NumPy vs. Python Comparison


NumPy	Python 5.0 out of 5 stars	+	+
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About Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.	About The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Supported
Audience Component Library solution for DevOps teams	Audience Developers interested in a beautiful but advanced programming language
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Not Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Not Supported	Pricing Free Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 features 5.0 / 5 design 5.0 / 5 support 5.0 / 5 Read all reviews
	Pros & Cons from Real Users Pros Python is simple, easy to learn, but powerful and extensible. Python in my opinion is the best programming language to learn today. Cons I don't have any issues with Python at all. It's my favorite programming language.
Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information NumPy numpy.org	Company Information Python Founded: 1991 www.python.org
Alternatives Polars	Alternatives IBM SPSS Statistics IBM 4.4 out of 5 stars
h5py HDF5	AMPL
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PyQtGraph	IronPython
Dask View All	Cython View All
Categories Component Libraries Supported	Categories Programming Languages Supported

Integrations 3LC Supported Avanzai Supported Codédex Supported Coiled Supported Cython Supported Dash Supported Flower Supported Gensim Supported JAX Supported MPI for Python (mpi4py) Supported PaizaCloud Supported PyCharm Supported Spyder Supported Train in Data Supported Unify AI Supported Visual Studio Code Supported Yandex Data Proc Supported h5py Supported imageio Supported scikit-learn Supported Show More Integrations View All 22 Integrations	Integrations 3LC Supported Avanzai Supported Codédex Supported Coiled Supported Cython Supported Dash Supported Flower Supported Gensim Supported JAX Supported MPI for Python (mpi4py) Supported PaizaCloud Supported PyCharm Supported Spyder Supported Train in Data Supported Unify AI Supported Visual Studio Code Supported Yandex Data Proc Supported h5py Supported imageio Supported scikit-learn Supported Show More Integrations View All 1561 Integrations
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