MATCH function in r [duplicate]

Question

This question already has an answer here:

• How to join (merge) data frames (inner, outer, left, right) 13 answers

have lists, the first one (list1) has id,name,age and the other ones (list2,list3,..) has ids and test value (unique).

list 1:

id  age name    bio-test    
1   40  danny
2   16  nora            
3   35  james
4   21  ben

list 2 (bio-test):

id  test passed year   
1   100   yes   1
5   80    yes   n/a      
4   55    no    2

I am trying to add to list1 the test value to each id (not every id have a test value).

this is part of the code:

for (i in 1:length(list1)) { 
list1$test1value <- list2$test[match(list1$id[i], list2$id[i]),
nomatch = NA_integer_, incomparables = NULL)] }

but instead looking up the test value by id ,it copied just the first test value from list2 and copied it to 200 cells and the other 3000 are N/A.

what is wrong?

Answer 1

First you have typos in your example. Secondly, the assignment of 'list1$test1value' should have an '[i]' added to it to not save over each round. There should also not be an '[i]' added to list2$id since you want to search the entire vector for the lookup.

for (i in 1:length(list1)) { 
  list1$test1value[i] <- list2$test[match(list1$id[i], list2$id,
                             nomatch = NA_integer_, incomparables = NULL)] }

The code works, but there is no reason for any loops here. You are showing a lack of understanding in how R operates. The below code does the exact same thing much faster.

list1$test1value <- list2$test[match(list1$id, list2$id)]

R is built so that you do not have to hold its hand and instruct it how to go through each element of the vector. match will automatically iterate through each member one by one and look it up in the other vector for you. It will also assign the result in an orderly way in the dataset.

I will close this as a duplicate because as others suggested, merge is perfect for this.

merge(list1, list2[c("id", "test")], all.x=TRUE)
#  id age  name test
#1  1  40 danny  100
#2  2  16  nora   NA
#3  3  35 james   NA
#4  4  21   ben   55