Function change_cellstatus() allows to change|modify the anonymization state
of single table cells for objects of class sdcProblem.
change_cellstatus(object, specs, rule, verbose = FALSE, ...)an object of class sdcProblem
input that defines which cells to query; the function expects either (see examples below)
a named character vector: with names referring to the names of the dimensional variables and the values to its labels. In this case each vector-element must contain a single value (label)
a data.frame where the column-names refer to the names of the dimensional
variables and the values to the labels
scalar character vector specifying a valid anonymization code ('u', 'z', 'x', 's') to which all the desired cells under consideration should be set.
scalar logical value defining verbosity, defaults to FALSE
additional parameters for potential future use, currently unused.
a sdcProblem object
# load example-problem
# (same as example from ?makeProblem)
p <- sdc_testproblem(with_supps = FALSE)
# goal: set cells with region = "D" and gender != "total" as primary sensitive
# using a data.frame as input
specs <- data.frame(
region = "D",
gender = c("male", "female", "total")
)
# marking the cells as sensitive
p <- change_cellstatus(
object = p,
specs = specs,
rule = "u"
)
# check
cell_info(p, specs = specs)
#> id strID region gender freq val sdcStatus is_primsupp is_secondsupp
#> 1: 14 0401 D male 11 366 u TRUE FALSE
#> 2: 15 0402 D female 14 152 u TRUE FALSE
#> 3: 13 0400 D total 25 518 u TRUE FALSE
# using a named vector for a single cell to revert
# setting D/total as primary-sensitive
specs <- c(gender = "total", region = "D")
p <- change_cellstatus(
object = p,
specs = specs,
rule = "s"
)
# and check again
cell_info(p, specs = specs)
#> id strID region gender freq val sdcStatus is_primsupp is_secondsupp
#> 1: 13 0400 D total 25 518 s FALSE FALSE