Dear R users, I have a question on using weighted.mean() while aggregating a data frame. I have a data frame with columns Sub, Length and Slope:
> x[1:5,] Sub Length Slope 1 2 351.547 0.0025284969 2 2 343.738 0.0025859390 3 1 696.659 0.0015948968 4 2 5442.338 0.0026132544 5 1 209.483 0.0005304225 and I would like to calculate the weighted.mean of Slope, using Length as weights, for each value of Sub. The obvious way: > aggregate(list(Mean.Slope=x$Slope), by=list(Sub=x$Sub), FUN=weighted.mean, w=x$Length) does not work. weighted.mean() generates warnings that "longer object length is not a multiple of shorter object length in: x * w", from which I conclude that weights are not supplied as I intend, instead each subset of Sub, when passed to weighted.mean(), receives the whole x$Length as weights, which is not correct. Is there an elegant way to do this, or do I have to have a loop here? Thank you, Aleksey -- Aleksey Naumov GIS Analyst Center for Health and Social Research Buffalo State College ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
