I’m learning to write code for my data analysis and numerical modelling work in Python. I quite like learning how to make tidy code and developing an understanding for the tricks of a specific language, but at the same time I’m deeply impatient as I really just want to get to the answer. I think what I’m saying is that if I had a time machine I’d really like learning programming. If.
Anyway the reality is that my students are better at it than me, and I have much to learn, and it seems to take me ages. Luckily there is a heap of material out there to help make learning easier and faster. In fact almost overwhelming. Also its not just that I need to learn python but also all the useful packages I need in my work. So here are some resources that I am finding useful so far – I will update it as I find new things.
Tutorials/workshops/lecture notes:
- http://fabienmaussion.info/acinn_python_workshop
- https://www.stavros.io/tutorials/python/
- https://pandas.pydata.org/pandas-docs/stable/10min.html
- http://www.scipy-lectures.org/index.html
- http://www.labri.fr/perso/nrougier/teaching/numpy.100/
- http://scipy-cookbook.readthedocs.io/
Articles (suggested by my colleague Fabien Maussion):
- Nature article “Programming: Pick up Python”
http://www.nature.com/news/programming-pick-up-python-1.16833 - BAMS article “Why Python Is the Next Wave in Earth
Sciences Computing” http://journals.ametsoc.org/doi/full/10.1175/BAMS-D-12-00148.1 - Nature article “Climate scientist Damien Irving on Python libraries” http://www.nature.com/news/my-digital-toolbox-climate-scientist-damien-irving-on-python-libraries-16805
If you have other recommendations, do let me know, both to help me and so I can add it to the list! In the meantime, enjoy some encouragement from xkcd ….
