### Install Missings.jl Package in Julia

Source: https://github.com/juliadata/missings.jl/blob/main/README.md

Instructions to add the Missings.jl package to your Julia environment using the Pkg manager.

```Julia
import Pkg;
Pkg.add("Missings")
```

--------------------------------

### Missings.jl Core Functionality API Overview

Source: https://github.com/juliadata/missings.jl/blob/main/README.md

Overview of key functions provided by the Missings.jl package for handling missing values, including type conversion, function wrapping, and collection manipulation.

```APIDOC
nonmissingtype(::Type{Union{T, Missing}})::Type{T}
  Extracts the non-missing type T from a Union{T, Missing} type.

allowmissing(::Vector{T})::Vector{Union{T, Missing}}
disallowmissing(::Vector{Union{T, Missing}})::Vector{T}
  Converts between Vector{T} and Vector{Union{T, Missing}}.

passmissing(f::Function)::Function
  Wraps a function so that it returns `missing` if any of its positional arguments is `missing`.

levels(v::AbstractVector)::Vector
  Gets the unique values in a vector, excluding `missing`, and in their preferred order.

Missings.replace(collection, value)
  Wraps a collection in a (possibly indexable) iterator, replacing `missing` with another specified value.

Missings.fail(collection)
  Wraps a collection in a (possibly indexable) iterator, throwing an error if `missing` is encountered.

skipmissings(iterators...)
  Loops through a collection of iterators, excluding indices where any iterators are `missing`.

missingsmallest(f::Function)::Function
  Creates 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.
```

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