On Apr 20, 2012, at 3:00 PM, Jeff Newmiller wrote:
I think
x[x>7.5]
> y <-c(1,1)
> y[y>2]
numeric(0)
> y[which(y>2)]
numeric(0)
gives more unsurprising results when none of the data meets the
criteria than
x[which(x>7.5)]
I don't see a difference.
Look at:
> x <-c(NA, 1)
> x[which(x >2)]
numeric(0)
> x[x>0]
[1] NA 1
> x[which(x >0)]
[1] 1
> length( x[x>0])
[1] 2
> length( x[which(x>0)])
[1] 1
I hope reasonable people can disagree on this one.
Using 'which' gives more unsurprising results when the logical test is
applied to a large dataset for which the number of NA's exceeds the
number of targets by a large margin. There are differences of opinion
as to which surprise is most undesirable. There are also gotcha's
regarding the use of "-" in front of 'which'. I seem to have a false
memory that there is an isTRUE function that is the _correct_ way of
doing this, but I cannot recover that lost memory and it appears that
isTRUE is not vectorized.
--
David.
does.
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David Winsemius <dwinsem...@comcast.net> wrote:
On Apr 20, 2012, at 9:49 AM, Yellow wrote:
I now filtered the Na and Inf out of my data.
And the number is exactly the same als the output from the excel
file.
Thanks everyone. :)
Now I can finish my work.
In the future it might be safer to use subset() or perhaps
x[which(x>7.5)]. That would omit the NA or NaN values (although it
might not remove the Inf values, but I didn't realize the Excel had a
concept of Inf).
--
David Winsemius, MD
West Hartford, CT
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David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
