NumPy, short for Numerical Python, is a fundamental library in Python designed for scientific computing. It provides support for large multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays efficiently. This makes it an essential tool for data manipulation and numerical computations in various fields, including data science and analytics ⁵.

The core feature of NumPy is its n-dimensional array object, known as ndarray. These arrays are more compact and faster to read/write compared to Python’s built-in lists. NumPy also offers a vast library of mathematical functions that allow for operations on arrays without the need for explicit loops, enhancing computational efficiency ⁵.

To get started with NumPy, you need to install it using pip, the Python package installer. You can do this by running the command pip install numpy in your terminal or command prompt. Once installed, you can import it in your Python scripts or Jupyter notebooks using import numpy as np, which is a common best practice for concise code ⁴.