Matching IDs in two datasets

Question

I have two sets of data, comprising pre and a post data. Respondents have unique IDs, and I want to create a subset which includes only those who responded to both surveys. Example dataset:

pre.data <- data.frame(ID = c(1:10), Y = sample(c("yes", "no"), 10, replace = TRUE),
  Survey = 1)

post.data <- data.frame(ID = c(1:3,6:10), Y = sample(c("yes", "no"), 8, replace = TRUE),
  Survey = 2)

all.data <- rbind(pre.data, post.data)

I have the following function:

match <- function(dat1, dat2, dat3){  #dat1 is whole dataset(both stitched together) 
  #dat2 is pre dataset #dat3 is post dataset
  selectedRows <- (dat1$ID %in% dat2$ID & 
                     dat1$ID %in% dat3$ID)

  matchdata <- dat1[selectedRows,]
  return(matchdata)
}

prepost.match.data <- match(all.data, pre.data, post.data)

I think there must be a better way than this function of doing the same thing, but I cannot think how. How I have done it seems a bit messy. I mean, it works - it does what I want it to, but I can't help thinking there's a better way.

My apologies if this has already been asked in a similar way but I was unable to find it - in which case please do point me towards a relevant answer.

Something like: all.data[all.data$ID %in% intersect(pre.data$ID, post.data$ID), ]? — Arun

juba juba · Accepted Answer · 2013-04-18T14:12:10

Note : Arun posted the same answer in a comment a bit earlier than me.

You can use intersect like this :

all.data[all.data$ID %in% intersect(pre.data$ID, post.data$ID),]

Which gives :

   ID   Y Survey
1   1 yes      1
2   2  no      1
3   3  no      1
6   6 yes      1
7   7 yes      1
8   8 yes      1
9   9  no      1
10 10 yes      1
11  1  no      2
12  2 yes      2
13  3  no      2
14  6  no      2
15  7 yes      2
16  8 yes      2
17  9  no      2
18 10 yes      2

Matching IDs in two datasets

2 Answers