I would like to calculate the mean of tree leader increment growth over 5 years (I1 through I5) where each tree is a row and each row has 5 columns. So far I have achieved this using rowMeans when all columns are numeric type and used in the calculation:
Data1 <- data.frame(cbind(I1 = 3, I2 = c(0,3:1, 2:5,NA), I3 =c(1:4,NA,5:2),I4=2,I5=3)) Data1 Data1$mean_5 <- rowMeans(Data1, na.rm =T) Data1 My real dataset has many columns including several Factor type. Is it possible to specify a range of columns within a data frame using rowMeans dims= (say where there is a one Factor column called Species leading I1 to I5, and one Factor column called Moisture following, so 7 columns total) , or do I either need to extract those columns to a new data frame, calculate means, and reattach to the original data frame, or use a different function such as apply? Unfortunately I am fairly new to R and have a difficult time with some terminology and concepts in R Help. -- View this message in context: http://www.nabble.com/rowMean%2C-specify-subset-of-columns-within-Dataframe--tf4871420.html#a13939204 Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]] ______________________________________________ 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.