The NumPy Array: A Structure for Efficient Numerical Computation

@article{Walt2011TheNA,
  title={The NumPy Array: A Structure for Efficient Numerical Computation},
  author={S. Walt and S. Colbert and G. Varoquaux},
  journal={Computing in Science \& Engineering},
  year={2011},
  volume={13},
  pages={22-30}
}
In the Python world, NumPy arrays are the standard representation for numerical data and enable efficient implementation of numerical computations in a high-level language. As this effort shows, NumPy performance can be improved through three techniques: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts. 
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NumPy is a volunteer effort
  • NumPy is a volunteer effort
NumPy's documentation is maintained using a WikiPedia-like community forum
  • Discussions take place on the project mailing list
NumPy's documentation is maintained using a WikiPedia-like community forum, available at http://docs.scipy.org/. Discussions take place on the project mailing list
  • NumPy's documentation is maintained using a WikiPedia-like community forum, available at http://docs.scipy.org/. Discussions take place on the project mailing list