R: column binding with unequal number of rows

Question

I have two data sets. Each of them has variables ID, Block, and RT (reaction time). I want to merge/column bind the two sets so that I have one data set with variables: ID, Block, RT1, RT2. The problem is there is unequal number of rows in the two sets. Also, it is important that the ID and block number match. Missing values should be replaced with NA. So what I have:

head(blok1, 10) 
ID Blok RT1 
1 1 1 592 
2 1 1 468 
3 1 1 530 
4 1 1 546 
5 1 1 452 
6 1 1 483 
7 1 2 499 
8 1 2 452 
9 1 2 608 
10 1 2 530

head(blok2, 10) 
ID Blok RT2 
1 1 1 592 
2 1 1 920 
3 1 1 686 
4 1 1 561 
5 1 1 561 
6 1 2 327 
7 1 2 686 
8 1 2 670 
9 1 2 702 
10 1 3 920

What I want to have:

ID Blok RT1 RT2 
1 1 1 592 592 
2 1 1 468 920 
3 1 1 530 686 
4 1 1 546 561 
5 1 1 452 561 
6 1 1 483 NA 
7 1 2 499 327 
8 1 2 452 686 
9 1 2 608 670 
10 1 2 530 702

etc.

kevinykuo kevinykuo · Accepted Answer · 2014-11-10T23:00:30

Here's a solution using dplyr, also utilizing an index or unique ID:

blok1 <- data.frame(ID = c(1, 1, 2), RT1 = c(11, 12, 13))
blok2 <- data.frame(ID = c(1, 2, 2), RT2 = c(21, 22, 23))

library(dplyr)

## if you want NAs for RT2 only
blok1 %>%
  mutate(uID = row_number()) %>%
  left_join(blok2 %>% mutate(uID = row_number()), by = c("uID", "ID"))
# uID ID RT1 RT2
# 1   1  1  11  21
# 2   2  1  12  NA
# 3   3  2  13  23

## if you want NAs for both RT1 and RT2
blok1 %>%
  mutate(uID = row_number()) %>%
  outer_join(blok2 %>% mutate(uID = row_number()), by = c("uID", "ID"))
#    uID ID RT1 RT2
# 1   1  1  11  21
# 2   2  1  12  NA
# 3   3  2  13  23
# 4   2  2  NA  22

R: column binding with unequal number of rows

1 Answers