What you need is the conda package manager (from anaconda python), in my opinion. Docker is very powerful, but is useful for other purposes (e.g deploying code) than simply grabbing a bunch of python modules and running analyses in a notebook.
Standard procedure, takes two minutes and I have a Jupyter notebook up, smartly automated base processes for dependency management, full control of environment variables and can deploy/ integrate this in any other Python setup (if I were to port IPython code to pure Python).
Is this more a thing of each his own or am I missing a crucial advantage of Anaconda?
[1] https://github.com/kennethreitz/autoenv [2] https://github.com/jazzband/pip-tools [3] https://github.com/pyupio/pyup
I've been to enough software carpentry talks where people nod and smile, and then promptly ignore the "how to be a responsible developer" advice. They don't care. They just want to run Python and plot some stuff or classify some data without worrying about multiple CLI tools. People seem to accept Anaconda because it comes across as a monolith and it's easier to understand for new programmers than virtualenvs and worrying about pinning pip installs.
That said, I don't use Anaconda on Mac or Linux.