R: Read and write SPSS files

read_spss {haven} | R Documentation

## Read and write SPSS files

### Description

`read_sav()` reads both `.sav` and `.zsav` files; `write_sav()` creates `.zsav` files when `compress = TRUE`. `read_por()` reads `.por` files. `read_spss()` uses either `read_por()` or `read_sav()` based on the file extension.

### Usage

    read_sav(
      file,
      encoding = NULL,
      user_na = FALSE,
      col_select = NULL,
      skip = 0,
      n_max = Inf,
      .name_repair = "unique"
    )

    read_por(
      file,
      user_na = FALSE,
      col_select = NULL,
      skip = 0,
      n_max = Inf,
      .name_repair = "unique"
    )

    write_sav(data, path, compress = FALSE)

    read_spss(
      file,
      user_na = FALSE,
      col_select = NULL,
      skip = 0,
      n_max = Inf,
      .name_repair = "unique"
    )

### Arguments

`file` | Either a path to a file, a connection, or literal data (either a single string or a raw vector). Files ending in `.gz`, `.bz2`, `.xz`, or `.zip` will be automatically uncompressed. Files starting with `http://`, `https://`, `ftp://`, or `ftps://` will be automatically downloaded. Remote gz files can also be automatically downloaded and decompressed. Literal data is most useful for examples and tests. It must contain at least one new line to be recognised as data (instead of a path) or be a vector of greater than length 1. Using a value of `clipboard()` will read from the system clipboard.
`encoding` | The character encoding used for the file. The default, `NULL`, use the encoding specified in the file, but sometimes this value is incorrect and it is useful to be able to override it.
`user_na` | If `TRUE` variables with user defined missing will be read into `labelled_spss()` objects. If `FALSE`, the default, user-defined missings will be converted to `NA`.
`col_select` | One or more selection expressions, like in `dplyr::select()`. Use `c()` or `list()` to use more than one expression. See `?dplyr::select` for details on available selection options. Only the specified columns will be read from `data_file`.
`skip` | Number of lines to skip before reading data.
`n_max` | Maximum number of lines to read.
`.name_repair` | Treatment of problematic column names: `"minimal"`: No name repair or checks, beyond basic existence, `"unique"`: Make sure names are unique and not empty, `"check_unique"`: (default value), no name repair, but check they are `unique`, `"universal"`: Make the names `unique` and syntactic a function: apply custom name repair (e.g., `.name_repair = make.names` for names in the style of base R). A purrr-style anonymous function, see `rlang::as_function()` This argument is passed on as `repair` to `vctrs::vec_as_names()`. See there for more details on these terms and the strategies used to enforce them.
`data` | Data frame to write.
`path` | Path to a file where the data will be written.
`compress` | If `TRUE`, will compress the file, resulting in a `.zsav` file. Otherwise the `.sav` file will be bytecode compressed.

### Details

Currently haven can read and write logical, integer, numeric, character and factors. See `labelled_spss()` for how labelled variables in SPSS are handled in R.

### Value

A tibble, data frame variant with nice defaults.

Variable labels are stored in the "label" attribute of each variable. It is not printed on the console, but the RStudio viewer will show it.

`write_sav()` returns the input `data` invisibly.

### Examples

    path <- system.file("examples", "iris.sav", package = "haven")
    read_sav(path)

    tmp <- tempfile(fileext = ".sav")
    write_sav(mtcars, tmp)
    read_sav(tmp)

[Package haven version 2.4.3 Index]