数据框列中的列表或向量，以便能够比较每个值并计算与 R 项目的匹配项

Question

'Lists or vectors within a column of a data frame, to be able to compare each value and count the matches with R project'

Col1	Col2
a	3,2,20,6
b	3,0,20,15
a	3,2,20,50
b	3,6,59,0
a	3,4,20,6

'I have two columns, Col2 is a character, but I need to transform it to a vector, example: c(“3”, ”2”, ”20”, ”6”, ”4”, ”64”, ”7”, ”65”, ”76”, ”26”, ”52”, ”67”, ”66”, ”76”, ”22”), to be able to apply %in% and obtain the number of True, example:'

'Table$Col3 <- Table$Col2[1] %in% Table$Col2 and get'

Col1	Col2	Col3
a	3,2,20,6
b	3,0,20,15	true, false, true, false
a	3,2,20,50
b	3,6,59,0	true, false, false, false
a	3,4,20,6	true, false, true, false

'And finally count the number of True'

Col1	Col2	Col3	Col4
a	3,2,20,6
b	3,0,20,15	true, false, true, false	2
a	3,2,20,50	true, true, true, false	3
b	3,6,59,0	true, false, false, false	1
a	3,4,20,6	true, false, true, false	2

'But I cannot transform Table$Col2[1] into a vector or list, I always get all the content between quotes “c(“3”, ”2”, ”20”, ”6”, ”4”, ”64” , ”7”, ”65”, ”76”, ”26”, ”52”, ”67”, ”66”, ”76”, ”22”)”, as a single value, in this way it compares the entire lists, not the values inside, not each value.'

'How can I solve that? It occurs to me that I could separate the values, creating more columns formatted as integers, and then join the values to create the vector or list, but I think that would be very inefficient.'

Answer 1

We may extract the first list element with [[ , loop over the list column with map/imap (from purrr ), create a logical vector with %in% and get the count of TRUE values in Col4 by taking the sum of TRUE ( TRUE -> 1 and FALSE -> 0)

library(purrr)
library(dplyr)
df1 %>%
   mutate(Col3 = imap(Col2, ~ if(.y == 1) NA else .x %in% Col2[[1]]), 
     Col4 = map_dbl(Col3, ~ sum(.x, na.rm = TRUE)))

-output

# A tibble: 5 × 4
  Col1  Col2      Col3       Col4
  <chr> <list>    <list>    <dbl>
1 a     <dbl [4]> <lgl [1]>     0
2 b     <dbl [4]> <lgl [4]>     2
3 a     <dbl [4]> <lgl [4]>     3
4 b     <dbl [4]> <lgl [4]>     2
5 a     <dbl [4]> <lgl [4]>     3

data

df1 <- structure(list(Col1 = c("a", "b", "a", "b", "a"), Col2 = list(
    c(3, 2, 20, 6), c(3, 0, 20, 15), c(3, 2, 20, 50), c(3, 6, 
    59, 0), c(3, 4, 20, 6))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -5L))