The second part of this hands-on series will introduce you to a few libraries that enable Python to function as a powerful numerical programming language, including NumPy, SciPy, and Pandas. We will focus on a few illustrative problems, such as exploratory statistical analysis and visualization, curve fitting, finding solutions to a set of linear equations, and numerical differentiation and integration, with the aim being to provide a good foundation for further exploration and programming activity. By the end, you will be familiar with the ecosystem of numerical tools contained in these libraries and fundamental ways to use them.