SAS to R - if you don't have a SAS license
while I move data between SAS and R all the time, personally I don't think your recommendation is very practical. Instead, I feel SAS transport file is much better than csv. Plus, the sas dataset created on unix can't be opened by sas viewer on windows. It is even undoable if the dataset is large. Just my $0.02.
On Dec 27, 2007 6:33 PM, Gyula Gulyas <gygulyas at yahoo.ca> wrote:
Hi all, if you do not have a SAS license but want to convert native SAS data files, the solution below will work. # read SAS data without SAS # 1. Download free SAS System Viewer from either of the sites below: # http://www.sas.com/apps/demosdownloads/setupcat.jsp?cat=SAS+System+Viewer (requires registration) # http://www.umass.edu/statdata/software/downloads/SASViewer/index.html # 2. Open SAS data in the SAS System Viewer # 3. View-Formatted sets the data in formatted view # 4. Save As File...csv file - this is your SAS data file # 5. View-Variables (now showing the variable names and formats) # 6. Save As File...csv file - this is your SAS variable definition file # run code below wrkdir<-getwd() # save working directory to reset later # Select the SAS data file... sas.data<-read.table(file.choose(),header=T, sep=",", na.strings=".") # Select SAS variable definition file... sas.def<-read.csv(file.choose()) # str(sas.def) # sas.def$SASFORMAT[sas.def$Type=="Char"]<-"character" # sas.def$SASFORMAT[sas.def$Type=="Num"]<-"numeric" sas.def$SASFORMAT[substr(sas.def$Format,1,4)=="DATE"]<-"date" sas.def<-sas.def[,length(names(sas.def))] # pick last column tmp<-which(sas.def=="date") sas.data[,tmp] <- as.data.frame(strptime(sas.data[,tmp], "%d%b%Y:%H:%M:%S")) str(sas.data) print(head(sas.data)) setwd(wrkdir) # reset working directory rm(wrkdir,tmp,sas.def) # the end
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=============================== WenSui Liu Statistical Project Manager ChoicePoint Precision Marketing (http://spaces.msn.com/statcompute/blog)