extract: Methods for "[": Extraction or Subsetting arules Objects

In arules: Mining Association Rules and Frequent Itemsets

Methods for "[": Extraction or Subsetting arules Objects

Description

Methods for "[", i.e., extraction or subsetting for arules objects.

Usage

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

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

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

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

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

Arguments

x	an object of class itemMatrix, transactions or associations.
i	select rows/sets using an integer vector containing row numbers or a logical vector.
j	select columns/items using an integer vector containing column numbers (i.e., item IDs), a logical vector or a vector of strings containing parts of item labels.
...	further arguments are ignored.
drop	ignored.

Author(s)

Michael Hahsler

See Also

Other associations functions: abbreviate(), associations-class, c(), duplicated(), inspect(), is.closed(), is.generator(), is.maximal(), is.redundant(), is.significant(), is.superset(), itemsets-class, match(), rules-class, sample(), sets, size(), sort(), unique()

Other itemMatrix and transactions functions: abbreviate(), c(), crossTable(), duplicated(), hierarchy, image(), inspect(), is.superset(), itemFrequency(), itemFrequencyPlot(), itemMatrix-class, match(), merge(), random.transactions(), sample(), sets, size(), supportingTransactions(), tidLists-class, transactions-class, unique()

Examples

data(Adult)
Adult

## select first 10 transactions
Adult[1:10]

## select first 10 items for first 100 transactions
Adult[1:100, 1:10]

## select the first 100 transactions for the items containing
## "income" or "age=Young" in their labels
Adult[1:100, c("income=small", "income=large", "age=Young")]

arules documentation built on June 8, 2025, 12:10 p.m.