There is a lengthy discussion on GitHub describing some of the challenges when exporting data from R for use in SAS via haven
. In addition to providing a solution on how to automate data transfer from R to SAS, I hope this can serve as an answer to some related questions.
If one wants to use tools designed by SAS for interoperability with R, RSWAT
on GitHub is likely a more robust option. However, this will assume that you have access to SAS Cloud Analytics Services configured for this purpose.
If you are working with a SAS 9.4 on your machine and perhaps also connect to SAS servers (i.e. using rsubmit;
commands), it should be relatively straightforward to pass a data-set directly from R into a SAS library. There are three steps:
- Format dataset for SAS; although
foreign
will do a lot of the formatting changes, I prefer converting factors back to characters and having NA
replaced with ""
. This I find ensures that no special formatting is needed by colleagues to open the final table in SAS.
# Example data
data <- data.frame(ID = c(123, NA, 125),
disease = factor(c('syphilis', 'gonorrhea', NA)),
AdmitDate = as.Date(c("2014-04-05", NA, "2016-02-03")),
DOB = as.Date(c("1990-01-01", NA, NA)))
# Function defined for converting factors and blanks
convert_format_r2sas <- function(data){
data <- data %>%
dplyr::mutate_if(is.factor, as.character) %>%
dplyr::mutate_if(is.character, tidyr::replace_na, replace = "")
return(data)
}
# Convert some formatting
data <- convert_format_r2sas(data)
- Use
foreign
to export the data and associated code
library(foreign)
# Ensure the data and code files are saved in an easily accessible location (ideally in or downstream of your R project directory)
write.foreign(df = data ,
datafile = 'data.txt',
codefile = 'data.sas',
dataname = 'libraryname.tablename', # Destination in SAS to save the data
package = 'SAS')
- Pass code to local SAS installation using custom function. You may need to adjust the location of the SAS.exe as well as the configuration file. This will work both passing a list of SAS files, or SAS code written directly in R as a character vector.
# Define function for passing the code to SAS and upload data (may require tweaking the local SAS installation location and configuration file)
pass_code_to_sas <- function(sas_file_list = NULL, inputstring = NULL,
sas_path = "C:/LocationTo/SASHome/SASFoundation/9.4/sas.exe",
configFile = "C:/LocationTo/SASHome/SASFoundation/9.4/SASV9.CFG") {
# If provided list of scripts, check they are all valid
if(!is.null(sas_file_list)){
if(any(purrr::map_lgl(sas_file_list, file.exists)) == FALSE | is.list(sas_file_list) == F){
stop("You entered an invalid file location or did not provide the locations as a list of characters")
}
}
sink(file.path(R.home(), "temp_codePass.sas"))
if(!is.null(sas_file_list)){
for(i in 1:length(sas_file_list)){
cat(readLines(sas_file_list[[i]]), sep = "\n")
}
}
cat(inputstring)
sink()
# Output message to view what code was sent...
message(paste0("The above info was passed to SAS: ",
if(!is.null(sas_file_list)){for(i in 1:length(sas_file_list)){cat(readLines(sas_file_list[[i]]), sep = "\n")}},
print(inputstring)))
# Run SAS
system2(sas_path,
args = paste0(
"\"", file.path(R.home(), "temp_codePass.sas"), "\"",
if(!is.null(configFile)) { paste0(" -config \"", configFile, "\"")}
)
)
# Delete the SAS file
file.remove(file.path(R.home(), "temp_codePass.sas"))
}
# Pass data to SAS
pass_code_to_sas(sas_file_list = 'path2codefile/data.sas')