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JuliaStats/DataArrays.jl: DEPRECATED: Data structures that allow missing values

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称:

JuliaStats/DataArrays.jl

开源软件地址:

https://github.com/JuliaStats/DataArrays.jl

开源编程语言:

Julia 100.0%

开源软件介绍:

DataArrays.jl

Build Status Coverage Status

Latest release: DataArrays

Documentation:

THIS PACKAGE IS DEPRECATED with Julia versions above 0.7. Use Array{Union{T, Missing}} instead: see this blog post.

The DataArrays package provides the DataArray type for working efficiently with missing data in Julia, based on the missing value from the Missings.jl package.

Most Julian arrays cannot contain missing values: only Array{Union{T, Missing}} and more generally Array{>:Missing} can contain missing values.

The generic use of heterogeneous Array is discouraged in Julia versions below 0.7 because it is inefficient: accessing any value requires dereferencing a pointer. The DataArray type allows one to work around this inefficiency by providing tightly-typed arrays that can contain values of exactly one type, but can also contain missing values.

For example, a DataArray{Int} can contain integers and missing values. We can construct one as follows:

da = @data([1, 2, missing, 4])

This package used to provide the PooledDataArray type, a variant of DataArray{T} optimized for representing arrays that contain many repetitions of a small number of unique values. PooledDataArray has been deprecated in favor of CategoricalArray or PooledArray.




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