Return multiple possible matches when fuzzy joining two dataframes or vectors in R if they share a w-CodePudding

Is there a way of joining two dataframes via where a row in the first dataframe is joined with every row in the second dataframe if they share a word in common?

For example:

companies1 <- data.frame(company_name = c("Walmart", "Amazon", "Apple", "CVS Health", "UnitedHealth Group", "Berkshire Hathaway", "Alphabet"))
companies2 <- data.frame(company_name = "Walmart Stores", "Walmart Inc", "Amazon Web Services", "Amazon Alexa", "Apple", "Apple Products", "CVS Health", "UnitedHealth Group", "Berkshire Hathaway", "Berkshire Hathaway Asset Management", "Meta"))

I'd like to match these so every single possible match between the left and right column is then returned, as below:

I've tried packages like fuzzymatch and stringdist, but for matching these seem to return the best match only. However, as the matching I'm doing isn't as neat as the above and is much bigger, my plan is to find possible matches, then give them a distance score (e.g. using Jaro-Winkler distance), at which point I'll have to manually select the right match (if any).

CodePudding user response：

With fuzzy_join:

library(fuzzyjoin)
fuzzy_join(companies2, companies1, match_fun = stringr::str_detect)

                        company_name.x     company_name.y
1                       Walmart Stores            Walmart
2                          Walmart Inc            Walmart
3                  Amazon Web Services             Amazon
4                         Amazon Alexa             Amazon
5                                Apple              Apple
6                       Apple Products              Apple
7                           CVS Health         CVS Health
8                   UnitedHealth Group UnitedHealth Group
9                   Berkshire Hathaway Berkshire Hathaway
10 Berkshire Hathaway Asset Management Berkshire Hathaway

Or, if you want to respect the order of the columns:

fuzzy_join(companies1, companies2, match_fun = function(x, y) stringr::str_detect(y, x))

       company_name.x                      company_name.y
1             Walmart                      Walmart Stores
2             Walmart                         Walmart Inc
3              Amazon                 Amazon Web Services
4              Amazon                        Amazon Alexa
5               Apple                               Apple
6               Apple                      Apple Products
7          CVS Health                          CVS Health
8  UnitedHealth Group                  UnitedHealth Group
9  Berkshire Hathaway                  Berkshire Hathaway
10 Berkshire Hathaway Berkshire Hathaway Asset Management