Convert data files (CSV, R, other statistics packages) into .omv-files for the statistical spreadsheet 'jamovi' (https://www.jamovi.org)

convert_to_omv(
  fleInp = "",
  fleOut = "",
  varSrt = c(),
  usePkg = c("foreign", "haven"),
  selSet = "",
  ...
)

Arguments

fleInp: Name (including the path, if required) of the data file to be read ("FILENAME.ext"; default: ""); supports CSV and R-files natively, or other file types if "foreign" or "haven" are installed
fleOut: Name (including the path, if required) of the data file to be written ("FILENAME.omv"; default: ""); if empty, the extension of fleInp is replaced with ".omv"
varSrt: Variable(s) that are used to sort the data frame (see Details; if empty, the row order of the input file is kept; default: c())
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

The ellipsis-parameter (...) can be used to submit arguments / parameters to the functions that are used for reading the data. These are: read_omv (for jamovi-files), read.table (for CSV / TSV files), readRDS (for rds-files), read_sav (needs R-package "haven") or read.spss (needs 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. For reading CSV / TSV files, similar defaults as read.csv (CSV) and read.delim (TSV) are used; both are based upon read.table but with setting reasonable defaults for the respective file types. If you would like to use "haven", it may be needed to install it manually (i.e., install.packages("haven", dep = TRUE)).

Examples

if (FALSE) {
library(jmvReadWrite);

# Example 1: Convert from RDS
# (use ToothGrowth as example, save it as RDS)
nmeInp <- paste0(tempfile(), ".rds");
nmeOut <- paste0(tempfile(), ".omv");
saveRDS(jmvReadWrite::ToothGrowth, nmeInp);
convert_to_omv(fleInp = nmeInp, fleOut = nmeOut);
cat(list.files(dirname(nmeOut), basename(nmeOut)));
# -> "file[...].omv" ([...] contains a random combination of numbers / characters
cat(file.info(nmeOut)$size);
# -> 2448 (size may differ on different OSes)
cat(str(read_omv(nmeOut, sveAtt = FALSE)));
# gives a overview of the dataframe (all columns and some attributes,
# sveAtt is intentionally set to FALSE to make the output not too overwhelming)
unlink(nmeInp);
unlink(nmeOut);

# Example 2: Convert from CSV
# (use ToothGrowth again as example, this time save it as CSV)
nmeInp <- paste0(tempfile(), ".csv");
nmeOut <- paste0(tempfile(), ".omv");
write.csv(jmvReadWrite::ToothGrowth, nmeInp);
convert_to_omv(fleInp = nmeInp, fleOut = nmeOut);
cat(list.files(dirname(nmeOut), basename(nmeOut)));
cat(file.info(nmeOut)$size);
# -> 2104 (size may differ acc. to OS; the size is smaller than for the RDS-file
# because CSV can store fewer attributes, e.g., labels)
cat(str(read_omv(nmeOut, sveAtt = FALSE)));
# gives a overview of the dataframe (all columns and some attributes)
unlink(nmeInp);
unlink(nmeOut);
}