Numpy

One of the most popular Python libraries for scientific computing is numpy. Python is not renowned for its run speed but its speed of writing. numpy helps with this as it brings fast numeric computations to Python. It is also a powerful tool for linear algebra (matrices) although it cannot handle symbolic variables.

Important

In this chapter we will cover:

• How to create and manipulate numpy arrays.

• How to create specific numpy arrays like linear spaces.

• How to use numpy’s random number generator.

• How to invert a matrix.

• How to fit a polynomial to data.