I try to do a CA analysis from the vegan package.
This is the code I use:
install.packages("vegan") library(vegan) plots <- c("plotA", "plotB", "plotC", "plotD", "plotE") animal1 <- c(2,7,4,8,1) animal2 <- c(4,3,7,1,0) animal3 <- c(8,5,0,1,3) animal4 <- c(2,2,9,5,2) animal5 <- c(1,6,9,8,7) animalData <- data.frame (plots, animal1, animal2, animal3, animal4, animal5) attach(animalData) animalData.ca <- cca(animalData) But then, I always get an error:
Error in rowSums(X) : 'x' must be numeric
I know that the labels are a factor and the analysis works if I delete the first column. But then the analysis creates own labels and I cannot use mine. Is there a way to get my own labels (plotA, plotB etc. ) included?
11 Answer
You need to have the plots variable stored as the rownames attribute of the animalData data frame, not as a variable in the actual data.
You want:
library(vegan) plots <- c("plotA", "plotB", "plotC", "plotD", "plotE") animal1 <- c(2,7,4,8,1) animal2 <- c(4,3,7,1,0) animal3 <- c(8,5,0,1,3) animal4 <- c(2,2,9,5,2) animal5 <- c(1,6,9,8,7) animalData <- data.frame(animal1, animal2, animal3, animal4, animal5) rownames(animalData) <- plots animalData now should look like this:
> animalData animal1 animal2 animal3 animal4 animal5 plotA 2 4 8 2 1 plotB 7 3 5 2 6 plotC 4 7 0 9 9 plotD 8 1 1 5 8 plotE 1 0 3 2 7 Then for the CA
animalData.ca <- cca(animalData) which works:
> animalData.ca Call: cca(X = animalData) Inertia Rank Total 0.3793 Unconstrained 0.3793 4 Inertia is mean squared contingency coefficient Eigenvalues for unconstrained axes: CA1 CA2 CA3 CA4 0.219528 0.099206 0.055572 0.005018 Plotting this object results in
plot(animalData.ca, type = "text", scaling = 3) 
which as you can see, has used the attribute data from the animalData data frame.
Also, don't attach() data sets like this; it isn't required and is in fact dangerous as the data are not attached, but an independent copy.