For example, if the data is like below, Cultivar=rep(c("CV1","CV2"),each=12) Nitrogen=rep(rep(c("N0","N1","N2","N3"), each=3),2) Block=rep(c("I","II","III"),8) Yield=c(99,109,89,115,142,133,121,157,142,125,150,139,82,104,99,117, 125,127,145,154,154,151,166,175) Protein=c(25,35,45,55,44,33,21,57,42,25,50,39,72,14,79,71,25,27,45,54,47,51,66,75) dataA=data.frame(Cultivar,Nitrogen,Block,Yield,Protein) I’d like to summarize yield and protein data. So I used the below code. library (plyr) dataB=ddply(dataA, c("Cultivar","Nitrogen"), summarise, mean=mean(Yield), sd=sd(Yield), n=length(Yield), se=sd/sqrt(n)) dataC=ddply(dataA, c("Cultivar","Nitrogen"), summarise, mean=mean(Protein), sd=sd(Protein), n=length(Protein), se=sd/sqrt(n)) dataB$Protein=dataC$mean dataB$Protein_se=dataC$se dataB Cultivar Nitrogen mean sd n se… Read More How to summarize several independent variables at once in R?

I have the following situation: V1 V2 A A1 A A1 A A1 A A2 A A2 A A3 B B1 B B2 B B2 and i need to group by V1, and summarise counting how many distinct groups each V1 level has in V2. Something like this: V1 n A 3 B 2 How… Read More How to group_by(x) and summarise by counting distinct(y) for each x level?