Getting started with NumPy

When you start developing larger applications, and especially when you start using multiple modules like scipy (SciPy) and the matplotlib plotting system, it can become difficult to remember which functions came from which module.

The cure for this problem is to import the entire module and then refer to things inside the module using the syntax “M.thing” where M is the name of the module and thing is the name of the item within the module.

Place a line like this with your other import statements:

import numpy as np

Then you use np.array() to create an array, or use np.arange() to create an arithmetic progression array, and so forth.

In the rest of this document, we will assume that you use the second form of import. For example:

>>> import numpy as np
>>> print np.pi, np.e
3.14159265359 2.71828182846
>>> print np.arange(0.0, 1.0, 0.1)
[ 0.   0.1  0.2  0.3  0.4  0.5  0.6  0.7  0.8  0.9]

The term namespace hygiene refers to the commendable practice of keeping items from different namespaces separate, so you can tell what comes from where.