HI,
With merge(), you could use:
merge(new,old,by=c("group","ID"),all.x=TRUE)
# group ID SomedataCol
#1 1 23 9.2
#2 1 542 NA
#3 1 800 NA
#4 2 23 4.2
#5 2 45 15.6
#6 2 2318 NA
#7 3 232 18.0
#8 3 800 3.3
#9 3 1345 21.1
A.K.
----- Original Message -----
From: lind35 <li...@vcu.edu>
To: r-help@r-project.org
Cc:
Sent: Sunday, November 25, 2012 1:22 PM
Subject: [R] "argument is missing, with no default" OR "replacement has length
zero"
Hello,
I have a new data set and an old data set. Both have the same columns
representing the same sort of measure. Within each data set (old and new)
are 18 groups (simplified to three groups below). Within each group are
individuals with unique ID numbers. These ID numbers may be the same as
other ID numbers in different groups, but a particular ID number only
appears once in each group.
The old data set does not include all of the individuals from the new data
set - meaning IDs within groups in the new data set are not found within the
old data set or visa versa. I am trying to extract data from a particular
column for unique individuals within a unique group from the old data set
and put that info into a column within the row for that particular unique
individual/group in the new data set. However, I keep coming up with R
errors.
Basically it's set up like this (i've simplified the data to illustrate the
important stuff)
old <- read.csv("/Users/Me/Desktop/old data.csv")
new <- read.csv("/Users/Me/Desktop/new data.csv")
> new
[group] [ID] [column where I want to put the data, currently blank]
[1,] 1 800 __
[2,] 1 23 __
[3,] 1 542 __
[4,] 2 23 __
[5,] 2 2318 __
[6,] 2 45 __
[7,] 3 1345 __
[8,] 3 800 __
[9,] 3 232 __
> old
[group] [ID] [data I want for the new.object]
[1,] 1 300 12.2
[2,] 1 155 10.8
[3,] 1 23 9.2
[4,] 2 45 15.6
[5,] 2 1289 5.5
[6,] 2 23 4.2
[7,] 3 800 3.3
[8,] 3 232 18.0
[9,] 3 1345 21.1
#and this is what I want to get as an end result
> new
[1,] 1 800 __
[2,] 1 23 9.2
[3,] 1 542 __
[4,] 2 23 4.2
[5,] 2 2318 __
[6,] 2 45 15.6
[7,] 3 1345 21.1
[8,] 3 800 3.3
[9,] 3 232 18.0
I've tried the following codes but keep getting error messages
> for (i in 1) {
+ new[i,3] <- old[which(old[,2] == new[i,2] & old[,1] == new[i,1]),3]
+ }
Error in `[<-.data.frame`(`*tmp*`, i, 11, value = numeric(0)) :
replacement has length zero
#OR
> for (i in 1) {
+ data[[i,11]] <- as.numeric(old[[which(old[[,22]] == data[[i,2]] &
old[[,1]] == data[[i,1]]),46]])
+ }
Error in `[[.data.frame`(old, , 22) :
argument "..1" is missing, with no default
I just want to ignore the IDs in the old data set that aren't in the new
data set. How do I do this?
--
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and provide commented, minimal, self-contained, reproducible code.
