R package using Rcpp to parse an SPSS file into a data.frame().
Currently read.sav
and read.por
are the main functions and feature
of this package. Writing of SPSS files is provided by write.por
and
write.sav
. Writing is limited to uncompressed por and sav files and to
compressed sav file.
It works. Its read function is extensively tested on approximately 600+ sav-files and ~100 por-files. The code is maturing and is frequently tested. The read functions imports everything into a data frame. Including long strings and labels. Various features such as importing of value label or missings are tested and are working as intended.
The package features reading of
and (experimental) writing support of (un)compressed
Because of the R code wrapped Rcpp functions the package is pretty fast. The R code for factor conversion slows things down a bit, changing the encoding a bit more.
In comparison to haven
and foreign
this package preforms pretty
well. It reads more files than each of its predecessors, some are only
readable using readspss
and it covers a few more cases of missing
values.
Focus was not so much on winning every benchmark, but reading all
features of an SPSS file and to be as exactly as possible. So some
benchmarks are won and others are lost. It is entirely up to the task.
Besides the data itself readspss
ships additional information provided
by the SPSS files like the data label, documentation, date and
timestamp.
Reading of sav and por files is considered feature complete.
Writing of (un)compressed sav and por files is implemented and considered working. Unsupported features are reading and writing of dates (might no longer be true) and writing of long strings.
With remotes
:
remotes::install_github("JanMarvin/readspss")
Or from r-universe with:
options(repos = c(
janmarvin = 'https://janmarvin.r-universe.dev',
CRAN = 'https://cloud.r-project.org'))
install.packages('readspss')
fls <- system.file("extdata", "electric.sav", package = "readspss")
flp <- system.file("extdata", "electric.por", package = "readspss")
df_s <- read.sav(fls)
df_p <- read.por(flp)
all.equal(df_s, df_p, check.attributes = FALSE)
#> [1] TRUE