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Implement skipmissing argument to levels #391

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merged 3 commits into from
Sep 25, 2022
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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.

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 nalimilan requested a review from bkamins April 19, 2022 20:22
Comment on lines +2274 to +2277
@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...

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bkamins commented Apr 23, 2022

There are some issues with Julia nightly 😞.

@nalimilan nalimilan closed this Sep 25, 2022
@nalimilan nalimilan reopened this Sep 25, 2022
@nalimilan nalimilan merged commit 847a745 into master Sep 25, 2022
@nalimilan nalimilan deleted the nl/missinglevels branch September 25, 2022 18:59
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2 participants