In R, NA (which is almost, but not quite like NaN) actually has separate types for each result, so you can have NA_boolean, NA_integer etc. Its super confusing.
In R, NA (which is almost, but not quite like NaN) actually has separate types for each result, so you can have NA_boolean, NA_integer etc. Its super confusing.
It is a minor nuisance, but I think there's ultimately a pretty good reason for it.
Old-school base R is less type-sensitive and more "do what I mean", but that leads to slowness and bugs. Now we have the tidyverse, which among many other things provides a new generation of much faster functions with vectorized C implementations under the hood, but this requires them to be more rigid and type-sensitive.
When I want to stick a NA into one of these, I often have to give it the right type of NA, or it'll default to NA_boolean and I'll get type errors.
> When I want to stick a NA into one of these, I often have to give it the right type of NA, or it'll default to NA_boolean and I'll get type errors.
Yeah, I know. I hit this when I was building S4 classes, which are similarly type-strict.
Again, I think this was the right decision (pandas's decision was definitely not), but it was pretty confusing the first time.