As we approach quantitative sciences like physics and chemistry we tend to eschew the notion of 'coding practices'. "That is the domain of CS classes." This is fine but a lot of what we do involves learning not just the science and principles but the tools of the trade as well. Along with measurement and investigative techniques we need to learn how to process data and model phenomenon. Computers are tools we use to do this and, by necessity, some programming. Python is a fairly easy entry into this arena as it is very forgiving in its syntax. Nevertheless there are always some tricks that need to be addressed as students increase their exposure to this new tool.
This is a collection of python and Jupyter specific techniques for keeping this process simple and easy to use.