dear all,
yes but the problem with soundex for example is that it does not work when
an error occur in the first place (Canada vs Kanada) as it keeps the fist
character. It seems that you have to look after an approximate string
matching algorithm (for example, a very good one if from Porter-Jaro and
Winkler at the US Census bureau or have o look to the book of Navarro about
classification of algorithm).
HTH and an happy new year, erik.
-----Message d'origine-----
De: Gabor Grothendieck
A: Werner Wernersen
Cc: r-help@stat.math.ethz.ch
Date: 10/01/2006 21:16
Objet: Re: [R] matching country name tables from different sources
One other thing to try could be soundex. ITs normally used for
last names but it might work here too. Google to find the
soundex encoding rules. Reviewing the country names might
suggest minor modifications to the soundex algorithm to
improve it for your case.
On 1/10/06, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
> You can improve it somewhat by first accepting all the largest
> matches and removing the rows and columns for those and
> repeatedly doing that with what is left.
>
> On 1/10/06, Werner Wernersen <[EMAIL PROTECTED]> wrote:
> > Thanks for the nice code, Gabor!
> >
> > Unfortunately, it seems not to work for my purpose, confuses lots of
> > countries when I compare two lists of over 150 countries each.
> > Do you have any other suggestions?
> >
> >
> >
> > Gabor Grothendieck <[EMAIL PROTECTED]> schrieb:
> > If they were the same you could use merge. To figure out
> > the correspondence automatically or semiautomatically, try this:
> >
> > x <- c("Canada", "US", "Mexico")
> > y <- c("Kanada", "United States", "Mehico")
> > result <- outer(x, y, function(x,y) mapply(lcs2, x, y))
> > result[] <- sapply(result, nchar)
> > # try both which.max and which.min and if you are lucky
> > # one of them will give unique values and that is the one to use
> > # In this case which.max does.
> > apply(result, 1, which.max) # 1 2 3
> >
> > # calculate longest common subsequence between 2 strings
> > lcs2 <- function(s1,s2) {
> > longest <- function(x,y) if (nchar(x) > nchar(y)) x else y
> > # Make sure args are strings
> > a <- as.character(s1); an <- nchar(s1)+1
> > b <- as.character(s2); bn <- nchar(s2)+1
> >
> >
> > # If one arg is an empty string, returns the length of the other
> > if (nchar(a)==0) return(nchar(b))
> > if (nchar(b)==0) return(nchar(a))
> >
> >
> > # Initialize matrix for calculations
> > m <- matrix("", nrow=an, ncol=bn)
> >
> > for (i in 2:an)
> > for (j in 2:bn)
> > m[i,j] <- if (substr(a,i-1,i-1)==substr(b,j-1,j-1))
> > paste(m[i-1,j-1], substr(a,i-1,i-1), sep = "")
> > else
> > longest(m[i-1,j], m[i,j-1])
> >
> > # Returns the distance
> > m[an,bn]
> > }
> >
> >
> >
> > On 1/10/06, Werner Wernersen wrote:
> > > Hi,
> > >
> > > Before I reinvent the wheel I wanted to kindly ask you for your
opinion if
> > there is a simple way to do it.
> > >
> > > I want to merge a larger number of tables from different data
sources in R
> > and the matching criterium are country names. The tables are of
different
> > size and sometimes the country names do differ slightly.
> > >
> > > Has anyone done this or any recommendation on what commands I
should look
> > at to automize this task as much as possible?
> > >
> > > Thanks a lot for your effort in advance.
> > >
> > > All the best,
> > > Werner
> > >
> > >
> > >
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