On Sep 5, 2010, at 12:43 PM, David Winsemius wrote:
On Sep 5, 2010, at 11:38 AM, Damian Betebenner wrote:
Thanks for the invaluable help on my previous questions. The speed
up in create summary tables has been immense and I’m enthused about
all the possibilities going forward.
I’m currently stuck in trying to put together syntax for a “long”
for table. In the example below, each case is a unique Student by
Year combination. What I’m trying to do is take
such a table, aggregate on the student’s current year (i.e., 2009
in this data) SCHOOL_NUMBER, and calculate their mean score in the
previous year (i.e., 2008 in this data).
If the file were “wide”, with each case representing a unique
student with separate variables for the year, then it would be easy
to break on the 2009 SCHOOL_NUMBER and take the
mean of the 2008 SCORE.
But there is only one 2008 SCORE for each student???
Is conversion of long to wide necessary to do this?
Probably not. Are you familiar with the "ave" function in base R?
I am having some difficulty understanding the structure of the desired
output. I initially thought it might be something like:
rd.txt <-
function(txt, header=TRUE, ...) {
rd <- read.table(textConnection(txt), header=header, ...)
closeAllConnections()
rd }
txt <- rd.txt("STUDENT_ID SCHOOL_NUMBER YEAR SCORE
1 100 2008 39
1 200 2009 48
2 100 2008 64
2 200 2009 73
3 100 2008 35
3 200 2009 35
4 100 2008 52
4 200 2009 61
5 100 2008 51
5 200 2009 58
6 300 2008 45
6 400 2009 55
7 300 2008 69
7 400 2009 77
8 300 2008 47
8 400 2009 47
9 300 2008 57
9 400 2009 58
10 300 2008 47
10 400 2009 53")
dtxt <- data.table(txt)
> dtxt$avScr <- dtxt[ , ave(SCORE, list(STUDENT_ID))] # returns a
vector as long as its input
> dtxt
But now I am wondering if you wanted:
> dtxt[ , tapply(SCORE, list(STUDENT_ID), mean)] # returns vector
only as long as product of category levels.
1 2 3 4 5 6 7 8 9 10
43.5 68.5 35.0 56.5 54.5 50.0 73.0 47.0 57.5 50.0
STUDENT_ID SCHOOL_NUMBER YEAR SCORE
[1,] 1 100 2008 39
[2,] 1 200 2009 48
[3,] 2 100 2008 64
[4,] 2 200 2009 73
[5,] 3 100 2008 35
[6,] 3 200 2009 35
[7,] 4 100 2008 52
[8,] 4 200 2009 61
[9,] 5 100 2008 51
[10,] 5 200 2009 58
[11,] 6 300 2008 45
[12,] 6 400 2009 55
[13,] 7 300 2008 69
[14,] 7 400 2009 77
[15,] 8 300 2008 47
[16,] 8 400 2009 47
[17,] 9 300 2008 57
[18,] 9 400 2009 58
[19,] 10 300 2008 47
[20,] 10 400 2009 53
Thanks,
Damian
David Winsemius, MD
West Hartford, CT
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