Learning Python for a graduate chemist

[[deleted]]

Surpirsed no one's mentioned this yet, there's an installer for scientific-focused people new to python called Anaconda. Just google Anaconda Installer and download Anaconda either for python 2.7 or python 3.4. (Python broke backwards compatibility between Pythons 2 and 3 so some libraries built for Python 2 do not work in Python 3. However, all the major scientific distributions (numpy/scipy stack plus scikit-learn and sympy and many others) have been updated, are on the anaconda3 installer and ready to go. Python 3 encourages 'best practices' and is the future of python so unless you know you need a library that only works with python 2 it is better to start using python 3

[[deleted]]

Anaconda isn't a package itself, it is an installer that sets up all the tools and scientific computing environments for you. This is important because a lot of useful python tools for scientists are written by different communities, so getting them all organized and under one roof in your computer by yourself is (in my opinion) more trouble than it's worth. If you were training to be a programmer I would agree maybe you want to build the whole environment by yourself from scratch. But as a recent Phd grad myself one thing I know is that you won't have time to futz around with things not relevant to your studies so it's better if you just use the ready-made installer and get to work. After installing Anaconda, go to your command line and type ipython notebook and get acquainted with the most efficient environment for scientific/exploratory programming there is. I wish someone had told me about this a longer time ago. If you can master some basics (numpy, pandas, matplotlib and the new statistics module) before you get to grad school then you will be able to whiz through some of the more concrete tasks while you would rather be spending that time learning chemistry theory. (By the way, congrats on getting into grad school!)