NumPy is one of the most useful and popular Python tool-kits available for computer scientists, programmers, and data analysts. It is an open-sourced programming extension library that enables numerical computing in Python, i.e. arithmetic functions with arrays and matrices, statistics functions like finding means and medians, and linear algebra functions like finding the determinant of matrices and finding their dot and inner products. It is developed and improved upon in Github and overseen by its “Steering Council.” Click here to learn more.
Uses: NumPy is a widely used tool by data scientists. Use of the library allows for the use of arrays, vectors and matrices, and their respective functions and attributes (as listed above). This implementation allows for data to be collected and stored in manipulable dimensional spaces. Conceptually, NumPy bridges Python with linear algebra, allowing for the application of formulas and theorems in a Python virtual environment. These concepts allow data scientists to collect, store, manipulate and predict data in Python. These ideas are used in machine learning, artificial intelligence and countless other computer science fields.
Documentation: Click here.