 1, 2, 3, 4, 5])
>>> a.ndim
1
>>> a.shape
(6,)
We just created an array in a similar way to how we would create a list in Python.
However, NumPy arrays have additional information about the shape. In this case,
it is a one-dimensional array of five elements. No surprises so far.
We can now transform this array in to a 2D matrix.
>>> b = a.reshape((3,2))
>>> b
array([[0, 1],
[2, 3],
[4, 5]])
>>> b.ndim
2
>>> b.shape
(3, 2)
[ 13 ]