检查元素是否包含在不同长度的不相等元素上

Question

我试图找出一个字符向量的一部分是否与另一个字符向量的一部分重叠

x <- c("OCT/NOV/DEC", "JAN/DEC/AUG")
y <- c("JAN/FEB/MAR", "APR/MAY/JUN", "JUL/AUG/SEP")

# Months should be split into separate characters

So I would use:

list_x <- strsplit(x, '/')
list_x

#> [[1]]
#> [1] "OCT" "NOV" "DEC"
#> 
#> [[2]]
#> [1] "JAN" "DEC" "AUG"

list_y <- strsplit(y, '/')
list_y

#> [[1]]
#> [1] "JAN" "FEB" "MAR"
#> 
#> [[2]]
#> [1] "APR" "MAY" "JUN"
#> 
#> [[3]]
#> [1] "JUL" "AUG" "SEP"

正如我们所见，list_x[[1]] 没有任何元素位于 list_y 中，因此应该返回 FALSE；

list_x[[2]] 有 "JAN" 和 "AUG"，它们位于 list_y[[1]] 和 list_y[[3]]，所以应该返回一个 TRUE

# The response should be 

c(FALSE, TRUE) # for each of x elements

# I tried:

detect <- function(x, y){ 
  mapply(function(x, y) any(x %in% y), strsplit(x, '/'), strsplit(y, '/'))
}

detect(x,y)

# Which gives a warning stating the lengths are not multiple and:
#> [1] FALSE FALSE FALSE

那么我如何判断是否有 x 元素也在 y 元素中？

编辑：在 Akrun 的回复之后，我尝试了一种更复杂的方法，包括非 equi 连接

detect <- function(a,b){
  sapply(str_split(a, '/'), function(x) any(sapply(str_split(b, '/'),
                                                   function(y) any(x %in% y))))
}

a <- tibble(a1 = c("A/B/C", "F/E/G"),
            b1 = c(1,2),
            c1 = c("OCT/NOV/DEC", "JAN/DEC/AUG"))

b <- tibble(a2 = c("A/B/C", "D/E/F", "G/H/I"),
            b2 = c(1,2,3),
            c2 = c("JAN/FEB/MAR", "APR/MAY/JUN", "JUL/AUG/SEP"))

fuzzyjoin::fuzzy_left_join(a, b, by = c("a1" = "a2", 
                             "b1" = "b2",
                             "c1" = "c2"),
                match_fun = list(detect, `==`, detect))

## Wrong Result:
#>  a1       b1 c1          a2       b2 c2         
#>  <chr> <int> <chr>       <chr> <int> <chr>      
#> 1 A/B/C     1 OCT/NOV/DEC NA       NA NA         
#> 2 F/E/G     2 JAN/DEC/AUG D/E/F     2 APR/MAY/JUN

# Row 2: Although a1 and a2 have matching characters and b1 matches b2, c1 and c2 have no matching characters, so the join shouldn't be possible

## Expected:
#>  a1       b1 c1          a2       b2 c2         
#>  <chr> <int> <chr>       <chr> <int> <chr>      
#> 1 A/B/C     1 OCT/NOV/DEC NA       NA NA         
#> 2 F/E/G     2 JAN/DEC/AUG NA       NA NA

也许我误解了这个函数中的某些内容？

Answer 1

我们可以使用嵌套的sapply 和any

sapply(list_x, function(x) any(sapply(list_y, function(y) any(x %in% y))))
#[1] FALSE  TRUE

---

对于更新后的数据，如果我们将any 更改为all，它将给出预期的输出

detect <- function(a,b){
   sapply(str_split(a, '/'), function(x) all(sapply(str_split(b, '/'),
                                                    function(y) any(x %in% y))))
 }
 fuzzyjoin::fuzzy_left_join(a, b, by = c("a1" = "a2", 
                              "b1" = "b2",
                              "c1" = "c2"),
                 match_fun = list(detect, `==`, detect))
# A tibble: 2 x 6
#  a1       b1 c1          a2       b2 c2   
#  <chr> <dbl> <chr>       <chr> <dbl> <chr>
#1 A/B/C     1 OCT/NOV/DEC <NA>     NA <NA> 
#2 F/E/G     2 JAN/DEC/AUG <NA>     NA <NA>