SciPy is built on top of NumPy. It adds functionality such as numerical integration, optimization, statistics, and special functions. Historically, NumPy was part of SciPy but was then separated in order to be used by other Python libraries. These, when combined, define the common stack for scientific and numerical analysis. Of course, the stack itself is not set in stone; however, everybody agrees on NumPy being at the center of it all. The examples in this chapter should give you some idea about the power of the scientific Python ecosystem.

In this chapter, we will cover the following topics: