It's so strange to me that data scientists would need to be convinced to move to Python 3. It's superior in every way to legacy Python. I can understand maintaing Python 3 compatbility for legacy systems if you don't want to have Python 3 as a dependancy, but data scientists will be writing mostly ad hoc code and using Jupyter notebooks. The people around me are not allowed to use Python 2, in fact they're generally required to use the latest version of Python 3.
For anyone having trouble with maintaing multiple Python versions, I recommend Pyenv. You can install multiple local versions and switch between them. The selected version then uses the standard commands "python" and "pip", etc. which you can use to make your virtualenv from.
For anyone having trouble with maintaing multiple Python versions, I recommend Pyenv. You can install multiple local versions and switch between them. The selected version then uses the standard commands "python" and "pip", etc. which you can use to make your virtualenv from.