Calculate mean of each 2d array in a numpy array

Question

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?

np.mean(b, axis=0) or simply b.mean(axis=0) or axis=1 depending if you want to average rows or columns. — Itay
– Itay, Commented Aug 20, 2020 at 6:17
Does this answer your question? Calculate mean across dimension in a 2D array — RichieV
– RichieV, Commented Aug 20, 2020 at 6:25
No, none of these address the question I had. Please note that I have an array of 2D arrays. Not a 2D array. — Saqib Ali
– Saqib Ali, Commented Aug 20, 2020 at 6:37

Dishin Goyani · Accepted Answer · 2020-08-20 06:42:18Z

4

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. ])

edited Aug 20, 2020 at 6:42

answered Aug 20, 2020 at 6:31

Dishin Goyani

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4 Comments

Paul H Over a year ago

skip the loop. no point in looping for an operational like this on a numpy array

Saqib Ali Over a year ago

Thanks. This is exactly what I was looking for. I understand the FOR loop, but can you please explain the first solution you described?

Dishin Goyani Over a year ago

@PaulH yes, removed it.

Dishin Goyani Over a year ago

@SaqibAli It will performed mean on multiple dims as passed.

Ravish Jha · Accepted Answer · 2020-08-20 06:28:47Z

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))

answered Aug 20, 2020 at 6:28

Ravish Jha

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1 Comment

J.Doe Over a year ago

To expand on this: Axis of 0 is rows, 1 is columns. You iterate over rows to compute the sum of each column and you iterate over columns to compute the sum of each row which is how you get the code above.

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