NumPy is a numerical computing package built around the ndarray, a multidimensional array capable of storing and processing large collections of homogeneous data. It provides a foundation for scientific applications, statistical analysis and numerical algorithms.
Arrays can represent vectors, matrices and data with many dimensions. Rather than processing individual values in explicit loops, users can perform mathematical operations on entire arrays. This approach combines concise expressions with efficient numerical execution.
NumPy is particularly useful when working with numerical measurements, sampled signals, simulation results and other structured data. Its array model is also widely used for exchanging information between scientific computing applications and specialised analytical tools.
This is free and open source software.
Key Features
- Multidimensional ndarray objects with configurable shapes, data types and memory layouts.
- Broadcasting of compatible arrays to perform element-wise operations without explicit loops.
- Universal functions for mathematical, logical, comparison and other numerical operations.
- Advanced indexing, Boolean masking and slicing for selecting or modifying array data.
- Array manipulation through reshaping, stacking, splitting, transposing and broadcasting.
- Reduction and aggregation operations including sums, products, means, variances and quantiles.
- Linear algebra routines for matrix multiplication, decompositions, solving systems of equations and eigenvalue calculations.
- Discrete Fourier transforms for frequency-domain analysis of sampled data.
- Random number generation through configurable Generator objects and bit generators.
- Sorting, searching and set operations for numerical and categorical array values.
- Structured arrays, record arrays and masked arrays for specialised data representations.
- File input and output for NumPy array formats, text files and memory-mapped data.
- Interoperability with scientific computing packages through standard array interfaces.
- f2py interface generator for connecting numerical routines implemented in Fortran.
- Cross-platform support – runs on Linux, macOS, and Windows.
Website: numpy.org
Support:
Developer: NumPy Developers
License: BSD 3-Clause ‘New’ or ‘Revised’ License
NumPy is written in Python. Learn Python with our recommended free books and free tutorials.
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