Identifying variables are those variables that describe the (qualitative)
properties that make each observation (as described by the
observed variables
) unique.
setIDVar(
schema = NULL,
name = NULL,
type = "character",
value = NULL,
columns = NULL,
rows = NULL,
split = NULL,
merge = NULL,
distinct = FALSE
)
[schema(1)
]
In case this information is added to an
already existing schema, provide that schema here (overwrites previous
information).
[character(1)
]
Name of the new identifying variable.
[character(1)
]
data type of the new identifying
variable. Possible values are "c/character"
, "i/integer"
,
"n/numeric"
, "l/logical"
, "D/Date"
or "_/skip"
.
For "D/Date"
, the value has to follow the form YYYY-MM-DD
,
where dates that don't match that are replaced by NA.
[character(1)
]
In case the variable is an implicit
variable (i.e., which is not in the origin table), specify it here.
[integerish(.)
]
The column(s) in which the
values of the new variable are recorded.
[integerish(.)
]
In case the variable is in several
columns, specify here additionally the row in which the names are
recorded.
[character(1)
]
In case the variable is part of a
compound value, this should be a regular expression that splits the
respective value off of that compound value. See
extract
on how to set up the regular expression.
[character(1)
]
In case a variable is made up of
several columns, this should be the character string that would connect the
two columns (e.g., an empty space " "
).
[logical(1)
]
whether or not the variable is
distinct from a cluster. This is the case when the variable is not
systematically available for all clusters and thus needs to be registered
separately from clusters.
An object of class schema
.
Please also take a look at the currently suggested strategy to set up a schema description.
Other functions to describe table arrangement:
setCluster()
,
setFilter()
,
setFormat()
,
setGroups()
,
setObsVar()
# please check the vignette for examples