Mutate
Use mutate to alter the TidySet object. You can use activate with mutate or use the specific function. The S3 method filters using all the information on the TidySet.
## S3 method for class 'TidySet' mutate(.data, ...) mutate_set(.data, ...) mutate_element(.data, ...) mutate_relation(.data, ...)
.data |
The TidySet object. |
... |
The logical predicates in terms of the variables of the sets. |
A TidySet object
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(),
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()
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
b <- mutate_relation(a, Type = sample(c("PPI", "PF", "MP"), 12,
replace = TRUE
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