My Favorite NumPy and SciPy References

Here are some references I’ve found particularly useful when developing or debugging Python code with NumPy and SciPy.  (I can’t avoid the temptation to use the Australian pronunciation:  “Skippy.”

User’s Guides

These focus on techniques for using specific methods.  They are generally stronger than beginner’s introductions.

https://docs.scipy.org/doc/numpy/user/index.html

https://docs.scipy.org/doc/numpy-1.11.0/user/

http://www.scipy-lectures.org/intro/numpy/index.html

http://csc.ucdavis.edu/~chaos/courses/nlp/Software/NumPyBook.pdf

 

 

Reference Guides

These provide encyclopedic reference on the details of function and syntax.

Language Reference:

https://docs.scipy.org/doc/numpy/

https://docs.scipy.org/doc/numpy/numpy-ref-1.12.0.pdf

https://docs.scipy.org/doc/numpy/reference/index.html

 

Style Guides

These provide some best practices on structuring the code.

http://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_numpy.html

https://github.com/numpy/numpy/blob/master/doc/example.py

https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt

 

Glossary

https://docs.scipy.org/doc/numpy/glossary.html

Cookbooks

http://scipy-cookbook.readthedocs.io/

Tutorials

The better organized on-line tutorials easily serve as user’s guides.

https://docs.scipy.org/doc/numpy/user/quickstart.html

http://www.tutorialspoint.com/numpy/

http://cs231n.github.io/python-numpy-tutorial/

https://github.com/rougier/numpy-tutorial

http://www.scipy-lectures.org/intro/index.html

https://www.labri.fr/perso/nrougier/teaching/numpy/numpy.html

https://www.dataquest.io/blog/numpy-tutorial-python/

 

 


(Python logo provided courtesy of Python Software Foundation, used here under the “nominative use rules” of their policy.)

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