Comments (3)
This would make @tshort happy I suspect. It's definitely worth adding, but I'm a little worried about how it would fit into the system -- would you always use FloatDataArray
instead of DataArray
when working with floats?
from dataarrays.jl.
I'm not sure, although it seems safer to use a DataArray even when working with floats. With a DataArray you could potentially have values that are NaN
but not NA
, and thus should contaminate the result when NAs are ignored. This wrapper wouldn't be able to express that. On the other hand such cases probably arise rarely in practice. How does R treat NaN
vs. NA
?
from dataarrays.jl.
In R, NA
and NaN
have a different bit pattern (both of which are NaN
's). You could do the same in Julia.
NA
's and NaN
's can get mixed up if you mix operations that include both.NA + NaN
could be a different answer than NaN + NA
. I don't think you can avoid those issues. Anyway, I think it's rare to have conflicts between NA
and NaN
.
from dataarrays.jl.
Related Issues (20)
- #undef/uninitialised values from unique on PooledDataArray
- Get rid of @ngenerate
- Missing DataArray{T}(dims) constructors HOT 1
- MethodError in pooleddataarray.jl in Julia 0.6 HOT 7
- Inference failure/indexing issues HOT 14
- View on DataArray makes copy HOT 1
- broadcast() inference issue with mean() and > HOT 5
- In v 0.7 precompile fails with typeassert HOT 1
- `safe_mapslices` at test/reducedim.jl is broken on 0.7 HOT 2
- Can't load DataArrays HOT 9
- Weighted mean broken for matrices HOT 1
- Avoid copying input Array{Union{T, Null}} in DataArray{T} constructor
- getindex broken when using multidimensional index of DataArray{Bool}
- Division DataArray{Int} / Int results in Array{Any} HOT 2
- doesn't load on julia v0.7 because of `printf` HOT 1
- PooledDataArray depreciated? HOT 1
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from dataarrays.jl.