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.
From Julia REPL:
Pkg.add("RData")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')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".
Unless the convert=false 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 |
compact_xxxseq |
UnitRange/StepRange |
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).