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 Protein Protein_se
1 CV1 N0 99 10.000000 3 5.773503 35.00000 5.773503
2 CV1 N1 130 13.747727 3 7.937254 44.00000 6.350853
3 CV1 N2 140 18.083141 3 10.440307 40.00000 10.440307
4 CV1 N3 138 12.529964 3 7.234178 38.00000 7.234178
5 CV2 N0 95 11.532563 3 6.658328 55.00000 20.599353
6 CV2 N1 123 5.291503 3 3.055050 41.00000 15.011107
7 CV2 N2 151 5.196152 3 3.000000 48.66667 2.728451
8 CV2 N3 164 12.124356 3 7.000000 64.00000 7.000000
But I believe there are much simple codes to summarize several independent variables at once.
Could you let me know how to do that?
Many thanks,
You could use dplyr::summarize across the desired columns and specify the groups using .by and put all the summary statistics you want in a list:
library(dplyr)
dataA %>%
summarize(across(Yield:Protein,
.fns = list(Mean = mean,
SD = sd,
n = length,
se = ~ sd(.x)/sqrt(length(.x)))),
.by = c("Cultivar", "Nitrogen"))
Output:
Cultivar Nitrogen Yield_Mean Yield_SD Yield_n Yield_se Protein_Mean Protein_SD Protein_n Protein_se
1 CV1 N0 99 10.000000 3 5.773503 35.00000 10.000000 3 5.773503
2 CV1 N1 130 13.747727 3 7.937254 44.00000 11.000000 3 6.350853
3 CV1 N2 140 18.083141 3 10.440307 40.00000 18.083141 3 10.440307
4 CV1 N3 138 12.529964 3 7.234178 38.00000 12.529964 3 7.234178
5 CV2 N0 95 11.532563 3 6.658328 55.00000 35.679126 3 20.599353
6 CV2 N1 123 5.291503 3 3.055050 41.00000 26.000000 3 15.011107
7 CV2 N2 151 5.196152 3 3.000000 48.66667 4.725816 3 2.728451
8 CV2 N3 164 12.124356 3 7.000000 64.00000 12.124356 3 7.000000