Storing all values in the array in Python

Question

I have an array A with shape (2,4,1). I want to calculate the mean of A[0] and A[1] and store both the means in A_mean. I present the current and expected outputs.

import numpy as np

A=np.array([[[1.7],
        [2.8],
        [3.9],
        [5.2]],

       [[2.1],
        [8.7],
        [6.9],
        [4.9]]])

for i in range(0,len(A)):
    A_mean=np.mean(A[i])
print(A_mean)

The current output is

5.65

The expected output is

[3.4,5.65]

the problem is that you overwrite A_mean at each iteration of your loop, instead of appending a new value. @Warkaz's answer is the best solution, but a minimal fix to your loop would have been to first initialize A_mean=[] and then use A_mean.append(np,mean(A[i]) in the body of your loop. — joanis
– joanis, Commented Sep 10, 2022 at 13:41

Warkaz · Accepted Answer · 2022-09-10 13:38:16Z

2

The for loop is not necessary because NumPy already knows how to operate on vectors/matrices.

solution would be to remove the loop and just change axis as follows:

A_mean=np.mean(A, axis=1)
print(A_mean)

Outputs:

[[3.4 ]
 [5.65]]

Now you can also do some editing to remove the brackets with [3.4 5.65]:

print(A_mean.ravel())

answered Sep 10, 2022 at 13:38

Warkaz

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3 Comments

joanis Over a year ago

Excellent answer, taking full advantage of NumPy's internal optimizations. Note that if OP really wants the final results in a list, they could use A_mean = list(np.mean(A, axis=1).ravel()), but keeping the results in an array probably makes more sense for further processing with NumPy tools.

Warkaz Over a year ago

@joanis Thanks for the compliment, I already did add the part about ravel() (last line of code) as that was requested format by the OP

joanis Over a year ago

Yes, indeed, I noticed your added ravel() and that was a good idea, thanks for that edit!

Sharim09 · Accepted Answer · 2022-09-10 13:43:00Z

1

Try this.

import numpy as np

A=np.array([[[1.7],
        [2.8],
        [3.9],
        [5.2]],

       [[2.1],
        [8.7],
        [6.9],
        [4.9]]])
A_mean = []

for i in range(0,len(A)):
    A_mean.append(np.mean(A[i]))
print(A_mean)

answered Sep 10, 2022 at 13:43

Sharim09

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