Elements in a set not present in the other set. Equivalent to
setdiff().
Usage
subtract(object, set_in, not_in, ...)
# S4 method for class 'TidySet,characterORfactor,characterORfactor'
subtract(
object,
set_in,
not_in,
name = NULL,
keep = TRUE,
keep_relations = keep,
keep_elements = keep,
keep_sets = keep
)Arguments
- object
A TidySet object.
- set_in
Name of the sets where the elements should be present.
- not_in
Name of the sets where the elements should not be present.
- ...
Placeholder for other arguments that could be passed to the method. Currently not used.
- name
Name of the new set. By default it adds a "C".
- keep
Logical value to keep all the other sets.
- keep_relations
A logical value if you wan to keep old relations.
- keep_elements
A logical value if you wan to keep old elements.
- keep_sets
A logical value if you wan to keep old sets.
Methods (by class)
subtract( object = TidySet, set_in = characterORfactor, not_in = characterORfactor ): Elements present in sets but not in other sets
See also
Other complements:
complement(),
complement_element(),
complement_set()
Other methods that create new sets:
complement_element(),
complement_set(),
intersection(),
union()
Other methods:
TidySet-class,
activate(),
add_column(),
add_relation(),
arrange.TidySet(),
cartesian(),
complement(),
complement_element(),
complement_set(),
element_size(),
elements(),
filter.TidySet(),
group(),
group_by.TidySet(),
incidence(),
intersection(),
is.fuzzy(),
is_nested(),
move_to(),
mutate.TidySet(),
nElements(),
nRelations(),
nSets(),
name_elements<-(),
name_sets(),
name_sets<-(),
power_set(),
pull.TidySet(),
relations(),
remove_column(),
remove_element(),
remove_relation(),
remove_set(),
rename_elements(),
rename_set(),
select.TidySet(),
set_size(),
sets(),
union()
Examples
relations <- data.frame(
sets = c("A", "A", "B", "B", "C", "C"),
elements = letters[seq_len(6)],
fuzzy = runif(6)
)
TS <- tidySet(relations)
subtract(TS, "A", "B")
#> elements sets fuzzy
#> 1 a A 0.5155856195
#> 2 b A 0.8694592980
#> 3 c B 0.8565225946
#> 4 d B 0.3456831840
#> 5 e C 0.0001036914
#> 6 f C 0.2051797453
#> 7 a A∖B 0.5155856195
#> 8 b A∖B 0.8694592980
subtract(TS, "A", "B", keep = FALSE)
#> elements sets fuzzy
#> 1 a A∖B 0.5155856
#> 2 b A∖B 0.8694593