I have two data sets, both with dog breed names. I'd like to combine the data sets somehow, but a lot of dogs have multiple names, so for instance African Hairless Dogs are also called African Abyssinian Terriers.

I think these names are too different to match by the similarity of their words, so I'm wondering what's the best way to match them.

So for instance, suppose data set 1 is

Breed                           Height (inches)
African Hairless Dog            17 
Golden Retriever                20 
Labrador Retriever              22

And data set 2 is

Breed                           Weight (pounds)
African Abyssinian Terrier      30 
Golden Retriever                60 
Labrador Retriever              65

And I'd like a data set like the following below:

Breed                           Height (inches)           Weight (pounds)
African Hairless Dog            17                        30
Golden Retriever                20                        60
Labrador Retriever              22                        65

Here is a solution using tidyverse:

# library

# load test data
set1 <- tibble(Breed=c("African Hairless Dog","Golden Retriever","Labrador Retriever"), 

set2 <- tibble(Breed=c("Abyssinian Terriers","Golden Retriever","Labrador Retriever"),

# make a lookup table (you should add here otherBreeds and Nicknames)
lookup <- tibble(Breed=c("African Hairless Dog","other Breed"),
                 Nicknames=list(c("Abyssinian Terriers","other Nickname","other Nickname"),

#prepare the lookup table                 
lookup %>% unnest(cols=c(Nicknames)) -> lookup

# apply the lookup table to your set2
set2 %>%
  left_join(lookup, by=c("Breed"="Nicknames")) %>% 
  mutate(Breed=case_when(is.na(Breed.y)~Breed, TRUE ~Breed.y)) %>% 
  select(Breed,Weight) -> set2_new

# combine your data  
#> Joining, by = "Breed"
#> # A tibble: 3 x 3
#>   Breed                Height Weight
#>   <chr>                 <dbl>  <dbl>
#> 1 African Hairless Dog     17     30
#> 2 Golden Retriever         20     60
#> 3 Labrador Retriever       22     65

Created on 2020-04-05 by the reprex package (v0.3.0)


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