NumPy is a powerful Python library used for numerical computing. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays efficiently. NumPy is widely used for data analysis, machine learning, scientific computing, and more, due to its high performance and ease of use. It is particularly well-known for its ability to perform operations on arrays with high speed compared to traditional Python lists.
Some key features of NumPy include:
ndarray: A fast, flexible, and efficient multi-dimensional array. Vectorization: Allows for element-wise operations without the need for explicit loops. Broadcasting: Facilitates operations on arrays of different shapes. Mathematical functions: Provides a variety of built-in functions for linear algebra, statistics, and more. NumPy is the foundational package for scientific computing in Python, and many other libraries (like SciPy, pandas, and scikit-learn) rely on it.