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 the JuliaData collaborators. Responsiveness to pull requests and issues can vary, depending on the availability of key collaborators.

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

This package provides additional functionality for working with missing values:

• nonmissingtype to extract T from a Union{T, Missing} type
• allowmissing and disallowmissing to convert between Vector{T} and Vector{Union{T, Missing}}
• passmissing to wrap a function so that it returns missing if any of its positional arguments is missing
• levels to get the unique values in a vector excluding missing and in their preferred order
• Missings.replace to wrap a collection in a (possibly indexable) iterator replacing missing with another value
• Missings.fail to wrap a collection in a (possibly indexable) iterator throwing an error if missing is encountered
• skipmissings to loop through a collection of iterators excluding indices where any iterators are missing
• missingsmallest(f) to create a partial order function that treats missing as the smallest value and otherwise behaves like f
• missingsmallest: the standard isless function modified to treat missing as the smallest value rather than the largest one

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