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(Note: This was originally posted on Facebook) TL;DR While the sample counts of this year’s GE saw some huge deviations, they are mostly within expectation. The two hour extension brought about some online groans from friends who didn’t want to stay up late to follow the results. To help alleviate some of this anxiety, I decided to set up a tracking sheet for the sample counts with estimated win probabilities to let people decide if the final count was worth waiting for. ...

In the past 8 months, I’ve probably worked on close to 10 different projects. While half of these consists of not more than a few Jupyter notebooks, the others consist of intermediate data and different notebooks for preprocessing and modelling. Cookiecutter seems to be a good solution and framework: https://drivendata.github.io/cookiecutter-data-science/ Refactoring those projects will take some effort, but I believe it will be well worth the time to do so.