Dear all, please would you advise : do python and R have different ways to compute the standard deviation (sd) ?
for example, in python, starting with : a = np.array([[1,2,3], [4,5,6], [7,8,9]]) print(a.std(axis=1)) ### per row : [0.81649658 0.81649658 0.81649658] print(a.std(axis=0)) ### per column : [2.44948974 2.44948974 2.44948974] # and in R : z <- matrix(c(1,2,3,4,5,6,7,8,9), nrow=3, ncol=3, byrow=T) # z# [,1] [,2] [,3]#[1,] 1 2 3#[2,] 4 5 6#[3,] 7 8 9 # apply(z, 1, sd) sd(z[1,]) #1 sd(z[2,]) #1 sd(z[3,]) #1 # apply(z, 2, sd) sd(z[,1]) #3 sd(z[,2]) #3 sd(z[,3]) #3 [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.