In this chapter, we extensively discussed how to perform numerical computations using the NumPy and Scipy packages of Python. The concepts were presented along with example programs. The chapter started with a discussion on the fundamental objects of NumPy, and then we moved on to the advanced concepts of NumPy.

This chapter also discussed the functions and modules of SciPy. It covered the basic and special functions provided by SciPy, and then covered the special modules or sub packages. This was for showing advanced concepts, such as optimization, interpolation, Fourier transformation, signal processing, linear algebra, statistics, spatial algorithms, image processing, and file input and output.

In the next chapter, we will have an exhaustive discussion on symbolic computing, or CAS, using SymPy. Specifically, we will cover the core capabilities and extended functionalities for polynomials, calculus, equation solvers, discrete mathematics, geometry, and physics.