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Convenience functions for working with missing values in Julia

Installation: at the Julia REPL,import Pkg; Pkg.add("Missings")

Maintenance: Missings is maintained collectively by theJuliaData collaborators.Responsiveness to pull requests and issues can vary, depending on the availability of key collaborators.

Starting from Julia 1.0, theMissing type and basic related functionality are part of the language.For documentation seethe Julia manual section on missing values.

This package provides additional functionality for working withmissing values:

• nonmissingtype to extractT from aUnion{T, Missing} type
• allowmissing anddisallowmissing to convert betweenVector{T} andVector{Union{T, Missing}}
• passmissing to wrap a function so that it returnsmissing if any of its positional arguments ismissing
• levels to get the unique values in a vector excludingmissing and in their preferred order
• Missings.replace to wrap a collection in a (possibly indexable) iterator replacingmissing with another value
• Missings.fail to wrap a collection in a (possibly indexable) iterator throwing an error ifmissing is encountered
• skipmissings to loop through a collection of iterators excluding indices where any iterators aremissing
• missingsmallest(f) to create a partial order function that treatsmissing as the smallest value and otherwise behaves likef
• missingsmallest: the standardisless function modified to treatmissing as the smallest value rather than the largest one

Contributions are welcome, as are feature requests and suggestions.Please open anissue if you encounter any problems or would just like to ask a question.