Package to read and write all Stata file formats (version 14 and older) into a R data.frame. The dta file format versions 102 to 118 are supported.

The function read.dta from the foreign package imports only dta files from Stata versions <= 12. Due to the different structure and features of dta 117 files, we wrote a new file reader in Rcpp.

Additionally the package supports many features of the Stata dta format like label sets in different languages (?set.lang) or business calendars (?as.caldays).

The package is now hosted on CRAN.

install.packages("readstata13")

library(readstata13)
dat <- read.dta13("path to file.dta")
save.dta13(dat, file="newfile.dta")

To install the current release from github you need the plattform specific build tools. On Windows a current installation of Rtools is necessary, while OS X users need to install Xcode.

# install.packages("devtools")
devtools::install_github("sjewo/readstata13", ref="0.8.5")

Older Versions of devtools require a username option:

install_github("readstata13", username="sjewo", ref="0.8.5")

To install the current development version from github:

devtools::install_github("sjewo/readstata13", ref="testing")

• [0.8.5] fix errors on big-endians systems
• [0.8.4] fix valgrind errors. converting from dta.write to writestr
• [0.8.4] fix for empty data label
• [0.8.4] make replace.strl default
• [0.8.3] restrict length of varnames to 32 chars for compatibility with Stata 14
• [0.8.3] add many function tests
• [0.8.3] avoid converting of double to floats while writing compressed files
• [0.8.2] save NA values in character vector as empty string
• [0.8.2] convert.underscore=T will convert all non-literal characters to underscores
• [0.8.2] fix saving of Dates
• [0.8.2] save with convert.factors by default
• [0.8.2] test for NaN and inf values while writing missing values and replace with NA
• [0.8.2] remove message about saving factors
• [0.8.1] convert non-integer variables to factors (nonint.factors=T)
• [0.8.1] handle large datasets
• [0.8.1] working with strL variables is now a lot faster
• reading data files from disk or url and create a data.frame
• saving dta files to disk - most features of the dta file format are supported
• assign variable names
• read the new strL strings and save them as attribute
• convert stata label to factors and save them as attribute
• read some meta data (timestamp, dataset label, formats,...)
• convert strings to system encoding
• handle different NA values
• handle multiple label languages
• convert dates
• reading business calendar files

• cleanup of Rcpp code

Since our attributes differ from foreign::read.dta all.equal and identical report false. If you check the values, everything is identical.

library("foreign")
r12 <- read.dta("http://www.stata-press.com/data/r12/auto.dta")
r13 <- read.dta13("http://www.stata-press.com/data/r13/auto.dta")

Map(identical,r12,r13)

att <- names(attributes(r12))
for (i in seq(att))
	cat(att[i],":", all.equal(attr(r12,att[i]),attr(r13,att[i])),"\n")

r12 <- read.dta("http://www.stata-press.com/data/r12/auto.dta",convert.factors=F)
r13 <- read.dta13("http://www.stata-press.com/data/r13/auto.dta",convert.factors=F)

Map(identical,r12,r13)

Marvin Garbuszus (JanMarvin) and Sebastian Jeworutzki (both Ruhr-Universität Bochum)

GPL2