Create a meta data frame and map names.
Generally, this function only creates a data.frame, but using
this constructor instead of calling
data.frame(..., stringsAsFactors = FALSE), it becomes possible, to adapt
the metadata data.frame in later developments, e.g. if we decide to use
classes for the metadata, or if certain standard names of variable attributes
change. Also, a validity check is possible to implement here.
prep_create_meta(..., stringsAsFactors = FALSE, level, character.only = FALSE)named column vectors, names will be mapped using WELL_KNOWN_META_VARIABLE_NAMES, if included in WELL_KNOWN_META_VARIABLE_NAMES can also be a data frame, then its column names will be mapped using WELL_KNOWN_META_VARIABLE_NAMES
logical if the argument is a list of vectors, a
data frame will be
created. In this case, stringsAsFactors controls,
whether characters will be auto-converted to Factors,
which defaults here always to false independent from
the default.stringsAsFactors.
enum level of requirement (see also VARATT_REQUIRE_LEVELS)
set to NULL, if not a complete metadata frame is
created.
logical a logical indicating whether level can be assumed to be character strings.
a data frame with:
meta data attribute names mapped and
meta data checked using prep_check_meta_names and do some more verification about conventions, such as check for valid intervals in limits)
For now, this calls data.frame, but it already renames variable attributes,
if they have a different name assigned in WELL_KNOWN_META_VARIABLE_NAMES,
e.g. WELL_KNOWN_META_VARIABLE_NAMES$RECODE maps to recode in lower case.
NB: dataquieR exports all names from WELL_KNOWN_META_VARIABLE_NAME as
symbols, so RECODE also contains "recode".