extract-TidySet: Extract

In BaseSet: Working with Sets the Tidy Way

Extract

Description

Operators acting on TidySet to extract or replace parts. They are designed to resemble the basic operators.

Usage

## S4 method for signature 'TidySet'
x$name

## S4 replacement method for signature 'TidySet'
x$name <- value

## S4 method for signature 'TidySet'
x[i, j, k, ..., drop = TRUE]

## S4 replacement method for signature 'TidySet'
x[i, j, k, ...] <- value

## S4 method for signature 'TidySet'
x[[i, j, ..., exact = TRUE]]

## S4 replacement method for signature 'TidySet'
x[[i]] <- value

Arguments

x	A TidySet object.
name	The data about the TidysSet object to extract.
value	The value to overwrite
i	Which rows do you want to keep? By default all.
j	Which slot do you want to extract? One of "sets", "elements" or "relations".
k	Which columns do you want to extract. By default all.
...	Other arguments currently ignored.
drop	Remove remaining elements, sets and relations? Passed to all arguments of droplevels().
exact	A logical value. FALSE if fuzzy matching is wanted. Add values to the TidySet. Allows to control to which slot is it added.

Value

Always returns a valid TidySet.

Examples

TS <- tidySet(list(A = letters[1:5], B = letters[6]))
TS[, "sets", "origin"] <- sample(c("random", "non-random"), 2, replace = TRUE)
TS[, "sets", "type"] <- c("Fantastic", "Wonderful")
# This produces a warning
# Better to be explicit:
TS[, "relations", "description"] <- c("What", "can", "I", "say", "now", "?")
relations(TS)
TS[, "elements", "description"] <- rev(c("What", "can", "I", "say", "now", "?"))
elements(TS)
# Which will be deleted?
# TS$description <- NULL
TS$type
TS$origin <- c("BCN", "BDN")
# Different subsets
TS[1, "elements"]
TS[1, "sets"]
# Always print
TS
TS[, "sets", c("type", "origin")] # Same
TS[, "sets", "origin"] # Drop column type
is(TS[, "sets", "origin"])
TS[, "sets"]
TS[["A"]]
TS[["B"]]
TS[["C"]] # Any other set is the empty set

BaseSet documentation built on Aug. 22, 2023, 5:11 p.m.