The SciPy Stack

The Scipy “Stack” is poorly defined, but more or less means the collection of packages and tools that people use to do scientific software development and data analysis with Python. At the core of this is the numpy package.

However, there is a definition of the “core” scipy stack:

  • numpy
  • scipy
  • matplotlib
  • pandas
  • iPython

Most people will find themselves using these core tools, regardless of their area of focus.

There are a lot of introductions, bootcamps, etc. for all this. Here are a few resources I particularly like:

numpy

numpy is the core of it all – a good understanding to numpy is key to doing anything with copmutational programming.

Some links:

100 numpy exercises:
Little tricks and tips that will get you familiar with the nooks and crannies of numpy: https://github.com/rougier/numpy-100

SciPy

A full “course” focused on Python for atmospheric and oceanic sciences, but most is applicable to other fields:

https://github.com/Unidata/unidata-python-workshop

Here is a collection of resources for scientific programming with Python:

https://pyintro.org/resources.html