https://www.scipy.org/
https://docs.scipy.org/doc/scipy/tutorial/index.html
SciPy User Guide
https://pypi.org/project/scipy/
SciPy: Scientific Library for Python
https://scipy-cookbook.readthedocs.io/
SciPy Cookbook
https://www.scipy.org/install.html
ANACONDA Use 'conda' or graphical tools. PIP (in a virtual environment) python -m pip install numpy scipy matplotlib ipython jupyter pandas sympy nose APT (for the entire computer) Debian packages: python-scipy, python3-scipy, and dependencies. From SciPy.org: apt-get install python-numpy python-scipy python-matplotlib python-pandas apt-get install ipython ipython-notebook python-sympy python-nose
SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering [version 1.1.0 in Debian 10]. These are some of the core packages: NumPy, SciPy library, Matplotlib, IPython, SymPy, pandas, NetworkX, scikit-learn, scikit-image, h5py.
SciPy is organized into subpackages covering different scientific computing domains. These are summarized in the following table:
Subpackage Description cluster Clustering algorithms constants Physical and mathematical constants fftpack Fast Fourier Transform routines integrate Integration and ordinary differential equation solvers interpolate Interpolation and smoothing splines io Input and Output linalg Linear algebra ndimage N-dimensional image processing odr Orthogonal distance regression optimize Optimization and root-finding routines signal Signal processing sparse Sparse matrices and associated routines spatial Spatial data structures and algorithms special Special functions stats Statistical distributions and functions SciPy sub-packages need to be imported separately, for example: from scipy import linalg, optimize import scipy.special as sc # help(sc) import scipy.special as special