Python NumPy Library

NumPy (Numerical Python) is a foundational open-source Python library for numerical and mathematical computation.

It introduces the N-dimensional array (ndarray), a high-performance data structure for storing and manipulating large datasets efficiently. NumPy forms the computational foundation of the Python data-science ecosystem; major libraries such as Pandas, SciPy, scikit-learn, and TensorFlow build directly upon it.

This tutorial is designed to provide a concise yet practical overview of NumPy and to support day-to-day technical work through clear, task-oriented examples.

Key characteristics

• High performance: NumPy operations are implemented in highly optimised C, enabling many numerical workloads to run substantially faster than equivalent operations on standard Python lists.
• Vectorisation: NumPy reduces reliance on explicit Python loops by applying operations across entire arrays in a single expression.
• Memory efficiency: NumPy arrays store homogeneous data in contiguous memory blocks, typically reducing memory overhead relative to Python lists.

Core features and capabilities

NumPy provides a broad suite of tools for numerical computation, including:

• Multidimensional arrays: Creation and manipulation of 1D vectors, 2D matrices, and higher-dimensional structures.
• Broadcasting: Arithmetic operations between…