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Documentation
jl() methods vs jl environment
jl() methods
jl() method for executing julia code
jl() method as conversion from R to julia
jl environment
When installing the jl4R package, the jl variable is automatically created
in the global environment.
jl environment
jl$a <- c(1,3,2) length(jl$a) names(jl) jl$a[2] jl$a jl$b <- data.frame(aa=1:4,bb=TRUE,cc=c("toto","titi","toto","titi"),stringsAsFactors=TRUE) jl$b names(jl$b) jl$b$cc jlcall("levels",jl$b$cc) jl[[levels]](jl$b$cc) jl[[levels]](`b[!,:cc]`) class(jl$b$cc) levels(jl$b$cc) names(jl)
R> jl$a <- c(1,3,2) R> length(jl$a) [1] 3 R> names(jl) [1] "Dyndoc" "Ruby" "a" "b" R> jl$a[2] 3.0 R> jl$a 3-element Vector{Float64}: 1.0 3.0 2.0 R> jl$b <- data.frame(aa=1:4,bb=TRUE,cc=c("toto","titi","toto","titi"),stringsAsFactors=TRUE) R> jl$b 4×3 DataFrame Row │ aa bb cc │ Int64 Bool Cat… ─────┼─────────────────── 1 │ 1 true toto 2 │ 2 true titi 3 │ 3 true toto 4 │ 4 true titi R> names(jl$b) [1] "aa" "bb" "cc" R> jl$b$cc 4-element CategoricalArray{String,1,UInt32}: "toto" "titi" "toto" "titi" R> jlcall("levels",jl$b$cc) 2-element Vector{String}: "titi" "toto" R> jl[[levels]](jl$b$cc) 2-element Vector{String}: "titi" "toto" R> jl[[levels]](`b[!,:cc]`) 2-element Vector{String}: "titi" "toto" R> class(jl$b$cc) [1] "CategoricalArray" "jlvalue" R> levels(jl$b$cc) 2-element Vector{String}: "titi" "toto" R> names(jl) [1] "Dyndoc" "Ruby" "a" "b"