How to get mean value with 1D array and 2D array?

Question

Here is two lists: list = [[1, 2], [3, 4]] and list = [1, 2, 2, 3, 4]

I would like to calculate the mean of the lists. This is my code thus far and outputs:

 def summary(x):
      mean1 = np.mean(x)

      Dict = {"mean":mean1}
 return Dict

summary([1, 2, 2, 3, 4])
My output is == {'mean': 2.4}

summary([[1, 2], [3, 4]])
My output is == error

I would just like to know what should i change to my code so that 2D arrays also work if i give it as input and not only just 1D arrays?

I have seen that i should insert (x, axis=1) but then it only works for 2Darray and not again for the 1D array.

I would like the 2D mean to give me output: 'mean': [1.5, 3.5]

Does this answer your question? [Calculate mean across dimension in a 2D array](https://stackoverflow.com/questions/15819980/calculate-mean-across-dimension-in-a-2d-array) — Umair Mubeen, Mar 30 '21 at 10:47
@UmairMubeen i have tried the np.mean(x, axis=1) but then it only works for the 2D array and when i try to run the 1D array it does not work — Back Buddy, Mar 30 '21 at 10:51
@Nick i have changed it. I would just like the function to give for my 2D array output: 'mean': [1.5, 3.5] — Back Buddy, Mar 30 '21 at 10:58

user_na · Accepted Answer · 2021-03-30T11:17:32.140

0

There is an error in the summary definition instead of list you want to have x as parameter.

With this it works fine for me:

import numpy as np
def summary(x):
    mean1 = np.mean(x)

    Dict = {"mean":mean1}
    return Dict

a = summary([1, 2, 2, 3, 4])
print(a)
b = summary([[1, 2], [3, 4]])
print(b)

Result is:

{'mean': 2.4}
{'mean': 2.5}

[Update]

If you want to have the mean along a specific axis you can do it like the following. You have to check the array shape, because you want it in direction 1, which is not prsent for a 1D array.

import numpy as np
def summary(x):
    arr = np.array(x)
    if len(arr.shape) == 2:
        mean1 = np.mean(arr, axis=1)
    else:
        mean1 = np.mean(arr)

    Dict = {"mean":mean1}
    return Dict

a = summary([1, 2, 2, 3, 4])
print(a)
b = summary([[1, 2], [3, 4]])
print(b)

which returns

{'mean': 2.4}
{'mean': array([1.5, 3.5])}

edited Mar 30 '21 at 11:17

answered Mar 30 '21 at 10:50

user_na

2,154
1
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For the 2D one it should give output 'mean': [1.5, 3.5] and with that code it does not – Back Buddy Mar 30 '21 at 11:00
Is there a way the output remove the word "array" like just show the "mean": 1.5,3.5 – Back Buddy Mar 30 '21 at 11:36
you can print it like this: `print(f'mean: {b["mean"]}')` - `mean: [1.5 3.5]` is this what you want? – user_na Mar 30 '21 at 13:16

score 0 · Answer 2 · edited Mar 30 '21 at 10:53

0

try this:

import numpy as np

def summary(x):
      mean1 = np.mean(x)
      Dict = {"mean":mean1}
      return Dict

print(summary([1, 2, 2, 3, 4]))

print(summary([[1, 2], [3, 4]]))

edited Mar 30 '21 at 10:53

Nick

138,499
22
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answered Mar 30 '21 at 10:51

Luca Minutillo

41
3

For the 2D one it should give output 'mean': [1.5, 3.5] and with that code it does not – Back Buddy Mar 30 '21 at 10:56

How to get mean value with 1D array and 2D array?

2 Answers2