Matching columns in 2 data frames when numbers don't exactly match - r

Question

How do I match two different data frames when the values I am comparing are not exactly the same?
I was thinking of using merge() but I am not sure.
Table1:
ID Value.1
10001 x
18273-9 y
12824/5/6/7 z
10283/5/9 d
Table2:
ID Value.2
10001 a
18274 b
12826 c
10289 u
How do I merge Table 1 and 2 based on ID?
Which specific function of fuzzyjoin package would I use, especially with the "/" & "-" cases? How do I expand the "-" case from 18273-9 so that R will register 18273 / 18274 / 18275 / ...?

Answer 1

You can write a function to extract the corresponding sequences from the strings containing "/" or "-" and recombine them into a new data.frame as follows:
df1 <- data.frame(ID=c("10001","18273-9","15273-8", "15170-4", "12824/5/6/7","10283/5/9"),
value=c("a","c","c", "d","k", "l"), stringsAsFactors = F)
df2 <- data.frame(ID=c("10001","18274","12826","10289"),
value=c("o","p","q","r"), stringsAsFactors = F)
doIt <- function(df){
listAsDF <- function(l) {
x <- stack(setNames(l, temp$value))
names(x) <- c("ID", "value")
return(x)
}
Base <- df[!grepl("\\/", df$ID) & !grepl("\\-", df$ID), ]
#1 cases when - present
temp <- df[grep("\\-", df$ID),]
temp <- listAsDF(lapply(strsplit(temp$ID, "-"), function(e) seq(e[1], paste0(strtrim(e[1], nchar(e[1])-1), e[2]), 1)))
Base <- rbind(Base, temp)
#2 cases when / present
temp <- df[grep("\\/", df$ID),]
temp <- listAsDF(lapply(strsplit(temp$ID, "/"), function(a) c(a[1], paste0(strtrim(a[1], nchar(a[1])-1), a[-1]))))
Base <- rbind(Base, temp)
return(Base)
}
Then you can mergge the df2 and df1:
merge(doIt(df1), df2, by = "ID", all.x = T)
Hope this helps!

Answer 2

You could use the fuzzy string matching function "agrep" from base R.
df1 <- data.frame(ID=c("10001","18273-9","12824/5/6/7","10283/5/9"),
value=c("a","c","d","k"))
df2 <- data.frame(ID=c("10001","18274","12826","10289"),
value=c("o","p","q","r"))
apply(df1, 1, function(x) agrep(x["ID"], df2$ID, max = 3.5))
As you see it struggles to find the match for row 4. So it might make sense to clean your ID variable (e.g., take out the "/") before running agrep.

Answer 3

One option could consist in extracting the format of ID you want to keep. And then do your merge.
You can format your ID column as follow :
library(stringr)
library(dplyr)
If you want only the digits before any symbols
Table1 %>% mutate(ID = str_extract("[0-9]*"))
If you want to keep the first sequence of 5 digits
Table1 %>% mutate(ID = str_extract("[0-9]{5}"))
This answers your second question, but does not use the fuzzyjoin package