R - 使用grepl和相同的多个条件嵌套for循环

Question

I am trying to mark all fruit with a "1" if it is only supplied by one country or a "0" otherwise.

I have two tables of data:

Table 1:

Fruit - Each row has a different fruit in it eg Apple, Banana, Peach,etc...

Country - Each row has the fruits main country of supply in 2-digit iso format eg US, UK, NO, etc...

SourceUnique - This is the column I want to fill with "1" in rows with fruit that are only supplied by one country and "0" otherwise.

Table 2:

Country - Each row has the suppliers country in 2-digit iso format like the last table.

Supplies - Each row has a list of fruits that the supplier delivers eg row 1 is "Apple, Banana", row 2 is "Pineapple, Peach, Pear, Apple", etc...

Both tables are imported from CSV files then my code is as follows:

Table1$SourceUnique=rep(1,length(Table1$Country))

for(i in 1:length(Table1$Country)){
  for(k in 1:length(Table2$Country)){
    if(grepl(Table1$Fruit[i], Table2$Supplies[k])==TRUE && identical(Table1$Country[i], Table2$Country[k])==FALSE){
      Table1$SourceUnique[i]=0
    }
  }
}

I get no errors but the SourceUnique column does not fill correctly. I get 1's and 0's with some correct and others not. After lots of searching and messing around I have accepted that I have no idea and need help, so any advice or solutions would be fantastic.

Thanks.

Edit for more info:

Some fruits have many suppliers from the same country and Table2$Supplies is messy with other words in it annoyingly.

Example data:

Table1$Country <- c("UK","US","NO")
Table1$Fruit <- c("Apple","Banana","Pear")

Table2$Country <- c("UK","US","UK")
Table2$Supplies <- c("Apple,Pear","Banana,Pear","Banana and Apple")

Edit Again:

grepl and identical work in my code when I run them separately with numbers. I can't understand why they do not work in my loops... In theory my code loops through "Supplies", searches the two criteria and returns a 0 when both criteria are satisfied. It then moves on to the next i ("fruit") and repeats. Maybe the && is my problem? it seems correct from my knowledge.

An Excel solution would also work for my purpose but I am not experienced enough with Excel to know where to start with that.

Answer 1

Perhaps you can simplify the problem by counting the occurrences of each fruit in table 2 for each country:

for (i in Table1$Fruit){
  as.integer(rowSums(table(grepl(i,Table2$Supplies),Table2$Country))[2]==1)
}

This gives you 1 for those fruits that only occur once per country in table 2 and 0 otherwise.

Answer 2

Assuming it's possible to construct a regular expression to extract the values of "fruit" from the Supplies column in your real data, here's a data manipulation approach to the problem.

# prepare your sample data
fruit <- suppliers <- list()

fruit$Fruit <- c("Apple","Banana","Pear")
fruit$Country <- c("UK","US","NO")
fruit <- data.frame(fruit)

suppliers$Country <- c("UK","US","UK")
suppliers$Supplies <- c("Apple,Pear","Banana,Pear","Banana and Apple")
suppliers <- data.frame(suppliers)

library(dplyr)
library(tidyr)  # version 0.5.0 or later

# data manipulation for the desired result
suppliers %>%
    # split values of Supplies into a new row at each occurance of sep
    separate_rows(Supplies, sep = "\\s*(and|,)\\s*") %>%
    group_by(Supplies) %>%
    # summarize which fruit are supplied from only one country
    summarize(SourceUnique = as.numeric(n_distinct(Country) == 1)) %>%
    left_join(fruit, ., by = c("Fruit" = "Supplies"))
#        Fruit Country SourceUnique
#     1  Apple      UK            1
#     2 Banana      US            0
#     3   Pear      NO            0

If speed is desired, the same could likely be formulated using data.table s which provide excellent performance for working with large data.