Implement skipmissing argument to levels
#391
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The argument is added by DataAPI 1.10 (JuliaData/DataAPI.jl#46). When `skipmissing=true`, the method for `CategoricalArray` can be slightly more efficient than the fallback defined in DataAPI as it avoids calling `unique`.
nalimilan
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Apr 19, 2022
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| @test levels(x, skipmissing=true) == ["b", "c", "a"] | ||
| @test levels(x, skipmissing=true) isa Vector{String} | ||
| @test levels(x, skipmissing=false) == ["b", "c", "a"] | ||
| @test levels(x, skipmissing=false) isa Vector{Union{String, Missing}} |
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I couldn't find a way to make this inferrable, even by wrapping this in a function. Not sure why. It's not terrible since the return type is inferred as Union{Vector{Union{String, Missing}}, Vector{String}}. But still...
bkamins
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Apr 21, 2022
bkamins
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Apr 21, 2022
bkamins
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Apr 21, 2022
bkamins
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Apr 21, 2022
bkamins
approved these changes
Apr 23, 2022
|
There are some issues with Julia nightly 😞. |
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The argument is added by DataAPI 1.10 (JuliaData/DataAPI.jl#46).
When
skipmissing=true, the method forCategoricalArraycan be slightly more efficient than the fallback defined in DataAPIas it avoids calling
unique.