When building datascience APIs with kotlin, do you refer to missing values as NA nor null? Data-scientists are likely to prefer NA, and most kotlin programmer will prefer null. I'm asking because I want to add https://www.rdocumentation.org/packages/tidyr/versions/0.8.3/topics/drop_na to krangl (which is a data-frame implementation for kotlin) but the correct kotlin name seems to be

filterNotNull

.

Apart from nulls there are NaN and +-Infinity values that usually fell to the 'na' category. I would keep

drop_na

.

That's a very good point. I completely missed infinity.

No, not integers, only floating points (infinity and NaNs). No idea about doc sharing 🙂