Scientific computing mainly demands the facility of performing calculations on algebraic equations, matrices, differentiations, integrations, differential equations, statistics, equation solvers, and more. By default, Python doesn't come with these functionalities. However, the development of NumPy and SciPy has enabled us to perform these operations and far more advanced functionalities beyond them. NumPy and SciPy are very powerful Python packages that enable users to efficiently perform the desired operations for all types of scientific applications.
NumPy is the basic Python package for scientific computing. It provides the facilities of multidimensional arrays and basic mathematical operations, such as linear algebra. Python provides several data structures to store user data; the most popular data structures are lists and dictionaries. List objects may store any type of Python object as an element. These elements can be processed...