Fuzzy String Comparisons - UK Postcodes-CodePudding

If I have a data frame in R with two UK postcode fields (both in upper case), is there an easy, convenient way to define a score that is based on some kind of fuzzy comparison between these two fields?

Have done some googling but everything I found was some kind of "fuzzy join", and I don't need the join bit here.

So for example if I had:

my_df <- data.frame(postcode_1 = c("AB1 1AB", "DN17 2DF", "TN38 8LE", "FK1 2ZZ"),
                    postcode_2 = c("AB1 1AB", "EC1X 3WW", "TN38 9LE", "FK2 1ZZ"))

then I might like to do something like

my_df <- my_df |>
  mutate(score = fuzzy_string_compare_thingy(postcode_1, postcode_2))

to give me (for example):

my_df <- data.frame(postcode_1  = c("AB1 1AB", "DN17 2DF", "TN38 8LE", "FK1 2ZZ"),
                    postcode_2  = c("AB1 1AB", "EC1X 3WW", "TN38 9LE", "FK2 1ZZ"),
                    score       = c(1, 0.1, 0.9, 0.7))

(the values in the score field are made up of course)

CodePudding user response：

Choose your desired distance method using e.g. stringdist

library(stringdist)

cbind(my_df, 
  sapply(c("osa", "lv", "dl", "hamming", "lcs", "qgram",
           "cosine", "jaccard", "jw", "soundex" ), function(m) 
    apply(my_df, 1, function(x) stringdist(x[1], x[2], method=m))))
  postcode_1 postcode_2 osa lv dl hamming lcs qgram    cosine   jaccard
1    AB1 1AB    AB1 1AB   0  0  0       0   0     0 0.0000000 0.0000000
2   DN17 2DF   EC1X 3WW   6  6  6       6  12    12 0.8000000 0.8333333
3   TN38 8LE   TN38 9LE   1  1  1       1   2     2 0.1055728 0.1250000
4    FK1 2ZZ    FK2 1ZZ   2  2  2       2   4     0 0.0000000 0.0000000
          jw soundex
1 0.00000000       0
2 0.50000000       1
3 0.08333333       0
4 0.04761905       0

Using "jw", also "normalize" to 1 (meaning identity) with dplyr

library(dplyr)

my_df %>% 
  mutate(score_1 = 1 - stringdist(postcode_1, postcode_2, method="jw"))
  postcode_1 postcode_2   score_1
1    AB1 1AB    AB1 1AB 1.0000000
2   DN17 2DF   EC1X 3WW 0.5000000
3   TN38 8LE   TN38 9LE 0.9166667
4    FK1 2ZZ    FK2 1ZZ 0.9523810