| valids_test {quest} | R Documentation |
Test for Invalid Elements in Data
Description
Valid.test tests whether data has any invalid elements. Valid values
are specified by valid. Each variable is tested independently. If the
variable in data[vrb.nm] has any values other than valid, then
FALSE is returned for that variable; If the variable in data[vrb.nm]
only has values in valid, then TRUE is returned for that variable.
Usage
valids_test(data, vrb.nm, valid, na.rm = TRUE)
Arguments
data |
data.frame of data. |
vrb.nm |
character vector of colnames from |
valid |
atomic vector or list vector of valid values. |
na.rm |
logical vector of length 1 specifying whether NA should be ignored from the validity test. If TRUE (default), then any NAs are treated as valid. |
Value
logical vector with length = length(vrb.nm) and names =
vrb.nm specifying whether all elements in each variable of
data[vrb.nm] are valid. If FALSE, then (at least one) invalid values
are present in that variable of data[vrb.nm].
See Also
Examples
valids_test(data = psych::bfi, vrb.nm = names(psych::bfi)[1:25],
valid = 1:6) # return TRUE
valids_test(data = psych::bfi, vrb.nm = names(psych::bfi)[1:25],
valid = 0:5) # 6 is not present in `valid`
valids_test(data = psych::bfi, vrb.nm = names(psych::bfi)[1:25],
valid = 1:6, na.rm = FALSE) # NA is not present in `valid`
valids_test(data = ToothGrowth, vrb.nm = c("supp","dose"),
valid = list("VC", "OJ", 0.5, 1.0, 2.0)) # list vector as `valid` to allow for
# elements of different typeof