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NumFOCUS

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26 reviews
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4.7
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NumFOCUS Reviews

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Vivek  R.
VR
Vivek R.
09/09/2024
Validated Reviewer
Review source: G2 invite
Incentivized Review

Versatile Python library for mathematical and statistical problem

Easy to sync with other libraries. Well mix of C and fortran makes it better than standard python
Verified User in Computer Software
UC
Verified User in Computer Software
09/02/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

Best python library for numerical operations

Numpy is used for complex mathematical and numerical operations. It provides efficient calculations of arrays and matrices. Execution speed is high. Arbitrary data types can be defined in Numpy.
deniz y.
DY
deniz y.
Business Intelligence Manager / Data & Insights Manager
11/19/2021
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Verified Current User
Review source: G2 invite
Incentivized Review

Easy and Convenient

It's a great library for doing advanced math that helps us work with Python's multidimensional arrays and matrices. It is very easy to use. It comes with Anaconda. It can be used efficiently with data science related libraries. It facilitates processing on large datasets.

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What is NumFOCUS?

NumFOCUS is a non-profit organization that supports and promotes open-source software initiatives aimed at the fields of data science and scientific research. It is dedicated to fostering an inclusive community that encourages the use of open-source software for better reproducibility in science. NumFOCUS is behind several prominent projects such as NumPy, pandas, Jupyter, and more, providing them with fiscal, legal, and administrative support to help ensure their growth and sustainability.The URL provided (https://pypi.org/project/numpy/) leads to the PyPI (Python Package Index) page for NumPy, which is one of the key projects supported by NumFOCUS. NumPy is a fundamental package for scientific computing in Python, offering support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

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pypi.org