NumPy is the most fundamental package for scientific computing with Python. It adds to the Python language a data structure (the NumPy array) that has access to a large library of mathematical functions and operations, providing a powerful framework for fast computations in multiple dimensions. NumPy is the basis for all SciPy packages which extends vastly the computational and algorithmic capabilities of Python as well as many visualization tools like Matplotlib, Chaco or Mayavi.
This tutorial will teach students the fundamentals of NumPy, including fast vector-based calculations on numpy arrays, the origin of its efficiency and a short introduction to the matplotlib plotting library. In the final section, more advanced concepts will be introduced including structured arrays, broadcasting and memory mapping.