R versus numpy when applying functions to rows and columns

r_vs_py.R

# R -------------------------
x = matrix(c(1,2,0, 4,3,7), ncol = 3, byrow = T)
x
#       [,1] [,2] [,3]
# [1,]    1    2    0
# [2,]    4    3    7

# row means (NB: R indexes from 1)
> apply(x, MARGIN = 1, mean)
# 1.000000 4.666667


# Python --------------------
x = np.mat('1 2 0; 4 3 7')
x
# [[1 2 0]
#  [4 3 7]]

# col means
x.mean(axis=0)
# array([2.5, 2.5, 3.5])