Analyzing Neural Time Series by Mike Cohen (2014) is a great book written for neuroscientists working with continuous neural data. Although it may seem like the book is mainly written for EEG analysis, I found that the topics in the book are easily translatable to any domain requiring continuous-data signal processing. Each chapter introduces a new technique, with heavy emphasis on concepts rather than mathematical rigor, and even has summaries at the end of each chapter with tips on how to describe the analysis in the methods section of your paper. The code included with the book is written in MATLAB, and is great; however, I thought it might be useful to translate this code into Python for fun, and because it may be useful for those who would like their analysis pipelines written in Python instead of MATLAB. I've decided to write the code in ipython (Jupyter) notebooks for clarity.

Feel free to flip through and use the code as you wish. If anything seems off, please let me know and I'll be sure to fix it asap.