4. What is SciPy?

Source

from the SciPy website

SciPy is a collection of mathematical algorithms and convenience functions built on the NumPy extension of Python. It adds significant power to the interactive Python session by providing the user with high-level commands and classes for manipulating and visualizing data. With SciPy, an interactive Python session becomes a data-processing and system-prototyping environment rivaling systems, such as MATLAB, IDL, Octave, R-Lab, and SciLab.

SciPy capabilities

• FUNDAMENTAL ALGORITHMS: Algorithms for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics and many other classes of problems.

• BROADLY APPLICABLE: The algorithms and data structures provided by SciPy are broadly applicable across domains.

• FOUNDATIONAL: SciPy provides additional tools for array computing and provides specialized data structures.

• PERFORMANT: Wrapping highly-optimized implementations written in low-level languages like Fortran, C and C++ makes users enjoy the flexibility of Python with the speed of compiled code.

• EASY TO USE: SciPy’s high level syntax makes it accessible and productive for programmers from any background or experience level.

• OPEN SOURCE: Distributed under a liberal BSD license, SciPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.