Almost all scientific and numerical computing requires the representation of data in the form of vectors and matrices, and NumPy handles all these in terms of arrays.
NumPy and SciPy are computational modules of Python that provide convenient mathematical and numerical methods in precompiled, fast functions. The NumPy package provides basic routines to manipulate large arrays and matrices of numeric data. The SciPy package extends NumPy with a collection of useful algorithms with applied mathematical techniques. In NumPy, ndarray is an array object that represents a multidimensional, homogeneous array of items that have a known size.
NumPy not only uses array objects, but also linear algebraic functions that can be conveniently used for computations. It provides a fast implementation of arrays and associated array functionalities. Using an array object, one can perform operations that include matrix multiplication, transposition of vectors and matrices...