Given a TidySet adds new relations between elements and sets.
Usage
add_relation(object, relations, ...)
# S4 method for class 'TidySet,data.frame'
add_relation(object, relations)See also
Other methods:
TidySet-class,
activate(),
add_column(),
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(),
subtract(),
union()
Examples
relations <- data.frame(
sets = c(rep("A", 5), "B"),
elements = letters[seq_len(6)],
fuzzy = runif(6)
)
TS <- tidySet(relations)
relations <- data.frame(
sets = c(rep("A2", 5), "B2"),
elements = letters[seq_len(6)],
fuzzy = runif(6),
new = runif(6)
)
add_relation(TS, relations)
#> elements sets fuzzy new
#> 1 a A 0.38870131 NA
#> 2 b A 0.97554784 NA
#> 3 c A 0.28989230 NA
#> 4 d A 0.67838043 NA
#> 5 e A 0.73531960 NA
#> 6 f B 0.19595673 NA
#> 7 a A2 0.98053967 0.03123033
#> 8 b A2 0.74152153 0.22556253
#> 9 c A2 0.05144628 0.30083081
#> 10 d A2 0.53021246 0.63646561
#> 11 e A2 0.69582388 0.47902455
#> 12 f B2 0.68855600 0.43217126