Hello,
Your attachment didn't came through, R-Help strips off most types of
files, including CSV.
Anyway, the following will do what I understand of your question. Tested
with a fake dataset.
set.seed(3026) # make the results reproducible
data <- matrix(1:100, ncol = 10)
data[sample(100, 15)] <- 0
data[sample(100, 10)] <- NA
data <- as.data.frame(data)
zero <- sapply(data, function(x) sum(x == 0, na.rm = TRUE))
na <- sapply(data, function(x) sum(is.na(x)))
totals <- nrow(data) - zero - na # totals non zero per column
grand_total <- sum(totals) # total non zero
totals
# V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
# 6 8 8 8 8 7 7 8 6 10
grand_total
#[1] 76
# another way
prod(dim(data)) - sum(zero + na)
#[1] 76
Hope this helps,
Rui Barradas
Em 29-10-2017 10:25, Engin YILMAZ escreveu:
Dear R Staff
You can see my data.csv file in the annex.
I try to count non-zero values in dataset but I need to exclude NA in this
calculation
My code is very long (following),
How can I write this code more efficiently and shortly?
## [NA_Count] - Find NA values
data.na =sapply(data[,3:ncol(data)], function(c) sum(length(which(is.na
(c)))))
## [Zero] - Find zero values
data.z=apply(data[,3:ncol(data)], 2, function(c) sum(c==0))
## [Non-Zero] - Find non-zero values
data.nz=nrow(data[,3:ncol(data)])- (data.na+data.z)
Sincerely
Engin YILMAZ
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and provide commented, minimal, self-contained, reproducible code.
