RCall.jl is a real breakthrough for trying to put together Julia and R work, thanks for the pointer! Here is my example code: https://gist.github.com/multidis/7ac6f4779e09c986be39
The main advantage is that column types are converted properly (in particular Bool), and a native R object is saved in RData-file. Performance-wise I have not tested with large objects yet, so any advice on code improvement is appreciated. On Thursday, January 22, 2015 at 6:40:35 PM UTC-8, tshort wrote: > > I don't know if it can do it yet, but the RCall package might be able to > save data back to an RData file. It's a young package. > > Also, you could use CSV files. > > On Thu, Jan 22, 2015 at 2:09 PM, Pavel <[email protected] <javascript:> > > wrote: > >> While reading R datasets in Julia received sufficient attention already, >> sometimes the results of computations done in Julia need to be readable to >> R. To accomplish that I was trying to save a DataFrame.jl >> <https://github.com/JuliaStats/DataFrames.jl> object in HDF5 file. The >> code so far is in my StackOverflow question (probably should have posted >> here instead): >> >> http://stackoverflow.com/questions/28084403/saving-julia-dataframe-to-read-in-r-using-hdf5 >> >> The dataframe can then be reassembled in R using rhdf5 >> <http://www.bioconductor.org/packages/release/bioc/html/rhdf5.html> package >> tools. It works in principle, but is there a more elegant way to accomplish >> this? Something that does not require to split the dataframe apart and >> re-assemble in R, losing some column types (e.g. boolean does not work) >> along the way? >> > >
