The fundamental package for scientific computing with Python, providing support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
NumPy
- Python
- AI and Machine Learning, Data Analytics, Mathematics, Signal Processing, Simulation
- Artificial Intelligence (AI), Machine Learning, Mathematics, Software, Software Development Kit (SDK), Statistical Analysis, Statistical Process Control (SPC)
Features:
- N-dimensional array object (ndarray), efficient array operations (broadcasting, indexing, slicing), linear algebra functions, Fourier transforms, random number capabilities, tools for integrating C/C++ and Fortran code.
Pricing:
- Free
- Core library for numerical computing in Python, enables efficient array operations, foundational for many other scientific libraries (SciPy, pandas, scikit-learn), large community and extensive documentation.
- Array operations require understanding of vectorization for best performance, can be memory-intensive if not used carefully, API for some advanced features can be complex.
Best for:
- Virtually anyone doing numerical or scientific computing in Python, as it forms the bedrock for many data science, machine learning, and engineering tasks.