jmvReadWrite (version 0.4.10)

label_vars_omv: Label columns / variables in .omv-files for the statistical spreadsheet 'jamovi' (https://www.jamovi.org)

Description

Label columns / variables in .omv-files for the statistical spreadsheet 'jamovi' (https://www.jamovi.org)

Usage

label_vars_omv(
  dtaInp = NULL,
  fleOut = "",
  varLbl = NULL,
  psvAnl = FALSE,
  usePkg = c("foreign", "haven"),
  selSet = "",
  ...
)

Value

a data frame (only returned if fleOut is empty) where the order of variables / columns of the input data set is re-arranged

Arguments

dtaInp

Either a data frame or the name of a data file to be read (including the path, if required; "FILENAME.ext"; default: NULL); files can be of any supported file type, see Details below

fleOut

Name of the data file to be written (including the path, if required; "FILE_OUT.omv"; default: ""); if empty, the resulting data frame is returned instead

varLbl

Variable (default: NULL) containing either a character (a file name; the file must contain two columns one with variable names, the other with the labels), a data frame (one column the variable names, the other the labels), or a character vector (with the same length as the data set, containing the variable labels). See Details for more information.

psvAnl

Whether analyses that are contained in the input file shall be transferred to the output file (default: FALSE)

usePkg

Name of the package: "foreign" or "haven" that shall be used to read SPSS, Stata and SAS files; "foreign" is the default (it comes with base R), but "haven" is newer and more comprehensive

selSet

Name of the data set that is to be selected from the workspace (only applies when reading .RData-files)

...

Additional arguments passed on to methods; see Details below

Details

• varLbl can be either (1) a character with a file name to read (the file must contain to columns, one with the variable names, the other with the variable labels); (2) a data frame with two columns (one with the variable names, the other with the variable labels), or (3) a character vector containing the variable labels (with a length equal to the number of variables in the input data set).

• The ellipsis-parameter (...) can be used to submit arguments / parameters to the functions that are used for reading and writing the data. By clicking on the respective function under “See also”, you can get a more detailed overview over which parameters each of those functions take. The functions are: read_omv and write_omv (for jamovi-files), read.table (for CSV / TSV files; using similar defaults as read.csv for CSV and read.delim for TSV which both are based upon read.table), load (for .RData-files), readRDS (for .rds-files), read_sav (needs the R-package haven) or read.spss (needs the R-package foreign) for SPSS-files, read_dta (haven) / read.dta (foreign) for Stata-files, read_sas (haven) for SAS-data-files, and read_xpt (haven) / read.xport (foreign) for SAS-transport-files. If you would like to use haven, you may need to install it using install.packages("haven", dep = TRUE).

See Also

label_vars_omv internally uses the following functions for reading and writing data files in different formats: read_omv() and write_omv() for jamovi-files, utils::read.table() for CSV / TSV files, load() for reading .RData-files, readRDS() for .rds-files, haven::read_sav() or foreign::read.spss() for SPSS-files, haven::read_dta() or foreign::read.dta() for Stata-files, haven::read_sas() for SAS-data-files, and haven::read_xpt() or foreign::read.xport() for SAS-transport-files.

Examples

if (FALSE) {
# use one of the data files included in the package, but only the first 28 columns
# (the latter columns contain data for testing calculations, etc.)
nmeInp <- system.file("extdata", "bfi_sample.omv", package = "jmvReadWrite")
dtaInp <- jmvReadWrite::read_omv(nmeInp)[1:28]
nmeOut <- tempfile(fileext = ".omv")
# in the original file, the variable labels – attr(*, "jmv-desc") - are empty
lapply(dtaInp, attr, "jmv-desc")
# the definition of the variable labels can be read from a file with two columns,
# the first containing the variable name, the second the variable labels
# you can easily create such a file in Excel and save it as CSV
# if your CSV contains column names (e.g., varNme and varLbl) in the first row are they ignored
lblFle <- system.file("extdata", "label_example.csv", package = "jmvReadWrite")
lblDtF <- utils::read.csv(lblFle, header = FALSE)
str(lblDtF)

# there are three options to give the varLbl parameter:
# (1) as file name, ...
jmvReadWrite::label_vars_omv(dtaInp = dtaInp, fleOut = nmeOut, varLbl = lblFle)
lapply(jmvReadWrite::read_omv(nmeOut), attr, "jmv-desc")
unlink(nmeOut)

# (2) as data frame (using lblDtF from above), or ...
jmvReadWrite::label_vars_omv(dtaInp = dtaInp, fleOut = nmeOut, varLbl = lblDtF)
lapply(jmvReadWrite::read_omv(nmeOut), attr, "jmv-desc")
unlink(nmeOut)

# (3) as character vector (with the same length as there are columns in the input data set)
lblChr <- lblDtF[[2]]
head(lblChr)
jmvReadWrite::label_vars_omv(dtaInp = dtaInp, fleOut = nmeOut, varLbl = lblChr)
lapply(jmvReadWrite::read_omv(nmeOut), attr, "jmv-desc")
unlink(nmeOut)
}