try the following:
out <- tapply(data1$ID, list(data1$ID, data1$Year), length)
out[is.na(out)] <- 0
out
I hope it helps.
Best,
Dimitris
Tom La Bone wrote:
Assume that I have the dataframe "data1", which is listed at the end of this
message. I want count the number of lines that each person has for each
year. For example, the person with ID=213 has 15 entries (NinYear) for 1953.
The following bit of code calculates NinYear:
for (i in 1:length(data1$ID)) {
data1$NinYear[i] <- length(data1[data1$Year==data1$Year[i] &
data1$ID==data1$ID[i],1]) }
This seems to work but is horribly slow (some files I am working with have
over 500,000 lines). Can anyone suggest a faster way of doing this, perhaps
a way that does not use a for loop? Thanks.
Tom
ID Year NinYear
209 1971 0
209 1971 0
213 1951 0
213 1951 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1953 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1954 0
213 1955 0
213 1955 0
234 1953 0
234 1953 0
234 1953 0
234 1953 0
234 1953 0
234 1958 0
234 1958 0
234 1965 0
234 1965 0
234 1965 0
249 1952 0
249 1952 0
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
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