Practical Python Data Wrangling and Data Quality

Appendix A. More Python Programming Resources

As this book has hopefully illustrated, Python is a robust and flexible programming language, with a wide range of applications. While I’ve introduced many key concepts and popular libraries in the preceding chapters, I’ve created this appendix to provide you with some helpful resources and references for taking your Python work to the next level.

Official Python Documentation

Yes, there are always search engines and StackOverflow, but there’s value in getting comfortable reading official documentation—whether it’s for the Python language or for popular libraries like pandas, matplotlib, or seaborn. Though I wouldn’t suggest you sit down and read any programming documentation end to end, looking through the parameters and options of a data type or function you want to use can give you a better sense of what (in general) can be done with it, as well as an idea of how its mechanisms are organized. This can be especially helpful when you want to do something completely new, because it will give you an idea of where to look for paths forward.

For example, I knew when I started writing this book that seaborn and pandas were both built on top of matplotlib, and I had done some hacking around with making and customizing graphics with both of them. It wasn’t until I was looking through the latter’s documentation, however, that I came to understand the difference between the figure and axes objects that I so often saw referenced in example ...