Given a TidySet adds new relations between elements and sets.
Usage
add_relation(object, relations, ...)
# S4 method for TidySet,data.frame
add_relation(object, relations)Arguments
- object
A TidySet object
- relations
A data.frame object
- ...
Placeholder for other arguments that could be passed to the method. Currently not used.
See also
Other methods:
TidySet-class,
activate(),
add_column(),
arrange.TidySet(),
cartesian(),
complement_element(),
complement_set(),
complement(),
element_size(),
elements(),
filter.TidySet(),
group_by.TidySet(),
group(),
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 0.43720283 NA
#> 2 b A 0.95599970 NA
#> 3 c A 0.09789652 NA
#> 4 d A 0.11170224 NA
#> 5 e A 0.71279096 NA
#> 6 f B 0.85373463 NA
#> 7 a A2 0.59627865 0.05060243
#> 8 b A2 0.84534888 0.23706874
#> 9 c A2 0.97541441 0.81837118
#> 10 d A2 0.58076090 0.48077977
#> 11 e A2 0.32036635 0.18319573
#> 12 f B2 0.92583546 0.35872523