filter.TidySet {BaseSet} | R Documentation |
Filter TidySet
Description
Use filter to subset the TidySet object. You can use activate with filter or use the specific function. The S3 method filters using all the information on the TidySet.
Usage
## S3 method for class 'TidySet'
filter(.data, ...)
filter_set(.data, ...)
filter_element(.data, ...)
filter_relation(.data, ...)
Arguments
.data |
The TidySet object. |
... |
The logical predicates in terms of the variables of the sets. |
Value
A TidySet object.
See Also
dplyr::filter()
and activate()
Other methods:
TidySet-class
,
activate()
,
add_column()
,
add_relation()
,
arrange.TidySet()
,
cartesian()
,
complement_element()
,
complement_set()
,
complement()
,
element_size()
,
elements()
,
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", rep("a2", 5), "b2"),
elements = rep(letters[seq_len(6)], 2),
fuzzy = runif(12),
type = c(rep("Gene", 4), rep("lncRNA", 2))
)
TS <- tidySet(relations)
TS <- move_to(TS, from = "relations", to = "elements", column = "type")
filter(TS, elements == "a")
# Equivalent to filter_relation
filter(TS, elements == "a", sets == "a")
filter_relation(TS, elements == "a", sets == "a")
# Filter element
filter_element(TS, type == "Gene")
# Filter sets and by property of elements simultaneously
filter(TS, sets == "b", type == "lncRNA")
# Filter sets
filter_set(TS, sets == "b")