This should do the trick - disclaimer the file is 1.4Gb so everything takes a veerryyy long time on my MacBook air, and you will need an active internet connection for InstallR
to work. Note you have to escape \
internal R file paths and anything else that uses a double quote.
Firstly download the rdata version of the file from the link given.
Needs["RLink`"];
InstallR[];
REvaluate[
"load(\"~/Downloads/WVS_Longitudinal_1981_2014_R_v2015_04_18.rdata\"\)"];
(*{".Traceback","WVS_Longitudinal_1981_2014_R_v2015_04_18"}*)
Writes the data into an R Dataset called WVS_Longitudinal_1981_2014_R_v2015_04_18
REvaluate["write.csv(WVS_Longitudinal_1981_2014_R_v2015_04_18,file=\
"WVS_data_rlink.csv\")"];
Writes the data back out to a CSV. Note in this case the file is a simple tabular one. This might be more problematic for some of the more complex data structures that .rdata format permits.
Theoreticall you can actually import the WVS_Longitudinal_1981_2014_R_v2015_04_18 data directly into MMA and work with it natively from that point but requires me working through the rLink tutorial a bit more than I have time for right now. :)
EDIT : Some useful tips to explore the data directly.
Get Column Names
REvaluate["names(WVS_Longitudinal_1981_2014_R_v2015_04_18)"] // Short
Get a single column in this case S001
REvaluate["WVS_Longitudinal_1981_2014_R_v2015_04_18$S001"]
Get the first 10 lines of the R data.frame note the R data objects in there. head
is like the unix head not Head[]
This data is so wide and deep its hard to get it in a readable format without subsetting and slicing and dicing.
REvaluate["head(WVS_Longitudinal_1981_2014_R_v2015_04_18,n=10)"]