What is SciPy?
Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
SciPy is a tool in the Data Science Tools category of a tech stack.
SciPy is an open source tool with 6.4K GitHub stars and 3K GitHub forks. Here’s a link to SciPy's open source repository on GitHub
Who uses SciPy?
20 companies reportedly use SciPy in their tech stacks, including Suggestic, Botimize, and zetaops.
29 developers on StackShare have stated that they use SciPy.
Why developers like SciPy?
Here’s a list of reasons why companies and developers use SciPy
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SciPy Alternatives & Comparisons
What are some alternatives to SciPy?
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Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.