| select.TidySet {BaseSet} | R Documentation |
select from a TidySet
Description
Use select to extract the columns of a 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'
select(.data, ...)
select_set(.data, ...)
select_element(.data, ...)
select_relation(.data, ...)
Arguments
.data |
The TidySet object |
... |
The name of the columns you want to keep, remove or rename. |
Value
A TidySet object
See Also
dplyr::select() and activate()
Other methods:
TidySet-class,
activate(),
add_column(),
add_relation(),
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(),
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)
)
a <- tidySet(relations)
a <- mutate_element(a,
type = c(rep("Gene", 4), rep("lncRNA", 2))
)
a <- mutate_set(a, Group = c("UFM", "UAB", "UPF", "MIT"))
b <- select(a, -type)
elements(b)
b <- select_element(a, elements)
elements(b)
# Select sets
select_set(a, sets)