Import and Export 'SPSS', 'Stata' and 'SAS' Files

Import foreign statistical formats into R via the embedded 'ReadStat' C library, <>.

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Haven enables R to read and write various data formats used by other statistical packages by wrapping the fantastic ReadStat C library written by Evan Miller. Haven is part of the tidyverse. Currently it supports:

  • SAS: read_sas() reads .sas7bdat + .sas7bcat files and read_xpt() reads SAS transport files (version 5 and version 8).

  • SPSS: read_sav() reads .sav files and read_por() reads the older .por files. write_sav() writes .sav files.

  • Stata: read_dta() reads .dta files (up to version 15). write_dta() writes .dta files (versions 8-15).

The output objects:

  • Are tibbles, which have a better print method for very long and very wide files.

  • Translate value labels into a new labelled() class, which preserves the original semantics and can easily be coerced to factors with as_factor(). Special missing values are preserved. See vignette("semantics") for more details.

  • Dates and times are converted to R date/time classes. Character vectors are not converted to factors.


# The easiest way to get haven is to install the whole tidyverse:
# Alternatively, install just haven:
# Or the the development version from GitHub:
# install.packages("devtools")


write_sas(mtcars, "mtcars.sas7bdat")
write_sav(mtcars, "mtcars.sav")
# Stata
write_dta(mtcars, "mtcars.dta")


haven 2.1.0

Improved labelling

labelled objects get pretty printing that shows the labels and NA values when inside of a tbl_df. Turn this behaviour off with behavior using option(haven.show_pillar_labels = FALSE) (#340, @gergness).

labelled() and labelled_spss() now allow NULL labels. This makes both classes more flexible, allowing you to use them for their other attributes (#219).

labelled() tests that value labels are unique (@larmarange, #364)

Minor improvements and bug fixes

  • as_factor():

    • Is faster when input doesn't contain any missing values (@hughparsonage).
    • Added labelled method for backward compatbility (#414).
    • data.frame method now correctly passes ... along (#407, @zkamvar).
  • write_dta() now checks that the labelled values are integers, not the values themselves (#401).

  • Updated to latest ReadStat from @evanmiller:

    • read_por() can now read files from SPSS 25 (#412)
    • read_por() used base-10 instead of base-30 for the exponent (#413)
    • read_sas() can read zero column file (#420)
    • read_sav() reads long strings (#381)
    • read_sav() has greater memory limit allowing it to read more labels (#418)
    • read_spss() reads long variable labels (#422)
    • write_sav() creates incorrect column names when >10k columns (#410)
    • write_sav() no longer crashes when writing long label names (#395)

haven 2.0.0R


  • labelled() and labelled_spss() now produce objects with class "haven_labelled" and "haven_labelled_spss". Previously, the "labelled" class name clashed with the labelled class defined by Hmisc (#329).

    Unfortunately I couldn't come up with a way to fix this problem except to change the class name; it seems reasonable that haven should be the one to change names given that Hmisc has been around much longer. This will require some changes to packages that use haven, but shouldn't affect user code.

Minor improvements

  • labelled() and labelled_spss() now support adding the label attribute to the resulting object. The label is a short, human-readable description of the object, and is now also used when printing, and can be easily removed using the new zap_label() function. (#362, @huftis)

    Previously, the label attribute was supported both when reading and writing SPSS files, but it was not possible to actually create objects in R having the label attribute using the constructors labelled() or labelled_spss().

haven 1.1.2

  • haven can read and write non-ASCII paths in R 3.5 (#371).

  • labelled_spss objects preserve their attributes when subsetted (#360, @gergness).

  • read_sav() gains an encoding argument to override the encoding stored in the file (#305). read_sav() can now read .zsav files (#338).

  • write_*() functions now invisibly return the input data frame (as documented) (#349, @austensen).

  • write_dta() allows non-ASCII variable labels for version 14 and above (#383). It also uses a less strict check for integers so that a labelled double containing only integer values can written (#343).

  • write_sav() produces .zsav files when compress = TRUE (#338).

  • write_xpt() can now set the "member" name, which defaults to the file name san extension (#328).

  • Update to latest readstat.

    • Fixes out of memory error (#342)
    • Now supports reading and writing stata 15 files (#339)
    • Negative integer labelled values were tagged as missing (#367)
  • Fix for when as_factor() with option levels="labels" is used on tagged NAs (#340, @gergness)

haven 1.1.1

  • Update to latest readstat. Includes:

    • SPSS: empty charater columns now read as character (#311)
    • SPSS: now write long strings (#266)
    • Stata: reorder labelled vectors on write (#327)
    • State: encoding now affects value labels (#325)
    • SAS: can now write wide/long rows (#272, #335).
    • SAS: can now handle Windows Vietnamese character set (#336)
  • read_por() and read_xpt() now correctly preserve attributes if output needs to be reallocated (which is typical behaviour) (#313)

  • read_sas() recognises date/times format with trailing separator and width specifications (#324)

  • read_sas() gains a catalog_encoding argument so you can independently specify encoding of data and catalog (#312)

  • write_*() correctly measures lengths of non-ASCII labels (#258): this fixes the cryptic error "A provided string value was longer than the available storage size of the specified column."

  • write_dta() now checks for bad labels in all columns, not just the first (#326).

  • write_sav() no longer fails on empty factors or factors with an NA level (#301) and writes out more metadata for labelled_spss vectors (#334).

haven 1.1.0

  • Update to latest readstat. Includes:

    • SAS: support Win baltic code page (#231)
    • SAS: better error messages instead of crashes (#234, #270)
    • SAS: fix "unable to read error" (#271)
    • SPSS: support uppercase time stamps (#230)
    • SPSS: fixes for 252-255 byte strings (#226)
    • SPSS: fixes for 0 byte strings (#245)
  • Share as_factor() with forcats package (#256)

  • read_sav() once again correctly returns system defined missings as NA (rather than NaN) (#223). read_sav() and write_sav() preserve SPSS's display widths (@ecortens).

  • read_sas() gains experimental cols_only argument to only read in specified columns (#248).

  • tibbles are created with tibble::as_tibble(), rather than by "hand" (#229).

  • write_sav() checks that factors don't have levels with >120 characters (#262)

  • write_dta() no longer checks that all value labels are at most 32 characters (since this is not a restriction of dta files) (#239).

  • All write methds now check that you're trying to write a data frame (#287).

  • Add support for reading (read_xpt()) and writing (write_xpt()) SAS transport files.

  • write_* functions turn ordered factors into labelled vectors (#285)

haven 1.0.0

  • The ReadStat library is stored in a subdirectory of src (#209, @krlmlr).

  • Import tibble so that tibbles are printed consistently (#154, @krlmlr).

  • Update to latest ReadStat (#65). Includes:

    • Support for binary (aka Ross) compression for SAS (#31).
    • Support extended ASCII encoding for Stata (#71).
    • Support for Stata 14 files (#75, #212).
    • Support for SPSS value labels with more than 8 characters (#157).
    • More likely to get an error when attempting to create an invalid output file (#171).
  • Added support for reading and writing variable formats. Similarly to to variable labels, formats are stored as an attribute on the vector. Use zap_formats() if you want to remove these attributes. (@gorcha, #119, #123).

  • Added support for reading file "label" and "notes". These are not currently printed, but are stored in the attributes if you need to access them (#186).

  • Added support for "tagged" missing values (in Stata these are called "extended" and in SAS these are called "special") which carry an extra byte of information: a character label from "a" to "z". The downside of this change is that all integer columns are now converted to doubles, to support the encoding of the tag in the payload of a NaN.

  • New labelled_spss() is a subclass of labelled() that can model user missing values from SPSS. These can either be a set of distinct values, or for numeric vectors, a range. zap_labels() strips labels, and replaces user-defined missing values with NA. New zap_missing() just replaces user-defined missing vlaues with NA.

    labelled_spss() is potentially dangerous to work with in R because base functions don't know about labelled_spss() functions so will return the wrong result in the presence of user-defined missing values. For this reason, they will only be created by read_spss() when user_na = TRUE (normally user-defined missings are converted to NA).

  • as_factor() no longer drops the label attribute (variable label) when used (#177, @itsdalmo).

  • Using as_factor() with levels = "default or levels = "both" preserves unused labels (implicit missing) when converting (#172, @itsdalmo). Labels (and the resulting factor levels) are always sorted by values.

  • as_factor() gains a new levels = "default" mechanism. This uses the labels where present, and otherwise uses the labels. This is now the default, as it seems to map better to the semantics of labelled values in other statistical packages (#81). You can also use levels = "both" to combine the value and the label into a single string (#82). It also gains a method for data frames, so you can easily convert every labelled column to a factor in one function call.

  • New vignette("semantics", package = "haven") discusses the semantics of missing values and labelling in SAS, SPSS, and Stata, and how they are translated into R.

  • Support for hms() has been moved into the hms package (#162). Time varibles now have class c("hms", "difftime") and a units attribute with value "secs" (#162).

  • labelled() is less strict with its checks: you can mix double and integer value and labels (#86, #110, @lionel-), and is.labelled() is now exported (#124). Putting a labelled vector in a data frame now generates the correct column name (#193).

  • read_dta() now recognises "%d" and custom date types (#80, #130). It also gains an encoding parameter which you can use to override the default encoding. This is particularly useful for Stata 13 and below which did not store the encoding used in the file (#163).

  • read_por() now actually works (#35).

  • read_sav() now correctly recognises EDATE and JDATE formats as dates (#72). Variables with format DATE, ADATE, EDATE, JDATE or SDATE are imported as Date variables instead of POSIXct. You can now set user_na = TRUE to preserve user defined missing values: they will be given class labelled_spss.

  • read_dta(), read_sas(), and read_sav() have a better test for missing string values (#79). They can all read from connections and compressed files (@lionel-, #109)

  • read_sas() gains an encoding parameter to overide the encoding stored in the file if it is incorrect (#176). It gets better argument names (#214).

  • Added type_sum() method for labelled objects so they print nicely in tibbles.

  • write_dta() now verifies that variable names are valid Stata variables (#132), and throws an error if you attempt to save a labelled vector that is not an integer (#144). You can choose which version of Stata's file format to output (#217).

  • New write_sas() allows you to write data frames out to sas7bdat files. This is still somewhat experimental.

  • write_sav() writes hms variables to SPSS time variables, and the "measure" type is set for each variable (#133).

  • write_dta() and write_sav() support writing date and date/times (#25, #139, #145). Labelled values are always converted to UTF-8 before being written out (#87). Infinite values are now converted to missing values since SPSS and Stata don't support them (#149). Both use a better test for missing values (#70).

  • zap_labels() has been completely overhauled. It now works (@markriseley, #69), and only drops label attributes; it no longer replaces labelled values with NAs. It also gains a data frame method that zaps the labels from every column.

  • print.labelled() and print.labelled_spss() now display the type.

haven 0.2.0

  • fixed a bug in as_factor.labelled, which generated 's and wrong labels for integer labels.

  • zap_labels() now leaves unlabelled vectors unchanged, making it easier to apply to all columns.

  • write_dta() and write_sav() take more care to always write output as UTF-8 (#36)

  • write_dta() and write_sav() won't crash if you give them invalid paths, and you can now use ~ to refer to your home directory (#37).

  • Byte variables are now correctly read into integers (not strings, #45), and missing values are captured correctly (#43).

  • Added read_stata() as alias to read_dta() (#52).

  • read_spss() uses extension to automatically choose between read_sav() and read_por() (#53)

  • Updates from ReadStat. Including fixes for various parsing bugs, more encodings, and better support for large files.

  • hms objects deal better with missings when printing.

  • Fixed bug causing labels for numeric variables to be read in as integers and associated error: Error: `x` and `labels` must be same type

haven 0.1.1

  • Fixed memory initialisation problems found by valgrind.

Reference manual

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2.4.3 by Hadley Wickham, 3 months ago,,

Report a bug at

Browse source code at

Authors: Hadley Wickham [aut, cre] , Evan Miller [aut, cph] (Author of included ReadStat code) , RStudio [cph, fnd]

Documentation:   PDF Manual  

Task views: Official Statistics & Survey Methodology, Official Statistics & Survey Statistics

MIT + file LICENSE license

Imports forcats, hms, methods, readr, rlang, tibble, tidyselect, vctrs

Suggests cli, covr, crayon, fs, knitr, pillar, rmarkdown, testthat

Linking to cpp11

System requirements: GNU make, C++11, zlib

Imported by BEACH, DAMisc, DDIwR, DHS.rates, Dire, EdSurvey, ImportExport, LearningStats, RVA, RcmdrMisc, Rilostat, adepro, asciiSetupReader, aweSOM, bpnreg, casen, clinDataReview, clinUtils, codebook, crosswalkr, cspp, dataMaid, datadigest, describedata, duawranglr, eatGADS, ech, elaborator, electionsBR, essurvey, ezpickr, ggplotgui, hildareadR, iNZightTools, importinegi, ipumsr, jsmodule, labelled, libr, memapp, misty, mitml, netCoin, packDAMipd, rdhs, readit, recodeflow, retroharmonize, rio, ropercenter, sdcMicro, secuTrialR, skewlmm, tidyverse, uwo4419, vtable, webuse, xSub.

Depended on by cchsflow.

Suggested by AdhereRViz, Tplyr, compareGroups, crunch, dataverse, did2s, didimputation, egor, frequency, ggeffects, ivdesc, ivdoctr, lessR, manifestoR, marginaleffects, mark, mice, msSPChelpR, opencpu, preregr, resourcer, rock, sampleVADIR, sdmApp, simPop, sjlabelled, sjmisc, suddengains, syntaxr, tablet, troopdata, xplorerr.

Enhanced by memisc, optmatch.

See at CRAN