Hi everyone,
I have been working with the ccf function recently, and in particular to
do my calculations I have been using "na.action = na.pass". I noticed
that the help documentation mentions that with this option the computed
estimate may not be a valid autocorrelation sequence and was wond
If you want to remove the "N", then you can work with the indices:
> x
[1] NA "B" NA "B" "B" NA "N" "A" "B" "B" "A" NA "A" "N" "N" "N"
"A" "B" "B" "A"
> # if you want the indices of the non-"N", then
> (indx <- which(is.na(x) | x != "N"))
[1] 1 2 3 4 5 6 8 9 10 11 12 13 17 18 19 20
>
I have a data frame. It has lots of patient information, their age, their
gender, etc etc. I need to keep all this information whilst selecting
relevant rows. So, in the example of code I provided I want to remove all
those patients who have entry N in the column with.Wcode. The dimension of
th
Not sure exactly what you are trying to do since you did not provide
commented, minimal, self-contained, reproducible code. Let me take a
guess in that you also have to test for NAs:
> x <- sample(c("N", "A", "B", NA), 20, TRUE)
> x
[1] "A" "A" "B" NA "N" NA NA "B" "B" "N" "N" "N" "B" "A" NA
Hi All,
I have a data frame which has columns comprised mainly of "NA"s. I know
there are functions na.pass and na.omit etc which can be used in these
situations however I can't them to work in this case. I have a function
which returns the data according to some rule i.e. removal of N in this
c
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