NumPy

Numpy (short for Numerical Python) is a popular open-source software library used for numerical computing in Python. Numpy was created by Travis Oliphant in 2005 and is now maintained by a large community of developers. It extends the capabilities of the Python language in the areas of scientific computing, mathematics, and engineering.

Numpy is widely used in a variety of areas, including general data science, machine learning, scientific computing, and deep learning. It offers powerful numerical library features that enable users to operate on matrices, vectors, and arrays of data. Furthermore, it provides efficient implementations of several mathematical operations such as linear algebra, Fourier transforms, and discrete Fourier transforms.

Numpy provides a powerful set of features for manipulating multidimensional arrays. It allows users to conveniently access and process data stored in arrays in a two-dimensional form. Additionally, it provides access to advanced mathematical functions, such as random number generation, and statistical functions.

Numpy also includes numerous advanced tools, such as integration of C and Fortran libraries for optimized execution speed and memory usage, and support for distributed and multi processor computing. The library is also known for its intuitive commands, comprehensive documentation, and easy scalability to larger datasets. Lastly, Numpy’s popularity is due to its integration with a variety of data science tools such as SciPy, Pandas, and scikit-learn.