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Export Data to SPSS Format

Source: R/write_spss.R
write_spss.Rd

Writes a data frame to an SPSS .sav file, preserving variable labels, value labels, and user-defined missing values. When exporting data that was imported with read_spss() (with tag.na = TRUE), the tagged NAs are automatically converted back to SPSS user-defined missing values, enabling full roundtrip fidelity.

Usage

write_spss(data, path, compress = c("byte", "none", "zsav"))

Arguments

data

A data frame to export. Columns of class haven_labelled will have their labels and missing value metadata written to the .sav file.

path

Path to the output file. Must end in .sav or .zsav.

compress

Compression type. One of "byte" (default, byte-level compression), "none" (no compression), or "zsav" (zlib compression, requires SPSS v21+).

Value

Invisibly returns the file path.

Details

Tagged NA Roundtripping

Data imported via read_spss() stores SPSS user-defined missing values as tagged NAs with an na_tag_map attribute mapping tag characters to original codes (e.g., -9, -8). write_spss() reverses this process: tagged NAs are converted back to their original numeric codes, and the SPSS user-defined missing value specification is reconstructed so that the exported .sav file has the same missing value definitions as the original.

Cross-Format Export

When exporting data originally imported from Stata or SAS (with native extended missing values like .a-.z or .A-.Z), these cannot be represented as SPSS user-defined missing values. In this case, they are written as system missing (regular NA) with a warning.

When to Use This

Use write_spss() when you:

  • Need to export processed survey data back to SPSS format

  • Want to preserve user-defined missing value definitions

  • Need roundtrip fidelity: read_spss() -> processing -> write_spss()

See also

read_spss() for importing SPSS files, write_xlsx() for Excel export, write_stata() for Stata export, write_xpt() for SAS transport export, untag_na(), strip_tags()

Other data-export: write_stata(), write_xlsx(), write_xpt()

Examples

if (FALSE) { # \dontrun{
# Roundtrip: read SPSS, process, write back
data <- read_spss("survey.sav")
data_clean <- data[data$age >= 18, ]
write_spss(data_clean, "survey_adults.sav")

# Export with zlib compression (smaller file, requires SPSS v21+)
write_spss(data, "survey_compressed.zsav", compress = "zsav")
} # }