BaseSet (version 0.0.17)

pull.TidySet: Pull from a TidySet

Description

Use pull 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 TidySet
pull(.data, var = -1, name = NULL, ...)
pull_set(.data, var = -1, name = NULL, ...)
pull_element(.data, var = -1, name = NULL, ...)
pull_relation(.data, var = -1, name = NULL, ...)

Value

A TidySet object

Arguments

.data

The TidySet object

var

The literal variable name, a positive integer or a negative integer column position.

name

Column used to name the output.

...

Currently not used.

See Also

dplyr pull 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(), 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)
)
a <- tidySet(relations)
a <- mutate_element(a, type = c(rep("Gene", 4), rep("lncRNA", 2)))
pull(a, type)
# Equivalent to pull_relation
b <- activate(a, "relations")
pull_relation(b, elements)
pull_element(b, elements)
# Filter element
pull_element(a, type)
# Filter sets
pull_set(a, sets)