match | R Documentation |
Provides the generic function match()
and the methods for
associations, transactions and itemMatrix objects. match()
returns a vector
of the positions of (first) matches of its first argument in its second.
match(x, table, nomatch = NA_integer_, incomparables = NULL)
## S4 method for signature 'itemMatrix,itemMatrix'
match(x, table, nomatch = NA_integer_, incomparables = NULL)
## S4 method for signature 'rules,rules'
match(x, table, nomatch = NA_integer_, incomparables = NULL)
## S4 method for signature 'itemsets,itemsets'
match(x, table, nomatch = NA_integer_, incomparables = NULL)
## S4 method for signature 'itemMatrix,itemMatrix'
x %in% table
## S4 method for signature 'itemMatrix,character'
x %in% table
## S4 method for signature 'associations,associations'
x %in% table
## S4 method for signature 'itemMatrix,character'
x %pin% table
## S4 method for signature 'itemMatrix,character'
x %ain% table
## S4 method for signature 'itemMatrix,character'
x %oin% table
x |
an object of class itemMatrix, transactions or associations. |
table |
a set of associations or transactions to be matched against. |
nomatch |
the value to be returned in the case when no match is found. |
incomparables |
not implemented. |
%in%
is a more intuitive interface as a binary operator, which
returns a logical vector indicating if there is a match or not for the items
in the itemsets (left operand) with the items in the table (right operand).
arules defines additional binary operators for matching itemsets:
%pin%
uses partial matching on the table; %ain%
itemsets have to match/include all items in the table; %oin%
itemsets can only match/include the items in the table. The binary
matching operators or often used in subset()
.
match
: An integer vector of the same length as x
giving the position in table
of the first match if there is a match,
otherwise nomatch
.
%in%
, %pin%
, %ain%
, %oin%
: A logical vector,
indicating if a match was located for each element of x
.
Michael Hahsler
Other associations functions:
abbreviate()
,
associations-class
,
c()
,
duplicated()
,
extract
,
inspect()
,
is.closed()
,
is.generator()
,
is.maximal()
,
is.redundant()
,
is.significant()
,
is.superset()
,
itemsets-class
,
rules-class
,
sample()
,
sets
,
size()
,
sort()
,
unique()
Other itemMatrix and transactions functions:
abbreviate()
,
c()
,
crossTable()
,
duplicated()
,
extract
,
hierarchy
,
image()
,
inspect()
,
is.superset()
,
itemFrequency()
,
itemFrequencyPlot()
,
itemMatrix-class
,
merge()
,
random.transactions()
,
sample()
,
sets
,
size()
,
supportingTransactions()
,
tidLists-class
,
transactions-class
,
unique()
data("Adult")
## get unique transactions, count frequency of unique transactions
## and plot frequency of unique transactions
vals <- unique(Adult)
cnts <- tabulate(match(Adult, vals))
plot(sort(cnts, decreasing=TRUE))
## find all transactions which are equal to transaction 10 in Adult
which(Adult %in% Adult[10])
## for transactions we can also match directly with itemLabels.
## Find in the first 10 transactions the ones which
## contain age=Middle-aged (see help page for class itemMatrix)
Adult[1:10] %in% "age=Middle-aged"
## find all transactions which contain items that partially match "age=" (all here).
Adult[1:10] %pin% "age="
## find all transactions that only include the item "age=Middle-aged" (none here).
Adult[1:10] %oin% "age=Middle-aged"
## find al transaction which contain both items "age=Middle-aged" and "sex=Male"
Adult[1:10] %ain% c("age=Middle-aged", "sex=Male")
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