Anaconda vs SciPy: What are the differences?
Anaconda: The Enterprise Data Science Platform for Data Scientists, IT Professionals and Business Leaders. 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; SciPy: Scientific Computing Tools for Python. 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.
Anaconda and SciPy can be primarily classified as "Data Science" tools.
SciPy is an open source tool with 6.01K GitHub stars and 2.85K GitHub forks. Here's a link to SciPy's open source repository on GitHub.
Suggestic, Botimize, and Zetaops are some of the popular companies that use SciPy, whereas Anaconda is used by ADEXT, Luuna, and DLabs. SciPy has a broader approval, being mentioned in 12 company stacks & 4 developers stacks; compared to Anaconda, which is listed in 4 company stacks and 5 developer stacks.