How to force aggregate to exclude NA ?
Actually the second aggregate and second rowsum don't need the na.rm = TRUE so we only need: aggregate(!is.na(m[, -(1:2)]), m[1], sum) rowsum(0+!is.na(m[, -(1:2)]), m[,1]) You might also want to look at summaryBy in the doBy package. On Sun, Dec 7, 2008 at 7:43 AM, Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:
Try aggregate(m[, -(1:2)], m[1], sum, na.rm = TRUE) aggregate(!is.na(m[, -(1:2)]), m[1], sum, na.rm = TRUE) # or (this uses row names rather than a column for the group): rowsum(m[, -(1:2)], m[,1], na.rm = TRUE) rowsum(0+!is.na(m[, -(1:2)]), m[,1], na.rm = TRUE) On Sun, Dec 7, 2008 at 7:06 AM, Daren Tan <daren76 at hotmail.com> wrote:
The aggregate function does "almost" all that I need to summarize a datasets, except that I can't specify exclusion of NAs without a little bit of hassle.
set.seed(143) m <- data.frame(A=sample(LETTERS[1:5], 20, T), B=sample(LETTERS[1:10], 20, T), C=sample(c(NA, 1:4), 20, T), D=sample(c(NA,1:4), 20, T)) m
A B C D 1 E I 1 NA 2 A C NA NA 3 D I NA 3 4 C I 2 4 5 A C 3 2 6 E J 1 2 7 D J 2 2 8 C G 4 1 9 C D NA 3 10 B G 3 NA 11 C B 4 2 12 A B NA NA 13 E A NA 4 14 B B 3 3 15 E I 4 1 16 E J 3 1 17 B J 4 4 18 B J 1 3 19 D D 4 2 20 B B 4 3
aggregate(m[,-c(1:2)], by=list(m[,1]), sum)
Group.1 C D 1 A NA NA 2 B 15 NA 3 C NA 10 4 D NA 7 5 E NA NA
aggregate(m[,-c(1:2)], by=list(m[,1]), length)
Group.1 C D 1 A 3 3 2 B 5 5 3 C 4 4 4 D 3 3 5 E 5 5 My own defined version of length and sum to exclude NA
mylength <- function(x) { sum(as.logical(x), na.rm=T) }
mysum <- function(x) {sum(x, na.rm=T)}
aggregate(m[,-c(1:2)], by=list(m[,1]), mysum) <----------------- this computes correctly.
Group.1 C D 1 A 3 2 2 B 15 13 3 C 10 10 4 D 6 7 5 E 9 8
aggregate(m[,-c(1:2)], by=list(m[,1]), mylength) <----------------- this computes correctly.
Group.1 C D 1 A 1 1 2 B 5 4 3 C 3 4 4 D 2 3 5 E 4 4 There are other statistics I need to compute e.g. var, sd, and it is a hassle to create customized versions to exclude NA. Any alternative approaches ?
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