numpy adding columns

[rwahdan]

Hi,

I am trying to add columns to a numpy array but i am getting an error

import numpy as np
numbers = np.array([
    [2,4],
    [8,10],
    [50,100]
    ])

add = numbers[:,0] + numbers[:,1]
mul = numbers[:,0] * numbers[:,1]

numbers = np.hstack((numbers,add))
numbers = np.hstack((numbers,mul))

i am getting this error:

Error:
Traceback (most recent call last):
  File "main.py", line 11, in <module>
    numbers = np.hstack((numbers,add))
  File "<__array_function__ internals>", line 5, in hstack
  File "/usr/lib/python3.8/site-packages/numpy/core/shape_base.py", line 346, in hstack
    return _nx.concatenate(arrs, 1)
  File "<__array_function__ internals>", line 5, in concatenate
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension(s) and the array at index 1 has 1 dimension(s)

** Process exited - Return Code: 1 **
Press Enter to exit terminal

[jefsummers]

Not sure if this is what you are looking for, but here goes

import numpy as np
numbers = np.array([
    [2,4],
    [8,10],
    [50,100]
    ])
 
add = numbers[:,0] + numbers[:,1]
mul = numbers[:,0] * numbers[:,1]
print(numbers)
print(add.transpose()) 
numbers = np.append(numbers,add.transpose())
numbers = np.append(numbers,mul.transpose())
print(numbers)

Output:
[[  2   4]
 [  8  10]
 [ 50 100]]
[  6  18 150]
[   2    4    8   10   50  100    6   18  150    8   80 5000]

[rwahdan]

Not sure if this is what you are looking for, but here goes

import numpy as np
numbers = np.array([
    [2,4],
    [8,10],
    [50,100]
    ])
 
add = numbers[:,0] + numbers[:,1]
mul = numbers[:,0] * numbers[:,1]
print(numbers)
print(add.transpose()) 
numbers = np.append(numbers,add.transpose())
numbers = np.append(numbers,mul.transpose())
print(numbers)

Output:
[[  2   4]
 [  8  10]
 [ 50 100]]

[  6  18 150]

[   2    4    8   10   50  100    6   18  150    8   80 5000]

Thanks for the reply. What I am looking for is to add the 2 new arrays (add, mul) as columns so the answer should be (columns):

Output:
X      Y    SUM   Mul
2      4      6      8
8     10    18     80
50  100   150   5000

[rwahdan]

I just a solution but if anyone can think of a better way please share...

import numpy as np
numbers = np.array([
    [2,4],
    [8,10],
    [50,100]
    ])
  
add = numbers[:,0] + numbers[:,1]
add = add.reshape(3,1)
mul = numbers[:,0] * numbers[:,1]
mul = mul.reshape(3,1)
numbers_add = np.hstack((numbers, add))
numbers_mul = np.hstack((numbers_add, mul))
print(numbers_mul)

the results:

Output:
[[   2    4    6    8]
 [   8   10   18   80]
 [  50  100  150 5000]]


** Process exited - Return Code: 0 **
Press Enter to exit terminal

[deanhystad]

import numpy as np

numbers = np.array([[2,4], [8,10], [50,100]])
table = np.c_[numbers, np.sum(numbers, axis=1), np.prod(numbers, axis=1)]
print('     A    B    +    *', table, sep='\n')

Output:
     A    B    +    *
[[   2    4    6    8]
 [   8   10   18   80]
 [  50  100  150 5000]]