R Language Read and write Stata, SPSS and SAS files


Example

The packages foreign and haven can be used to import and export files from a variety of other statistical packages like Stata, SPSS and SAS and related software. There is a read function for each of the supported data types to import the files.

# loading the packages
library(foreign)
library(haven)
library(readstata13)
library(Hmisc)

Some examples for the most common data types:

# reading Stata files with `foreign`
read.dta("path\to\your\data")
# reading Stata files with `haven`
read_dta("path\to\your\data")

The foreign package can read in stata (.dta) files for versions of Stata 7-12. According to the development page, the read.dta is more or less frozen and will not be updated for reading in versions 13+. For more recent versions of Stata, you can use either the readstata13 package or haven. For readstata13, the files are

# reading recent Stata (13+) files with `readstata13`
read.dta13("path\to\your\data")

For reading in SPSS and SAS files

# reading SPSS files with `foreign`
read.spss("path\to\your\data.sav", to.data.frame = TRUE)
# reading SPSS files with `haven`
read_spss("path\to\your\data.sav")
read_sav("path\to\your\data.sav")
read_por("path\to\your\data.por")

# reading SAS files with `foreign`
read.ssd("path\to\your\data")
# reading SAS files with `haven`
read_sas("path\to\your\data")
# reading native SAS files with `Hmisc`
sas.get("path\to\your\data")   #requires access to saslib 
# Reading SA XPORT format ( *.XPT ) files
sasxport.get("path\to\your\data.xpt")  # does not require access to SAS executable

The SAScii package provides functions that will accept SAS SET import code and construct a text file that can be processed with read.fwf. It has proved very robust for import of large public-released datasets. Support is at https://github.com/ajdamico/SAScii

To export data frames to other statistical packages you can use the write functions write.foreign(). This will write 2 files, one containing the data and one containing instructions the other package needs to read the data.

# writing to Stata, SPSS or SAS files with `foreign`
write.foreign(dataframe, datafile, codefile,
              package = c("SPSS", "Stata", "SAS"), ...)
write.foreign(dataframe, "path\to\data\file", "path\to\instruction\file", package = "Stata")

# writing to Stata files with `foreign`
write.dta(dataframe, "file", version = 7L,
          convert.dates = TRUE, tz = "GMT",
          convert.factors = c("labels", "string", "numeric", "codes"))

# writing to Stata files with `haven`
write_dta(dataframe, "path\to\your\data")

# writing to Stata files with `readstata13`
save.dta13(dataframe, file, data.label = NULL, time.stamp = TRUE,
  convert.factors = TRUE, convert.dates = TRUE, tz = "GMT",
  add.rownames = FALSE, compress = FALSE, version = 117,
  convert.underscore = FALSE)

# writing to SPSS files with `haven`
write_sav(dataframe, "path\to\your\data")

File stored by the SPSS can also be read with read.spss in this way:

 foreign::read.spss('data.sav', to.data.frame=TRUE, use.value.labels=FALSE, 
                     use.missings=TRUE, reencode='UTF-8')
# to.data.frame if TRUE: return a data frame
# use.value.labels if TRUE: convert variables with value labels into R factors with those levels
# use.missings if TRUE: information on user-defined missing values will used to set the corresponding values to NA.
# reencode character strings will be re-encoded to the current locale. The default, NA, means to do so in a UTF-8 locale, only.