Web Reference: Mar 25, 2026 · NumPy arrays (ndarrays) are the backbone of the library. This section covers how to create and manipulate arrays effectively for data storage and processing. This section covers essential mathematical functions for array computations, including basic arithmetic, aggregation and mathematical transformations. You might hear of a 0-D (zero-dimensional) array referred to as a “scalar”, a 1-D (one-dimensional) array as a “vector”, a 2-D (two-dimensional) array as a “matrix”, or an N-D (N-dimensional, where “N” is typically an integer greater than 2) array as a “tensor”. In this tutorial, you'll learn everything you need to know to get up and running with NumPy, Python's de facto standard for multidimensional data arrays. NumPy is the foundation for most data science in Python, so if you're interested in that field, then this is a great place to start.
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