Comments (9)
It would be nice to have functions like skewness(A; dims)
taking a dims
keyword to reduce over, where A
can be a general N-dimensional Array. Any plans to implement this?
from statsbase.jl.
+1 if you mean something like this:
StatsBase.trimmean{T}(v::AbstractArray{T}, p, region) = mapslices(x->trimmean(x,p), v, region)
from statsbase.jl.
Any progress on this?
from statsbase.jl.
Now that Julia provides these, it is probably be better to use e.g. skewness.(eachrow(x))
and skewness.(eachcol(x))
. The dims=1
/dims=2
approach requires adjusting lots of methods and is less explicit.
from statsbase.jl.
@cossio There's a PR to add a generic eachslice
iterator to Base: JuliaLang/julia#32310; it's been under review for a while but there's recent activity...
from statsbase.jl.
This is now merged, time to close this issue?
from statsbase.jl.
skewness(rand(10,10), dims=1)
doesn't work on 1.9rc1 and latest StatsBase
from statsbase.jl.
@jamblejoe but you can use eachslice
on julia 1.8 to achieve the same:
julia> skewness.(eachslice(rand(10,10), dims=1))
10-element Vector{Float64}:
-0.357654736525527
-0.06636393783605732
-0.20782459433865907
1.25151036890323
0.13408296667729347
-0.4302398373636257
-0.14363707095203634
-0.00889806440269636
-0.6370034546305223
0.5832296811450159
from statsbase.jl.
@bjarthur works thanks! Can be closed from my side
from statsbase.jl.
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from statsbase.jl.