Eric -
What you're describing is taking the mean of each row while
ignoring missing values:
apply(DF,1,mean,na.rm=TRUE)
[1] 22.60 NaN NaN NaN NaN NaN NaN NaN 102.00 19.20
[11] 19.20 NaN NaN NaN 11.80 7.62 NaN NaN NaN NaN
[21] NaN 75.00 NaN 18.00 NaN 12.90
If this isn't suitable for your larger problem, please describe that
problem in greater detail.
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Fri, 25 Jun 2010, emorway wrote:
Forum,
Using the following data:
DF<-read.table(textConnection("A B
22.60 NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
NA NA
102.00 NA
19.20 NA
19.20 NA
NA NA
NA NA
NA NA
11.80 NA
7.62 NA
NA NA
NA NA
NA NA
NA NA
NA NA
75.00 NA
NA NA
18.30 18.2
NA NA
NA NA
8.44 NA
18.00 NA
NA NA
12.90 NA"),header=T)
closeAllConnections()
The second column is a duplicate reading of the first column, and when two
values are available, I would like to average column 1 and 2 (example code
below). But if there is only one reading, I would like to retain it, but I
haven't found a good way to exclude NA's using the following code:
t(as.matrix(aggregate(t(as.matrix(DF)),list(rep(1:1,each=2)),mean)[,-1]))
Currently, row 24 is the only row with a returned value. I'd like the
result to return column "A" if it is the only available value, and average
where possible. Of course, if both columns are NA, NA is the only possible
result.
The result I'm after would look like this (row 24 is an avg):
22.60
NA
NA
NA
NA
NA
NA
NA
102.00
19.20
19.20
NA
NA
NA
11.80
7.62
NA
NA
NA
NA
NA
75.00
NA
18.25
NA
NA
8.44
18.00
NA
12.90
This is a small example from a much larger data frame, so if you're
wondering what the deal is with list(), that will come into play for the
larger problem I'm trying to solve.
Respectfully,
Eric
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