[R] "argument is missing, with no default" OR "replacement has length zero"

[arun]

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 <lindb at vcu.edu>
To: r-help at 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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