stringdist  R Documentation 
stringdist
computes pairwise string distances between elements of
a
and b
, where the argument with less elements is recycled.
stringdistmatrix
computes the string distance matrix with rows
according to
a
and columns according to b
.
stringdist(
a,
b,
method = c("osa", "lv", "dl", "hamming", "lcs", "qgram", "cosine", "jaccard", "jw",
"soundex"),
useBytes = FALSE,
weight = c(d = 1, i = 1, s = 1, t = 1),
q = 1,
p = 0,
bt = 0,
nthread = getOption("sd_num_thread")
)
stringdistmatrix(
a,
b,
method = c("osa", "lv", "dl", "hamming", "lcs", "qgram", "cosine", "jaccard", "jw",
"soundex"),
useBytes = FALSE,
weight = c(d = 1, i = 1, s = 1, t = 1),
q = 1,
p = 0,
bt = 0,
useNames = c("none", "strings", "names"),
nthread = getOption("sd_num_thread")
)
a 
R object (target); will be converted by 
b 
R object (source); will be converted by 
method 
Method for distance calculation. The default is 
useBytes 
Perform bytewise comparison, see

weight 
For 
q 
Size of the 
p 
Prefix factor for JaroWinkler distance. The valid range for

bt 
Winkler's boost threshold. Winkler's prefix factor is
only applied when the Jaro distance is larger than 
nthread 
Maximum number of threads to use. By default, a sensible
number of threads is chosen, see 
useNames 
Use input vectors as row and column names? 
For stringdist
, a vector with string distances of size
max(length(a),length(b))
.
For stringdistmatrix
: if both a
and b
are passed, a
length(a)xlength(b)
matrix
. If a single argument a
is
given an object of class dist
is returned.
Distances are nonnegative if they can be computed, NA
if any of the
two argument strings is NA
and Inf
when maxDist
is
exceeded or, in case of the hamming distance, when the two compared strings
have different length.
stringsim
, qgrams
, amatch
, afind
# Simple example using optimal string alignment
stringdist("ca","abc")
# computing a 'dist' object
d < stringdistmatrix(c('foo','bar','boo','baz'))
# try plot(hclust(d))
# The following gives a matrix
stringdistmatrix(c("foo","bar","boo"),c("baz","buz"))
# An example using DamerauLevenshtein distance (multiple editing of substrings allowed)
stringdist("ca","abc",method="dl")
# string distance matching is case sensitive:
stringdist("ABC","abc")
# so you may want to normalize a bit:
stringdist(tolower("ABC"),"abc")
# stringdist recycles the shortest argument:
stringdist(c('a','b','c'),c('a','c'))
# stringdistmatrix gives the distance matrix (by default for optimal string alignment):
stringdist(c('a','b','c'),c('a','c'))
# different edit operations may be weighted; e.g. weighted substitution:
stringdist('ab','ba',weight=c(1,1,1,0.5))
# Nonunit weights for insertion and deletion makes the distance metric asymetric
stringdist('ca','abc')
stringdist('abc','ca')
stringdist('ca','abc',weight=c(0.5,1,1,1))
stringdist('abc','ca',weight=c(0.5,1,1,1))
# Hamming distance is undefined for
# strings of unequal lengths so stringdist returns Inf
stringdist("ab","abc",method="h")
# For strings of eqal length it counts the number of unequal characters as they occur
# in the strings from beginning to end
stringdist("hello","HeLl0",method="h")
# The lcs (longest common substring) distance returns the number of
# characters that are not part of the lcs.
#
# Here, the lcs is either 'a' or 'b' and one character cannot be paired:
stringdist('ab','ba',method="lcs")
# Here the lcs is 'surey' and 'v', 'g' and one 'r' of 'surgery' are not paired
stringdist('survey','surgery',method="lcs")
# qgrams are based on the difference between occurrences of q consecutive characters
# in string a and string b.
# Since each character abc occurs in 'abc' and 'cba', the q=1 distance equals 0:
stringdist('abc','cba',method='qgram',q=1)
# since the first string consists of 'ab','bc' and the second
# of 'cb' and 'ba', the q=2 distance equals 4 (they have no q=2 grams in common):
stringdist('abc','cba',method='qgram',q=2)
# Wikipedia has the following example of the Jarodistance.
stringdist('MARTHA','MATHRA',method='jw')
# Note that stringdist gives a _distance_ where wikipedia gives the corresponding
# _similarity measure_. To get the wikipedia result:
1  stringdist('MARTHA','MATHRA',method='jw')
# The corresponding JaroWinkler distance can be computed by setting p=0.1
stringdist('MARTHA','MATHRA',method='jw',p=0.1)
# or, as a similarity measure
1  stringdist('MARTHA','MATHRA',method='jw',p=0.1)
# This gives distance 1 since Euler and Gauss translate to different soundex codes.
stringdist('Euler','Gauss',method='soundex')
# Euler and Ellery translate to the same code and have distance 0
stringdist('Euler','Ellery',method='soundex')
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