How to square every element in NumPy array?

There are three ways of calculating the square of each element in NumPy array:

Square every element in NumPy array using numpy.square()

np.square() calculates the square of every element in NumPy array. It does not modify the original NumPy array and returns the element-wise square of the input array.

import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
newarr = np.square(arr)
print('Original array:')
print(arr)
print('Squared array:')
print(newarr)

Output

Original array:
[[1 2 3 4]
 [5 6 7 8]]
Squared array:
[[ 1  4  9 16]
 [25 36 49 64]]

Square every element in 1D NumPy array using while loop

while loop is used to loop through every element of NumPy array. During each iteration, the square of the element is calculated and stored in the original array.

import numpy as np
arr = np.array([1, 2, 3, 4])
i=0
while i < arr.size:
  arr[i] = arr[i]*arr[i]
  i = i + 1
print(arr)

Output

[ 1  4  9 16]

Square every element in 2D NumPy array using while loop

import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
rows, cols = arr.shape
i=0
while i < rows:
  j = 0
  while j < cols:
    arr[i, j] = arr[i, j]*arr[i, j]
    j = j + 1
  i = i + 1
print(arr)

Output

[[ 1  4  9 16]
 [25 36 49 64]]

Square every element in 1D NumPy array using nditer

By default, nditer does not allow the modification of NumPy array. To overcome this problem, you will need to use op_flags parameter and pass readwrite value to it.

import numpy as np
arr = np.array([1, 2, 3, 4])
for t in np.nditer(arr, op_flags=['readwrite']):
  t[...] = t*t
print(arr)

Output

[ 1  4  9 16]

Square every element in 2D NumPy array using nditer

import numpy as np
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
for t in np.nditer(arr, op_flags=['readwrite']):
  t[...] = t*t
print(arr)

Output

[[ 1  4  9 16]
 [25 36 49 64]]

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