I have an numpy array as following:
b = numpy.array([[[1,2,3], [4,5,6]], [[1,1,1],[3,3,3]]])
print(b)
[[[1 2 3]
[4 5 6]]
[[1 1 1]
[3 3 3]]]
now I wan't to calculate the mean of each 2-d array in the array. for e.g.
numpy.mean(b[0])
>>> 3.5
numpy.mean(b[1])
>>> 2.0
How do I do this without using a for loop?
I think this would give you your expected output
By passing multi-dim in axis - see doc for more about axis param
b.mean(axis=(1,2))
array([3.5, 2. ])
np.mean() can take in parameters for the axis, so according to your use, you can do either of the following
print("Mean of each column:")
print(x.mean(axis=0))
print("Mean of each row:")
print(x.mean(axis=1))