RData.jl
Read R data files (.rda, .RData) and optionally convert the contents into Julia equivalents.
Can read any R data archive, although not all R types could be converted into Julia.
For running R code from Julia see RCall.jl.
Installation
From Julia REPL:
Pkg.add("RData")
Compression formats
R data files could be compressed by either Gzip (the default), Bzip2 or Xz methods. RData.jl
supports Gzip-compressed files out-of-the-box. To read Bzip2 or Xz-compressed files CodecBzip2.jl or CodecXz.jl must be installed.
For example, to load a file compressed by Bzip2 you must first install the required codec:
Pkg.add("CodecBzip2")
Then ensure CodecBzip2 is loaded before calling RData.load:
using RData
import CodecBzip2
load('some_bzip2_compressed.rda')
Usage
To read R objects from "example.rda" file:
using RData
objs = load("path_to/example.rda")
The result is a dictionary (Dict{String, Any}
) of all R objects stored in "example.rda".
If convert=true
keyword option is specified, load()
will try to automatically
convert R objects into Julia equivalents:
R object | Julia object | |
---|---|---|
named vector, list | DictoVec | DictoVec allows indexing both by element index and by its name, just as R vectors and lists |
vector | Vector{T} | T is the appropriate Julia type. If R vector contains NA values, they are converted to missing , and the elements type of the resulting Vector is Union{T, Missing} . |
factor | CategoricalArray | CategoricalArrays.jl |
Date | Dates.Date | |
POSIXct date time | ZonedDateTime | TimeZones.jl |
data frame | DataFrame | DataFrames.jl |
If conversion to the Julia type is not supported (e.g. R closure or language expression), load()
will return the internal RData representation of the object (RSEXPREC
subtype).