NumPy is one of the fundamental packages used for scientific computing in the Python ecosystem. Specifically, NumPy is used for numerical computing and uses n-dimensional arrays.
What is NumPy?
NumPy is one of the fundamental packages used for scientific computing in the Python ecosystem. Specifically, NumPy is used for numerical computing and uses n-dimensional arrays. Topics include applications in quantum computing, statistical computing, image processing, bioinformatics, geosciences, chemistry, etc. It is also frequently used in machine learning and data visualization. It is open-sourced and distributed under the BDS License.
New to NumPy?
There are various resources including books, tutorials/workshops, etc. for those looking to learn how to use NumPy.
A popular introductory tutorial is:
SciPy 2019 Conference Tutorial:
An list of additional tutorials are listed on the NumPy website:
numpy Tag Usage
When posting questions about numpy, please take the following into consideration:
Topics/use cases that involve the use of other packages as well should include all other relevant tags as well to make questions easier to find.
Explicit programming related questions are more suitable for Stack Overflow and should not be posted on Stack Exchange Data Science.
Questions should include sufficient details and clarity to be able to provide support for the problem at hand. This includes linking/showing underlying data being used, providing code, highlighting relevant outputs/desired outcomes, etc.
External Resources
numpy: Documentation page
numpy: GitHub page
Important links
Mailing List: https://www.scipy.org/scipylib/mailing-lists.html
Contributing to NumPy: https://numpy.org/contribute/
