jmvReadWrite (version 0.4.10)

transpose_omv: Transpose .omv-files for the statistical spreadsheet 'jamovi' (https://www.jamovi.org)

Description

Transpose .omv-files for the statistical spreadsheet 'jamovi' (https://www.jamovi.org)

Usage

transpose_omv(
  dtaInp = NULL,
  fleOut = "",
  varNme = "",
  usePkg = c("foreign", "haven"),
  selSet = "",
  ...
)

Value

a data frame (only returned if fleOut is empty) where the input data set is transposed

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

varNme

Name of the variables in the output data frame; see Details below

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

• If varNme empty, the row names of the input data set are used (preceded by "V_" if all row names are numbers); if varNme has length 1, then it is supposed to point to a variable in the input data frame; if varNme has the same length as the number of rows in the input data frame, then the values in varNme are assigned as column names to the output data frame.

• 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

transpose_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) {
set.seed(1)
tmpDF <- stats::setNames(as.data.frame(matrix(sample(6, 1200, replace = TRUE), nrow = 16)),
                         sprintf("sbj_%03d", seq(75)))
str(tmpDF)
# Data sets that were extracted, e.g., from PsychoPy, may look like this (trials as rows
# and participants as columns, one for each participant, manually assembled / copy-and-pasted).
# However, for analyses, one wants the data set transposed (units / participants as columns)...
nmeOut <- tempfile(fileext = ".omv")
jmvReadWrite::transpose_omv(dtaInp = tmpDF, fleOut = nmeOut)
dtaFrm <- jmvReadWrite::read_omv(nmeOut)
unlink(nmeOut)
str(dtaFrm)
# if no varNme-parameter is given, generic variable names are created (V_...)
jmvReadWrite::transpose_omv(dtaInp = tmpDF, fleOut = nmeOut, varNme = sprintf("Trl_%02d", seq(16)))
dtaFrm <- jmvReadWrite::read_omv(nmeOut)
unlink(nmeOut)
str(dtaFrm)
# alternatively, the character vector with the desired variable names (of the same length as
# the number of rows in tmpDF) may be given, "Trl" can easily be exchanged by the name of your
# questionnaire, experimental conditions, etc.
}