Apologies for the noise, but would it make sense if the functions returned the same type as the parameter to improve composition with other functions & operators? My examples might be a hassle to use as-is.
> On Jul 26, 2020, at 1:10 PM, Troy Zimmerman <tazimmer...@me.com.INVALID> > wrote: > > Hi, > > Would it be possible to support additional types in the following functions, > or are they purposefully limited to decimal128? Naively, I assume the > following make sense: > > abs(float64) -> float64 > abs(int64) -> int64 > ceil(float64) -> int64 > floor(float64) -> int64 > trunc(float64) -> int64 > round(float64, int32) -> int64 > > The reason I ask is that when using the Python API, I have to wrap float > arguments with a cast to decimal when building & evaluating expressions. The > result array is also decimal128, which is an object dtype when converted to > pandas/numpy, so it would be convenient (and perhaps more efficient?) to have > float64 versions of the functions. > > Thank you for your effort. The arrow ecosystem is really impressive. > > Best, > Troy
