• NumPy is used to perform a wide variety of mathematical operations on arrays, fast.
• NumPy is a Python library used for working with arrays.
• It also has functions for working in the domain of linear algebra, Fourier transform, and matrices.
• NumPy was created in 2005 by Travis Oliphant.
• It is an open-source project and you can use it freely.
• NumPy stands for Numerical Python.
• https://github.com/numpy/numpy.

Why Use Numpy

• In Python, we have lists that serve the purpose of arrays, but they are slow to process.
• NumPy aims to provide an array object that is up to 50x faster than traditional Python lists.
• The array object in NumPy is called ndarray, it provides a lot of supporting functions that make working with ndarray very easy.
• Arrays are very frequently used in data science, where speed and resources are very important.

Why is NumPy Faster Than Lists?

• NumPy arrays are stored at one continuous place in memory, unlike lists.
  • So processes can access and manipulate them very efficiently.
• This behaviour is called the locality of reference in computer science.
• This is the main reason why NumPy is faster than lists.
• Also, it is optimized to work with the latest CPU architectures.