Exception handling in data science

I started coding in C and used C# before switching to Java (those were the dark days). Today, R and Python make up my daily stack (and I dabble in Julia for fun). Now, in retrospect, one habit I wish the data science community had developed better is exception handling. More often than not, I come across code that is doomed to crash (hey, it’s called an exception for a reason).

The next time you code to analyze data, remember this video of division by zero. This is the pain and suffering your computer goes through when your denominator hits zero. This is also a reminder to appreciate (not complain about) the errors and warnings in R and Python (my former and future students, hear me?).

Received the video in personal communication and happy to add a source.