You can always do this if they are single valued vectors:
if ((!is.na(data_filter)) & (!is.na(trigger)) & (data_filter == trigger))
This will catch the condition where either is an NA and therefore not
do the final compare which was giving your error.
On Fri, Sep 19, 2008 at 9:48 AM, Jason
On a related note, I am trying to do some matching using conditional
statements. These NULL values are being brought in to my data frame as NA,
as expected, but in a conditional if() statement, I cannot compare then to a
integer value, it fails the program. Here is a small snippet of where the
erro
Try length(na.omit())
Here's an example:
data <- runif(100,0,10)
data[runif(20,0,100)] <- NA
file.contents <- matrix(data, ncol = 5, byrow = TRUE)
for (i in 1:5) {
print (length(na.omit(file.contents[,i])))
}
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Beh
Phil's suggestion worked like a charm. My NA's were counted in the frequency
table.
Thanks for the help, all!
On Thu, Sep 18, 2008 at 1:28 PM, Henrik Bengtsson <[EMAIL PROTECTED]>wrote:
> What have you tried this far? Can't you parse them as missing values,
> i.e. NAs? See ?read.csv and argum
I haven't given it a shot yet. To complicate matters further, this file I
have already passed through a filter, which has already converted my null
values to NA. your insight might be of assistance.
On Thu, Sep 18, 2008 at 1:30 PM, Sebastian Weirich <[EMAIL PROTECTED]>wrote:
Hello,
maybe you lo
What have you tried this far? Can't you parse them as missing values,
i.e. NAs? See ?read.csv and arguments '...', i.e. the arguments
'...' are passed to read.table() which takes argument 'na.strings' - a
character *vector* of strings that you want to be interpreted as NAs.
See ?read.table for m
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