I’ve been working on the same thing. Does anyone here have tips on how to filter/mask a given time-based data set so that it infers data where possible (i.e. if

I’ve been working on the same thing. Does anyone here have tips on how to filter/mask a given time-based data set so that it infers data where possible (i.e. if I logged one mood for the day, it’s probably safe to map that across the whole day) and ignore unrealistic data (I.e. if I logged one meal for the day, that’s probably not a useful day of data). So far just been winging it on a case-by-case basis but curious if there’s a fundamental pattern I’m missing