基于字符串向量比较R中的两个字符向量

Question

I have two lists A and B . The dates in A are 2000 - 2022 while those in B are 2023-2030 .

names(A) and names(B) give the follow character vectors:

a <- c("ACC_a_his", "BCC_b_his", "Can_c_his", "CES_d_his")
b <- c("ACC_a_fu", "BCC_b_fu", "Can_c_fu", "CES_d_fu","FGO_c_fu")

Also, I have a string vector, c which is common across the names in a and b :

c=c("ACC","BCC", "Can", "CES", "FGO")

Note that the strings in c do not always appear in the same position in filenames. The string can be at the beginning, middle or end of filenames.

Challenge

1. Using the strings in c I would like to get the difference (ie, which name exists in b but not in a or vice versa) between the names in a and b

Expected output = "FGO_c_fu"

2. rbind (or whatever is best) matching dataframes in lists A and B if the names are similar based on string in c

Answer 1

Update: See OP's comment:

Try this:

library(dplyr)
library(tibble)
library(tidyr)
library(stringr)
# or just library(tidyverse)

df %>% 
  pivot_longer(everything()) %>% 
  mutate(x = str_extract(value, paste(c, collapse = "|"))
         ) %>% 
  group_by(x) %>% 
  filter(!any(row_number() > 1)) %>% 
  na.omit() %>% 
  pull(value)

[1] "FGO_c_fu"

First answer: Here is an alternative approach:

1. We create a list
2. the vectors are of unequal length
3. With data.frame(lapply(my_list, length<- , max(lengths(my_list)))) we create a data frame
4. pivot longer and group by all before the first underline
5. remove NA and filter:

library(dplyr)
library(tidyr)
library(tibble)

my_list <- tibble::lst(a, b)
df <- data.frame(lapply(my_list, `length<-`, max(lengths(my_list)))) 
 
df %>% 
  pivot_longer(everything()) %>% 
  group_by(x = sub("\\_.*", "", value)) %>% 
  filter(!any(row_number() > 1)) %>% 
  na.omit() %>% 
  pull(value)

[1] "FGO_c_fu"