How to fuzzy join 2 dataframes on 2 variables with differing “fuzzy logic”?

问题

# example
a <- data.frame(name=c("A","B","C"), KW=c(201902,201904,201905),price=c(1.99,3.02,5.00))
b <- data.frame(KW=c(201903,201904,201904),price=c(1.98,3.00,5.00),name=c("a","b","c"))

I want to match a and b with fuzzy logic, using the variables KW and price. I want to allow a tolerance of +/- 1 for KW and a tolerance for +/- 0.02 in price.

The desired outcome should look like this:

name.x   KW.x price.x   KW.y price.y name.y
1    A 201902    1.99 201903    1.98      a
2    B 201904    3.02 201904    3.00      b
3    C 201905    5.00 201904    5.00      c

I would prefer to find a solution using the fuzzyjoin package. I tried so far using the fuzzy_inner_join function and specifying my desired tolrences for KW and price using the match_fun argument. However, I couldn't get it to work.

Looking for help, how to solve this problem.

回答1:

You can create a cartesian product of two dataframes using merge and then subset the rows which follow our required conditions.

subset(merge(a, b, by = NULL), abs(KW.x - KW.y) <= 1 & 
                               abs(price.x - price.y) <= 0.02)

#  name.x   KW.x price.x   KW.y price.y name.y
#1      A 201902    1.99 201903    1.98      a
#5      B 201904    3.02 201904    3.00      b
#9      C 201905    5.00 201904    5.00      c

来源：https://stackoverflow.com/questions/60883566/how-to-fuzzy-join-2-dataframes-on-2-variables-with-differing-fuzzy-logic