Given TidySet retrieve the elements or substitute them.
Usage
elements(object)
elements(object) <- value
# S4 method for class 'TidySet'
elements(object)
# S4 method for class 'TidySet'
elements(object) <- value
replace_elements(object, value)
# S4 method for class 'TidySet,missing'
nElements(object)
# S4 method for class 'TidySet,logical'
nElements(object, all)Methods (by class)
- elements(TidySet): Retrieve the elements
- elements(TidySet) <- value: Modify the elements
- nElements(object = TidySet, all = missing): Return the number of elements
- nElements(object = TidySet, all = logical): Return the number of elements
See also
Other slots:
relations(),
sets()
Other methods:
TidySet-class,
activate(),
add_column(),
add_relation(),
arrange.TidySet(),
cartesian(),
complement(),
complement_element(),
complement_set(),
element_size(),
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
TS <- tidySet(list(A = letters[1:5], B = letters[2:10]))
elements(TS)
#>    elements
#> 1         a
#> 2         b
#> 3         c
#> 4         d
#> 5         e
#> 6         f
#> 7         g
#> 8         h
#> 9         i
#> 10        j
elements(TS) <- data.frame(elements = letters[10:1])
TS2 <- replace_elements(TS, data.frame(elements = letters[1:11]))
nElements(TS)
#> [1] 10
nElements(TS2)
#> [1] 11
