Dear all,
I am attempting to perform a calculation which counts the number of positive
(or negative) values based on the sample mean (on a per-row basis). If the mean
is>0 then only positive values should be counted, and if the mean is <0 then
only negative values should be counted. In cases where the mean is equal to
zero, the value -99999 should be returned.
The following is an example of the data frame I'm working on (all values are of
class 'numeric').
> head(combdframe)
V1 V2 V3 V4 V5 V6
1 -328.0999 3404.038 791.7602 211.23932 513.0479 -1178.079
2 -383.4249 3207.306 808.7268 141.20352 424.2388 -1164.402
3 -295.9050 2930.754 918.1146 11.74804 464.2448 -1133.109
4 -326.8606 2703.638 1052.2824 -104.17344 246.2851 -1103.887
5 -296.7194 2663.987 1202.7648 -87.15331 255.1338 -1090.147
6 -227.1772 2619.096 1343.1529 -75.89626 381.6089 -1064.733
The mean of the first row is 571 and therefore a count of the positive values
should be returned for this row (=4). *If* the mean was -571, then a count of
the negative values would be returned (=2).
If the 7th row was composed of values 1.5, -1.5, 2.5, -2.5, 0 and 0 (i.e. the
mean = 0), then -99999 should be returned for this row.
I've attempted to construct this code as follows:
direction_func <- function(combdframe) {
ifelse(mean(i> 0), sum(i> 0), ifelse(mean(i < 0), sum(i < 0), -99999))
}
for (i in nrow(combdframe)) {
direction <- apply(combdframe[i,],1, direction_func)
}
...but this, and varients on this, result in a bit of a mess!
Any guidance on how to perform this (whether it be a correction of the above or
a whole new approach) would be very much appreciated.
Many thanks,
Steve
_________________________________________________________________
We want to hear all your funny, exciting and crazy Hotmail stories. Tell us now
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
