NumPy
NumPy is the fundamental open-source package for numerical computing in Python. It provides a powerful N-dimensional array object and tools for performing high-performance mathematical operations on large datasets, making it a core dependency for many data science and machine learning libraries.
Key Features
N-Dimensional Arrays: Efficient storage and manipulation of large, multi-dimensional arrays.
Broadcasting Functions: Perform operations across arrays of different shapes.
Interoperability: Interfaces with C, C++, and Fortran code for optimized performance.
Mathematical Utilities: Includes functions for linear algebra, Fourier transforms, statistics, and random number generation.
Foundation for SciPy Stack: Powers libraries like pandas, scikit-learn, TensorFlow, and more.
Example Use Cases
Fast numerical operations on large datasets
Serving as the array backend for machine learning frameworks
Performing statistical or signal processing tasks in scientific research
Teaching numerical computing and vectorized operations